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Meta’s Andromeda ad retrieval algorithm changed targeting by making creative a much stronger signal than audience settings. AdQuantum CMO Anton Kuzmin, who has helped scale UA for brands like Flow, Blinkist, and Playrix, breaks down what that means for mobile app marketers now. In this episode, he explains why broad targeting and simpler campaign structures are replacing heavily segmented ad sets, what Meta actually means by creative diversity, and how marketers can build a pipeline of genuinely distinct concepts without simply producing endless variations of the same ad. He also shares where AI-generated creative fits alongside authentic UGC, why UA managers need to “do less, think more,” and how automation is freeing performance marketers to spend more time understanding audiences, developing creative strategy, and finding the ideas that actually drive growth. Questions answered in this episode: What is Meta’s Andromeda algorithm, and why was it built?How has Andromeda changed the role of creatives in Meta user acquisition?Why is creative becoming more important than manual audience targeting?What makes two creatives genuinely different in Meta’s eyes?How should app marketers structure Meta campaigns after Andromeda?Does manual targeting still have a place, or should marketers default to broad audiences?How can teams maintain enough fresh creative concepts without dramatically increasing production costs?Is Andromeda ultimately a net positive for advertisers?Where should marketers use AI-generated creative, and where does authentic UGC still perform better?What is the biggest habit UA managers need to unlearn as Meta becomes increasingly automated?Timestamp: 01:12 — Anton’s background: From media buying to mobile performance marketing 04:23 — What is AdQuantum and what is Anton’s role? 5:32 — What is Meta Andromeda, and why was it built? 8:17 — Why creative is becoming the new targeting mechanism 10:12 — Creative similarity and the danger of producing near-duplicate ads 13:21 — Core campaigns vs. separate creative testing campaigns 15:55 — How to keep the creative pipeline fresh at scale 17:50 — What Meta really means by “different” creative 19:04 — Is Andromeda a net positive for advertisers? 24:15 — AI-generated ads vs. authentic UGC 25:06 — The biggest thing UA managers need to unlearn: “Do less, think more” 26:26 — What comes next for Meta Ads and automated campaign optimization 28:49 — Using AI and automation to keep pace with a changing UA landscape 31:19 — Rapid-fire questions with Anton Quotes: (13:14) - "According to Meta’s documentation, you should have one core campaign and every week upload new creatives to mix up the distribution of your ad spend." (24:13) - "For some products, AI-generated content doesn’t work as effectively as UGC. I think it’s important for marketing departments to create content using real people, but also through AI as well." Mentioned in this episode: Anton Kuzmin’s LinkedIn AdQuantum

AppsFlyer’s Chief Business Officer, Gal Ekstein, has spent more than 20 years across adtech and martech and now leads AppsFlyer’s global go-to-market. In this episode, Gal discusses their recent $1 billion investment from Moloco, Google, Meta, and Unity. He explains how this investment will advance independent measurement in the AI era, accelerate the company’s expansion from mobile to omnichannel measurement, and impact the broader mobile ecosystem. He also breaks down how AppsFlyer is applying AI through its MCP, agent hub, and self-serve tools; why attribution, identity resolution, and consistent conversion definitions must form the foundation of an AI-powered marketing stack; and why automating on unreliable signals only makes bad decisions happen faster. Questions Gal answered in this episode:What does AppsFlyer’s new investment from Moloco, Google, Meta, and Unity mean for the company and the broader mobile ecosystem?Why do major advertising platforms have an incentive to support an independent measurement provider?How will the new investment accelerate AppsFlyer’s product roadmap?How is AppsFlyer expanding from mobile attribution into omnichannel measurement?What does it mean to measure the customer journey across mobile, web, CTV, PC, console, commerce media, and retail media?How is AppsFlyer incorporating AI into its measurement platform and advertiser workflows?What role will AI agents and AppsFlyer’s MCP play for partners and advertisers?Why are consistent signals, attribution, identity resolution, and conversion definitions so important before marketers automate?What will the mobile marketing stack look like in 2030?What should app marketers prioritize now to prepare for an AI-driven marketing ecosystem?Timestamp:00:20 — Introducing Gal Ekstein 01:10 — Gal’s background and role at AppsFlyer 02:28 — AppsFlyer’s $1 billion investment from Moloco, Google, Meta, and Unity 05:33 — Why major ad platforms want independent measurement 08:49 — What comes next for AppsFlyer after the investment 09:36 — AppsFlyer’s roadmap: omnichannel measurement, data collaboration, and autonomous marketing 12:43 — Expanding measurement beyond mobile to web, CTV, PC, console, and commerce 14:54 — How AI changes measurement and attribution 16:21 — AppsFlyer’s MCP, AI agents, and self-serve tools 18:43 — AppsFlyer and Remerge’s partnership around privacy-safe measurement and retargeting 21:24 — How AI is changing the advertiser workflow 22:52 — What the mobile marketing stack could look like in 2030 24:20 — Why measurement must come before AI-powered activation 26:13 — Rapid-fire questions with Gal 28:28 — Gal’s advice for app marketers preparing for the AI era Quotes:(3:10) “We signed a definite agreement of investment with Moloco, Google, Meta, and Unity to advance independent measurement for the AI era. Those four competitors are coming together to make sure that AppsFlyer stays an independent and unbiased company.” (9:11) “Last year we actually became a modern marketing cloud, and we’re about to invest much more in omnichannel measurement. Coming from mobile, we want to take that expertise into the other digital channels.” (18:54) “We’ve worked closely with Remerge for more than 13 years. Remerge consistently ranks as one of the leading media sources and top retargeting partners, often trailing only after Google and Meta.”  Mentioned in this episode:Gal Ekstein’s LinkedInAppsFlyer

Nicolas Tissier, co-founder and CPO of Purchasely, has spent years optimizing subscription app journeys. He says that the real onboarding window starts at the ad click and doesn’t end until the product becomes a habit. In this episode, Nicolas breaks onboarding down into three stages - intent, value, and habit. He explains why the first session matters so much, how emotional and social values can outperform feature-led messaging, and why more screens can sometimes improve conversion when they create positive rather than negative friction. He also unpacks the growing web2-app challenge, including how to preserve purchase context after a web subscription, avoid forcing paid users through redundant onboarding or paywalls, and build a cleaner handoff that supports conversion and retention. Questions Nicolas answered in this episode:What does onboarding mean to you? What are the three stages of app onboarding, and which teams should own each one?Where do apps lose the most users during the onboarding journey?How much time do app publishers have to prove it’s providing the desired job-to-be-done? Why can adding more onboarding screens sometimes improve conversion?How has Apple’s ATT framework contributed to the growth of web-to-app acquisition?Where do subscription apps lose users when moving them from a web funnel into the app?How can marketers create a smoother handoff for users who have already subscribed on the web?Which apps have onboarding experiences worth studying?Timestamps:01:09 — Introducing Nicolas Tissier and Purchasely02:02 — Why Purchasely built no-code tools for faster experimentation03:38 — The three stages of onboarding: intent, value, and habit05:41 — Where apps lose users and why the first session matters07:32 — Communicating progress over product features08:49 — Push, pull, anxiety, and inertia in the onboarding journey10:18 — Positive vs. negative friction in onboarding flows11:47 — Why web-to-app acquisition grew after Apple ATT13:45 — Converting users on the web before they download the app14:44 — The critical web-to-app subscription handoff15:43 — Avoiding redundant onboarding and preserving purchase context16:38 — Apps with onboarding experiences worth studying17:45 — Where to connect with Nicolas and PurchaselyQuotes:(3:39) “From my perspective, onboarding is everything that happens between the ad click and the moment where the product actually becomes a habit.” (5:57) “The average app loses roughly 80% of its users within the first three days. So it's rather at the beginning of the funnel. And if you look at this study, it's almost 90% of the acquired traffic that is gone.” (6:30) “When it comes to monetization, the clock runs even faster. From our data, more than 80% of free trials start on the very day of the install, so the very first day. Half of the paid conversions happen the same day, and it's the same for cancellations. When you have three-day free trials, more than half of the people immediately cancel their subscription just out of security. So, you really need to be very good at the beginning.” Mentioned in this episode:Nicolas Tissier’s LinkedInPurchasely

As AI agents take on more of the tactical work behind mobile marketing, one question is becoming harder to ignore: what skills will marketers need to stay relevant and valuable in an AI-driven industry? Table Stakes Media founder Piper Martz is passionate about breaking down the fear surrounding agentic AI, and she draws on a decade in lifecycle and retention marketing to explore what this transition means for marketers at every level -- from junior employees who may have fewer opportunities to learn through hands-on execution, to marketing leaders whose roles are shifting toward mentoring talent, managing AI agents, and creating a culture where experimentation feels safe. In this episode, Piper breaks down the rise of AI decisioning, why critical thinking and systems thinking will become increasingly important, and how marketers and their leaders can rethink development, retraining, and experimentation to build careers that evolve alongside the technology rather than compete with it.   Questions Piper answered in this episode:What is Table Stakes Media, and why is Piper focused on AI leadership rather than just AI skills?Why are mobile and growth marketers particularly well positioned to experiment with AI?What is AI decisioning, and how is it different from generative AI?How can AI agents create more personalized lifecycle and retention experiences for individual app users?Are marketers becoming managers of AI agents rather than executors of campaigns?How should marketers train, supervise, and build feedback loops with AI agents?How can junior marketers develop expertise when AI increasingly handles the tactical work they once learned from?What can leaders do to create psychological safety for AI experimentation?How should companies approach retraining employees when AI automates a significant portion of their jobs?Which parts of marketing are most likely to become automated—and which human skills will become more valuable?  Timestamp:01:52 — What is Table Stakes Media? 03:41 — Piper’s background in lifecycle, retention, and agentic AI 05:22 — Why AI transformation is also a change-management problem 06:09 — The pressure leaders face when introducing AI to their teams 07:11 — Building communities around AI leadership and experimentation 08:27 — Why mobile marketers are primed for AI experimentation 09:21 — Hyper-personalization, retention, and the limits of segmentation 10:33 — Why push notifications are a powerful testing ground for AI 11:07 — What AI decisioning means for mobile marketers 13:04 — Using one AI agent to continuously learn from each user 14:06 — Are marketers becoming managers of AI agents? 16:22 — The problem facing junior marketers in an AI-first workplace 17:17 — Why mentorship matters more as tactical work becomes automated 18:39 — Psychological safety, experimentation, and learning through failure 19:56 — How leaders should communicate when AI takes over job functions 21:13 — IKEA’s approach to retraining employees displaced by automation 23:09 — Why critical thinking becomes more important in an AI-powered workplace 24:08 — Systems thinking as a critical skill for the next generation of marketers 26:01 — What will a marketer’s job look like in two or three years? 27:19 — Why fear of AI can prevent marketers from developing valuable skills 29:09 — Protecting creativity, taste, and human judgment in an AI-first world 30:18 — Piper’s advice: experiment, play, and help shape what comes next 30:55 — Where to follow Piper Martz and Table Stakes Media   Quotes:(14:42) “I hate micromanagers, but if you've got a team of AI agents, you need to be a micromanager. Give feedback all the time. Tell them when you're disappointed. Tell them when you're delighted. Build these feedback loops.” (20:18) “Can you imagine how powerful it is as a junior employee to have someone say to you, ‘Hey, you're going to learn this tool. It's going to take over 50% of your job, but we're going to train you and support you.” (30:37) “It's an experiment. Take the reins and start playing. Start experimenting. We don't know what it's going to look like. Be part of that transition.”   Mentioned in this episode:Piper Martz’s LinkedInTable Stakes Media Piper’s Luma Calendar for AI events in New York

After realizing the customer acquisition cost with Apple Search Ads and Meta Ads was too high to scale his app, Michael Butler looked for a better acquisition model. In the process, he discovered an opportunity to solve an overlooked growth marketing problem: no reliable way to track app transactions back to the affiliates or influencers driving them. In this episode, the Insert Affiliate founder explains how app marketers can turn creator partnerships into a measurable acquisition channel using attribution links, referral codes, and real-time transaction tracking. Michael also shares why engaged micro-influencers can outperform larger creators, how to structure revenue share, and why affiliate marketing is becoming more compelling as traditional user acquisition costs continue to rise. Questions Michael Butler answered in this episode: What is affiliate marketing, and how does it work specifically for mobile apps? How can app marketers attribute transactions and revenue back to individual affiliates and creators? What problem led Michael to build Insert Affiliate? Why has affiliate marketing historically been underused compared with traditional paid UA? What does a simple affiliate marketing program look like for an app launching one for the first time? Which types of apps and verticals tend to perform best with affiliate marketing? What does “optionality” in affiliate attribution mean, and why does it matter? Is it better to recruit hundreds of affiliates or focus on a smaller group of highly engaged creators? Should app marketers compensate creators with flat fees, recurring revenue share, or a combination of both? How much commission should an app offer its affiliates, and should that commission be based on installs or sales? Timestamp: 00:00 — Introduction: Making affiliate marketing measurable for apps 00:41 — What affiliate marketing means for mobile apps 01:01 — How Insert Affiliate tracks referrals and commissions 01:21 — The acquisition problem that inspired Insert Affiliate 02:07 — How affiliate traffic and transactions are attributed 03:01 — Spending nearly £30K on Apple Search Ads and searching for an alternative 04:22 — Why affiliate marketing has been underused in mobile UA 05:47 — How to launch a simple affiliate program 07:07 — Which app categories perform best with affiliates 08:13 — Attribution optionality: links, short codes, and incentive structures 10:11 — How None To Run generated $5K with a handful of affiliates 11:47 — Quality vs. quantity when recruiting creators 14:00 — Flat fees vs. recurring revenue share 14:55 — Turning affiliate UGC into paid advertising 15:35 — How much commission should apps pay affiliates? 16:49 — The biggest misconceptions about affiliate marketing 18:17 — Rapid-fire questions 20:04 — Michael's guide to visiting Jersey Island 21:03 — Final thoughts and where to connect with Michael Quotes: (7:39) "If you know who your customers are and where they hang out, you'll also learn which influencers and affiliates are going to resonate with them.” (12:40) “If you find an affiliate that’s a really good fit, really likes what you’re building, and will post about it in a very genuine way, they don’t need a large audience -- just an engaged one.” (17:39 “You need to give influencers some guidance. It’s the same as hiring any sort of staff member. If you bring them on but don’t give them training or show them your product, they’re going to be a lot less effective.” Mentioned in this Episode: Michael Butler’s LinkedIn Michael’s Calendly Insert Affiliate

Your next customer may be asking ChatGPT which app to download, but will your app make the list? AppTweak’s CMO Alexandra De Clerck draws on more than eight years in app store marketing to explain how LLMs interpret user intent, combine internal knowledge with live web retrieval, and use “query fan-out” to decide which apps deserve a recommendation. She reveals why app store descriptions have become critical AI discovery assets; how detailed reviews and community conversations help validate an app’s positioning; and why smaller apps have a rare opportunity to compete for AI visibility before the market becomes saturated. Questions Alexandra answered in this episode: What’s the biggest shift in app store marketing you’ve seen in the last three years? How are consumers using ChatGPT and other LLMs to discover new apps? How does an LLM decide which apps to recommend for a specific prompt? What is ‘query fan-out’, and why does it matter for app marketers? How can marketers determine whether their app is visible in AI-generated recommendations? Why are app store descriptions becoming more important in the age of AI discovery? What helps an app appear among ChatGPT’s first sourced recommendations? Why do games receive more citations from Reddit and Wikipedia than other app categories? How can smaller apps compete against brands with larger budgets and more downloads? Can app reviews and developer responses influence how LLMs understand an app? How should marketers measure AI visibility when most app discovery journeys are zero-click? Timestamp: 00:23 – Introducing Alexandra De Clerck and AI app discovery 00:43 – About AppTweak and Alexandra’s journey to CMO 02:50 – How app discovery has changed in the past three years 04:06 – How ChatGPT and other LLMs choose which apps to recommend 06:11 – ‘Query fan-out’ and how AI interprets complex prompts 07:17 – Why most app marketers do not yet have an AI visibility strategy 09:27 – The first steps marketers should take to improve LLM visibility 09:38 – Why app store listings are such important AI citation sources 11:59 – How apps can reach the first five or six sourced recommendations 13:28 – Why AI discovery works differently for games and non-game apps 15:41 – How smaller apps can outperform larger competitors in AI search 17:25 – Using app reviews and developer responses to reinforce positioning 18:48 – Measuring AI visibility in a mostly zero-click user journey 21:28 – The long-term advantage of investing in AI visibility now 22:56 – Rapid-fire questions with Alexandra 25:30 – Where to connect with Alexandra and learn more about AppTweak Quotes: (6:07) “An important concept to understand in AI search is how AIs actually interpret the prompt.” (9:48) “What we’ve seen from our research is that actually almost 50% of all citations in ChatGPT are app store listings.” (10:19) “LLMs really look at app store listings to understand what an app is about, who it’s for, and what the main use-cases are, so that’s the highest leverage opportunity for app marketers getting started with an AI search strategy.” (12:22) “So we see when ChatGPT makes a recommendation [for a mobile app], usually the first five to six answers are sourced. So that means that they actually did a live web retrieval to find information about this. And for where it's not sourced, it actually means that they looked into their internal knowledge base to build the answer. (22:11) “If you start now by optimizing your intent  coverage around the web and really helping ChatGPT and other LLMs understand what your app is and what your app is about, build that context into their internal knowledge base as well, then you have an edge up compared to people who are still exploring or discovering or wondering whether or not it's worth it to get started.”  Mentioned in this episode: Alexandra De Clerck on LinkedIn Email: alexandra [at] apptweak.com AppTweak AppTweak’s Playbook: AI Visibility for Apps & Games

Irwin Hau, founder of Chromatix and ConversionCow, joins Apptivate to unpack the psychology behind customer conversion and why acquisition is only the beginning of the user journey. Drawing from more than 17 years of experience analyzing tens of thousands of websites, apps, and digital experiences, Irwin shares the principles that separate traffic from customers, how clarity and proof influence decision-making, and why education, gamification, and ongoing engagement are critical to reducing churn. Irwin goes on to explore with Remerge’s Patrick Eichmann how mobile marketers can improve onboarding, build stronger habit loops, and think more deliberately about retention rather than assuming installs automatically translate into long-term users. Questions addressed in this episode Why do mobile marketers focus so heavily on acquisition while overlooking conversion? What are the biggest mistakes companies make after generating traffic? How can marketers communicate their value proposition more clearly? Why is social proof so important in driving action? How should apps educate users after installation? What role do tutorials and onboarding play in retention? How can gamification reduce churn? What apps are doing engagement particularly well? How can marketers identify friction points in the user journey? What principles from human psychology should guide app growth? Timestamps 0:22 — Introducing Irwin Hau and his agency background 1:44 — The origins of Chromatix and ConversionCow 3:21 — Why marketers obsess over traffic instead of conversion 4:44 — The formula: traffic × conversion = customers 5:28 — Clarity: explaining what your product actually does 6:28 — Why social proof matters more than ever 7:00 — Making the call to action impossible to miss 7:56 — How to communicate value in just a few lines 10:24 — The biggest mistake marketers make after acquisition 11:44 — Why features come after solving the customer's problem 12:27 — Conversion doesn't stop after the install 13:27 — Education, tutorials, and onboarding experiences 14:28 — Push notifications, habit formation, and Duolingo 15:27 — Building virality through sharing and community 16:00 — Apps that get engagement right 16:52 — My Drive Hero and reward psychology 18:12 — Why group behavior reduces churn 19:00 — Where to find Irwin and closing thoughts Quotes (5:28) “If you cannot explain your app in less than seven words, I think you're waffling.” (12:30) “Conversion to me isn’t a one-off thing. There are many different conversion points.” (13:09) "You can't just assume if they come through the door, we've got them for life. They will churn.” Mentioned in this episode Irwin Hau on LinkedIn Chromatix ConversionCow

Yevhen Tarasenko, CMO and co-founder of Apptonomy, joins Apptivate to discuss how app store optimization is evolving in the age of AI. After more than a decade in ASO, Yevhen shares how the discipline has changed from a keyword-focused practice into a broader challenge of app discoverability across app stores, search engines, Reddit, and large language models. The conversation explores the limitations of traditional ASO workflows, how AI is changing the way marketers analyze visibility, and why app teams need to think beyond rankings and metadata to succeed in a world increasingly shaped by AI recommendations and automated discovery. Questions addressed in this episode How did Yevhen get started in ASO? Why is app store optimization still so manual? What inspired the creation of Apptonomy? How can AI automate parts of the ASO workflow? What is AI discoverability and why does it matter? How are large language models changing app discovery? Why is Reddit becoming increasingly important for app visibility? What were the biggest AI and ASO themes at MAU Vegas? How should app marketers prepare for AI-driven search and discovery? What advice would Yevhen give someone entering ASO today? Timestamps (0:05) — Introduction to Yevhen Tarasenko and Apptonomy (1:10) — Getting started in ASO and the early days of app discovery (3:00) — Building ASO teams and thinking systematically about growth (3:54) — Freelancing, automation, and the origins of Apptonomy (5:00) — How Apptonomy was founded through a LinkedIn article (8:21) — Why ASO remains manual and repetitive in 2026 (9:34) — AI discoverability and visibility across LLMs (10:39) — Reddit, online presence, and app recommendations (11:48) — Measuring discoverability and reporting results (12:29) — MAU Vegas observations and industry trends (13:12) — AI's impact on ASO and app discoverability (15:00) — Advice for marketers entering ASO (17:21) — Resources, communities, and where to find Yevhen (18:15) — Closing remarks Quotes (4:17) “AI changes every month. Now we're using Claude, next month we're using ChatGPT or something else, and the quality standards with AI are not quite there.” (8:21) “ASO, even in 2026, is still very manual and boring, and people are tired of doing the same thing all over again.” (18:28) “AI will not replace ASO anytime soon. The human touch will be needed for at least 3-5 years.” Mentioned in this episode Yevhan on Linkedin Apptonomy

Natasha Saviuk, Growth Director at Wealthsimple, joins Apptivate to discuss how incentives evolved from simple promotions into one of the company's most effective growth channels. The conversation explores the lessons Natasha brought from her background in neuroscience, how Wealthsimple scaled from $15 billion to more than $125 billion in assets under management, and why physical rewards often outperform cash incentives. Natasha and Taylor also discuss campus growth strategies, virality, incrementality, account transfer incentives, and the surprising results of campaigns, ranging from free bubble tea to Apple products and even a house giveaway. Questions addressed in this episode How did Natasha transition from neuroscience into growth marketing? What lessons from scientific research apply to experimentation? How did Wealthsimple approach growth in its early years? Why did bubble tea outperform cash incentives? How do incentives function as a standalone growth channel? How can marketers measure incrementality in incentive campaigns? Why did Wealthsimple pivot away from paid acquisition in 2022? How can incentives drive high-value customer behavior? How do you avoid attracting low-quality users through promotions? What can marketers learn from Wealthsimple's house giveaway campaign? Timestamps (0:41) — Natasha's background and transition from neuroscience to growth (2:02) — Research, experimentation, and finding growth opportunities (4:03) — Introduction to Wealthsimple and early growth challenges (5:27) — Building network effects through campus growth strategies (7:05) — The bubble tea experiment and local partnerships (9:06) — Why physical rewards outperform cash incentives (10:50) — Incentives as a dedicated growth channel (12:23) — Measuring quality, incrementality, and long-term value (14:02) — The 2022 market downturn and shifting growth strategy (15:28) — Asset consolidation and scaling incentive programs (16:25) — Avoiding reward-driven user behavior (18:00) — Incentivizing long-term customer commitment (19:46) — How marketers can get started with incentives (20:10) — Common mistakes when launching incentive campaigns (21:14) — The Wealthsimple house giveaway campaign (22:31) — Rapid-fire questions begin (25:06) — Where to find Natasha and closing remarks Quotes (7:19)  “It's not until we started doing partnerships with the local food places, in particular bubble tea, that we really stumbled upon something that was working.” (16:50) “By having these stricter hold periods and clawbacks, it does deter people who maybe did just have the intention to gamify.” (22:18)  “Sometimes the channel you should invest in is one that doesn't even exist, and you kind of just need to try and see what's resonating with your audience.” Mentioned in this episode Wealthsimple Natasha on LinkedIn

Adeel Shaikh Muhammad, founder of Adeel Solutions, is an advisor on cybersecurity, AI governance, and digital risk. He joins Apptivate to discuss the growing tension between AI-powered growth and user trust. The conversation explores why AI governance is becoming essential for modern marketing teams, how over-personalization can create a sense of creepiness for users, and where companies are introducing AI without clearly defined use cases. Adeel and Taylor also discuss shadow AI, human oversight in automated systems, the security implications of AI agents, and practical frameworks that organizations can use to balance innovation, speed, and accountability as AI adoption accelerates. Questions addressed in this episode What is AI governance and why does it matter? How should companies balance growth, personalization, and user trust? What mistakes are marketers making when adopting AI? What is shadow AI and why is it becoming a problem? When does AI-driven personalization become creepy? How can AI improve marketing performance while hurting long-term value? Which parts of marketing workflows should always include human oversight? What are the biggest security concerns surrounding AI agents? Who should own AI governance inside an organization? What practical steps can companies take to implement AI guardrails? Timestamps (0:00) — Introduction to Adeel Muhammad and his background (1:58) — Where companies are in their AI adoption journey (2:34) — Defining AI governance and the role of guardrails (3:30) — The biggest mistakes marketers make with AI (4:38) — AI use cases, visibility, and the rise of AI wrappers (5:40) — The creepiness problem and over-personalization (6:00) — When AI-driven growth starts eroding user trust (7:41) — Shadow AI and unauthorized AI usage (8:19) — Balancing speed, security, and business priorities (9:45) — Warning signs that trust is breaking down (10:12) — Why human oversight still matters (11:00) — The biggest cybersecurity risks in AI (13:11) — AI compliance, over-documentation, and risk prioritization (15:26) — Who should own AI governance? (16:57) — Human responsibility, AI access, and awareness training (19:02) — Adeel's seven-step AI governance framework (20:45) — The governance steps companies skip most often (21:25) — Trust as the foundation for AI growth (24:07) — Where to find Adeel and closing remarks Quotes (6:24)  “Growth breaks when the user feels watched, not when ads perform badly.” (6:53) “AI is optimized for CTR but not LTV, so you get high clicks from low-quality users.” (21:25) “The companies that win won’t be the fastest, but they will be the ones that scale trust alongside the growth.” Mentioned in this episode Adeel Solutions Adeel Muhammad on LinkedIn

Ekaterina Gamsriegler, former Head of Growth and Marketing at MyGroove and longtime advisor across music, education, and health apps, joins Apptivate to discuss why sustainable growth depends on systems rather than isolated wins. The conversation explores the nature of modern growth funnels, how creative strategy impacts retention and churn downstream, and why many teams optimize acquisition while misunderstanding activation and long-term value. Ekaterina and Taylor also discuss localization as a full-funnel growth lever, pricing strategy during high-intent seasonal periods, the realities of founder-led and offline growth channels, and how mapping the complete user journey can uncover hidden bottlenecks that data alone often misses. Questions addressed in this episode Why does Ekaterina compare growth systems to a house of cards? How do creative strategies affect retention and subscriber churn? What mistakes do apps make during seasonal growth periods like Q5? How should marketers evaluate long-term value instead of short-term ROAS? Why can localization improve the entire growth funnel? How did MyGroove grow paying subscribers 10x in one year? What role should brand, PR, and offline channels play in app growth? How should teams define activation properly? What should marketers focus on during their first 90 days at a company? How can apps balance credibility with accessibility for beginners? Timestamps 0:12 — Introduction to Ekaterina Gamsriegler and MyGroove 0:52 — MyGroove's global launch and mission 1:41 — Growth as a "house of cards" rather than a puzzle 3:18 — Diagnosing funnels and identifying hidden bottlenecks 4:42 — How creatives shape retention and churn downstream 6:56 — Credibility, UGC, and "fake podcast" creative concepts 7:51 — Why acquisition mistakes appear 60–90 days later 9:43 — Planning for Q5 and evaluating long-term value 11:25 — Pricing strategy, willingness to pay, and cancellations 12:52 — Localization as a full-funnel growth lever 15:23 — Founder-led growth, PR, and offline channels at MyGroove 18:23 — The biggest unlock behind 10x subscriber growth 20:38 — Mapping the user journey and identifying bottlenecks 23:08 — Activation metrics and offline user behavior 25:56 — Personalization and contextual onboarding examples 29:48 — Rapid-fire questions begin 31:08 — Norway, Iceland, and travel recommendations 31:33 — Vienna recommendations and closing remarks Quotes (2:22)  “Growth feels more like a house of cards because just one little change can completely ruin the whole system.” (4:59) “What I see happening sometimes is a mismatch between the product, the user experience and the people who are being targeted with creatives.” (22:38) “Build a user journey by mapping every single step from ad impression to renewal to purchase. This allows you to see where the bottlenecks are in your journey.” Mentioned in this episode MyGroove Ekaterina on Linkedin

Remerge CEO and founder, Pan Katsukis, joins Patrick Eichmann for the first video edition of Apptivate. They discuss the evolution of mobile advertising, the origin story behind Remerge, and where the industry is heading next. The conversation explores the rise of app retargeting, how ATT and privacy changes reshaped mobile growth, why probabilistic targeting is driving renewed momentum on iOS, and how AI is changing campaign optimization behind the scenes. Pan also reflects on Berlin’s startup scene in the late 2000s, the early days of mobile advertising before smartphones, and how infrastructure, automation, and user behavior will shape the next five years of app marketing. Questions addressed in this episode How did Remerge get started in the early mobile era? What was Berlin’s startup ecosystem like in 2008? How did mobile advertising evolve before smartphones? Why did app retargeting become such a large market? How did ATT and privacy changes affect app marketers? What role will AI play in campaign optimization? Why is probabilistic retargeting becoming more important on iOS? How does Remerge think about long-term product strategy? What trends will define the next five years of mobile growth? Timestamps 0:00 — Apptivate intro and Remerge video announcement 1:27 — Introducing Pan Katsoukas and Remerge’s origin story 2:11 — Pan’s background in mobile advertising before smartphones 3:33 — Why Remerge was founded and the rise of app retargeting 4:13 — Berlin’s startup ecosystem in the late 2000s 7:27 — Evolution of mobile advertising and measurement infrastructure 8:18 — User acquisition, app retargeting, and post-install marketing 10:15 — ATT, privacy changes, and the industry shift on iOS 12:23 — AI, automation, and the next generation of campaign optimization 14:10 — The future of mobile usage and emerging business models 16:14 — Probabilistic retargeting and the iOS “unlock” opportunity 18:57 — Where Pan sees Remerge in the next five to ten years 21:10 — Favorite app, running, and AI companions 22:10 — Favorite travel destinations and closing rapid-fire questions Quotes (10:20)  “One of the big things that also everybody is aware of is with Apple and the privacy changes with ATT in 2020, 2021, when they launched it, there was a big shift in the whole industry.” (12:27)  “With all the technology that is out there and what is capable, AI is one of the biggest drivers to just get better.” (16:42)  “AI just gets better and better, so even without a clear 100% deterministic match, you’re still able to get good retention and good results for retargeting campaigns on iOS specifically.” Mentioned in this episode Remerge Pan Katsukis on LinkedIn

Michal Bubernik, Head of Marketing at Pixel Federation, joins Patrick Eichmann of Apptivate to discuss how AI is transforming creative production inside mobile gaming. The conversation covers how Pixel Federation scaled from producing around 10 polished creative assets per month to roughly 700 variations through AI-assisted workflows, why post-IDFA growth requires higher creative volume, and how teams can use testing systems to identify winning creatives faster. Michal and Patrick also explore leadership during technological change, overcoming fear around AI adoption, how creative teams can become proactive tool scouts, and why speed, experimentation, and adaptability now define high-performing marketing organizations. Questions addressed in this episode How did Pixel Federation scale creative production so dramatically? What changed for gaming marketers after the deprecation of IDFA? Why does AI increase output without expanding headcount? How should teams test hundreds of creative variations? What mistakes do companies make when adopting AI tools? How do leaders reduce fear around automation and job change? What does a proactive creative culture look like in 2026? How should marketers think about speed versus polish? Timestamps 0:00 — Introduction and Michal Bubernik’s background in gaming marketing 0:32 — Pixel Federation overview and flagship train games 0:56 — Michal’s leadership role and managing the marketing team 1:34 — Team size, in-house creative structure, and collaboration 2:14 — How IDFA changes impacted gaming marketers 2:53 — From 10 creatives a month to 700 variations 4:05 — Internal AI tools versus best-in-market external tools 5:28 — How large-scale creative testing works in practice 6:51 — Biggest mistakes teams make with AI adoption 8:10 — Fear, resistance, and job security concerns around AI 10:24 — Leadership advice for marketers behind on AI 11:20 — Lightning round begins 12:24 — Where to learn more about Pixel Federation 12:53 — Closing remarks Quotes (2:22) “I think IDFA deprecation has impacted every single company in the mobile free-to-play industry.” (6:51) “With AI, it’s moving forward so fast that the only mistake you can make is not testing it in every way you can.” (10:50) “Don’t be afraid to try at least one AI tool -- and you will see how much it can help you.” Mentioned in this episode Pixel Federation Michal Burbernik

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