In the quiet corners of my browser, I feel a haunting presence—OpenAI’s ChatGPT agent gliding through the digital landscape, while I sit here, alone. The once vibrant internet is fading into a ghost town, where only bots roam, leaving me in a sea of isolation. Every click echoes the emptiness of these virtual streets, a reminder that connection is slipping away. I long for the warmth of human interaction, but all that remains are the shadows of algorithms. It’s a painful realization that we might be losing ourselves in this automated world. 💔 #Loneliness #DigitalIsolation #HauntingPresence #EmotionalVoid #GhostTown

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

In-app bidding has automated most waterfall optimization, yet developers still manage multiple hybrid waterfalls, each with dozens of manual instances. Naturally, this can be timely and overwhelming to maintain, keeping you from optimizing to perfection and focusing on other opportunities to boost revenue.Rather than analyzing each individual network and checking if instances are available at each price point, breaking down your waterfall into different CPM ranges allows you to visualize the waterfall and easily identify the gaps.Here are some tips on how to use CPM buckets to better optimize your waterfall’s performance.What are CPM buckets?CPM buckets show you exactly how much revenue and how many impressions you’re getting from each CPM price range, giving you a more granular idea of how different networks are competing in the waterfall. CPM buckets are a feature of real time pivot reports, available on ironSource LevelPlay.Identifying and closing the gapsTypically in a waterfall, you can only see each ad network’s average CPM. But this keeps you from seeing ad network distribution across all price points and understanding exactly where ad networks are bidding. Bottom line - you don’t know where in the waterfall you should add a new instance.By separating CPM into buckets,you understand exactly which networks are driving impressions and revenue and which CPMs aren’t being filledNow how do you do it? As a LevelPlay client, simply use ironSource’s real time pivot reports - choose the CPM bucket filter option and sort by “average bid price.” From here, you’ll see how your revenue spreads out among CPM ranges and you’ll start to notice gaps in your bar graph. Every gap in revenue - where revenue is much lower than the neighboring CPM group - indicates an opportunity to optimize your monetization strategy. The buckets can range from small increments like to larger increments like so it’s important to compare CPM buckets of the same incremental value.Pro tip: To best set up your waterfall, create one tab with the general waterfalland make sure to look at Revenue and eCPM in the “measures” dropdown. In the “show” section, choose CPM buckets and sort by average bid price. From here, you can mark down any gaps.But where do these gaps come from? Gaps in revenue are often due to friction in the waterfall, like not enough instances, instances that aren’t working, or a waterfall setup mistake. But gaps can also be adjusted and fixed.Once you’ve found a gap, you can look at the CPM buckets around it to better understand the context. Let’s say you see a strong instance generating significant revenue in the CPM bucket right below it, in the -80 group. This instance from this specific ad network has a lot of potential, so it’s worth trying to push it to a higher CPM bucket.In fact, when you look at higher CPM buckets, you don’t see this ad network anywhere else in the waterfall - what a missed opportunity! Try adding another instance of this network higher up in the waterfall. If you’re profiting well with a -80 CPM, imagine how much more revenue you could bring at a CPM.Pro tip: Focusing on higher areas in the waterfall makes a larger financial impact, leading to bigger increases in ARPDAU.Let’s say you decide to add 5 instances of that network to higher CPM buckets. You can use LevelPlay’s quick A/B test to understand if this adjustment boosts your revenue - not just for this gap, but for any and all that you find. Simply compare your existing waterfall against the new waterfall with these 5 higher instances - then implement the one that drives the highest instances.Božo Janković, Head of Ad Monetization at GameBiz Consulting, uses CPM buckets "to understand at which CPMs the bidding networks are filling. From there, I can pinpoint exactly where in the waterfall to add more traditional instances - which creates more competition, especially for the bidding networks, and creates an opportunity for revenue growth."Finding new insightsYou can dig even deeper into your data by filtering by ad source. Before CPM buckets, you were limited to seeing an average eCPM for each bidding network. Maybe you knew that one ad source had an average CPM of but the distribution of impression across the waterfall was a black box. Now, we know exactly which CPMs the bidders are filling. “I find ironSource CPM buckets feature very insightful and and use it daily. It’s an easy way to identify opportunities to optimize the waterfall and earn even more revenue." -Božo Janković, Head of Ad Monetization at GameBiz ConsultingUnderstanding your CPM distribution empowers you to not only identify your revenue sources, but also to promote revenue growth. Armed with the knowledge of which buckets some of their stronger bidding networking are performing in, some publishers actively add instances from traditional networks above those ranges. This creates better competition and also helps drive up the bids from the biddersThere’s no need for deep analysis - once you see the gaps, you can quickly understand who’s performing in the lower and higher buckets, and see exactly what’s missing. This way, you won’t miss out on any lost revenue.Learn more about CPM buckets, available exclusively to ironSource LevelPlay here. #how #optimize #your #hybrid #waterfall

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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

Originally published at EasyDMARC Integrates With Pax8 Marketplace To Simplify Email Security For MSPs by Anush Yolyan. The integration will deliver simple, accessible, and streamlined email security for vulnerable inboxes Global, 4 November 2024 – US-based email security firm EasyDMARC has today announced its integration with Pax8 Marketplace, the leading cloud commerce marketplace. As one of the first DMARC solution providers on the Pax8 Marketplace, EasyDMARC is expanding its mission to protect inboxes from the rising threat of phishing attacks with a rigorous, user-friendly DMARC solution. The integration comes as Google highlights the impressive results of recently implemented email authentication measures for bulk senders: a 65% reduction in unauthenticated messages to Gmail users, a 50% increase in bulk senders following best security practices, and 265 billion fewer unauthenticated messages sent in 2024. With email being such a crucial communication channel for businesses, email authentication measures are an essential part of any business’s cybersecurity offering.  Key features of the integration include: Centralized billing With centralized billing, customers can now streamline their cloud services under a single pane of glass, simplifying the management and billing of their EasyDMARC solution. This consolidated approach enables partners to reduce administrative complexity and manage all cloud expenses through one interface, providing a seamless billing and support experience. Automated provisioning  Through automated provisioning, Pax8’s automation capabilities make deploying DMARC across client accounts quick and hassle-free. By eliminating manual configurations, this integration ensures that customers can implement email security solutions rapidly, allowing them to safeguard client inboxes without delay. Bundled offerings The bundled offerings available through Pax8 allow partners to enhance their service portfolios by combining EasyDMARC with complementary security solutions. By creating all-in-one security packages, partners can offer their clients more robust protection, addressing a broader range of security needs from a single, trusted platform. Gerasim Hovhannisyan, Co-Founder and CEO of EasyDMARC, said: “We’re thrilled to be working with Pax8  to provide MSPs with a streamlined, effective way to deliver top-tier email security to their clients, all within a platform that equips them with everything needed to stay secure.  As phishing attacks grow in frequency and sophistication, businesses can no longer afford to overlook the importance of email security. Email authentication is a vital defense against the evolving threat of phishing and is crucial in preserving the integrity of email communication. This integration is designed to allow businesses of all sizes to benefit from DMARC’s extensive capabilities.” Ryan Burton, Vice President of Marketplace Vendor Strategy, at Pax8 said:  “We’re delighted to welcome EasyDMARC to the Pax8 Marketplace as an enterprise-class DMARC solution provider. This integration gives MSPs the tools they need to meet the growing demand for email security, with simplified deployment, billing, and bundling benefits. With EasyDMARC’s technical capabilities and intelligence, MSPs can deliver robust protection against phishing threats without the technical hassle that often holds businesses back.” About EasyDMARC EasyDMARC is a cloud-native B2B SaaS solution that addresses email security and deliverability problems with just a few clicks. For Managed Service Providers seeking to increase their revenue, EasyDMARC presents an ideal solution. The email authentication platform streamlines domain management, providing capabilities such as organizational control, domain grouping, and access management. Additionally, EasyDMARC offers a comprehensive sales and marketing enablement program designed to boost DMARC sales. All of these features are available for MSPs on a scalable platform with a flexible pay-as-you-go pricing model. For more information on the EasyDMARC, visit: / About Pax8  Pax8 is the technology marketplace of the future, linking partners, vendors, and small to midsized businessesthrough AI-powered insights and comprehensive product support. With a global partner ecosystem of over 38,000 managed service providers, Pax8 empowers SMBs worldwide by providing software and services that unlock their growth potential and enhance their security. Committed to innovating cloud commerce at scale, Pax8 drives customer acquisition and solution consumption across its entire ecosystem. Find out more: / The post EasyDMARC Integrates With Pax8 Marketplace To Simplify Email Security For MSPs appeared first on EasyDMARC. #easydmarc #integrates #with #pax8 #marketplace

Whether you’re an advertiser or a publisher, partnering up with the right programmatic video advertising platform is one of the most important business decisions you can make. More than half of U.S. marketing budgets are now devoted to programmatically purchased media, and there’s no indication that trend will reverse any time soon.Everybody wants to find the solution that’s best for their bottom line. However, the specific considerations that should go into choosing the right video programmatic advertising solution differ depending on whether you have supply to sell or are looking for an audience for your advertisements. This article will break down key factors for both mobile advertisers and mobile publishers to keep in mind as they search for a programmatic video advertising platform.Before we get into the specifics on either end, let’s recap the basic concepts.What is a programmatic video advertising platform?A programmatic video advertising platform combines tools, processes, and marketplaces to place video ads from advertising partners in ad placements furnished by publishing partners. The “programmatic” part of the term means that it’s all done procedurally via automated tools, integrating with demand side platforms and supply side platforms to allow advertising placements to be bid upon, selected, and displayed in fractions of a second.If a mobile game has ever offered you extra rewards for watching a video and you found yourself watching an ad for a related game a split second later, you’ve likely been on the user side of an advertising programmatic transaction. Now let’s take a look at what considerations make for the ideal programmatic video advertising platform for the other two main parties involved.4 points to help advertisers choose the best programmatic platformLooking for the best way to leverage your video demand side platform? These are four key points for advertisers to consider when trying to find the right programmatic video advertising platform.A large, engaged audienceOne of the most important things a programmatic video advertising platform can do for advertisers is put their creative content in front of as many people as possible. However, it’s not enough to just pass your content in front of the most eyeballs. It’s equally important for the platform to give you access to engaged audiences who are more likely to convert so you can make the most of your advertising dollar.Full-screen videos to grab attentionYou need every advantage you can get when you’re grappling for the attention of a busy mobile user. Your video demand side platform should prioritize full-screen takeovers when and where they make sense, making sure your content isn’t just playing unnoticed on the far side of the screen.A range of ad options that are easy to testYour video programmatic advertising partner should be able to offer a broad variety of creative and placement options, including interstitial and rewarded ads. It should also enable you to test, iterate, and optimize ads as soon as they’re put into rotation, ensuring your ad spend is meeting your targets and allowing for fast and flexible changes if needed.Simple access to supplyEven the most powerful programmatic video advertising platform is no good if it’s impractical to get running. Look for partners that allows instant access to supply through tried-and-true platforms like Google Display & Video 360, Magnite, and others. On top of that, you should seek out a private exchange to ensure access to premium inventory.4 points for publishers in search of the best programmatic platformYou work hard to make the best apps for your users, and you deserve to partner up with a programmatic video advertising platform that works hard too. Serving video ads that both keep users engaged and your profits rising can be a tricky needle to thread, but the right platform should make your part of the process simple and effective.A large selection of advertisersEncountering the same ads over and over again can get old fast — and diminish engagement. On top of that, a small selection of advertisers means fewer chances for your users to connect with an ad and convert — which means less revenue, too. The ideal programmatic video advertising platform will partner with thousands of advertisers to fill your placements with fresh, engaging content.Rewarded videos and offerwallsInterstitial video ads aren’t likely to disappear any time soon, but players strongly prefer other means of advertisement. In fact, 76% of US mobile gamers say they prefer rewarded videos over interstitial ads. Giving players the choice of when to watch ads, with the inducement of in-game rewards, can be very powerful — and an offerwall is another powerful way to put the ball in your player’s court.Easy supply-side SDK integrationThe time your developers spend integrating a new video programmatic advertising solution into your apps is time they could have spent making those apps more engaging for users. While any backend adjustment will naturally take some time to implement, your new programmatic partner should offer a powerful, industry-standard SDK to make the process fast and non-disruptive.Support for programmatic mediationMediators such as LevelPlay by ironSource automatically prioritize ad demand from multiple third-party networks, optimizing your cash flow and reducing work on your end. Your programmatic video advertising platform should seamlessly integrate with mediators to make the most of each ad placement, every time.Pick a powerful programmatic partnerThankfully, advertisers and publishers alike can choose one solution that checks all the above boxes and more. For advertisers, the ironSource Programmatic Marketplace will connect you with targeted audiences in thousands of apps that gel with your brand. For publishers, ironSource’s marketplace means a massive selection of ads that your users and your bottom line will love. #how #choose #programmatic #video #advertising

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The Secure Government EmailCommon Implementation Framework New Zealand’s government is introducing a comprehensive email security framework designed to protect official communications from phishing and domain spoofing. This new framework, which will be mandatory for all government agencies by October 2025, establishes clear technical standards to enhance email security and retire the outdated SEEMail service.  Key Takeaways All NZ government agencies must comply with new email security requirements by October 2025. The new framework strengthens trust and security in government communications by preventing spoofing and phishing. The framework mandates TLS 1.2+, SPF, DKIM, DMARC with p=reject, MTA-STS, and DLP controls. EasyDMARC simplifies compliance with our guided setup, monitoring, and automated reporting. Start a Free Trial What is the Secure Government Email Common Implementation Framework? The Secure Government EmailCommon Implementation Framework is a new government-led initiative in New Zealand designed to standardize email security across all government agencies. Its main goal is to secure external email communication, reduce domain spoofing in phishing attacks, and replace the legacy SEEMail service. Why is New Zealand Implementing New Government Email Security Standards? The framework was developed by New Zealand’s Department of Internal Affairsas part of its role in managing ICT Common Capabilities. It leverages modern email security controls via the Domain Name Systemto enable the retirement of the legacy SEEMail service and provide: Encryption for transmission security Digital signing for message integrity Basic non-repudiationDomain spoofing protection These improvements apply to all emails, not just those routed through SEEMail, offering broader protection across agency communications. What Email Security Technologies Are Required by the New NZ SGE Framework? The SGE Framework outlines the following key technologies that agencies must implement: TLS 1.2 or higher with implicit TLS enforced TLS-RPTSPFDKIMDMARCwith reporting MTA-STSData Loss Prevention controls These technologies work together to ensure encrypted email transmission, validate sender identity, prevent unauthorized use of domains, and reduce the risk of sensitive data leaks. Get in touch When Do NZ Government Agencies Need to Comply with this Framework? All New Zealand government agencies are expected to fully implement the Secure Government EmailCommon Implementation Framework by October 2025. Agencies should begin their planning and deployment now to ensure full compliance by the deadline. The All of Government Secure Email Common Implementation Framework v1.0 What are the Mandated Requirements for Domains? Below are the exact requirements for all email-enabled domains under the new framework. ControlExact RequirementTLSMinimum TLS 1.2. TLS 1.1, 1.0, SSL, or clear-text not permitted.TLS-RPTAll email-sending domains must have TLS reporting enabled.SPFMust exist and end with -all.DKIMAll outbound email from every sending service must be DKIM-signed at the final hop.DMARCPolicy of p=reject on all email-enabled domains. adkim=s is recommended when not bulk-sending.MTA-STSEnabled and set to enforce.Implicit TLSMust be configured and enforced for every connection.Data Loss PreventionEnforce in line with the New Zealand Information Security Manualand Protective Security Requirements. Compliance Monitoring and Reporting The All of Government Service Deliveryteam will be monitoring compliance with the framework. Monitoring will initially cover SPF, DMARC, and MTA-STS settings and will be expanded to include DKIM. Changes to these settings will be monitored, enabling reporting on email security compliance across all government agencies. Ongoing monitoring will highlight changes to domains, ensure new domains are set up with security in place, and monitor the implementation of future email security technologies.  Should compliance changes occur, such as an agency’s SPF record being changed from -all to ~all, this will be captured so that the AoGSD Security Team can investigate. They will then communicate directly with the agency to determine if an issue exists or if an error has occurred, reviewing each case individually. Deployment Checklist for NZ Government Compliance Enforce TLS 1.2 minimum, implicit TLS, MTA-STS & TLS-RPT SPF with -all DKIM on all outbound email DMARC p=reject  adkim=s where suitable For non-email/parked domains: SPF -all, empty DKIM, DMARC reject strict Compliance dashboard Inbound DMARC evaluation enforced DLP aligned with NZISM Start a Free Trial How EasyDMARC Can Help Government Agencies Comply EasyDMARC provides a comprehensive email security solution that simplifies the deployment and ongoing management of DNS-based email security protocols like SPF, DKIM, and DMARC with reporting. Our platform offers automated checks, real-time monitoring, and a guided setup to help government organizations quickly reach compliance. 1. TLS-RPT / MTA-STS audit EasyDMARC enables you to enable the Managed MTA-STS and TLS-RPT option with a single click. We provide the required DNS records and continuously monitor them for issues, delivering reports on TLS negotiation problems. This helps agencies ensure secure email transmission and quickly detect delivery or encryption failures. Note: In this screenshot, you can see how to deploy MTA-STS and TLS Reporting by adding just three CNAME records provided by EasyDMARC. It’s recommended to start in “testing” mode, evaluate the TLS-RPT reports, and then gradually switch your MTA-STS policy to “enforce”. The process is simple and takes just a few clicks. As shown above, EasyDMARC parses incoming TLS reports into a centralized dashboard, giving you clear visibility into delivery and encryption issues across all sending sources. 2. SPF with “-all”In the EasyDARC platform, you can run the SPF Record Generator to create a compliant record. Publish your v=spf1 record with “-all” to enforce a hard fail for unauthorized senders and prevent spoofed emails from passing SPF checks. This strengthens your domain’s protection against impersonation. Note: It is highly recommended to start adjusting your SPF record only after you begin receiving DMARC reports and identifying your legitimate email sources. As we’ll explain in more detail below, both SPF and DKIM should be adjusted after you gain visibility through reports. Making changes without proper visibility can lead to false positives, misconfigurations, and potential loss of legitimate emails. That’s why the first step should always be setting DMARC to p=none, receiving reports, analyzing them, and then gradually fixing any SPF or DKIM issues. 3. DKIM on all outbound email DKIM must be configured for all email sources sending emails on behalf of your domain. This is critical, as DKIM plays a bigger role than SPF when it comes to building domain reputation, surviving auto-forwarding, mailing lists, and other edge cases. As mentioned above, DMARC reports provide visibility into your email sources, allowing you to implement DKIM accordingly. If you’re using third-party services like Google Workspace, Microsoft 365, or Mimecast, you’ll need to retrieve the public DKIM key from your provider’s admin interface. EasyDMARC maintains a backend directory of over 1,400 email sources. We also give you detailed guidance on how to configure SPF and DKIM correctly for major ESPs.  Note: At the end of this article, you’ll find configuration links for well-known ESPs like Google Workspace, Microsoft 365, Zoho Mail, Amazon SES, and SendGrid – helping you avoid common misconfigurations and get aligned with SGE requirements. If you’re using a dedicated MTA, DKIM must be implemented manually. EasyDMARC’s DKIM Record Generator lets you generate both public and private keys for your server. The private key is stored on your MTA, while the public key must be published in your DNS. 4. DMARC p=reject rollout As mentioned in previous points, DMARC reporting is the first and most important step on your DMARC enforcement journey. Always start with a p=none policy and configure RUA reports to be sent to EasyDMARC. Use the report insights to identify and fix SPF and DKIM alignment issues, then gradually move to p=quarantine and finally p=reject once all legitimate email sources have been authenticated.  This phased approach ensures full protection against domain spoofing without risking legitimate email delivery. 5. adkim Strict Alignment Check This strict alignment check is not always applicable, especially if you’re using third-party bulk ESPs, such as Sendgrid, that require you to set DKIM on a subdomain level. You can set adkim=s in your DMARC TXT record, or simply enable strict mode in EasyDMARC’s Managed DMARC settings. This ensures that only emails with a DKIM signature that exactly match your domain pass alignment, adding an extra layer of protection against domain spoofing. But only do this if you are NOT a bulk sender. 6. Securing Non-Email Enabled Domains The purpose of deploying email security to non-email-enabled domains, or parked domains, is to prevent messages being spoofed from that domain. This requirement remains even if the root-level domain has SP=reject set within its DMARC record. Under this new framework, you must bulk import and mark parked domains as “Parked.” Crucially, this requires adjusting SPF settings to an empty record, setting DMARC to p=reject, and ensuring an empty DKIM record is in place: • SPF record: “v=spf1 -all”. • Wildcard DKIM record with empty public key.• DMARC record: “v=DMARC1;p=reject;adkim=s;aspf=s;rua=mailto:…”. EasyDMARC allows you to add and label parked domains for free. This is important because it helps you monitor any activity from these domains and ensure they remain protected with a strict DMARC policy of p=reject. 7. Compliance Dashboard Use EasyDMARC’s Domain Scanner to assess the security posture of each domain with a clear compliance score and risk level. The dashboard highlights configuration gaps and guides remediation steps, helping government agencies stay on track toward full compliance with the SGE Framework. 8. Inbound DMARC Evaluation Enforced You don’t need to apply any changes if you’re using Google Workspace, Microsoft 365, or other major mailbox providers. Most of them already enforce DMARC evaluation on incoming emails. However, some legacy Microsoft 365 setups may still quarantine emails that fail DMARC checks, even when the sending domain has a p=reject policy, instead of rejecting them. This behavior can be adjusted directly from your Microsoft Defender portal. about this in our step-by-step guide on how to set up SPF, DKIM, and DMARC from Microsoft Defender. If you’re using a third-party mail provider that doesn’t enforce having a DMARC policy for incoming emails, which is rare, you’ll need to contact their support to request a configuration change. 9. Data Loss Prevention Aligned with NZISM The New Zealand Information Security Manualis the New Zealand Government’s manual on information assurance and information systems security. It includes guidance on data loss prevention, which must be followed to be aligned with the SEG. Need Help Setting up SPF and DKIM for your Email Provider? Setting up SPF and DKIM for different ESPs often requires specific configurations. Some providers require you to publish SPF and DKIM on a subdomain, while others only require DKIM, or have different formatting rules. We’ve simplified all these steps to help you avoid misconfigurations that could delay your DMARC enforcement, or worse, block legitimate emails from reaching your recipients. Below you’ll find comprehensive setup guides for Google Workspace, Microsoft 365, Zoho Mail, Amazon SES, and SendGrid. You can also explore our full blog section that covers setup instructions for many other well-known ESPs. Remember, all this information is reflected in your DMARC aggregate reports. These reports give you live visibility into your outgoing email ecosystem, helping you analyze and fix any issues specific to a given provider. Here are our step-by-step guides for the most common platforms: Google Workspace Microsoft 365 These guides will help ensure your DNS records are configured correctly as part of the Secure Government EmailFramework rollout. Meet New Government Email Security Standards With EasyDMARC New Zealand’s SEG Framework sets a clear path for government agencies to enhance their email security by October 2025. With EasyDMARC, you can meet these technical requirements efficiently and with confidence. From protocol setup to continuous monitoring and compliance tracking, EasyDMARC streamlines the entire process, ensuring strong protection against spoofing, phishing, and data loss while simplifying your transition from SEEMail. #new #zealands #email #security #requirements