Apptivate: App Marketing Explained

Description Apptivate hosts and Remerge team members, Patrick Eichmann and Taylor Lobdell, sit down to discuss the outlook for mobile marketing in 2026 and the shifts shaping the industry. The conversation covers the move toward probabilistic attribution, the growing role of AI in campaign execution, and how advertisers are adapting to signal loss. They explore why retargeting strategies are becoming simpler and more holistic, where teams still fall short in testing and budget allocation, and how growth organizations are reorganizing around the full user lifecycle rather than channel silos. Patrick and Taylor also examine what defines a strong DSP partner today, along with how automation, CTV, and consolidation are influencing the future of programmatic advertising. Questions addressed in this episode How is mobile advertising changing in 2026? What does the shift from deterministic to probabilistic attribution mean in practice? Is iOS retargeting still viable? What mistakes are advertisers making with testing and budget allocation? Why should UA and retargeting be treated as one system? How are growth teams restructuring around lifecycle marketing? What should marketers look for in a DSP partner? What optimizations should be happening behind the scenes in programmatic? How will automation, AI, and CTV shape the next phase of mobile growth? Timestamps (0:04) — Opening: 2026 landscape and market pressures (0:39) — Key shifts: probabilistic attribution and AI (1:57) — iOS retargeting misconceptions and probabilistic unlock (2:47) — Simplifying retargeting strategies and segmentation (3:15) — IDFA impact and rediscovering lost audiences (4:00) — Testing challenges and budget inconsistency (4:58) — UA and retargeting as one system (5:58) — Lifecycle-based marketing and team structure shifts (7:09) — Advice: continuous testing beyond creative (7:33) — Campaign experimentation and automation tools (8:33) — AI vs fundamentals in marketing (9:39) — What makes a strong DSP (12:55) — Post-launch optimization and AI-driven bidding (14:25) — Fraud detection and prevention (15:42) — Future outlook: consolidation, lifecycle, automation (17:07 — Rise of CTV as a performance channel (17:36 — Lightning round begins Quotes (0:52)  “I think one thing we see a lot in our business is the shift from deterministic to probabilistic attribution.” (2:27) “Normal opt-in rates sit around 20%-40% depending on the app. And we're able to get a ton more users targeted through probabilistic retargeting.” (4:20)  “There's a real willingness to test different approaches, but people are not necessarily putting consistent budget behind this testing.” (6:30)  “I think we have to think less about channel-specific or technique-specific approaches and really think more about the lifecycle of the user itself and build around that.” Mentioned in this episode Patrick Eichmann on LinkedIn Taylor Lobdell on Linkedin Remerge

Dieter Rappold, co-founder and CEO of Context SDK, joins Apptivate to explore how motion sensor data and on-device AI are reshaping mobile marketing strategies. He explains how contextual signals from accelerometers, gyroscopes, and other device inputs can help marketers identify the right moment to engage users, optimize conversion timing, and improve monetization without relying on personal data or tracking permissions. The conversation covers the evolution from event-based to moment-based optimization, practical implementation considerations, privacy implications, fraud detection use cases, and how contextual intelligence could power the next generation of agentic AI and decision-making in mobile growth. Questions addressed in this episode: What types of smartphone sensor signals can marketers use today? How does Context SDK turn motion data into actionable growth insights? What is the difference between event-based and moment-based optimization? Which app categories benefit most from contextual engagement timing? How does on-device AI change personalization in a privacy-first world? What implementation effort is required to test contextual optimization? How can motion signals support fraud detection and ad performance? Where could contextual intelligence influence agentic AI and future UX? What strategic priorities should mobile marketers focus on next? Timestamps (0:04) — Motion sensor data in mobile marketing (0:56) — Accelerometer and gyroscope explained (2:06) — Founding story and origins of Context SDK (3:10) — Awareness gap among mobile marketers about sensor data (4:24) — Airbnb example illustrating real-world user intent (5:44) — Physics-based data vs opinion-driven marketing models (6:55) — Session duration differences and conversion timing opportunities (8:22) — Event-based vs moment-based optimization strategy (10:13) — App verticals and use cases for contextual timing (11:15) — Additional signals beyond motion sensors (12:02) — Model training requirements and data scale needed (14:02) — Privacy compliance, ATT and permissionless personalization (15:11) — Fraud detection applications using motion behavior (15:43) — Ad network integration and performance uplift example (17:28) — Context data as signal layer for agentic AI (19:18) — Strategic priorities and competitive positioning for marketers (20:23) — Limits of sociodemographic targeting frameworks (22:06) — How to connect with Context SDK team (22:29) — Rapid-fire questions  (24:58) — Episode wrap  Quotes (4:45) “If you're walking down the street and open Airbnb. You probably look for the key code of the apartment that you have booked. But if you're comfy on the sofa and open Airbnb, you are probably planning your next vacation.” (5:03) “Humans constantly move in a three dimensional space while they're using their smartphones and the apps on it… we have different needs, different pain points, different session durations and different likelihoods to convert in different actions.” (8:47)  “I do believe that we should not get rid of event based, but we should combine it with moment based because both things can tell us something. Event based gives us behavioral context, meaning the behavior in the app. But the question is, when is the timing right?” (13:35)  “Based on how we built this, our architecture and our approach, we don't need ATT, we don't need any permissions, and we are out of the box GDPR compliant because we don't collect any PII, we don't collect a unique user ID, we don't collect unique device ID.” Mentioned in this episode: Dieter Rappold on Linkedin Context SDK

Bani Malhotra, former head of personalization and site experience for Walmart’s e-commerce platform, joins Apptivate to unpack the real drivers of revenue growth in modern digital products. She explores how recommendation systems, search behavior, ratings and reviews can influence conversion rates across the funnel.  She also discusses why many teams misdiagnose the cause of revenue leaks, and how behavioral signals increasingly outperform demographic targeting. Bani also discusses the evolving responsibilities of product leaders, including ownership of go-to-market and revenue outcomes, and shares lessons from building AI-native consumer apps where product systems must handle probabilistic outputs, uncertainty, and the balance between automation and user control. Questions addressed in this episode Which product levers most reliably drive revenue in e-commerce? Where do companies actually lose revenue in the funnel? How should teams think about personalization without creating discovery problems? What behavioral signals best predict purchase intent? How is the product leadership role evolving? What changes when building AI-native consumer products? How should teams design systems when AI outputs are probabilistic? Timestamps (0:03) — Bani Malhotra’s background and experience leading personalization at Walmart (3:17) — Why revenue growth comes from multiple connected drivers (4:02) — Recommendation systems and the evolution of personalization (5:10) — The impact of ratings and reviews on customer confidence (8:37) — Search behavior as a signal of user intent (13:35) — Diagnosing revenue leaks across the funnel (20:03) — When personalization becomes an echo chamber (27:27) — Why upselling can damage customer trust (32:35) — Behavioral signals versus demographic targeting (37:41) — How the product leadership role has evolved (40:54) — Designing AI-native consumer products (44:44) — Rapid-fire questions and closing Quotes (3:30) “Revenue isn't just working on one level. There are multiple revenue drivers that connect to each other, and when they work together in tandem, it compounds.” (8:48) “When somebody searches, not only are they starting consideration, they are giving you intent.” (13:39) “More often than not I have seen the biggest revenue leaks to be mid-funnel and bottom of the funnel.” Mentioned in this episode Bani on Linkedin

Artsiom Kazimirchyk, co-founder and CEO of Campaignswell, joins Apptivate to break down predictive LTV modeling, the critical flaws in how teams measure unit economics, and why today's mobile marketers need unified tools that connect profitability analysis across channels. The conversation covers what's broken in traditional LTV reporting, the technical pain points of fragmented data definitions across platforms, and how accurate cohort analysis can unlock smarter budget allocation. Questions addressed in this episode: What is Campaignswell, and what problem is it solving for mobile marketers? What is wrong with traditional LTV reporting? What exactly is predictive LTV and how far out can you forecast? Which monetization models are easiest versus hardest to predict LTV? When teams estimate their own LTV, how accurate are they usually? What immediate changes can marketers make if their LTV is poorly defined? How does Campaignswell guide budget allocation across different channels? What is the elevator pitch for Campaignswell to get teams to adopt it? Why is cohort analytics misunderstood by most marketing teams? How should marketers think about payback periods when measuring campaign efficiency? Timestamps: (0:26) — What Campaignswell is and what problem it solves for marketers (1:24) — Building Campaignswell as a single source across all teams (5:20) — Why speed matters in campaign decisions (7:50) — The hidden costs in LTV (9:47) — Predictive LTV and calculating on specific horizons (11:19) — Why subscription monetization is easiest to predict (16:19) — Client LTV predictions: When teams' numbers are off by 2x or more (20:27) — Matching optimization targets to the right LTV metrics across channels (26:22) — Why cohort analytics is misunderstood by most marketing teams (28:20) — Lightning round: First thing every morning (29:49) — Closing: Where Artsiom wants to travel next Quotes: (8:07) "Apple takes 30 percent of your revenue by default. It's really huge. It might be all your margin. And if you cannot calculate it, your comparison with customer acquisition cost might be wrong.” (25:20) “Using Campaignswell, you won't be in a situation where one team says they have a CPA of $20 bucks and another team says it’s $30.” (29:14) "I noticed that marketing spend was $600,000 per day with really strong performance. ROI was something around 30 percent. So it's a really huge amount of marketing budget. The first thing I thought was there’s probably something wrong." Mentioned in this episode: Campaignswell Artisom on Linkedin

Louis Tanguay, founder of App Growth Summit, returns to dissect why user retention is defining success for mobile in 2026. The conversation ranges from in-person event strategy to hands-on UX tactics, with practical lessons for product teams facing an era of AI, off-app payments, and high user expectations. Louis shares what top apps get wrong about onboarding, how to use gamification without gimmicks, and where the next phase of community is headed.Questions addressed in this episode:What does it take to build a real app community in 2026?Why has retention overtaken acquisition as the key metric?Where do most onboarding flows lose users?What old-school tactics still drive engagement in an AI world?How can product teams bridge the gap between digital and in-person experiences?Timestamps:(0:03) — Louis Tanguay: first steps in app growth and events(2:20) — Building in-person communities and event philosophies(4:10) — User experience, retention, and the changing funnel(6:05) — Off-app conversion and new payment strategies(9:12) — Why retention is the hardest metric(12:04) — What product teams miss on onboarding(15:08) — Early wins, gamification, and balancing friction(19:12) — Testing, analytics, and segmenting users(21:24) — Human connection, digital convergence, and long-term habits(25:42) — Lightning round: daily routines, advice, and closing thoughtsQuotes:(5:34) “You have to do the research and see how much traffic you are actually losing by sending people out of your app or your site.”(8:22) “Growth is more like a circle than a funnel. I never really liked the funnel term.”(19:24) "If you're going to gamify, then in the user preferences, allow me to turn off gamification. Some people want those experiences, but always give users control. You can't force everyone into the same play pattern."Mentioned in this episode:App Growth SummitLouis Tanguay  on Linkedin

Jyoti Pannu, Product Manager at Booking.com, shares how AI is transforming the way travelers discover, plan, and book their next adventure. From AI trip planners that surface new possibilities to the integration of GenAI and ChatGPT into the core product, Jyoti explains why travel discovery is moving beyond simple search, how user intent is now mapped through nuanced signals, and what the rise of LLMs means for attribution, retention, and the future of app UX. She also dives into cross-vertical product lessons, balancing novelty and personalization, and offers advice for elevating women in product management.Questions addressed in this episode:What is Booking.com, and what does Jyoti’s role cover?How is AI being used at Booking.com beyond chatbots and content generation?What does intent-based and natural language discovery look like in practice?How is the app experience changing with AI-driven trip planners and smart filters?How does Booking.com balance user personalization and novelty in recommendations?How do LLM-based discovery channels affect paid UA and retargeting strategies?What guardrails and metrics are important for launching new AI features?What lessons cross over from fintech, e-commerce, and travel in app retention?How should product teams think about post-purchase and post-trip experience?What advice does Jyoti have for women building a career in product and tech?Timestamps:(0:03) – Jyoti’s role at Booking.com and scope of the app(1:39) – AI trip planners and intent-driven product development(3:17) – Smart filters and natural language input for hotel discovery(4:03) – How Booking.com infers trip purpose and personalizes UX(6:09) – LLMs, ChatGPT, and new search/discovery interfaces(8:13) – Attribution, channel mix, and UA economics in an AI-first world(11:01) – Avoiding the filter bubble in travel recommendations(13:41) – Booking.com plugins and booking via ChatGPT(15:41) – Cross-vertical product lessons from e-commerce, fintech, and travel(17:58) – Brand omnipresence, loyalty, and retention(19:04) – Emotional stakes and UX in travel vs. transactional apps(21:37) – Post-trip and post-purchase: product touchpoints(22:50) – Testing AI features for retention and quality(24:24) – Guardrails, review, and data governance(25:29) – Elevating women in product and leadership(27:50) – Rapid-fire: travel, career, life, and favorite placesQuotes:(3:35) “We have an option for users called smart filters, where they can make searches in the form of natural language, like how you would interact with a human. We map this in our systems to provide personalized results for these users.”(17:00) “If a user has interacted with our platform and they have made a purchase from two different categories, they are more likely to become a high value customer than someone who has bought multiple times in the same category.”Mentioned in This Episode:Jyoti Pannu on LinkedInBooking.com

Lenny Rabin, founder of direct advertising group Brown Boots and their reward app platform GoKart, joins Taylor Lobdell to dissect the evolution of rewarded user acquisition, focusing on how direct publisher-advertiser relationships can solve long-standing industry inefficiencies. Rabin, with over a decade in rewarded traffic and ad tech, explains why most publishers dislike third-party monetization platforms, how custom tech stacks like GoKart enable deeper, more transparent deals, and what both advertisers and publishers must do to thrive in an increasingly mainstream and competitive rewards ecosystem. This episode tracks the practical realities of running direct-sold inventory at scale, dives into shifts in audience intent (from GPT sites to fintechs), and breaks down why most campaigns fail. Rabin also shares founder lessons for building in ad tech without an engineering background.Questions addressed in this episode:What’s the origin story behind Brown Boots and Go-Kart?Why do most publishers dislike monetizing via third-party networks?What core problems do direct publisher-advertiser relationships solve that networks can’t?What are the unique challenges in building a tech stack for rewarded offers?How does Go-Kart’s programmatic model differ from legacy platforms?Who is the ideal client for Brown Boots vs. Go-Kart?What major changes has Rabin seen in rewarded marketing over 15 years?How do publisher audiences shape campaign strategy and outcomes?What retention and LTV signals matter most for performance marketers?What timeline is realistic for testing new rewarded channels?Where do most advertisers and publishers fail in UA campaign collaboration?What’s Rabin’s advice for ad tech founders without a technical background?Timestamps:(0:04) – Intro and Lenny’s background(0:27) – Brown Boots & Go-Kart origin story(1:55) – Direct publisher-advertiser relationships explained(3:22) – Building custom tech for publishers(5:20) – Ideal customer for Brown Boots and Go-Kart(6:30) – Fintech, UA, and why rewarded offers are growing(9:00) - What has changed the most in rewarded traffic acquisition(11:15) – How intent differs between GPT sites and fintech audiences(13:05) - How does that change the value proposition for app marketers(13:45) – Advertiser mistakes: not understanding publisher audiences(15:06) – How long to test new channels; why 90 days matters(16:46) – The retention metric and why it drives value(17:46) – Go-Kart’s programmatic disruption(18:18) – Why last-mile delivery in rewarded UA is broken(21:00) – The tech stack vision: features, flexibility, and future(27:00) – Lessons in building ad tech as a non-engineer(35:00) - Rapid fire roundQuotes:(1:05) "Publishers wanted less opaqueness in the revenues that they were making and also deeper partnerships with the advertisers."(5:00) "Rewarded traffic is a medium which continues to grow and is becoming more mainstream."(6:46) "Any app that has a core product offering not related to rewarded marketing and has a rewarding mechanism is a good target."(11:29) "On a GPT site, users come to the site specifically to earn rewards... Your quality of your user is inherently low."(13:55) "Every publisher will have a specific and unique audience and catering the campaign specifically to that audience is a big miss."(21:55) "Let's not be spending our time dealing with data loss and dealing with small decisions. Let's spend our time talking about how we create custom campaigns."Mentioned in this episode:Brown BootsLenny on LinkedinGoKart

In this insightful discussion, guests share their expertise on app marketing strategies for 2025. Andre Kempe examines the balance between AI efficiency and human creativity in ad production. Luca Stefanutti reveals how experimentation drives user retention at Adidas, while Advi Bishnoi emphasizes the importance of community-driven strategies. Sue Azari outlines tactics for e-commerce during Q5, focusing on loyalty and remarketing. Shilpa Reddy discusses leveraging podcasts to build brand trust and validate LTV investments, showcasing diverse paths to engagement and growth.

Lisanne Vera, VP of Growth at KashKick, joins Taylor Lobdell to talk about the incentives economy, a marketplace where leisure becomes an asset. From her early affiliate-marketing roots to leading growth at one of the fastest-growing rewards apps, Lisanne unpacks how KashKick designs offers that respect user time, prevent bait-and-switch dynamics, and build long-term trust. She discusses how micro-earnings sustain engagement, why transparency matters more than flashy payouts, and why being relentlessly user-focused, even at the cost of short-term ROAS, can drive the strongest growth stories in mobile today.Key Topics and QuestionsMonetizing leisure time as engagement, how to align offers with user habits.Micro vs. large payouts: why early small rewards matter more for retention.Identifying drop-off, how can you spot value mismatches at first action, not D7.Trust and expectation: showing average, attainable outcomes, not edge cases.Marketplace curation to add only offers users already want, not random buys.User and advertiser transparency for clear education, ratings, and funnel data.Which social platforms are delivering the most reliable new users?How to design for seasoned rewards users versus newcomers.What steps help marketers adapt when retargeting and paid attribution get harder?Why value energy and attitude over traditional credentials when building a team?Which user-focused investments have delivered the clearest returns in long-term retention or brand strength?Timestamps(0:00) – Intro and Lisanne’s background in affiliate marketing(2:04) – What KashKick is and how the marketplace works(2:21) – Treating leisure time as a market asset(3:00) – User-first campaign design and offer selection(3:37) – Why genuine interest matters more than payout size(5:29) – Designing offers that respect user time(5:48) – How micro-rewards sustain engagement(7:04) – Balancing small wins with big payout motivation(8:01) – Measuring engagement versus pure volume(8:58) – How KashKick incentivizes fintech and charity actions(11:12) – Building trust through transparency and education(13:03) – Giving partners visibility and fraud prevention(14:09) – Why affiliates and content creators still work(15:40) – Push, email, and the next wave of engagement(16:35) – Playing the long game with user-first growth(18:09) – What Lisanne looks for in new hires(19:00) – Advice for junior marketers(22:16) – Ocala travel tips and hidden springsSelected quotes(3:45) – “If the user isn’t genuinely interested, no incentive will change that. You can offer six hundred dollars, but if it’s not relevant, they won’t do it.”(5:48) – “We give people rewards along the way, micro-earnings that make their time feel valued. Small wins keep users engaged.”(11:44) – “We tell users exactly how tracking works and why we need it. Transparency builds trust, and that’s what keeps them coming back.”Mentioned in this episodeLisanne Vera on LinkedinKashKick app

It’s often said that for e-commerce brands, the holiday season is the 5th quarter of the year. Sue Azari, e-commerce industry lead at AppsFlyer, joins Taylor Lobdell for a tactical breakdown of how the smartest e-commerce apps move from Q4 user acquisition to Q5 retention and remarketing. From UK and EMEA trends to global shifts in spend, Sue details why remarketing spend surges fivefold at the end of the year, how loyalty and personalization schemes actually drive a second purchase, and what makes non-organic installs disproportionately valuable for real app revenue. Referencing real examples from brands like Zara, H&M, Temu, and Shein, Sue lays out the structural shifts, practical tactics, and emerging risks facing every marketer trying to build durable, app-based revenue in a volatile global market.Key topics and questionsThe in-house consultant role at AppsFlyer and its cross-functional focusHow the UK’s mature e-commerce market shapes global strategiesWhy Q5 matters, and how its install/revenue spike emergedWhen and why remarketing eclipses UA spendTactics for turning a Q4 buyer into a repeat customer in Q5Personalization, loyalty, and exclusive drops to drive frequencyUGC, influencer content, and AI tools for creative ideationWhat e-commerce needs to steal from gaming’s diversified media mixWhy DSPs and Reddit remain underused in e-commercePaid–organic uplift: why half of installs deliver three-quarters of revenueHow to respond to high December CPMs and new market entrantsThe 70-20-10 rule for channel testingGlobal UA patterns: Android vs iOS, tariffs, rapid spend reallocationQR codes, in-store modes, and the app as a bridge to physical retailSegmentation: why abandon basket and uninstalled users matter mostStaying current in a market defined by privacy shifts and macro volatilityTimestamps(0:03) – Intro, Sue’s cross-functional role and background(1:11) – UK and EMEA, market maturity, lessons, and cross-region strategy(2:52) – Defining Q5, why end-of-year cycles matter for apps and travel(4:10) – Black Friday: remarketing spend is five times UA at peak(5:03) – Tactics: loyalty, personalization, and getting to the second purchase(6:12) – Creative best practices, UGC, influencers, and new AI tools(7:02) – Diversifying media, DSPs, app-to-app installs, and what e-commerce misses(7:55) – Community and AI as emerging channels(9:13) – Paid–organic uplift, nearly three-quarters of revenue is non-organic(10:38) – Coping with high CPMs, moving spend, leaning on owned media(11:43) – Testing new channels; the 70-20-10 rule for risk(13:47) – Regional differences in UA: China, tariffs, and aggressive spend moves(17:00) – How Sue tracks trends, privacy changes, and new industry moves(17:32) – Temu/Shein: billion-dollar UA, loyalty pivots, and physical store expansions(19:42) – QR codes, attribution, and bridging digital and physical with apps(20:51) – Retargeting segments: abandon basket and uninstalled users(21:46) – Lightning round: favorite channels, brands, tactics, and London recommendationsSelected quotes(4:13) – “When we look at spend, remarketing spend is five times that of UA for e-commerce apps during the end of Q4.”(10:06) – “Nearly three quarters of purchase revenue comes from non-organic sources. Users are much more likely to buy something if they’ve been driven to the app by a particular marketing campaign.”(21:01) – “Abandoned baskets are my primary focus for remarketing, because 70% of users who install an e-commerce app will abandon their basket. The other one that I think is not as commonly done, but I think it’s very valuable, is remarketing to uninstalled users.”Mentioned in this episodeAppsFlyerSue Azari on Linkedin