• Are you ready to elevate your online presence and embrace the future of search? Tracking your Google AI Mode visibility with Semrush is your key to unlocking new opportunities!

    By analyzing your competitors and monitoring your rankings, you can strategically grow your presence in the AI search space. Imagine the possibilities when you harness the power of data to enhance your visibility!

    Let’s dive in, learn, and thrive together! Remember, every step you take today brings you closer to your goals tomorrow!

    #GoogleAIMode #Semrush #DigitalMarketing #SEO #Inspiration
    🌟 Are you ready to elevate your online presence and embrace the future of search? 🚀 Tracking your Google AI Mode visibility with Semrush is your key to unlocking new opportunities! 🔑 By analyzing your competitors and monitoring your rankings, you can strategically grow your presence in the AI search space. Imagine the possibilities when you harness the power of data to enhance your visibility! 🌈✨ Let’s dive in, learn, and thrive together! Remember, every step you take today brings you closer to your goals tomorrow! 💪💖 #GoogleAIMode #Semrush #DigitalMarketing #SEO #Inspiration
    How to Track Your Google AI Mode Visibility with Semrush
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    Learn how to track your Google AI Mode visibility using Semrush. Analyze competitors, track rankings, and grow your presence in AI search.
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  • Ah, "Power Line Patrols: The Grid’s Eye in the Sky" — because nothing says excitement like watching power lines from above. Who needs to follow the latest TikTok dance trends when you can track the thrilling escapades of utility vehicles patrolling our electrifying infrastructure? Forget air traffic — the real drama is in the hum of electricity and the occasional flutter of a bird dodging a high-voltage wire. Who knew that the real "eye in the sky" would be monitoring lines instead of planes? Next time you’re bored, maybe check out some power patrols — just don’t forget your popcorn for this electrifying show!

    #PowerLinePatrols #UtilityDrama #ElectricEntertainment #GridWatchers #SkyHighThrills
    Ah, "Power Line Patrols: The Grid’s Eye in the Sky" — because nothing says excitement like watching power lines from above. Who needs to follow the latest TikTok dance trends when you can track the thrilling escapades of utility vehicles patrolling our electrifying infrastructure? Forget air traffic — the real drama is in the hum of electricity and the occasional flutter of a bird dodging a high-voltage wire. Who knew that the real "eye in the sky" would be monitoring lines instead of planes? Next time you’re bored, maybe check out some power patrols — just don’t forget your popcorn for this electrifying show! #PowerLinePatrols #UtilityDrama #ElectricEntertainment #GridWatchers #SkyHighThrills
    Power Line Patrols: The Grid’s Eye in the Sky
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  • Hey everyone! Are you ready to elevate your brand visibility in 2025? Discover the power of the 9 best LLM monitoring tools that will help you track your AI presence like never before! These tools are designed to compare features, pricing, and capabilities, ensuring you find the perfect fit for your brand's needs.

    Embrace the future with confidence and watch your brand shine! Let’s take this journey together and unlock new opportunities! Remember, the best is yet to come!

    #BrandVisibility #MonitoringTools #AITracking #Positivity #FutureReady
    ✨ Hey everyone! Are you ready to elevate your brand visibility in 2025? 🚀 Discover the power of the 9 best LLM monitoring tools that will help you track your AI presence like never before! 🌟 These tools are designed to compare features, pricing, and capabilities, ensuring you find the perfect fit for your brand's needs. Embrace the future with confidence and watch your brand shine! 💪 Let’s take this journey together and unlock new opportunities! Remember, the best is yet to come! 🌈 #BrandVisibility #MonitoringTools #AITracking #Positivity #FutureReady
    The 9 Best LLM Monitoring Tools for Brand Visibility in 2025
    www.semrush.com
    Discover the 9 best LLM monitoring tools. Compare features, pricing, & capabilities to track your AI presence.
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  • Have you ever experienced the heartbreak of melted ice cream? Scott Baker turned a frustrating moment into inspiration with his innovative freezer monitor! Because let's face it, ice cream is a dish best served cold, and we all deserve to enjoy it at its best! With this clever device, you can ensure your frozen treats stay perfectly chilled, avoiding any future mishaps. Remember, every setback can be a setup for a comeback! Embrace technology and keep your ice cream dreams alive!

    #FreezerMonitoring #IceCreamLovers #StayChilled #Inspiration #TechForGood
    Have you ever experienced the heartbreak of melted ice cream? 🍦💔 Scott Baker turned a frustrating moment into inspiration with his innovative freezer monitor! 🌟 Because let's face it, ice cream is a dish best served cold, and we all deserve to enjoy it at its best! With this clever device, you can ensure your frozen treats stay perfectly chilled, avoiding any future mishaps. 🚀✨ Remember, every setback can be a setup for a comeback! Embrace technology and keep your ice cream dreams alive! 🥳 #FreezerMonitoring #IceCreamLovers #StayChilled #Inspiration #TechForGood
    Freezer Monitoring: Because Ice Cream Is a Dish Best Served Cold
    hackaday.com
    [Scott Baker] wrote in to let us know about his freezer monitor. After a regrettable incident where the ice cream melted because the freezer failed [Scott] decided that what was …read more
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  • Hey there, fabulous friends!

    Are you ready to take your market research game to the next level? Today, I want to share with you something that can truly transform how you see competition! In this fast-paced world, every entrepreneur and marketer needs to be equipped with the right tools to uncover hidden gems in the market. And guess what? The answer lies in the **14 Best Competitive Intelligence Tools for Market Research**!

    Imagine having the power to peek behind the curtain of your competitors and discover their strategies and tactics! With these amazing tools, you can gather insights that will not only help you understand your market better but also give you the edge you need to soar higher than ever before!

    One standout tool that I absolutely adore is the **Semrush Traffic & Market Toolkit**. It’s like having a secret weapon in your back pocket! This toolkit provides invaluable data about traffic sources, keyword strategies, and much more! Say goodbye to guesswork and hello to informed decisions! Each piece of information you gather brings you one step closer to your goals.

    But that’s not all! Each of the 14 tools has its own unique features that cater to different aspects of competitive intelligence. Whether it's analyzing social media performance, tracking keywords, or monitoring brand mentions, there’s something for everyone! It’s time to embrace the power of knowledge and turn it into your competitive advantage!

    I know that diving into market research might seem daunting, but let me tell you, it’s a thrilling adventure! Every insight you uncover is like finding a treasure map leading you to success! So, don’t shy away from exploring these tools. Embrace them with open arms and watch your business flourish!

    Remember, the only limit to your success is the extent of your imagination and the determination to use the right resources. So gear up, equip yourself with these 14 best competitive intelligence tools, and let’s conquer the market together!

    Let’s lift each other up and share our discoveries! What tools are you excited to try? Drop your thoughts in the comments below! Let’s inspire one another to reach new heights!

    #MarketResearch #CompetitiveIntelligence #BusinessGrowth #Semrush #Inspiration
    🌟 Hey there, fabulous friends! 🌟 Are you ready to take your market research game to the next level? 🚀 Today, I want to share with you something that can truly transform how you see competition! In this fast-paced world, every entrepreneur and marketer needs to be equipped with the right tools to uncover hidden gems in the market. And guess what? The answer lies in the **14 Best Competitive Intelligence Tools for Market Research**! 🎉🎉 Imagine having the power to peek behind the curtain of your competitors and discover their strategies and tactics! With these amazing tools, you can gather insights that will not only help you understand your market better but also give you the edge you need to soar higher than ever before! 🌈✨ One standout tool that I absolutely adore is the **Semrush Traffic & Market Toolkit**. It’s like having a secret weapon in your back pocket! 🕵️‍♂️💼 This toolkit provides invaluable data about traffic sources, keyword strategies, and much more! Say goodbye to guesswork and hello to informed decisions! Each piece of information you gather brings you one step closer to your goals. 🌟 But that’s not all! Each of the 14 tools has its own unique features that cater to different aspects of competitive intelligence. Whether it's analyzing social media performance, tracking keywords, or monitoring brand mentions, there’s something for everyone! It’s time to embrace the power of knowledge and turn it into your competitive advantage! 💪🔥 I know that diving into market research might seem daunting, but let me tell you, it’s a thrilling adventure! Every insight you uncover is like finding a treasure map leading you to success! 🗺️💖 So, don’t shy away from exploring these tools. Embrace them with open arms and watch your business flourish! 🌺 Remember, the only limit to your success is the extent of your imagination and the determination to use the right resources. So gear up, equip yourself with these 14 best competitive intelligence tools, and let’s conquer the market together! 🌍💫 Let’s lift each other up and share our discoveries! What tools are you excited to try? Drop your thoughts in the comments below! 👇💬 Let’s inspire one another to reach new heights! #MarketResearch #CompetitiveIntelligence #BusinessGrowth #Semrush #Inspiration
    www.semrush.com
    Discover the competition and reveal strategies and tactics of any industry player with these top 14 competitive intelligence tools, including the Semrush Traffic & Market Toolkit.
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  • Ankur Kothari Q&A: Customer Engagement Book Interview

    Reading Time: 9 minutes
    In marketing, data isn’t a buzzword. It’s the lifeblood of all successful campaigns.
    But are you truly harnessing its power, or are you drowning in a sea of information? To answer this question, we sat down with Ankur Kothari, a seasoned Martech expert, to dive deep into this crucial topic.
    This interview, originally conducted for Chapter 6 of “The Customer Engagement Book: Adapt or Die” explores how businesses can translate raw data into actionable insights that drive real results.
    Ankur shares his wealth of knowledge on identifying valuable customer engagement data, distinguishing between signal and noise, and ultimately, shaping real-time strategies that keep companies ahead of the curve.

     
    Ankur Kothari Q&A Interview
    1. What types of customer engagement data are most valuable for making strategic business decisions?
    Primarily, there are four different buckets of customer engagement data. I would begin with behavioral data, encompassing website interaction, purchase history, and other app usage patterns.
    Second would be demographic information: age, location, income, and other relevant personal characteristics.
    Third would be sentiment analysis, where we derive information from social media interaction, customer feedback, or other customer reviews.
    Fourth would be the customer journey data.

    We track touchpoints across various channels of the customers to understand the customer journey path and conversion. Combining these four primary sources helps us understand the engagement data.

    2. How do you distinguish between data that is actionable versus data that is just noise?
    First is keeping relevant to your business objectives, making actionable data that directly relates to your specific goals or KPIs, and then taking help from statistical significance.
    Actionable data shows clear patterns or trends that are statistically valid, whereas other data consists of random fluctuations or outliers, which may not be what you are interested in.

    You also want to make sure that there is consistency across sources.
    Actionable insights are typically corroborated by multiple data points or channels, while other data or noise can be more isolated and contradictory.
    Actionable data suggests clear opportunities for improvement or decision making, whereas noise does not lead to meaningful actions or changes in strategy.

    By applying these criteria, I can effectively filter out the noise and focus on data that delivers or drives valuable business decisions.

    3. How can customer engagement data be used to identify and prioritize new business opportunities?
    First, it helps us to uncover unmet needs.

    By analyzing the customer feedback, touch points, support interactions, or usage patterns, we can identify the gaps in our current offerings or areas where customers are experiencing pain points.

    Second would be identifying emerging needs.
    Monitoring changes in customer behavior or preferences over time can reveal new market trends or shifts in demand, allowing my company to adapt their products or services accordingly.
    Third would be segmentation analysis.
    Detailed customer data analysis enables us to identify unserved or underserved segments or niche markets that may represent untapped opportunities for growth or expansion into newer areas and new geographies.
    Last is to build competitive differentiation.

    Engagement data can highlight where our companies outperform competitors, helping us to prioritize opportunities that leverage existing strengths and unique selling propositions.

    4. Can you share an example of where data insights directly influenced a critical decision?
    I will share an example from my previous organization at one of the financial services where we were very data-driven, which made a major impact on our critical decision regarding our credit card offerings.
    We analyzed the customer engagement data, and we discovered that a large segment of our millennial customers were underutilizing our traditional credit cards but showed high engagement with mobile payment platforms.
    That insight led us to develop and launch our first digital credit card product with enhanced mobile features and rewards tailored to the millennial spending habits. Since we had access to a lot of transactional data as well, we were able to build a financial product which met that specific segment’s needs.

    That data-driven decision resulted in a 40% increase in our new credit card applications from this demographic within the first quarter of the launch. Subsequently, our market share improved in that specific segment, which was very crucial.

    5. Are there any other examples of ways that you see customer engagement data being able to shape marketing strategy in real time?
    When it comes to using the engagement data in real-time, we do quite a few things. In the recent past two, three years, we are using that for dynamic content personalization, adjusting the website content, email messaging, or ad creative based on real-time user behavior and preferences.
    We automate campaign optimization using specific AI-driven tools to continuously analyze performance metrics and automatically reallocate the budget to top-performing channels or ad segments.
    Then we also build responsive social media engagement platforms like monitoring social media sentiments and trending topics to quickly adapt the messaging and create timely and relevant content.

    With one-on-one personalization, we do a lot of A/B testing as part of the overall rapid testing and market elements like subject lines, CTAs, and building various successful variants of the campaigns.

    6. How are you doing the 1:1 personalization?
    We have advanced CDP systems, and we are tracking each customer’s behavior in real-time. So the moment they move to different channels, we know what the context is, what the relevance is, and the recent interaction points, so we can cater the right offer.
    So for example, if you looked at a certain offer on the website and you came from Google, and then the next day you walk into an in-person interaction, our agent will already know that you were looking at that offer.
    That gives our customer or potential customer more one-to-one personalization instead of just segment-based or bulk interaction kind of experience.

    We have a huge team of data scientists, data analysts, and AI model creators who help us to analyze big volumes of data and bring the right insights to our marketing and sales team so that they can provide the right experience to our customers.

    7. What role does customer engagement data play in influencing cross-functional decisions, such as with product development, sales, and customer service?
    Primarily with product development — we have different products, not just the financial products or products whichever organizations sell, but also various products like mobile apps or websites they use for transactions. So that kind of product development gets improved.
    The engagement data helps our sales and marketing teams create more targeted campaigns, optimize channel selection, and refine messaging to resonate with specific customer segments.

    Customer service also gets helped by anticipating common issues, personalizing support interactions over the phone or email or chat, and proactively addressing potential problems, leading to improved customer satisfaction and retention.

    So in general, cross-functional application of engagement improves the customer-centric approach throughout the organization.

    8. What do you think some of the main challenges marketers face when trying to translate customer engagement data into actionable business insights?
    I think the huge amount of data we are dealing with. As we are getting more digitally savvy and most of the customers are moving to digital channels, we are getting a lot of data, and that sheer volume of data can be overwhelming, making it very difficult to identify truly meaningful patterns and insights.

    Because of the huge data overload, we create data silos in this process, so information often exists in separate systems across different departments. We are not able to build a holistic view of customer engagement.

    Because of data silos and overload of data, data quality issues appear. There is inconsistency, and inaccurate data can lead to incorrect insights or poor decision-making. Quality issues could also be due to the wrong format of the data, or the data is stale and no longer relevant.
    As we are growing and adding more people to help us understand customer engagement, I’ve also noticed that technical folks, especially data scientists and data analysts, lack skills to properly interpret the data or apply data insights effectively.
    So there’s a lack of understanding of marketing and sales as domains.
    It’s a huge effort and can take a lot of investment.

    Not being able to calculate the ROI of your overall investment is a big challenge that many organizations are facing.

    9. Why do you think the analysts don’t have the business acumen to properly do more than analyze the data?
    If people do not have the right idea of why we are collecting this data, we collect a lot of noise, and that brings in huge volumes of data. If you cannot stop that from step one—not bringing noise into the data system—that cannot be done by just technical folks or people who do not have business knowledge.
    Business people do not know everything about what data is being collected from which source and what data they need. It’s a gap between business domain knowledge, specifically marketing and sales needs, and technical folks who don’t have a lot of exposure to that side.

    Similarly, marketing business people do not have much exposure to the technical side — what’s possible to do with data, how much effort it takes, what’s relevant versus not relevant, and how to prioritize which data sources will be most important.

    10. Do you have any suggestions for how this can be overcome, or have you seen it in action where it has been solved before?
    First, cross-functional training: training different roles to help them understand why we’re doing this and what the business goals are, giving technical people exposure to what marketing and sales teams do.
    And giving business folks exposure to the technology side through training on different tools, strategies, and the roadmap of data integrations.
    The second is helping teams work more collaboratively. So it’s not like the technology team works in a silo and comes back when their work is done, and then marketing and sales teams act upon it.

    Now we’re making it more like one team. You work together so that you can complement each other, and we have a better strategy from day one.

    11. How do you address skepticism or resistance from stakeholders when presenting data-driven recommendations?
    We present clear business cases where we demonstrate how data-driven recommendations can directly align with business objectives and potential ROI.
    We build compelling visualizations, easy-to-understand charts and graphs that clearly illustrate the insights and the implications for business goals.

    We also do a lot of POCs and pilot projects with small-scale implementations to showcase tangible results and build confidence in the data-driven approach throughout the organization.

    12. What technologies or tools have you found most effective for gathering and analyzing customer engagement data?
    I’ve found that Customer Data Platforms help us unify customer data from various sources, providing a comprehensive view of customer interactions across touch points.
    Having advanced analytics platforms — tools with AI and machine learning capabilities that can process large volumes of data and uncover complex patterns and insights — is a great value to us.
    We always use, or many organizations use, marketing automation systems to improve marketing team productivity, helping us track and analyze customer interactions across multiple channels.
    Another thing is social media listening tools, wherever your brand is mentioned or you want to measure customer sentiment over social media, or track the engagement of your campaigns across social media platforms.

    Last is web analytical tools, which provide detailed insights into your website visitors’ behaviors and engagement metrics, for browser apps, small browser apps, various devices, and mobile apps.

    13. How do you ensure data quality and consistency across multiple channels to make these informed decisions?
    We established clear guidelines for data collection, storage, and usage across all channels to maintain consistency. Then we use data integration platforms — tools that consolidate data from various sources into a single unified view, reducing discrepancies and inconsistencies.
    While we collect data from different sources, we clean the data so it becomes cleaner with every stage of processing.
    We also conduct regular data audits — performing periodic checks to identify and rectify data quality issues, ensuring accuracy and reliability of information. We also deploy standardized data formats.

    On top of that, we have various automated data cleansing tools, specific software to detect and correct data errors, redundancies, duplicates, and inconsistencies in data sets automatically.

    14. How do you see the role of customer engagement data evolving in shaping business strategies over the next five years?
    The first thing that’s been the biggest trend from the past two years is AI-driven decision making, which I think will become more prevalent, with advanced algorithms processing vast amounts of engagement data in real-time to inform strategic choices.
    Somewhat related to this is predictive analytics, which will play an even larger role, enabling businesses to anticipate customer needs and market trends with more accuracy and better predictive capabilities.
    We also touched upon hyper-personalization. We are all trying to strive toward more hyper-personalization at scale, which is more one-on-one personalization, as we are increasingly capturing more engagement data and have bigger systems and infrastructure to support processing those large volumes of data so we can achieve those hyper-personalization use cases.
    As the world is collecting more data, privacy concerns and regulations come into play.
    I believe in the next few years there will be more innovation toward how businesses can collect data ethically and what the usage practices are, leading to more transparent and consent-based engagement data strategies.
    And lastly, I think about the integration of engagement data, which is always a big challenge. I believe as we’re solving those integration challenges, we are adding more and more complex data sources to the picture.

    So I think there will need to be more innovation or sophistication brought into data integration strategies, which will help us take a truly customer-centric approach to strategy formulation.

     
    This interview Q&A was hosted with Ankur Kothari, a previous Martech Executive, for Chapter 6 of The Customer Engagement Book: Adapt or Die.
    Download the PDF or request a physical copy of the book here.
    The post Ankur Kothari Q&A: Customer Engagement Book Interview appeared first on MoEngage.
    #ankur #kothari #qampampa #customer #engagement
    Ankur Kothari Q&A: Customer Engagement Book Interview
    Reading Time: 9 minutes In marketing, data isn’t a buzzword. It’s the lifeblood of all successful campaigns. But are you truly harnessing its power, or are you drowning in a sea of information? To answer this question, we sat down with Ankur Kothari, a seasoned Martech expert, to dive deep into this crucial topic. This interview, originally conducted for Chapter 6 of “The Customer Engagement Book: Adapt or Die” explores how businesses can translate raw data into actionable insights that drive real results. Ankur shares his wealth of knowledge on identifying valuable customer engagement data, distinguishing between signal and noise, and ultimately, shaping real-time strategies that keep companies ahead of the curve.   Ankur Kothari Q&A Interview 1. What types of customer engagement data are most valuable for making strategic business decisions? Primarily, there are four different buckets of customer engagement data. I would begin with behavioral data, encompassing website interaction, purchase history, and other app usage patterns. Second would be demographic information: age, location, income, and other relevant personal characteristics. Third would be sentiment analysis, where we derive information from social media interaction, customer feedback, or other customer reviews. Fourth would be the customer journey data. We track touchpoints across various channels of the customers to understand the customer journey path and conversion. Combining these four primary sources helps us understand the engagement data. 2. How do you distinguish between data that is actionable versus data that is just noise? First is keeping relevant to your business objectives, making actionable data that directly relates to your specific goals or KPIs, and then taking help from statistical significance. Actionable data shows clear patterns or trends that are statistically valid, whereas other data consists of random fluctuations or outliers, which may not be what you are interested in. You also want to make sure that there is consistency across sources. Actionable insights are typically corroborated by multiple data points or channels, while other data or noise can be more isolated and contradictory. Actionable data suggests clear opportunities for improvement or decision making, whereas noise does not lead to meaningful actions or changes in strategy. By applying these criteria, I can effectively filter out the noise and focus on data that delivers or drives valuable business decisions. 3. How can customer engagement data be used to identify and prioritize new business opportunities? First, it helps us to uncover unmet needs. By analyzing the customer feedback, touch points, support interactions, or usage patterns, we can identify the gaps in our current offerings or areas where customers are experiencing pain points. Second would be identifying emerging needs. Monitoring changes in customer behavior or preferences over time can reveal new market trends or shifts in demand, allowing my company to adapt their products or services accordingly. Third would be segmentation analysis. Detailed customer data analysis enables us to identify unserved or underserved segments or niche markets that may represent untapped opportunities for growth or expansion into newer areas and new geographies. Last is to build competitive differentiation. Engagement data can highlight where our companies outperform competitors, helping us to prioritize opportunities that leverage existing strengths and unique selling propositions. 4. Can you share an example of where data insights directly influenced a critical decision? I will share an example from my previous organization at one of the financial services where we were very data-driven, which made a major impact on our critical decision regarding our credit card offerings. We analyzed the customer engagement data, and we discovered that a large segment of our millennial customers were underutilizing our traditional credit cards but showed high engagement with mobile payment platforms. That insight led us to develop and launch our first digital credit card product with enhanced mobile features and rewards tailored to the millennial spending habits. Since we had access to a lot of transactional data as well, we were able to build a financial product which met that specific segment’s needs. That data-driven decision resulted in a 40% increase in our new credit card applications from this demographic within the first quarter of the launch. Subsequently, our market share improved in that specific segment, which was very crucial. 5. Are there any other examples of ways that you see customer engagement data being able to shape marketing strategy in real time? When it comes to using the engagement data in real-time, we do quite a few things. In the recent past two, three years, we are using that for dynamic content personalization, adjusting the website content, email messaging, or ad creative based on real-time user behavior and preferences. We automate campaign optimization using specific AI-driven tools to continuously analyze performance metrics and automatically reallocate the budget to top-performing channels or ad segments. Then we also build responsive social media engagement platforms like monitoring social media sentiments and trending topics to quickly adapt the messaging and create timely and relevant content. With one-on-one personalization, we do a lot of A/B testing as part of the overall rapid testing and market elements like subject lines, CTAs, and building various successful variants of the campaigns. 6. How are you doing the 1:1 personalization? We have advanced CDP systems, and we are tracking each customer’s behavior in real-time. So the moment they move to different channels, we know what the context is, what the relevance is, and the recent interaction points, so we can cater the right offer. So for example, if you looked at a certain offer on the website and you came from Google, and then the next day you walk into an in-person interaction, our agent will already know that you were looking at that offer. That gives our customer or potential customer more one-to-one personalization instead of just segment-based or bulk interaction kind of experience. We have a huge team of data scientists, data analysts, and AI model creators who help us to analyze big volumes of data and bring the right insights to our marketing and sales team so that they can provide the right experience to our customers. 7. What role does customer engagement data play in influencing cross-functional decisions, such as with product development, sales, and customer service? Primarily with product development — we have different products, not just the financial products or products whichever organizations sell, but also various products like mobile apps or websites they use for transactions. So that kind of product development gets improved. The engagement data helps our sales and marketing teams create more targeted campaigns, optimize channel selection, and refine messaging to resonate with specific customer segments. Customer service also gets helped by anticipating common issues, personalizing support interactions over the phone or email or chat, and proactively addressing potential problems, leading to improved customer satisfaction and retention. So in general, cross-functional application of engagement improves the customer-centric approach throughout the organization. 8. What do you think some of the main challenges marketers face when trying to translate customer engagement data into actionable business insights? I think the huge amount of data we are dealing with. As we are getting more digitally savvy and most of the customers are moving to digital channels, we are getting a lot of data, and that sheer volume of data can be overwhelming, making it very difficult to identify truly meaningful patterns and insights. Because of the huge data overload, we create data silos in this process, so information often exists in separate systems across different departments. We are not able to build a holistic view of customer engagement. Because of data silos and overload of data, data quality issues appear. There is inconsistency, and inaccurate data can lead to incorrect insights or poor decision-making. Quality issues could also be due to the wrong format of the data, or the data is stale and no longer relevant. As we are growing and adding more people to help us understand customer engagement, I’ve also noticed that technical folks, especially data scientists and data analysts, lack skills to properly interpret the data or apply data insights effectively. So there’s a lack of understanding of marketing and sales as domains. It’s a huge effort and can take a lot of investment. Not being able to calculate the ROI of your overall investment is a big challenge that many organizations are facing. 9. Why do you think the analysts don’t have the business acumen to properly do more than analyze the data? If people do not have the right idea of why we are collecting this data, we collect a lot of noise, and that brings in huge volumes of data. If you cannot stop that from step one—not bringing noise into the data system—that cannot be done by just technical folks or people who do not have business knowledge. Business people do not know everything about what data is being collected from which source and what data they need. It’s a gap between business domain knowledge, specifically marketing and sales needs, and technical folks who don’t have a lot of exposure to that side. Similarly, marketing business people do not have much exposure to the technical side — what’s possible to do with data, how much effort it takes, what’s relevant versus not relevant, and how to prioritize which data sources will be most important. 10. Do you have any suggestions for how this can be overcome, or have you seen it in action where it has been solved before? First, cross-functional training: training different roles to help them understand why we’re doing this and what the business goals are, giving technical people exposure to what marketing and sales teams do. And giving business folks exposure to the technology side through training on different tools, strategies, and the roadmap of data integrations. The second is helping teams work more collaboratively. So it’s not like the technology team works in a silo and comes back when their work is done, and then marketing and sales teams act upon it. Now we’re making it more like one team. You work together so that you can complement each other, and we have a better strategy from day one. 11. How do you address skepticism or resistance from stakeholders when presenting data-driven recommendations? We present clear business cases where we demonstrate how data-driven recommendations can directly align with business objectives and potential ROI. We build compelling visualizations, easy-to-understand charts and graphs that clearly illustrate the insights and the implications for business goals. We also do a lot of POCs and pilot projects with small-scale implementations to showcase tangible results and build confidence in the data-driven approach throughout the organization. 12. What technologies or tools have you found most effective for gathering and analyzing customer engagement data? I’ve found that Customer Data Platforms help us unify customer data from various sources, providing a comprehensive view of customer interactions across touch points. Having advanced analytics platforms — tools with AI and machine learning capabilities that can process large volumes of data and uncover complex patterns and insights — is a great value to us. We always use, or many organizations use, marketing automation systems to improve marketing team productivity, helping us track and analyze customer interactions across multiple channels. Another thing is social media listening tools, wherever your brand is mentioned or you want to measure customer sentiment over social media, or track the engagement of your campaigns across social media platforms. Last is web analytical tools, which provide detailed insights into your website visitors’ behaviors and engagement metrics, for browser apps, small browser apps, various devices, and mobile apps. 13. How do you ensure data quality and consistency across multiple channels to make these informed decisions? We established clear guidelines for data collection, storage, and usage across all channels to maintain consistency. Then we use data integration platforms — tools that consolidate data from various sources into a single unified view, reducing discrepancies and inconsistencies. While we collect data from different sources, we clean the data so it becomes cleaner with every stage of processing. We also conduct regular data audits — performing periodic checks to identify and rectify data quality issues, ensuring accuracy and reliability of information. We also deploy standardized data formats. On top of that, we have various automated data cleansing tools, specific software to detect and correct data errors, redundancies, duplicates, and inconsistencies in data sets automatically. 14. How do you see the role of customer engagement data evolving in shaping business strategies over the next five years? The first thing that’s been the biggest trend from the past two years is AI-driven decision making, which I think will become more prevalent, with advanced algorithms processing vast amounts of engagement data in real-time to inform strategic choices. Somewhat related to this is predictive analytics, which will play an even larger role, enabling businesses to anticipate customer needs and market trends with more accuracy and better predictive capabilities. We also touched upon hyper-personalization. We are all trying to strive toward more hyper-personalization at scale, which is more one-on-one personalization, as we are increasingly capturing more engagement data and have bigger systems and infrastructure to support processing those large volumes of data so we can achieve those hyper-personalization use cases. As the world is collecting more data, privacy concerns and regulations come into play. I believe in the next few years there will be more innovation toward how businesses can collect data ethically and what the usage practices are, leading to more transparent and consent-based engagement data strategies. And lastly, I think about the integration of engagement data, which is always a big challenge. I believe as we’re solving those integration challenges, we are adding more and more complex data sources to the picture. So I think there will need to be more innovation or sophistication brought into data integration strategies, which will help us take a truly customer-centric approach to strategy formulation.   This interview Q&A was hosted with Ankur Kothari, a previous Martech Executive, for Chapter 6 of The Customer Engagement Book: Adapt or Die. Download the PDF or request a physical copy of the book here. The post Ankur Kothari Q&A: Customer Engagement Book Interview appeared first on MoEngage. #ankur #kothari #qampampa #customer #engagement
    Ankur Kothari Q&A: Customer Engagement Book Interview
    www.moengage.com
    Reading Time: 9 minutes In marketing, data isn’t a buzzword. It’s the lifeblood of all successful campaigns. But are you truly harnessing its power, or are you drowning in a sea of information? To answer this question (and many others), we sat down with Ankur Kothari, a seasoned Martech expert, to dive deep into this crucial topic. This interview, originally conducted for Chapter 6 of “The Customer Engagement Book: Adapt or Die” explores how businesses can translate raw data into actionable insights that drive real results. Ankur shares his wealth of knowledge on identifying valuable customer engagement data, distinguishing between signal and noise, and ultimately, shaping real-time strategies that keep companies ahead of the curve.   Ankur Kothari Q&A Interview 1. What types of customer engagement data are most valuable for making strategic business decisions? Primarily, there are four different buckets of customer engagement data. I would begin with behavioral data, encompassing website interaction, purchase history, and other app usage patterns. Second would be demographic information: age, location, income, and other relevant personal characteristics. Third would be sentiment analysis, where we derive information from social media interaction, customer feedback, or other customer reviews. Fourth would be the customer journey data. We track touchpoints across various channels of the customers to understand the customer journey path and conversion. Combining these four primary sources helps us understand the engagement data. 2. How do you distinguish between data that is actionable versus data that is just noise? First is keeping relevant to your business objectives, making actionable data that directly relates to your specific goals or KPIs, and then taking help from statistical significance. Actionable data shows clear patterns or trends that are statistically valid, whereas other data consists of random fluctuations or outliers, which may not be what you are interested in. You also want to make sure that there is consistency across sources. Actionable insights are typically corroborated by multiple data points or channels, while other data or noise can be more isolated and contradictory. Actionable data suggests clear opportunities for improvement or decision making, whereas noise does not lead to meaningful actions or changes in strategy. By applying these criteria, I can effectively filter out the noise and focus on data that delivers or drives valuable business decisions. 3. How can customer engagement data be used to identify and prioritize new business opportunities? First, it helps us to uncover unmet needs. By analyzing the customer feedback, touch points, support interactions, or usage patterns, we can identify the gaps in our current offerings or areas where customers are experiencing pain points. Second would be identifying emerging needs. Monitoring changes in customer behavior or preferences over time can reveal new market trends or shifts in demand, allowing my company to adapt their products or services accordingly. Third would be segmentation analysis. Detailed customer data analysis enables us to identify unserved or underserved segments or niche markets that may represent untapped opportunities for growth or expansion into newer areas and new geographies. Last is to build competitive differentiation. Engagement data can highlight where our companies outperform competitors, helping us to prioritize opportunities that leverage existing strengths and unique selling propositions. 4. Can you share an example of where data insights directly influenced a critical decision? I will share an example from my previous organization at one of the financial services where we were very data-driven, which made a major impact on our critical decision regarding our credit card offerings. We analyzed the customer engagement data, and we discovered that a large segment of our millennial customers were underutilizing our traditional credit cards but showed high engagement with mobile payment platforms. That insight led us to develop and launch our first digital credit card product with enhanced mobile features and rewards tailored to the millennial spending habits. Since we had access to a lot of transactional data as well, we were able to build a financial product which met that specific segment’s needs. That data-driven decision resulted in a 40% increase in our new credit card applications from this demographic within the first quarter of the launch. Subsequently, our market share improved in that specific segment, which was very crucial. 5. Are there any other examples of ways that you see customer engagement data being able to shape marketing strategy in real time? When it comes to using the engagement data in real-time, we do quite a few things. In the recent past two, three years, we are using that for dynamic content personalization, adjusting the website content, email messaging, or ad creative based on real-time user behavior and preferences. We automate campaign optimization using specific AI-driven tools to continuously analyze performance metrics and automatically reallocate the budget to top-performing channels or ad segments. Then we also build responsive social media engagement platforms like monitoring social media sentiments and trending topics to quickly adapt the messaging and create timely and relevant content. With one-on-one personalization, we do a lot of A/B testing as part of the overall rapid testing and market elements like subject lines, CTAs, and building various successful variants of the campaigns. 6. How are you doing the 1:1 personalization? We have advanced CDP systems, and we are tracking each customer’s behavior in real-time. So the moment they move to different channels, we know what the context is, what the relevance is, and the recent interaction points, so we can cater the right offer. So for example, if you looked at a certain offer on the website and you came from Google, and then the next day you walk into an in-person interaction, our agent will already know that you were looking at that offer. That gives our customer or potential customer more one-to-one personalization instead of just segment-based or bulk interaction kind of experience. We have a huge team of data scientists, data analysts, and AI model creators who help us to analyze big volumes of data and bring the right insights to our marketing and sales team so that they can provide the right experience to our customers. 7. What role does customer engagement data play in influencing cross-functional decisions, such as with product development, sales, and customer service? Primarily with product development — we have different products, not just the financial products or products whichever organizations sell, but also various products like mobile apps or websites they use for transactions. So that kind of product development gets improved. The engagement data helps our sales and marketing teams create more targeted campaigns, optimize channel selection, and refine messaging to resonate with specific customer segments. Customer service also gets helped by anticipating common issues, personalizing support interactions over the phone or email or chat, and proactively addressing potential problems, leading to improved customer satisfaction and retention. So in general, cross-functional application of engagement improves the customer-centric approach throughout the organization. 8. What do you think some of the main challenges marketers face when trying to translate customer engagement data into actionable business insights? I think the huge amount of data we are dealing with. As we are getting more digitally savvy and most of the customers are moving to digital channels, we are getting a lot of data, and that sheer volume of data can be overwhelming, making it very difficult to identify truly meaningful patterns and insights. Because of the huge data overload, we create data silos in this process, so information often exists in separate systems across different departments. We are not able to build a holistic view of customer engagement. Because of data silos and overload of data, data quality issues appear. There is inconsistency, and inaccurate data can lead to incorrect insights or poor decision-making. Quality issues could also be due to the wrong format of the data, or the data is stale and no longer relevant. As we are growing and adding more people to help us understand customer engagement, I’ve also noticed that technical folks, especially data scientists and data analysts, lack skills to properly interpret the data or apply data insights effectively. So there’s a lack of understanding of marketing and sales as domains. It’s a huge effort and can take a lot of investment. Not being able to calculate the ROI of your overall investment is a big challenge that many organizations are facing. 9. Why do you think the analysts don’t have the business acumen to properly do more than analyze the data? If people do not have the right idea of why we are collecting this data, we collect a lot of noise, and that brings in huge volumes of data. If you cannot stop that from step one—not bringing noise into the data system—that cannot be done by just technical folks or people who do not have business knowledge. Business people do not know everything about what data is being collected from which source and what data they need. It’s a gap between business domain knowledge, specifically marketing and sales needs, and technical folks who don’t have a lot of exposure to that side. Similarly, marketing business people do not have much exposure to the technical side — what’s possible to do with data, how much effort it takes, what’s relevant versus not relevant, and how to prioritize which data sources will be most important. 10. Do you have any suggestions for how this can be overcome, or have you seen it in action where it has been solved before? First, cross-functional training: training different roles to help them understand why we’re doing this and what the business goals are, giving technical people exposure to what marketing and sales teams do. And giving business folks exposure to the technology side through training on different tools, strategies, and the roadmap of data integrations. The second is helping teams work more collaboratively. So it’s not like the technology team works in a silo and comes back when their work is done, and then marketing and sales teams act upon it. Now we’re making it more like one team. You work together so that you can complement each other, and we have a better strategy from day one. 11. How do you address skepticism or resistance from stakeholders when presenting data-driven recommendations? We present clear business cases where we demonstrate how data-driven recommendations can directly align with business objectives and potential ROI. We build compelling visualizations, easy-to-understand charts and graphs that clearly illustrate the insights and the implications for business goals. We also do a lot of POCs and pilot projects with small-scale implementations to showcase tangible results and build confidence in the data-driven approach throughout the organization. 12. What technologies or tools have you found most effective for gathering and analyzing customer engagement data? I’ve found that Customer Data Platforms help us unify customer data from various sources, providing a comprehensive view of customer interactions across touch points. Having advanced analytics platforms — tools with AI and machine learning capabilities that can process large volumes of data and uncover complex patterns and insights — is a great value to us. We always use, or many organizations use, marketing automation systems to improve marketing team productivity, helping us track and analyze customer interactions across multiple channels. Another thing is social media listening tools, wherever your brand is mentioned or you want to measure customer sentiment over social media, or track the engagement of your campaigns across social media platforms. Last is web analytical tools, which provide detailed insights into your website visitors’ behaviors and engagement metrics, for browser apps, small browser apps, various devices, and mobile apps. 13. How do you ensure data quality and consistency across multiple channels to make these informed decisions? We established clear guidelines for data collection, storage, and usage across all channels to maintain consistency. Then we use data integration platforms — tools that consolidate data from various sources into a single unified view, reducing discrepancies and inconsistencies. While we collect data from different sources, we clean the data so it becomes cleaner with every stage of processing. We also conduct regular data audits — performing periodic checks to identify and rectify data quality issues, ensuring accuracy and reliability of information. We also deploy standardized data formats. On top of that, we have various automated data cleansing tools, specific software to detect and correct data errors, redundancies, duplicates, and inconsistencies in data sets automatically. 14. How do you see the role of customer engagement data evolving in shaping business strategies over the next five years? The first thing that’s been the biggest trend from the past two years is AI-driven decision making, which I think will become more prevalent, with advanced algorithms processing vast amounts of engagement data in real-time to inform strategic choices. Somewhat related to this is predictive analytics, which will play an even larger role, enabling businesses to anticipate customer needs and market trends with more accuracy and better predictive capabilities. We also touched upon hyper-personalization. We are all trying to strive toward more hyper-personalization at scale, which is more one-on-one personalization, as we are increasingly capturing more engagement data and have bigger systems and infrastructure to support processing those large volumes of data so we can achieve those hyper-personalization use cases. As the world is collecting more data, privacy concerns and regulations come into play. I believe in the next few years there will be more innovation toward how businesses can collect data ethically and what the usage practices are, leading to more transparent and consent-based engagement data strategies. And lastly, I think about the integration of engagement data, which is always a big challenge. I believe as we’re solving those integration challenges, we are adding more and more complex data sources to the picture. So I think there will need to be more innovation or sophistication brought into data integration strategies, which will help us take a truly customer-centric approach to strategy formulation.   This interview Q&A was hosted with Ankur Kothari, a previous Martech Executive, for Chapter 6 of The Customer Engagement Book: Adapt or Die. Download the PDF or request a physical copy of the book here. The post Ankur Kothari Q&A: Customer Engagement Book Interview appeared first on MoEngage.
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  • Monitoring and Support Engineer at Keyword Studios

    Monitoring and Support EngineerKeyword StudiosPasig City Metro Manila Philippines2 hours agoApplyWe are seeking an experienced Monitoring and Support Engineer to support the technology initiatives of the IT Infrastructure team at Keywords. The Monitoring and Support Engineer will be responsible for follow-the-sun monitoring of IT infrastructure, prompt reaction on all infrastructure incident, primary resolution of infrastructure incidents and support requests.ResponsibilitiesFull scope of tasks including but not limited to:Ensure that all incidents are handled within SLAs.Initial troubleshooting of Infrastructure incidents.Ensure maximum network & service availability through proactive monitoring.Ensure all the incident and alert tickets contain detailed technical information.Initial troubleshooting of Infrastructure incidents, restoration of services and escalation to level 3 experts if necessary.Participate in Problem management processes.Ensure that all incidents and critical alerts are documented and escalated if necessary.Ensure effective communication to customers about incidents and outages.Identify opportunities for process improvement and efficiency enhancements.Participate in documentation creation to reduce BAU support activities by ensuring that the Service Desks have adequate knowledge articles to close support tickets as level 1.Participate in reporting on monitored data and incidents on company infrastructure.Implement best practices and lessons learned from initiatives and projects to optimize future outcomes.RequirementsBachelor's degree in a relevant technical field or equivalent experience.Understanding of IT Infrastructure technologies, standards and trends.Technical background with 3+ years’ experience in IT operations role delivering IT infrastructure support, monitoring and incident management.Technical knowledge of the Microsoft Stack, Windows networking, Active Directory, ExchangeTechnical knowledge of Network, Storage and Server equipment, virtualization and production setupsExceptional communication and presentation skills, with the ability to articulate technical concepts to non-technical audiences.Strong analytical and problem-solving skills.Strong customer service orientation.BenefitsGreat Place to Work certified for 4 consecutive yearsFlexible work arrangementGlobal exposure
    Create Your Profile — Game companies can contact you with their relevant job openings.
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    #monitoring #support #engineer #keyword #studios
    Monitoring and Support Engineer at Keyword Studios
    Monitoring and Support EngineerKeyword StudiosPasig City Metro Manila Philippines2 hours agoApplyWe are seeking an experienced Monitoring and Support Engineer to support the technology initiatives of the IT Infrastructure team at Keywords. The Monitoring and Support Engineer will be responsible for follow-the-sun monitoring of IT infrastructure, prompt reaction on all infrastructure incident, primary resolution of infrastructure incidents and support requests.ResponsibilitiesFull scope of tasks including but not limited to:Ensure that all incidents are handled within SLAs.Initial troubleshooting of Infrastructure incidents.Ensure maximum network & service availability through proactive monitoring.Ensure all the incident and alert tickets contain detailed technical information.Initial troubleshooting of Infrastructure incidents, restoration of services and escalation to level 3 experts if necessary.Participate in Problem management processes.Ensure that all incidents and critical alerts are documented and escalated if necessary.Ensure effective communication to customers about incidents and outages.Identify opportunities for process improvement and efficiency enhancements.Participate in documentation creation to reduce BAU support activities by ensuring that the Service Desks have adequate knowledge articles to close support tickets as level 1.Participate in reporting on monitored data and incidents on company infrastructure.Implement best practices and lessons learned from initiatives and projects to optimize future outcomes.RequirementsBachelor's degree in a relevant technical field or equivalent experience.Understanding of IT Infrastructure technologies, standards and trends.Technical background with 3+ years’ experience in IT operations role delivering IT infrastructure support, monitoring and incident management.Technical knowledge of the Microsoft Stack, Windows networking, Active Directory, ExchangeTechnical knowledge of Network, Storage and Server equipment, virtualization and production setupsExceptional communication and presentation skills, with the ability to articulate technical concepts to non-technical audiences.Strong analytical and problem-solving skills.Strong customer service orientation.BenefitsGreat Place to Work certified for 4 consecutive yearsFlexible work arrangementGlobal exposure Create Your Profile — Game companies can contact you with their relevant job openings. Apply #monitoring #support #engineer #keyword #studios
    gamejobs.co
    Monitoring and Support EngineerKeyword StudiosPasig City Metro Manila Philippines2 hours agoApplyWe are seeking an experienced Monitoring and Support Engineer to support the technology initiatives of the IT Infrastructure team at Keywords. The Monitoring and Support Engineer will be responsible for follow-the-sun monitoring of IT infrastructure, prompt reaction on all infrastructure incident, primary resolution of infrastructure incidents and support requests.ResponsibilitiesFull scope of tasks including but not limited to:Ensure that all incidents are handled within SLAs.Initial troubleshooting of Infrastructure incidents.Ensure maximum network & service availability through proactive monitoring.Ensure all the incident and alert tickets contain detailed technical information.Initial troubleshooting of Infrastructure incidents, restoration of services and escalation to level 3 experts if necessary.Participate in Problem management processes.Ensure that all incidents and critical alerts are documented and escalated if necessary.Ensure effective communication to customers about incidents and outages.Identify opportunities for process improvement and efficiency enhancements.Participate in documentation creation to reduce BAU support activities by ensuring that the Service Desks have adequate knowledge articles to close support tickets as level 1.Participate in reporting on monitored data and incidents on company infrastructure.Implement best practices and lessons learned from initiatives and projects to optimize future outcomes.RequirementsBachelor's degree in a relevant technical field or equivalent experience.Understanding of IT Infrastructure technologies, standards and trends.Technical background with 3+ years’ experience in IT operations role delivering IT infrastructure support, monitoring and incident management.Technical knowledge of the Microsoft Stack, Windows networking, Active Directory, ExchangeTechnical knowledge of Network, Storage and Server equipment, virtualization and production setupsExceptional communication and presentation skills, with the ability to articulate technical concepts to non-technical audiences.Strong analytical and problem-solving skills.Strong customer service orientation.BenefitsGreat Place to Work certified for 4 consecutive yearsFlexible work arrangementGlobal exposure Create Your Profile — Game companies can contact you with their relevant job openings. Apply
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  • The AI execution gap: Why 80% of projects don’t reach production

    Enterprise artificial intelligence investment is unprecedented, with IDC projecting global spending on AI and GenAI to double to billion by 2028. Yet beneath the impressive budget allocations and boardroom enthusiasm lies a troubling reality: most organisations struggle to translate their AI ambitions into operational success.The sobering statistics behind AI’s promiseModelOp’s 2025 AI Governance Benchmark Report, based on input from 100 senior AI and data leaders at Fortune 500 enterprises, reveals a disconnect between aspiration and execution.While more than 80% of enterprises have 51 or more generative AI projects in proposal phases, only 18% have successfully deployed more than 20 models into production.The execution gap represents one of the most significant challenges facing enterprise AI today. Most generative AI projects still require 6 to 18 months to go live – if they reach production at all.The result is delayed returns on investment, frustrated stakeholders, and diminished confidence in AI initiatives in the enterprise.The cause: Structural, not technical barriersThe biggest obstacles preventing AI scalability aren’t technical limitations – they’re structural inefficiencies plaguing enterprise operations. The ModelOp benchmark report identifies several problems that create what experts call a “time-to-market quagmire.”Fragmented systems plague implementation. 58% of organisations cite fragmented systems as the top obstacle to adopting governance platforms. Fragmentation creates silos where different departments use incompatible tools and processes, making it nearly impossible to maintain consistent oversight in AI initiatives.Manual processes dominate despite digital transformation. 55% of enterprises still rely on manual processes – including spreadsheets and email – to manage AI use case intake. The reliance on antiquated methods creates bottlenecks, increases the likelihood of errors, and makes it difficult to scale AI operations.Lack of standardisation hampers progress. Only 23% of organisations implement standardised intake, development, and model management processes. Without these elements, each AI project becomes a unique challenge requiring custom solutions and extensive coordination by multiple teams.Enterprise-level oversight remains rare Just 14% of companies perform AI assurance at the enterprise level, increasing the risk of duplicated efforts and inconsistent oversight. The lack of centralised governance means organisations often discover they’re solving the same problems multiple times in different departments.The governance revolution: From obstacle to acceleratorA change is taking place in how enterprises view AI governance. Rather than seeing it as a compliance burden that slows innovation, forward-thinking organisations recognise governance as an important enabler of scale and speed.Leadership alignment signals strategic shift. The ModelOp benchmark data reveals a change in organisational structure: 46% of companies now assign accountability for AI governance to a Chief Innovation Officer – more than four times the number who place accountability under Legal or Compliance. This strategic repositioning reflects a new understanding that governance isn’t solely about risk management, but can enable innovation.Investment follows strategic priority. A financial commitment to AI governance underscores its importance. According to the report, 36% of enterprises have budgeted at least million annually for AI governance software, while 54% have allocated resources specifically for AI Portfolio Intelligence to track value and ROI.What high-performing organisations do differentlyThe enterprises that successfully bridge the ‘execution gap’ share several characteristics in their approach to AI implementation:Standardised processes from day one. Leading organisations implement standardised intake, development, and model review processes in AI initiatives. Consistency eliminates the need to reinvent workflows for each project and ensures that all stakeholders understand their responsibilities.Centralised documentation and inventory. Rather than allowing AI assets to proliferate in disconnected systems, successful enterprises maintain centralised inventories that provide visibility into every model’s status, performance, and compliance posture.Automated governance checkpoints. High-performing organisations embed automated governance checkpoints throughout the AI lifecycle, helping ensure compliance requirements and risk assessments are addressed systematically rather than as afterthoughts.End-to-end traceability. Leading enterprises maintain complete traceability of their AI models, including data sources, training methods, validation results, and performance metrics.Measurable impact of structured governanceThe benefits of implementing comprehensive AI governance extend beyond compliance. Organisations that adopt lifecycle automation platforms reportedly see dramatic improvements in operational efficiency and business outcomes.A financial services firm profiled in the ModelOp report experienced a halving of time to production and an 80% reduction in issue resolution time after implementing automated governance processes. Such improvements translate directly into faster time-to-value and increased confidence among business stakeholders.Enterprises with robust governance frameworks report the ability to many times more models simultaneously while maintaining oversight and control. This scalability lets organisations pursue AI initiatives in multiple business units without overwhelming their operational capabilities.The path forward: From stuck to scaledThe message from industry leaders that the gap between AI ambition and execution is solvable, but it requires a shift in approach. Rather than treating governance as a necessary evil, enterprises should realise it enables AI innovation at scale.Immediate action items for AI leadersOrganisations looking to escape the ‘time-to-market quagmire’ should prioritise the following:Audit current state: Conduct an assessment of existing AI initiatives, identifying fragmented processes and manual bottlenecksStandardise workflows: Implement consistent processes for AI use case intake, development, and deployment in all business unitsInvest in integration: Deploy platforms to unify disparate tools and systems under a single governance frameworkEstablish enterprise oversight: Create centralised visibility into all AI initiatives with real-time monitoring and reporting abilitiesThe competitive advantage of getting it rightOrganisations that can solve the execution challenge will be able to bring AI solutions to market faster, scale more efficiently, and maintain the trust of stakeholders and regulators.Enterprises that continue with fragmented processes and manual workflows will find themselves disadvantaged compared to their more organised competitors. Operational excellence isn’t about efficiency but survival.The data shows enterprise AI investment will continue to grow. Therefore, the question isn’t whether organisations will invest in AI, but whether they’ll develop the operational abilities necessary to realise return on investment. The opportunity to lead in the AI-driven economy has never been greater for those willing to embrace governance as an enabler not an obstacle.
    #execution #gap #why #projects #dont
    The AI execution gap: Why 80% of projects don’t reach production
    Enterprise artificial intelligence investment is unprecedented, with IDC projecting global spending on AI and GenAI to double to billion by 2028. Yet beneath the impressive budget allocations and boardroom enthusiasm lies a troubling reality: most organisations struggle to translate their AI ambitions into operational success.The sobering statistics behind AI’s promiseModelOp’s 2025 AI Governance Benchmark Report, based on input from 100 senior AI and data leaders at Fortune 500 enterprises, reveals a disconnect between aspiration and execution.While more than 80% of enterprises have 51 or more generative AI projects in proposal phases, only 18% have successfully deployed more than 20 models into production.The execution gap represents one of the most significant challenges facing enterprise AI today. Most generative AI projects still require 6 to 18 months to go live – if they reach production at all.The result is delayed returns on investment, frustrated stakeholders, and diminished confidence in AI initiatives in the enterprise.The cause: Structural, not technical barriersThe biggest obstacles preventing AI scalability aren’t technical limitations – they’re structural inefficiencies plaguing enterprise operations. The ModelOp benchmark report identifies several problems that create what experts call a “time-to-market quagmire.”Fragmented systems plague implementation. 58% of organisations cite fragmented systems as the top obstacle to adopting governance platforms. Fragmentation creates silos where different departments use incompatible tools and processes, making it nearly impossible to maintain consistent oversight in AI initiatives.Manual processes dominate despite digital transformation. 55% of enterprises still rely on manual processes – including spreadsheets and email – to manage AI use case intake. The reliance on antiquated methods creates bottlenecks, increases the likelihood of errors, and makes it difficult to scale AI operations.Lack of standardisation hampers progress. Only 23% of organisations implement standardised intake, development, and model management processes. Without these elements, each AI project becomes a unique challenge requiring custom solutions and extensive coordination by multiple teams.Enterprise-level oversight remains rare Just 14% of companies perform AI assurance at the enterprise level, increasing the risk of duplicated efforts and inconsistent oversight. The lack of centralised governance means organisations often discover they’re solving the same problems multiple times in different departments.The governance revolution: From obstacle to acceleratorA change is taking place in how enterprises view AI governance. Rather than seeing it as a compliance burden that slows innovation, forward-thinking organisations recognise governance as an important enabler of scale and speed.Leadership alignment signals strategic shift. The ModelOp benchmark data reveals a change in organisational structure: 46% of companies now assign accountability for AI governance to a Chief Innovation Officer – more than four times the number who place accountability under Legal or Compliance. This strategic repositioning reflects a new understanding that governance isn’t solely about risk management, but can enable innovation.Investment follows strategic priority. A financial commitment to AI governance underscores its importance. According to the report, 36% of enterprises have budgeted at least million annually for AI governance software, while 54% have allocated resources specifically for AI Portfolio Intelligence to track value and ROI.What high-performing organisations do differentlyThe enterprises that successfully bridge the ‘execution gap’ share several characteristics in their approach to AI implementation:Standardised processes from day one. Leading organisations implement standardised intake, development, and model review processes in AI initiatives. Consistency eliminates the need to reinvent workflows for each project and ensures that all stakeholders understand their responsibilities.Centralised documentation and inventory. Rather than allowing AI assets to proliferate in disconnected systems, successful enterprises maintain centralised inventories that provide visibility into every model’s status, performance, and compliance posture.Automated governance checkpoints. High-performing organisations embed automated governance checkpoints throughout the AI lifecycle, helping ensure compliance requirements and risk assessments are addressed systematically rather than as afterthoughts.End-to-end traceability. Leading enterprises maintain complete traceability of their AI models, including data sources, training methods, validation results, and performance metrics.Measurable impact of structured governanceThe benefits of implementing comprehensive AI governance extend beyond compliance. Organisations that adopt lifecycle automation platforms reportedly see dramatic improvements in operational efficiency and business outcomes.A financial services firm profiled in the ModelOp report experienced a halving of time to production and an 80% reduction in issue resolution time after implementing automated governance processes. Such improvements translate directly into faster time-to-value and increased confidence among business stakeholders.Enterprises with robust governance frameworks report the ability to many times more models simultaneously while maintaining oversight and control. This scalability lets organisations pursue AI initiatives in multiple business units without overwhelming their operational capabilities.The path forward: From stuck to scaledThe message from industry leaders that the gap between AI ambition and execution is solvable, but it requires a shift in approach. Rather than treating governance as a necessary evil, enterprises should realise it enables AI innovation at scale.Immediate action items for AI leadersOrganisations looking to escape the ‘time-to-market quagmire’ should prioritise the following:Audit current state: Conduct an assessment of existing AI initiatives, identifying fragmented processes and manual bottlenecksStandardise workflows: Implement consistent processes for AI use case intake, development, and deployment in all business unitsInvest in integration: Deploy platforms to unify disparate tools and systems under a single governance frameworkEstablish enterprise oversight: Create centralised visibility into all AI initiatives with real-time monitoring and reporting abilitiesThe competitive advantage of getting it rightOrganisations that can solve the execution challenge will be able to bring AI solutions to market faster, scale more efficiently, and maintain the trust of stakeholders and regulators.Enterprises that continue with fragmented processes and manual workflows will find themselves disadvantaged compared to their more organised competitors. Operational excellence isn’t about efficiency but survival.The data shows enterprise AI investment will continue to grow. Therefore, the question isn’t whether organisations will invest in AI, but whether they’ll develop the operational abilities necessary to realise return on investment. The opportunity to lead in the AI-driven economy has never been greater for those willing to embrace governance as an enabler not an obstacle. #execution #gap #why #projects #dont
    The AI execution gap: Why 80% of projects don’t reach production
    www.artificialintelligence-news.com
    Enterprise artificial intelligence investment is unprecedented, with IDC projecting global spending on AI and GenAI to double to $631 billion by 2028. Yet beneath the impressive budget allocations and boardroom enthusiasm lies a troubling reality: most organisations struggle to translate their AI ambitions into operational success.The sobering statistics behind AI’s promiseModelOp’s 2025 AI Governance Benchmark Report, based on input from 100 senior AI and data leaders at Fortune 500 enterprises, reveals a disconnect between aspiration and execution.While more than 80% of enterprises have 51 or more generative AI projects in proposal phases, only 18% have successfully deployed more than 20 models into production.The execution gap represents one of the most significant challenges facing enterprise AI today. Most generative AI projects still require 6 to 18 months to go live – if they reach production at all.The result is delayed returns on investment, frustrated stakeholders, and diminished confidence in AI initiatives in the enterprise.The cause: Structural, not technical barriersThe biggest obstacles preventing AI scalability aren’t technical limitations – they’re structural inefficiencies plaguing enterprise operations. The ModelOp benchmark report identifies several problems that create what experts call a “time-to-market quagmire.”Fragmented systems plague implementation. 58% of organisations cite fragmented systems as the top obstacle to adopting governance platforms. Fragmentation creates silos where different departments use incompatible tools and processes, making it nearly impossible to maintain consistent oversight in AI initiatives.Manual processes dominate despite digital transformation. 55% of enterprises still rely on manual processes – including spreadsheets and email – to manage AI use case intake. The reliance on antiquated methods creates bottlenecks, increases the likelihood of errors, and makes it difficult to scale AI operations.Lack of standardisation hampers progress. Only 23% of organisations implement standardised intake, development, and model management processes. Without these elements, each AI project becomes a unique challenge requiring custom solutions and extensive coordination by multiple teams.Enterprise-level oversight remains rare Just 14% of companies perform AI assurance at the enterprise level, increasing the risk of duplicated efforts and inconsistent oversight. The lack of centralised governance means organisations often discover they’re solving the same problems multiple times in different departments.The governance revolution: From obstacle to acceleratorA change is taking place in how enterprises view AI governance. Rather than seeing it as a compliance burden that slows innovation, forward-thinking organisations recognise governance as an important enabler of scale and speed.Leadership alignment signals strategic shift. The ModelOp benchmark data reveals a change in organisational structure: 46% of companies now assign accountability for AI governance to a Chief Innovation Officer – more than four times the number who place accountability under Legal or Compliance. This strategic repositioning reflects a new understanding that governance isn’t solely about risk management, but can enable innovation.Investment follows strategic priority. A financial commitment to AI governance underscores its importance. According to the report, 36% of enterprises have budgeted at least $1 million annually for AI governance software, while 54% have allocated resources specifically for AI Portfolio Intelligence to track value and ROI.What high-performing organisations do differentlyThe enterprises that successfully bridge the ‘execution gap’ share several characteristics in their approach to AI implementation:Standardised processes from day one. Leading organisations implement standardised intake, development, and model review processes in AI initiatives. Consistency eliminates the need to reinvent workflows for each project and ensures that all stakeholders understand their responsibilities.Centralised documentation and inventory. Rather than allowing AI assets to proliferate in disconnected systems, successful enterprises maintain centralised inventories that provide visibility into every model’s status, performance, and compliance posture.Automated governance checkpoints. High-performing organisations embed automated governance checkpoints throughout the AI lifecycle, helping ensure compliance requirements and risk assessments are addressed systematically rather than as afterthoughts.End-to-end traceability. Leading enterprises maintain complete traceability of their AI models, including data sources, training methods, validation results, and performance metrics.Measurable impact of structured governanceThe benefits of implementing comprehensive AI governance extend beyond compliance. Organisations that adopt lifecycle automation platforms reportedly see dramatic improvements in operational efficiency and business outcomes.A financial services firm profiled in the ModelOp report experienced a halving of time to production and an 80% reduction in issue resolution time after implementing automated governance processes. Such improvements translate directly into faster time-to-value and increased confidence among business stakeholders.Enterprises with robust governance frameworks report the ability to many times more models simultaneously while maintaining oversight and control. This scalability lets organisations pursue AI initiatives in multiple business units without overwhelming their operational capabilities.The path forward: From stuck to scaledThe message from industry leaders that the gap between AI ambition and execution is solvable, but it requires a shift in approach. Rather than treating governance as a necessary evil, enterprises should realise it enables AI innovation at scale.Immediate action items for AI leadersOrganisations looking to escape the ‘time-to-market quagmire’ should prioritise the following:Audit current state: Conduct an assessment of existing AI initiatives, identifying fragmented processes and manual bottlenecksStandardise workflows: Implement consistent processes for AI use case intake, development, and deployment in all business unitsInvest in integration: Deploy platforms to unify disparate tools and systems under a single governance frameworkEstablish enterprise oversight: Create centralised visibility into all AI initiatives with real-time monitoring and reporting abilitiesThe competitive advantage of getting it rightOrganisations that can solve the execution challenge will be able to bring AI solutions to market faster, scale more efficiently, and maintain the trust of stakeholders and regulators.Enterprises that continue with fragmented processes and manual workflows will find themselves disadvantaged compared to their more organised competitors. Operational excellence isn’t about efficiency but survival.The data shows enterprise AI investment will continue to grow. Therefore, the question isn’t whether organisations will invest in AI, but whether they’ll develop the operational abilities necessary to realise return on investment. The opportunity to lead in the AI-driven economy has never been greater for those willing to embrace governance as an enabler not an obstacle.(Image source: Unsplash)
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  • Stolen iPhones disabled by Apple's anti-theft tech after Los Angeles looting

    What just happened? As protests against federal immigration enforcement swept through downtown Los Angeles last week, a wave of looting left several major retailers, including Apple, T-Mobile, and Adidas, counting the cost of smashed windows and stolen goods. Yet for those who made off with iPhones from Apple's flagship store, the thrill of the heist quickly turned into a lesson in high-tech security.
    Apple's retail locations are equipped with advanced anti-theft technology that renders display devices useless once they leave the premises. The moment a demonstration iPhone is taken beyond the store's Wi-Fi network, it is instantly disabled by proximity software and a remote "kill switch."
    Instead of a functioning smartphone, thieves were met with a stark message on the screen: "Please return to Apple Tower Theatre. This device has been disabled and is being tracked. Local authorities will be alerted." The phone simultaneously sounds an alarm and flashes the warning, ensuring it cannot be resold or activated elsewhere.
    This system is not new. During the nationwide unrest of 2020, similar scenes played out as looters discovered that Apple's security measures turned their stolen goods into little more than expensive paperweights.
    The technology relies on a combination of location tracking and network monitoring. As soon as a device is separated from the store's secure environment, it is remotely locked, its location is tracked, and law enforcement is notified.
    // Related Stories

    Videos circulating online show stolen iPhones blaring alarms and displaying tracking messages, making them impossible to ignore and virtually worthless on the black market.
    According to the Los Angeles Police Department, at least three individuals were arrested in connection with the Apple Store burglary, including one suspect apprehended at the scene and two others detained for looting.
    The crackdown on looting comes amid a broader shift in California's approach to retail crime. In response to public outcry over rising thefts, state and local officials have moved away from previously lenient policies. The passage of Proposition 36 has empowered prosecutors to file felony charges against repeat offenders, regardless of the value of stolen goods, and to impose harsher penalties for organized group theft.
    Under these new measures, those caught looting face the prospect of significant prison time, a marked departure from the misdemeanor charges that were common under earlier laws.
    District attorneys in Southern California have called for even harsher penalties, particularly for crimes committed during states of emergency. Proposals include making looting a felony offense, increasing prison sentences, and ensuring that suspects are not released without judicial review. The goal, officials say, is to deter opportunistic criminals who exploit moments of crisis, whether during protests or natural disasters.
    #stolen #iphones #disabled #apple039s #antitheft
    Stolen iPhones disabled by Apple's anti-theft tech after Los Angeles looting
    What just happened? As protests against federal immigration enforcement swept through downtown Los Angeles last week, a wave of looting left several major retailers, including Apple, T-Mobile, and Adidas, counting the cost of smashed windows and stolen goods. Yet for those who made off with iPhones from Apple's flagship store, the thrill of the heist quickly turned into a lesson in high-tech security. Apple's retail locations are equipped with advanced anti-theft technology that renders display devices useless once they leave the premises. The moment a demonstration iPhone is taken beyond the store's Wi-Fi network, it is instantly disabled by proximity software and a remote "kill switch." Instead of a functioning smartphone, thieves were met with a stark message on the screen: "Please return to Apple Tower Theatre. This device has been disabled and is being tracked. Local authorities will be alerted." The phone simultaneously sounds an alarm and flashes the warning, ensuring it cannot be resold or activated elsewhere. This system is not new. During the nationwide unrest of 2020, similar scenes played out as looters discovered that Apple's security measures turned their stolen goods into little more than expensive paperweights. The technology relies on a combination of location tracking and network monitoring. As soon as a device is separated from the store's secure environment, it is remotely locked, its location is tracked, and law enforcement is notified. // Related Stories Videos circulating online show stolen iPhones blaring alarms and displaying tracking messages, making them impossible to ignore and virtually worthless on the black market. According to the Los Angeles Police Department, at least three individuals were arrested in connection with the Apple Store burglary, including one suspect apprehended at the scene and two others detained for looting. The crackdown on looting comes amid a broader shift in California's approach to retail crime. In response to public outcry over rising thefts, state and local officials have moved away from previously lenient policies. The passage of Proposition 36 has empowered prosecutors to file felony charges against repeat offenders, regardless of the value of stolen goods, and to impose harsher penalties for organized group theft. Under these new measures, those caught looting face the prospect of significant prison time, a marked departure from the misdemeanor charges that were common under earlier laws. District attorneys in Southern California have called for even harsher penalties, particularly for crimes committed during states of emergency. Proposals include making looting a felony offense, increasing prison sentences, and ensuring that suspects are not released without judicial review. The goal, officials say, is to deter opportunistic criminals who exploit moments of crisis, whether during protests or natural disasters. #stolen #iphones #disabled #apple039s #antitheft
    Stolen iPhones disabled by Apple's anti-theft tech after Los Angeles looting
    www.techspot.com
    What just happened? As protests against federal immigration enforcement swept through downtown Los Angeles last week, a wave of looting left several major retailers, including Apple, T-Mobile, and Adidas, counting the cost of smashed windows and stolen goods. Yet for those who made off with iPhones from Apple's flagship store, the thrill of the heist quickly turned into a lesson in high-tech security. Apple's retail locations are equipped with advanced anti-theft technology that renders display devices useless once they leave the premises. The moment a demonstration iPhone is taken beyond the store's Wi-Fi network, it is instantly disabled by proximity software and a remote "kill switch." Instead of a functioning smartphone, thieves were met with a stark message on the screen: "Please return to Apple Tower Theatre. This device has been disabled and is being tracked. Local authorities will be alerted." The phone simultaneously sounds an alarm and flashes the warning, ensuring it cannot be resold or activated elsewhere. This system is not new. During the nationwide unrest of 2020, similar scenes played out as looters discovered that Apple's security measures turned their stolen goods into little more than expensive paperweights. The technology relies on a combination of location tracking and network monitoring. As soon as a device is separated from the store's secure environment, it is remotely locked, its location is tracked, and law enforcement is notified. // Related Stories Videos circulating online show stolen iPhones blaring alarms and displaying tracking messages, making them impossible to ignore and virtually worthless on the black market. According to the Los Angeles Police Department, at least three individuals were arrested in connection with the Apple Store burglary, including one suspect apprehended at the scene and two others detained for looting. The crackdown on looting comes amid a broader shift in California's approach to retail crime. In response to public outcry over rising thefts, state and local officials have moved away from previously lenient policies. The passage of Proposition 36 has empowered prosecutors to file felony charges against repeat offenders, regardless of the value of stolen goods, and to impose harsher penalties for organized group theft. Under these new measures, those caught looting face the prospect of significant prison time, a marked departure from the misdemeanor charges that were common under earlier laws. District attorneys in Southern California have called for even harsher penalties, particularly for crimes committed during states of emergency. Proposals include making looting a felony offense, increasing prison sentences, and ensuring that suspects are not released without judicial review. The goal, officials say, is to deter opportunistic criminals who exploit moments of crisis, whether during protests or natural disasters.
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  • Over 8M patient records leaked in healthcare data breach

    Published
    June 15, 2025 10:00am EDT close IPhone users instructed to take immediate action to avoid data breach: 'Urgent threat' Kurt 'The CyberGuy' Knutsson discusses Elon Musk's possible priorities as he exits his role with the White House and explains the urgent warning for iPhone users to update devices after a 'massive security gap.' NEWYou can now listen to Fox News articles!
    In the past decade, healthcare data has become one of the most sought-after targets in cybercrime. From insurers to clinics, every player in the ecosystem handles some form of sensitive information. However, breaches do not always originate from hospitals or health apps. Increasingly, patient data is managed by third-party vendors offering digital services such as scheduling, billing and marketing. One such breach at a digital marketing agency serving dental practices recently exposed approximately 2.7 million patient profiles and more than 8.8 million appointment records.Sign up for my FREE CyberGuy ReportGet my best tech tips, urgent security alerts, and exclusive deals delivered straight to your inbox. Plus, you’ll get instant access to my Ultimate Scam Survival Guide — free when you join. Illustration of a hacker at work  Massive healthcare data leak exposes millions: What you need to knowCybernews researchers have discovered a misconfigured MongoDB database exposing 2.7 million patient profiles and 8.8 million appointment records. The database was publicly accessible online, unprotected by passwords or authentication protocols. Anyone with basic knowledge of database scanning tools could have accessed it.The exposed data included names, birthdates, addresses, emails, phone numbers, gender, chart IDs, language preferences and billing classifications. Appointment records also contained metadata such as timestamps and institutional identifiers.MASSIVE DATA BREACH EXPOSES 184 MILLION PASSWORDS AND LOGINSClues within the data structure point toward Gargle, a Utah-based company that builds websites and offers marketing tools for dental practices. While not a confirmed source, several internal references and system details suggest a strong connection. Gargle provides appointment scheduling, form submission and patient communication services. These functions require access to patient information, making the firm a likely link in the exposure.After the issue was reported, the database was secured. The duration of the exposure remains unknown, and there is no public evidence indicating whether the data was downloaded by malicious actors before being locked down.We reached out to Gargle for a comment but did not hear back before our deadline. A healthcare professional viewing heath data     How healthcare data breaches lead to identity theft and insurance fraudThe exposed data presents a broad risk profile. On its own, a phone number or billing record might seem limited in scope. Combined, however, the dataset forms a complete profile that could be exploited for identity theft, insurance fraud and targeted phishing campaigns.Medical identity theft allows attackers to impersonate patients and access services under a false identity. Victims often remain unaware until significant damage is done, ranging from incorrect medical records to unpaid bills in their names. The leak also opens the door to insurance fraud, with actors using institutional references and chart data to submit false claims.This type of breach raises questions about compliance with the Health Insurance Portability and Accountability Act, which mandates strong security protections for entities handling patient data. Although Gargle is not a healthcare provider, its access to patient-facing infrastructure could place it under the scope of that regulation as a business associate. A healthcare professional working on a laptop  5 ways you can stay safe from healthcare data breachesIf your information was part of the healthcare breach or any similar one, it’s worth taking a few steps to protect yourself.1. Consider identity theft protection services: Since the healthcare data breach exposed personal and financial information, it’s crucial to stay proactive against identity theft. Identity theft protection services offer continuous monitoring of your credit reports, Social Security number and even the dark web to detect if your information is being misused. These services send you real-time alerts about suspicious activity, such as new credit inquiries or attempts to open accounts in your name, helping you act quickly before serious damage occurs. Beyond monitoring, many identity theft protection companies provide dedicated recovery specialists who assist you in resolving fraud issues, disputing unauthorized charges and restoring your identity if it’s compromised. See my tips and best picks on how to protect yourself from identity theft.2. Use personal data removal services: The healthcare data breach leaks loads of information about you, and all this could end up in the public domain, which essentially gives anyone an opportunity to scam you.  One proactive step is to consider personal data removal services, which specialize in continuously monitoring and removing your information from various online databases and websites. While no service promises to remove all your data from the internet, having a removal service is great if you want to constantly monitor and automate the process of removing your information from hundreds of sites continuously over a longer period of time. Check out my top picks for data removal services here. GET FOX BUSINESS ON THE GO BY CLICKING HEREGet a free scan to find out if your personal information is already out on the web3. Have strong antivirus software: Hackers have people’s email addresses and full names, which makes it easy for them to send you a phishing link that installs malware and steals all your data. These messages are socially engineered to catch them, and catching them is nearly impossible if you’re not careful. However, you’re not without defenses.The best way to safeguard yourself from malicious links that install malware, potentially accessing your private information, is to have strong antivirus software installed on all your devices. This protection can also alert you to phishing emails and ransomware scams, keeping your personal information and digital assets safe. Get my picks for the best 2025 antivirus protection winners for your Windows, Mac, Android and iOS devices.4. Enable two-factor authentication: While passwords weren’t part of the data breach, you still need to enable two-factor authentication. It gives you an extra layer of security on all your important accounts, including email, banking and social media. 2FA requires you to provide a second piece of information, such as a code sent to your phone, in addition to your password when logging in. This makes it significantly harder for hackers to access your accounts, even if they have your password. Enabling 2FA can greatly reduce the risk of unauthorized access and protect your sensitive data.5. Be wary of mailbox communications: Bad actors may also try to scam you through snail mail. The data leak gives them access to your address. They may impersonate people or brands you know and use themes that require urgent attention, such as missed deliveries, account suspensions and security alerts. Kurt’s key takeawayIf nothing else, this latest leak shows just how poorly patient data is being handled today. More and more, non-medical vendors are getting access to sensitive information without facing the same rules or oversight as hospitals and clinics. These third-party services are now a regular part of how patients book appointments, pay bills or fill out forms. But when something goes wrong, the fallout is just as serious. Even though the database was taken offline, the bigger problem hasn't gone away. Your data is only as safe as the least careful company that gets access to it.CLICK HERE TO GET THE FOX NEWS APPDo you think healthcare companies are investing enough in their cybersecurity infrastructure? Let us know by writing us at Cyberguy.com/ContactFor more of my tech tips and security alerts, subscribe to my free CyberGuy Report Newsletter by heading to Cyberguy.com/NewsletterAsk Kurt a question or let us know what stories you'd like us to coverFollow Kurt on his social channelsAnswers to the most asked CyberGuy questions:New from Kurt:Copyright 2025 CyberGuy.com.  All rights reserved.   Kurt "CyberGuy" Knutsson is an award-winning tech journalist who has a deep love of technology, gear and gadgets that make life better with his contributions for Fox News & FOX Business beginning mornings on "FOX & Friends." Got a tech question? Get Kurt’s free CyberGuy Newsletter, share your voice, a story idea or comment at CyberGuy.com.
    #over #patient #records #leaked #healthcare
    Over 8M patient records leaked in healthcare data breach
    Published June 15, 2025 10:00am EDT close IPhone users instructed to take immediate action to avoid data breach: 'Urgent threat' Kurt 'The CyberGuy' Knutsson discusses Elon Musk's possible priorities as he exits his role with the White House and explains the urgent warning for iPhone users to update devices after a 'massive security gap.' NEWYou can now listen to Fox News articles! In the past decade, healthcare data has become one of the most sought-after targets in cybercrime. From insurers to clinics, every player in the ecosystem handles some form of sensitive information. However, breaches do not always originate from hospitals or health apps. Increasingly, patient data is managed by third-party vendors offering digital services such as scheduling, billing and marketing. One such breach at a digital marketing agency serving dental practices recently exposed approximately 2.7 million patient profiles and more than 8.8 million appointment records.Sign up for my FREE CyberGuy ReportGet my best tech tips, urgent security alerts, and exclusive deals delivered straight to your inbox. Plus, you’ll get instant access to my Ultimate Scam Survival Guide — free when you join. Illustration of a hacker at work  Massive healthcare data leak exposes millions: What you need to knowCybernews researchers have discovered a misconfigured MongoDB database exposing 2.7 million patient profiles and 8.8 million appointment records. The database was publicly accessible online, unprotected by passwords or authentication protocols. Anyone with basic knowledge of database scanning tools could have accessed it.The exposed data included names, birthdates, addresses, emails, phone numbers, gender, chart IDs, language preferences and billing classifications. Appointment records also contained metadata such as timestamps and institutional identifiers.MASSIVE DATA BREACH EXPOSES 184 MILLION PASSWORDS AND LOGINSClues within the data structure point toward Gargle, a Utah-based company that builds websites and offers marketing tools for dental practices. While not a confirmed source, several internal references and system details suggest a strong connection. Gargle provides appointment scheduling, form submission and patient communication services. These functions require access to patient information, making the firm a likely link in the exposure.After the issue was reported, the database was secured. The duration of the exposure remains unknown, and there is no public evidence indicating whether the data was downloaded by malicious actors before being locked down.We reached out to Gargle for a comment but did not hear back before our deadline. A healthcare professional viewing heath data     How healthcare data breaches lead to identity theft and insurance fraudThe exposed data presents a broad risk profile. On its own, a phone number or billing record might seem limited in scope. Combined, however, the dataset forms a complete profile that could be exploited for identity theft, insurance fraud and targeted phishing campaigns.Medical identity theft allows attackers to impersonate patients and access services under a false identity. Victims often remain unaware until significant damage is done, ranging from incorrect medical records to unpaid bills in their names. The leak also opens the door to insurance fraud, with actors using institutional references and chart data to submit false claims.This type of breach raises questions about compliance with the Health Insurance Portability and Accountability Act, which mandates strong security protections for entities handling patient data. Although Gargle is not a healthcare provider, its access to patient-facing infrastructure could place it under the scope of that regulation as a business associate. A healthcare professional working on a laptop  5 ways you can stay safe from healthcare data breachesIf your information was part of the healthcare breach or any similar one, it’s worth taking a few steps to protect yourself.1. Consider identity theft protection services: Since the healthcare data breach exposed personal and financial information, it’s crucial to stay proactive against identity theft. Identity theft protection services offer continuous monitoring of your credit reports, Social Security number and even the dark web to detect if your information is being misused. These services send you real-time alerts about suspicious activity, such as new credit inquiries or attempts to open accounts in your name, helping you act quickly before serious damage occurs. Beyond monitoring, many identity theft protection companies provide dedicated recovery specialists who assist you in resolving fraud issues, disputing unauthorized charges and restoring your identity if it’s compromised. See my tips and best picks on how to protect yourself from identity theft.2. Use personal data removal services: The healthcare data breach leaks loads of information about you, and all this could end up in the public domain, which essentially gives anyone an opportunity to scam you.  One proactive step is to consider personal data removal services, which specialize in continuously monitoring and removing your information from various online databases and websites. While no service promises to remove all your data from the internet, having a removal service is great if you want to constantly monitor and automate the process of removing your information from hundreds of sites continuously over a longer period of time. Check out my top picks for data removal services here. GET FOX BUSINESS ON THE GO BY CLICKING HEREGet a free scan to find out if your personal information is already out on the web3. Have strong antivirus software: Hackers have people’s email addresses and full names, which makes it easy for them to send you a phishing link that installs malware and steals all your data. These messages are socially engineered to catch them, and catching them is nearly impossible if you’re not careful. However, you’re not without defenses.The best way to safeguard yourself from malicious links that install malware, potentially accessing your private information, is to have strong antivirus software installed on all your devices. This protection can also alert you to phishing emails and ransomware scams, keeping your personal information and digital assets safe. Get my picks for the best 2025 antivirus protection winners for your Windows, Mac, Android and iOS devices.4. Enable two-factor authentication: While passwords weren’t part of the data breach, you still need to enable two-factor authentication. It gives you an extra layer of security on all your important accounts, including email, banking and social media. 2FA requires you to provide a second piece of information, such as a code sent to your phone, in addition to your password when logging in. This makes it significantly harder for hackers to access your accounts, even if they have your password. Enabling 2FA can greatly reduce the risk of unauthorized access and protect your sensitive data.5. Be wary of mailbox communications: Bad actors may also try to scam you through snail mail. The data leak gives them access to your address. They may impersonate people or brands you know and use themes that require urgent attention, such as missed deliveries, account suspensions and security alerts. Kurt’s key takeawayIf nothing else, this latest leak shows just how poorly patient data is being handled today. More and more, non-medical vendors are getting access to sensitive information without facing the same rules or oversight as hospitals and clinics. These third-party services are now a regular part of how patients book appointments, pay bills or fill out forms. But when something goes wrong, the fallout is just as serious. Even though the database was taken offline, the bigger problem hasn't gone away. Your data is only as safe as the least careful company that gets access to it.CLICK HERE TO GET THE FOX NEWS APPDo you think healthcare companies are investing enough in their cybersecurity infrastructure? Let us know by writing us at Cyberguy.com/ContactFor more of my tech tips and security alerts, subscribe to my free CyberGuy Report Newsletter by heading to Cyberguy.com/NewsletterAsk Kurt a question or let us know what stories you'd like us to coverFollow Kurt on his social channelsAnswers to the most asked CyberGuy questions:New from Kurt:Copyright 2025 CyberGuy.com.  All rights reserved.   Kurt "CyberGuy" Knutsson is an award-winning tech journalist who has a deep love of technology, gear and gadgets that make life better with his contributions for Fox News & FOX Business beginning mornings on "FOX & Friends." Got a tech question? Get Kurt’s free CyberGuy Newsletter, share your voice, a story idea or comment at CyberGuy.com. #over #patient #records #leaked #healthcare
    Over 8M patient records leaked in healthcare data breach
    www.foxnews.com
    Published June 15, 2025 10:00am EDT close IPhone users instructed to take immediate action to avoid data breach: 'Urgent threat' Kurt 'The CyberGuy' Knutsson discusses Elon Musk's possible priorities as he exits his role with the White House and explains the urgent warning for iPhone users to update devices after a 'massive security gap.' NEWYou can now listen to Fox News articles! In the past decade, healthcare data has become one of the most sought-after targets in cybercrime. From insurers to clinics, every player in the ecosystem handles some form of sensitive information. However, breaches do not always originate from hospitals or health apps. Increasingly, patient data is managed by third-party vendors offering digital services such as scheduling, billing and marketing. One such breach at a digital marketing agency serving dental practices recently exposed approximately 2.7 million patient profiles and more than 8.8 million appointment records.Sign up for my FREE CyberGuy ReportGet my best tech tips, urgent security alerts, and exclusive deals delivered straight to your inbox. Plus, you’ll get instant access to my Ultimate Scam Survival Guide — free when you join. Illustration of a hacker at work   (Kurt "CyberGuy" Knutsson)Massive healthcare data leak exposes millions: What you need to knowCybernews researchers have discovered a misconfigured MongoDB database exposing 2.7 million patient profiles and 8.8 million appointment records. The database was publicly accessible online, unprotected by passwords or authentication protocols. Anyone with basic knowledge of database scanning tools could have accessed it.The exposed data included names, birthdates, addresses, emails, phone numbers, gender, chart IDs, language preferences and billing classifications. Appointment records also contained metadata such as timestamps and institutional identifiers.MASSIVE DATA BREACH EXPOSES 184 MILLION PASSWORDS AND LOGINSClues within the data structure point toward Gargle, a Utah-based company that builds websites and offers marketing tools for dental practices. While not a confirmed source, several internal references and system details suggest a strong connection. Gargle provides appointment scheduling, form submission and patient communication services. These functions require access to patient information, making the firm a likely link in the exposure.After the issue was reported, the database was secured. The duration of the exposure remains unknown, and there is no public evidence indicating whether the data was downloaded by malicious actors before being locked down.We reached out to Gargle for a comment but did not hear back before our deadline. A healthcare professional viewing heath data      (Kurt "CyberGuy" Knutsson)How healthcare data breaches lead to identity theft and insurance fraudThe exposed data presents a broad risk profile. On its own, a phone number or billing record might seem limited in scope. Combined, however, the dataset forms a complete profile that could be exploited for identity theft, insurance fraud and targeted phishing campaigns.Medical identity theft allows attackers to impersonate patients and access services under a false identity. Victims often remain unaware until significant damage is done, ranging from incorrect medical records to unpaid bills in their names. The leak also opens the door to insurance fraud, with actors using institutional references and chart data to submit false claims.This type of breach raises questions about compliance with the Health Insurance Portability and Accountability Act, which mandates strong security protections for entities handling patient data. Although Gargle is not a healthcare provider, its access to patient-facing infrastructure could place it under the scope of that regulation as a business associate. A healthcare professional working on a laptop   (Kurt "CyberGuy" Knutsson)5 ways you can stay safe from healthcare data breachesIf your information was part of the healthcare breach or any similar one, it’s worth taking a few steps to protect yourself.1. Consider identity theft protection services: Since the healthcare data breach exposed personal and financial information, it’s crucial to stay proactive against identity theft. Identity theft protection services offer continuous monitoring of your credit reports, Social Security number and even the dark web to detect if your information is being misused. These services send you real-time alerts about suspicious activity, such as new credit inquiries or attempts to open accounts in your name, helping you act quickly before serious damage occurs. Beyond monitoring, many identity theft protection companies provide dedicated recovery specialists who assist you in resolving fraud issues, disputing unauthorized charges and restoring your identity if it’s compromised. See my tips and best picks on how to protect yourself from identity theft.2. Use personal data removal services: The healthcare data breach leaks loads of information about you, and all this could end up in the public domain, which essentially gives anyone an opportunity to scam you.  One proactive step is to consider personal data removal services, which specialize in continuously monitoring and removing your information from various online databases and websites. While no service promises to remove all your data from the internet, having a removal service is great if you want to constantly monitor and automate the process of removing your information from hundreds of sites continuously over a longer period of time. Check out my top picks for data removal services here. GET FOX BUSINESS ON THE GO BY CLICKING HEREGet a free scan to find out if your personal information is already out on the web3. Have strong antivirus software: Hackers have people’s email addresses and full names, which makes it easy for them to send you a phishing link that installs malware and steals all your data. These messages are socially engineered to catch them, and catching them is nearly impossible if you’re not careful. However, you’re not without defenses.The best way to safeguard yourself from malicious links that install malware, potentially accessing your private information, is to have strong antivirus software installed on all your devices. This protection can also alert you to phishing emails and ransomware scams, keeping your personal information and digital assets safe. Get my picks for the best 2025 antivirus protection winners for your Windows, Mac, Android and iOS devices.4. Enable two-factor authentication: While passwords weren’t part of the data breach, you still need to enable two-factor authentication (2FA). It gives you an extra layer of security on all your important accounts, including email, banking and social media. 2FA requires you to provide a second piece of information, such as a code sent to your phone, in addition to your password when logging in. This makes it significantly harder for hackers to access your accounts, even if they have your password. Enabling 2FA can greatly reduce the risk of unauthorized access and protect your sensitive data.5. Be wary of mailbox communications: Bad actors may also try to scam you through snail mail. The data leak gives them access to your address. They may impersonate people or brands you know and use themes that require urgent attention, such as missed deliveries, account suspensions and security alerts. Kurt’s key takeawayIf nothing else, this latest leak shows just how poorly patient data is being handled today. More and more, non-medical vendors are getting access to sensitive information without facing the same rules or oversight as hospitals and clinics. These third-party services are now a regular part of how patients book appointments, pay bills or fill out forms. But when something goes wrong, the fallout is just as serious. Even though the database was taken offline, the bigger problem hasn't gone away. Your data is only as safe as the least careful company that gets access to it.CLICK HERE TO GET THE FOX NEWS APPDo you think healthcare companies are investing enough in their cybersecurity infrastructure? Let us know by writing us at Cyberguy.com/ContactFor more of my tech tips and security alerts, subscribe to my free CyberGuy Report Newsletter by heading to Cyberguy.com/NewsletterAsk Kurt a question or let us know what stories you'd like us to coverFollow Kurt on his social channelsAnswers to the most asked CyberGuy questions:New from Kurt:Copyright 2025 CyberGuy.com.  All rights reserved.   Kurt "CyberGuy" Knutsson is an award-winning tech journalist who has a deep love of technology, gear and gadgets that make life better with his contributions for Fox News & FOX Business beginning mornings on "FOX & Friends." Got a tech question? Get Kurt’s free CyberGuy Newsletter, share your voice, a story idea or comment at CyberGuy.com.
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