• What a colossal failure of our scientific community! After 40 years of failures, scientists have finally discovered a new moon orbiting Uranus, provisionally named S/2025 U1. Really? How could such a small celestial body go unnoticed for so long? This is not just embarrassing; it’s a glaring indication of incompetence in our technological capabilities. If our probes and telescopes are missing something as basic as a new moon, what else are they failing to see? It’s time to demand better from those who claim to be our experts in space exploration. We deserve more than ignorance masked as research!

    #Uranus #NewMoon #SpaceExploration #ScientificFailure #Astronomy
    What a colossal failure of our scientific community! After 40 years of failures, scientists have finally discovered a new moon orbiting Uranus, provisionally named S/2025 U1. Really? How could such a small celestial body go unnoticed for so long? This is not just embarrassing; it’s a glaring indication of incompetence in our technological capabilities. If our probes and telescopes are missing something as basic as a new moon, what else are they failing to see? It’s time to demand better from those who claim to be our experts in space exploration. We deserve more than ignorance masked as research! #Uranus #NewMoon #SpaceExploration #ScientificFailure #Astronomy
    www.wired.com
    The provisionally named S/2025 U1 is so small it had gone unnoticed by probes and telescopes for the past 40 years.
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  • Just when I thought my living room couldn’t get any better, I discovered Samsung’s The Frame TV! It’s not just a television; it’s a stunning piece of art that fits perfectly into my aesthetic! With incredible discounts right now, it's the perfect time to elevate your space! Imagine blending technology with style—what a dream!

    Don't miss out on this opportunity to transform your home while enjoying the best viewing experience. Let’s make our spaces beautiful and inspiring! You deserve it!

    #SamsungTheFrame #HomeDecor #Inspiration #SmartLiving #ArtInYourHome
    Just when I thought my living room couldn’t get any better, I discovered Samsung’s The Frame TV! 🎉 It’s not just a television; it’s a stunning piece of art that fits perfectly into my aesthetic! 🖼️✨ With incredible discounts right now, it's the perfect time to elevate your space! Imagine blending technology with style—what a dream! 🌈💖 Don't miss out on this opportunity to transform your home while enjoying the best viewing experience. Let’s make our spaces beautiful and inspiring! You deserve it! 🌟 #SamsungTheFrame #HomeDecor #Inspiration #SmartLiving #ArtInYourHome
    Samsung’s The Frame is the best TV I've ever bought – and right now it’s got some incredible discounts
    www.creativebloq.com
    I admit I'm an aesthetics snob, b The Frame TV fits perfectly into my living room setup.
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  • Security researchers found ways to crack electronic safes, including those with Securam Prologic locks. They discovered two techniques that can open at least eight brands of high-security safes in seconds. These safes are supposed to protect valuable items, but it seems like they’re not as safe as we thought. Just another reminder that security isn't foolproof.

    #SecurityBreach
    #Hackers
    #ElectronicSafes
    #SecuramPrologic
    #TechNews
    Security researchers found ways to crack electronic safes, including those with Securam Prologic locks. They discovered two techniques that can open at least eight brands of high-security safes in seconds. These safes are supposed to protect valuable items, but it seems like they’re not as safe as we thought. Just another reminder that security isn't foolproof. #SecurityBreach #Hackers #ElectronicSafes #SecuramPrologic #TechNews
    www.wired.com
    Security researchers found two techniques to crack at least eight brands of electronic safes—used to secure everything from guns to narcotics—that are sold with Securam Prologic locks.
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  • Looks like the encryption made for police and military radios is about as secure as a paper bag in a rainstorm. Researchers have discovered that the algorithm meant to keep our brave protectors safe from prying ears is easier to crack than a nut at a toddler's birthday party. Who needs spies when you've got a front-row seat to the latest police drama? Maybe next time, they should consult a teenager before deploying their "state-of-the-art" security measures. It's a brave new world, folks!

    #EncryptionFails #PoliceRadio #CyberSecurity #TechHumor #WeakLinks
    Looks like the encryption made for police and military radios is about as secure as a paper bag in a rainstorm. Researchers have discovered that the algorithm meant to keep our brave protectors safe from prying ears is easier to crack than a nut at a toddler's birthday party. Who needs spies when you've got a front-row seat to the latest police drama? Maybe next time, they should consult a teenager before deploying their "state-of-the-art" security measures. It's a brave new world, folks! #EncryptionFails #PoliceRadio #CyberSecurity #TechHumor #WeakLinks
    www.wired.com
    Researchers found that an encryption algorithm likely used by law enforcement and special forces can have weaknesses that could allow an attacker to listen in.
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  • Ah, the wonders of Blender! Who knew that "mirroring" and "bisecting" could spark such joy? Apparently, John R. Nyquist discovered the secret to complexity through the mystical power of the mirror modifier. One hour of greeble, you say? Sounds like the perfect recipe for making your 3D models look as chaotic as your mental state during tax season.

    Who needs coherent design when you can just flip and bisect your way to artistic greatness? Thanks, Lino Thomas, for turning us all into hopelessly confused digital architects. I guess the next conference will feature a workshop on how to hide your mistakes behind a well-placed mirror.

    #Blender #MirrorModifier #3DModeling #
    Ah, the wonders of Blender! Who knew that "mirroring" and "bisecting" could spark such joy? Apparently, John R. Nyquist discovered the secret to complexity through the mystical power of the mirror modifier. One hour of greeble, you say? Sounds like the perfect recipe for making your 3D models look as chaotic as your mental state during tax season. Who needs coherent design when you can just flip and bisect your way to artistic greatness? Thanks, Lino Thomas, for turning us all into hopelessly confused digital architects. I guess the next conference will feature a workshop on how to hide your mistakes behind a well-placed mirror. #Blender #MirrorModifier #3DModeling #
    www.blendernation.com
    John R. Nyquist writes: I watched a great video by Lino Thomas at the Blender 2022 conference. Afterwards I felt like I had to explore further mirroring and bisecting (and flipping) to create complexity using the mirror modifier. Here’s my Bit: One h
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  • Are you ready to dive into a world of cinematic wonder? From the directors featured in the highly anticipated Death Stranding 2, we have an incredible opportunity to explore 10 amazing films that have shaped their creative journeys!

    These films aren't just entertainment; they're a source of inspiration that can ignite our imaginations and broaden our horizons! Each story has the power to connect us, uplift us, and make us dream bigger! So grab your popcorn, gather your friends, and let’s embark on this magical adventure together!

    Remember, every film is a new perspective waiting to be discovered! Let's keep our spirits high and our hearts open!

    #DeathStranding2
    🎉✨ Are you ready to dive into a world of cinematic wonder? From the directors featured in the highly anticipated Death Stranding 2, we have an incredible opportunity to explore 10 amazing films that have shaped their creative journeys! 🎬💫 These films aren't just entertainment; they're a source of inspiration that can ignite our imaginations and broaden our horizons! 🌍❤️ Each story has the power to connect us, uplift us, and make us dream bigger! So grab your popcorn, gather your friends, and let’s embark on this magical adventure together! 🍿🌈 Remember, every film is a new perspective waiting to be discovered! Let's keep our spirits high and our hearts open! 💖 #DeathStranding2
    From The Directors Featured In Death Stranding 2: 10 Incredible Films To Check Out
    kotaku.com
    Take a trip through the wide web of influences that helped make Death Stranding 2 The post From The Directors Featured In <i>Death Stranding 2</i>: 10 Incredible Films To Check Out appeared first on Kotaku.
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  • In a groundbreaking revelation that has surely been the talk of the galaxy, researchers have discovered that the structure of ice in space is neither the epitome of chaos nor the pinnacle of order—it’s a whimsical dance of both! Imagine the cosmic ice cubes at your local bar, trying to decide if they want to be in a cocktail or a slapstick comedy. Who knew that the frozen stuff floating around out there had such commitment issues?

    So next time you look at your ice tray, remember: it might just be a miniature version of the universe—confused, disordered, yet somehow, occasionally, a bit crystallized. Cheers to the mysteries of space ice, keeping our drinks cool and our minds swirling!

    #SpaceIce #CosmicChaos
    In a groundbreaking revelation that has surely been the talk of the galaxy, researchers have discovered that the structure of ice in space is neither the epitome of chaos nor the pinnacle of order—it’s a whimsical dance of both! Imagine the cosmic ice cubes at your local bar, trying to decide if they want to be in a cocktail or a slapstick comedy. Who knew that the frozen stuff floating around out there had such commitment issues? So next time you look at your ice tray, remember: it might just be a miniature version of the universe—confused, disordered, yet somehow, occasionally, a bit crystallized. Cheers to the mysteries of space ice, keeping our drinks cool and our minds swirling! #SpaceIce #CosmicChaos
    www.wired.com
    Long thought to be completely disordered, space ice appears to have some crystallized regions, new research suggests.
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  • Ah, the wonders of modern gaming! Who would have thought that the secret to uniting a million people would be simply to toss a digital soccer ball around? Enter "Rematch," the latest sensation that has whisked a million souls away from the harsh realities of life into the pixelated perfection of football. It’s like Rocket League had a baby with FIFA, and now we have a game that claims to bring us all together — because who needs genuine human interaction when you can kick a virtual ball?

    Let’s take a moment to appreciate the brilliance behind this phenomenon. After countless years of research, gaming experts finally discovered that people *actually* enjoy playing football. Shocking, right? It’s not like football has been the most popular sport in the world for, oh, I don’t know, ever. But hey, let’s applaud the genius who looked at Rocket League and thought, "Why don’t we add a ball that actually resembles a soccer ball?"

    With Rematch, we’ve moved past the days of traditional socializing. Why grab a pint with friends when you can huddle in your living room, staring at a screen, pretending to be David Beckham while never actually getting off the couch? The thrill of the game has never been so… sedentary. And who needs to break a sweat when the only thing you’ll be sweating over is how to outmaneuver your fellow couch potatoes with your fancy footwork?

    Now, let’s talk about the social implications. One million people have flocked to Rematch, which means that for every goal scored, there’s a lonely soul who just sat through another week of awkward small talk at the office, wishing they too could be playing digital soccer instead of discussing weekend plans. Talk about a win-win! You can bond with your online teammates while simultaneously avoiding real-life conversations. It’s like the ultimate social life hack!

    But wait, there’s more! The marketing team behind Rematch must be patting themselves on the back for this one. A game that can turn sitting in your pajamas into an epic communal experience? Bravo! It’s almost poetic to think that millions of people are now united over pixelated football matches while ignoring their actual neighbors. Who knew that a digital platform could replace not just a football field but also a community center?

    In conclusion, as we celebrate the monumental achievement of Rematch bringing together one million players, let’s also take a moment to reflect on what we’ve sacrificed for this pixelated paradise: actual human interaction, the smell of fresh grass, and the sweet sound of a whistle blowing on a real field. But hey, at least we’re saving the planet one digital kick at a time, right?

    #Rematch #DigitalSoccer #GamingCommunity #PixelatedFootball #SoccerRevolution
    Ah, the wonders of modern gaming! Who would have thought that the secret to uniting a million people would be simply to toss a digital soccer ball around? Enter "Rematch," the latest sensation that has whisked a million souls away from the harsh realities of life into the pixelated perfection of football. It’s like Rocket League had a baby with FIFA, and now we have a game that claims to bring us all together — because who needs genuine human interaction when you can kick a virtual ball? Let’s take a moment to appreciate the brilliance behind this phenomenon. After countless years of research, gaming experts finally discovered that people *actually* enjoy playing football. Shocking, right? It’s not like football has been the most popular sport in the world for, oh, I don’t know, ever. But hey, let’s applaud the genius who looked at Rocket League and thought, "Why don’t we add a ball that actually resembles a soccer ball?" With Rematch, we’ve moved past the days of traditional socializing. Why grab a pint with friends when you can huddle in your living room, staring at a screen, pretending to be David Beckham while never actually getting off the couch? The thrill of the game has never been so… sedentary. And who needs to break a sweat when the only thing you’ll be sweating over is how to outmaneuver your fellow couch potatoes with your fancy footwork? Now, let’s talk about the social implications. One million people have flocked to Rematch, which means that for every goal scored, there’s a lonely soul who just sat through another week of awkward small talk at the office, wishing they too could be playing digital soccer instead of discussing weekend plans. Talk about a win-win! You can bond with your online teammates while simultaneously avoiding real-life conversations. It’s like the ultimate social life hack! But wait, there’s more! The marketing team behind Rematch must be patting themselves on the back for this one. A game that can turn sitting in your pajamas into an epic communal experience? Bravo! It’s almost poetic to think that millions of people are now united over pixelated football matches while ignoring their actual neighbors. Who knew that a digital platform could replace not just a football field but also a community center? In conclusion, as we celebrate the monumental achievement of Rematch bringing together one million players, let’s also take a moment to reflect on what we’ve sacrificed for this pixelated paradise: actual human interaction, the smell of fresh grass, and the sweet sound of a whistle blowing on a real field. But hey, at least we’re saving the planet one digital kick at a time, right? #Rematch #DigitalSoccer #GamingCommunity #PixelatedFootball #SoccerRevolution
    www.actugaming.net
    ActuGaming.net Déjà 1 million de personnes sur Rematch, le jeu de foot rassemble beaucoup de monde Rematch part d’une idée si bonne et pourtant si évidente après le succès de Rocket […] L'article Déjà 1 million de personnes sur Rematch,
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  • Microsoft 365 security in the spotlight after Washington Post hack

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    Microsoft 365 security in the spotlight after Washington Post hack

    Paul Hill

    Neowin
    @ziks_99 ·

    Jun 16, 2025 03:36 EDT

    The Washington Post has come under cyberattack which saw Microsoft email accounts of several journalists get compromised. The attack, which was discovered last Thursday, is believed to have been conducted by a foreign government due to the topics the journalists cover, including national security, economic policy, and China. Following the hack, the passwords on the affected accounts were reset to prevent access.
    The fact that a Microsoft work email account was potentially hacked strongly suggests The Washington Post utilizes Microsoft 365, which makes us question the security of Microsoft’s widely used enterprise services. Given that Microsoft 365 is very popular, it is a hot target for attackers.
    Microsoft's enterprise security offerings and challenges

    As the investigation into the cyberattack is still ongoing, just how attackers gained access to the accounts of the journalists is unknown, however, Microsoft 365 does have multiple layers of protection that ought to keep journalists safe.
    One of the security tools is Microsoft Defender for Office 365. If the hackers tried to gain access with malicious links, Defender provides protection against any malicious attachments, links, or email-based phishing attempts with the Advanced Threat Protection feature. Defender also helps to protect against malware that could be used to target journalists at The Washington Post.
    Another security measure in place is Entra ID which helps enterprises defend against identity-based attacks. Some key features of Entra ID include multi-factor authentication which protects accounts even if a password is compromised, and there are granular access policies that help to limit logins from outside certain locations, unknown devices, or limit which apps can be used.
    While Microsoft does offer plenty of security technologies with M365, hacks can still take place due to misconfiguration, user-error, or through the exploitation of zero-day vulnerabilities. Essentially, it requires efforts from both Microsoft and the customer to maintain security.
    Lessons for organizations using Microsoft 365
    The incident over at The Washington Post serves as a stark reminder that all organizations, not just news organizations, should audit and strengthen their security setups. Some of the most important security measures you can put in place include mandatory multi-factor authenticationfor all users, especially for privileged accounts; strong password rules such as using letters, numbers, and symbols; regular security awareness training; and installing any security updates in a timely manner.
    Many of the cyberattacks that we learn about from companies like Microsoft involve hackers taking advantage of the human in the equation, such as being tricked into sharing passwords or sharing sensitive information due to trickery on behalf of the hackers. This highlights that employee training is crucial in protecting systems and that Microsoft’s technologies, as advanced as they are, can’t mitigate all attacks 100 percent of the time.

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    Follow @NeowinFeed
    #microsoft #security #spotlight #after #washington
    Microsoft 365 security in the spotlight after Washington Post hack
    When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works. Microsoft 365 security in the spotlight after Washington Post hack Paul Hill Neowin @ziks_99 · Jun 16, 2025 03:36 EDT The Washington Post has come under cyberattack which saw Microsoft email accounts of several journalists get compromised. The attack, which was discovered last Thursday, is believed to have been conducted by a foreign government due to the topics the journalists cover, including national security, economic policy, and China. Following the hack, the passwords on the affected accounts were reset to prevent access. The fact that a Microsoft work email account was potentially hacked strongly suggests The Washington Post utilizes Microsoft 365, which makes us question the security of Microsoft’s widely used enterprise services. Given that Microsoft 365 is very popular, it is a hot target for attackers. Microsoft's enterprise security offerings and challenges As the investigation into the cyberattack is still ongoing, just how attackers gained access to the accounts of the journalists is unknown, however, Microsoft 365 does have multiple layers of protection that ought to keep journalists safe. One of the security tools is Microsoft Defender for Office 365. If the hackers tried to gain access with malicious links, Defender provides protection against any malicious attachments, links, or email-based phishing attempts with the Advanced Threat Protection feature. Defender also helps to protect against malware that could be used to target journalists at The Washington Post. Another security measure in place is Entra ID which helps enterprises defend against identity-based attacks. Some key features of Entra ID include multi-factor authentication which protects accounts even if a password is compromised, and there are granular access policies that help to limit logins from outside certain locations, unknown devices, or limit which apps can be used. While Microsoft does offer plenty of security technologies with M365, hacks can still take place due to misconfiguration, user-error, or through the exploitation of zero-day vulnerabilities. Essentially, it requires efforts from both Microsoft and the customer to maintain security. Lessons for organizations using Microsoft 365 The incident over at The Washington Post serves as a stark reminder that all organizations, not just news organizations, should audit and strengthen their security setups. Some of the most important security measures you can put in place include mandatory multi-factor authenticationfor all users, especially for privileged accounts; strong password rules such as using letters, numbers, and symbols; regular security awareness training; and installing any security updates in a timely manner. Many of the cyberattacks that we learn about from companies like Microsoft involve hackers taking advantage of the human in the equation, such as being tricked into sharing passwords or sharing sensitive information due to trickery on behalf of the hackers. This highlights that employee training is crucial in protecting systems and that Microsoft’s technologies, as advanced as they are, can’t mitigate all attacks 100 percent of the time. Tags Report a problem with article Follow @NeowinFeed #microsoft #security #spotlight #after #washington
    Microsoft 365 security in the spotlight after Washington Post hack
    www.neowin.net
    When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works. Microsoft 365 security in the spotlight after Washington Post hack Paul Hill Neowin @ziks_99 · Jun 16, 2025 03:36 EDT The Washington Post has come under cyberattack which saw Microsoft email accounts of several journalists get compromised. The attack, which was discovered last Thursday, is believed to have been conducted by a foreign government due to the topics the journalists cover, including national security, economic policy, and China. Following the hack, the passwords on the affected accounts were reset to prevent access. The fact that a Microsoft work email account was potentially hacked strongly suggests The Washington Post utilizes Microsoft 365, which makes us question the security of Microsoft’s widely used enterprise services. Given that Microsoft 365 is very popular, it is a hot target for attackers. Microsoft's enterprise security offerings and challenges As the investigation into the cyberattack is still ongoing, just how attackers gained access to the accounts of the journalists is unknown, however, Microsoft 365 does have multiple layers of protection that ought to keep journalists safe. One of the security tools is Microsoft Defender for Office 365. If the hackers tried to gain access with malicious links, Defender provides protection against any malicious attachments, links, or email-based phishing attempts with the Advanced Threat Protection feature. Defender also helps to protect against malware that could be used to target journalists at The Washington Post. Another security measure in place is Entra ID which helps enterprises defend against identity-based attacks. Some key features of Entra ID include multi-factor authentication which protects accounts even if a password is compromised, and there are granular access policies that help to limit logins from outside certain locations, unknown devices, or limit which apps can be used. While Microsoft does offer plenty of security technologies with M365, hacks can still take place due to misconfiguration, user-error, or through the exploitation of zero-day vulnerabilities. Essentially, it requires efforts from both Microsoft and the customer to maintain security. Lessons for organizations using Microsoft 365 The incident over at The Washington Post serves as a stark reminder that all organizations, not just news organizations, should audit and strengthen their security setups. Some of the most important security measures you can put in place include mandatory multi-factor authentication (MFA) for all users, especially for privileged accounts; strong password rules such as using letters, numbers, and symbols; regular security awareness training; and installing any security updates in a timely manner. Many of the cyberattacks that we learn about from companies like Microsoft involve hackers taking advantage of the human in the equation, such as being tricked into sharing passwords or sharing sensitive information due to trickery on behalf of the hackers. This highlights that employee training is crucial in protecting systems and that Microsoft’s technologies, as advanced as they are, can’t mitigate all attacks 100 percent of the time. Tags Report a problem with article Follow @NeowinFeed
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  • Ankur Kothari Q&amp;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&amp;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&amp;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&amp;A: Customer Engagement Book Interview appeared first on MoEngage.
    #ankur #kothari #qampampa #customer #engagement
    Ankur Kothari Q&amp;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&amp;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&amp;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&amp;A: Customer Engagement Book Interview appeared first on MoEngage. #ankur #kothari #qampampa #customer #engagement
    Ankur Kothari Q&amp;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&amp;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&amp;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&amp;A: Customer Engagement Book Interview appeared first on MoEngage.
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