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

Take the Speakers, Headphones, and Earphones SurveyTake other PCMag surveys. Each completed survey is a chance to win a $250 Amazon gift card. OFFICIAL SWEEPSTAKES RULESNO PURCHASE NECESSARY TO ENTER OR WIN. A PURCHASE WILL NOT INCREASE YOUR CHANCES OF WINNING. VOID WHERE PROHIBITED. Readers' Choice Sweepstakes (the "Sweepstakes") is governed by these official rules (the "Sweepstakes Rules"). The Sweepstakes begins on May 9, 2025, at 12:00 AM ET and ends on July 27, 2025, at 11:59 PM ET (the "Sweepstakes Period").SPONSOR: Ziff Davis, LLC, with an address of 360 Park Ave South, Floor 17, New York, NY 10010 (the "Sponsor").ELIGIBILITY: This Sweepstakes is open to individuals who are eighteen (18) years of age or older at the time of entry who are legal residents of the fifty (50) United States of America or the District of Columbia. 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Hi, friends! Welcome to Installer No. 87, your guide to the best and Verge-iest stuff in the world. (If you’re new here, welcome, happy It’s Officially Too Hot Now Week, and also you can read all the old editions at the Installer homepage.) This week, I’ve been reading about Sabrina Carpenter and Khaby Lame and intimacy coordinators, finally making a dent in Barbarians at the Gate, watching all the Ben Schwartz and Friends I can find on YouTube, planning my days with the new Finalist beta, recklessly installing all the Apple developer betas after WWDC, thoroughly enjoying Dakota Johnson’s current press tour, and trying to clear all my inboxes before I go on parental leave. It’s… going.I also have for you a much-awaited new browser, a surprise update to a great photo editor, a neat trailer for a meh-looking movie, a classic Steve Jobs speech, and much more. Slightly shorter issue this week, sorry; there’s just a lot going on, but I didn’t want to leave y’all hanging entirely. Oh, and: we’ll be off next week, for Juneteenth, vacation, and general summer chaos reasons. We’ll be back in full force after that, though! Let’s get into it.(As always, the best part of Installer is your ideas and tips. What do you want to know more about? What awesome tricks do you know that everyone else should? What app should everyone be using? Tell me everything: installer@theverge.com. And if you know someone else who might enjoy Installer, forward it to them and tell them to subscribe here.)The DropDia. I know there are a lot of Arc fans here in the Installerverse, and I know you, like me, will have a lot of feelings about the company’s new and extremely AI-focused browser. Personally, I don’t see leaving Arc anytime soon, but there are some really fascinating ideas (and nice design touches) in Dia already. Snapseed 3.0. I completely forgot Snapseed even existed, and now here’s a really nice update with a bunch of new editing tools and a nice new redesign! As straightforward photo editors go, this is one of the better ones. The new version is only on iOS right now, but I assume it’s heading to Android shortly.“I Tried To Make Something In America.” I was first turned onto the story of the Smarter Scrubber by a great Search Engine episode, and this is a great companion to the story about what it really takes to bring manufacturing back to the US. And why it’s hard to justify.. That link, and the trailer, will only do anything for you if you have a newer iPhone. But even if you don’t care about the movie, the trailer — which actually buzzes in sync with the car’s rumbles and revs — is just really, really cool. Android 16. You can’t get the cool, colorful new look just yet or the desktop mode I am extremely excited about — there’s a lot of good stuff in Android 16 but most of it is coming later. Still, Live Updates look good, and there’s some helpful accessibility stuff, as well.The Infinite Machine Olto. I am such a sucker for any kind of futuristic-looking electric scooter, and this one really hits the sweet spot. Part moped, part e-bike, all Blade Runner vibes. If it wasn’t $3,500, then I would’ve probably ordered one already.The Fujifilm X-E5. I kept wondering why Fujifilm didn’t just make, like, a hundred different great-looking cameras at every imaginable price because everyone wants a camera this cool. Well, here we are! It’s a spin on the X100VI but with interchangeable lenses and a few power-user features. All my photographer friends are going to want this.Call Her Alex. I confess I’m no Call Her Daddy diehard, but I found this two-part doc on Alex Cooper really interesting. Cooper’s story is all about understanding people, the internet, and what it means to feel connected now. It’s all very low-stakes and somehow also existential? It’s only two parts, you should watch it.“Steve Jobs - 2005 Stanford Commencement Address.” For the 20th anniversary of Jobs’ famous (and genuinely fabulous) speech, the Steve Jobs Archive put together a big package of stories, notes, and other materials around the speech. Plus, a newly high-def version of the video. This one’s always worth the 15 minutes.Dune: Awakening. Dune has ascended to the rare territory of “I will check out anything from this franchise, ever, no questions asked.” This game is big on open-world survival and ornithopters, too, so it’s even more my kind of thing. And it’s apparently punishingly difficult in spots.CrowdsourcedHere’s what the Installer community is into this week. I want to know what you’re into right now as well! Email installer@theverge.com or message me on Signal — @davidpierce.11 — with your recommendations for anything and everything, and we’ll feature some of our favorites here every week. For even more great recommendations, check out the replies to this post on Threads and this post on Bluesky.“I had tried the paper planner in the leather Paper Republic journal but since have moved onto the Remarkable Paper Pro color e-ink device which takes everything you like about paper but makes it editable and color coded. Combine this with a Remarkable planner in PDF format off of Etsy and you are golden.” — Jason“I started reading a manga series from content creator Cory Kenshin called Monsters We Make. So far, I love it. Already preordered Vol. 2.” — Rob“I recently went down the third party controller rabbit hole after my trusty adapted Xbox One controller finally kicked the bucket, and I wanted something I could use across my PC, phone, handheld, Switch, etc. I’ve been playing with the GameSir Cyclone 2 for a few weeks, and it feels really deluxe. The thumbsticks are impossibly smooth and accurate thanks to its TMR joysticks. The face buttons took a second for my brain to adjust to; the short travel distance initially registered as mushy, but once I stopped trying to pound the buttons like I was at the arcade, I found the subtle mechanical click super satisfying.” — Sam“The Apple TV Plus miniseries Long Way Home. It’s Ewan McGregor and Charley Boorman’s fourth Long Way series. This time they are touring some European countries on vintage bikes that they fixed, and it’s such a light-hearted show from two really down to earth humans. Connecting with other people in different cultures and seeing their journey is such a treat!” — Esmael“Podcast recommendation: Devil and the Deep Blue Sea by Christianity Today. A deep dive into the Satanic Panic of the 80’s and 90’s.” — Drew“Splatoon 3 (the free Switch 2 update) and the new How to Train Your Dragon.” — Aaron“I can’t put Mario Kart World down. When I get tired of the intense Knockout Tour mode I go to Free Roam and try to knock out P-Switch challenges, some of which are really tough! I’m obsessed.” — Dave“Fable, a cool app for finding books with virtual book clubs. It’s the closest to a more cozy online bookstore with more honest reviews. I just wish you could click on the author’s name to see their other books.” — Astrid“This is the Summer Games Fest week (formerly E3, RIP) and there are a TON of game demos to try out on Steam. One that has caught my attention / play time the most is Wildgate. It’s a team based spaceship shooter where ship crews battle and try to escape with a powerful artifact.” — Sean“Battlefront 2 is back for some reason. Still looks great.” — IanSigning offI have long been fascinated by weather forecasting. I recommend Andrew Blum’s book, The Weather Machine, to people all the time, as a way to understand both how we learned to predict the weather and why it’s a literally culture-changing thing to be able to do so. And if you want to make yourself so, so angry, there’s a whole chunk of Michael Lewis’s book, The Fifth Risk, about how a bunch of companies managed to basically privatize forecasts… based on government data. The weather is a huge business, an extremely powerful political force, and even more important to our way of life than we realize. And we’re really good at predicting the weather!I’ve also been hearing for years that weather forecasting is a perfect use for AI. It’s all about vast quantities of historical data, tiny fluctuations in readings, and finding patterns that often don’t want to be found. So, of course, as soon as I read my colleague Justine Calma’s story about a new Google project called Weather Lab, I spent the next hour poking through the data to see how well DeepMind managed to predict and track recent storms. It’s deeply wonky stuff, but it’s cool to see Big Tech trying to figure out Mother Nature — and almost getting it right. Almost.See you next week!See More: