Business of Apps Podcast

Campaigns that used to take a week now ship in 30 minutes. A broken trigger nobody spotted for five days cut marketplace revenue by 11%. And a bank’s login screen now sells microwaves, and lifted conversion by 26%.
Plenty of people talk about AI in app marketing. Far fewer open up the actual workflow and show how it was built, what it connects to, and where a human still signs off. In this panel, four growth leaders each walk through one real AI system they run today, then take questions from the audience.
This episode was recorded at Business of Apps NYC, with a panel of growth executives:
David Brown-Landron, CEO of Grohaus
Jenna Klebanoff, VP Marketing & Product Management at Realtor.com=
Alexander Guerra, VP, Head of Platform Strategy at Banco Azteca
Tyler Chandler, Head of Growth at WeWard
Kevin Agresto, Director of Lifecycle Marketing at CollX
Tyler shows the UA operating system WeWard built with Claude Code for 28 countries and eight or nine channels: deterministic rules, around 1,000 GitHub Actions, and bid, budget, and creative recommendations that land in Slack for a human to approve. Jenna explains how Realtor.com uses Claude-built build and QA agents to manage a CRM program of around a billion emails a month. Her longest-standing user is now at three times the output, while everyone in the company coding creates a new bottleneck at review. Kevin walks through the weekly alert bot CollX built with Claude and n8n to catch automations whose send volume suddenly drops.
And Alexander shares how Banco Azteca added a retail marketplace to a banking app with 300 million monthly sessions, using a Vertex AI “brain” to personalize login screens, with legal and content teams checking every output for hallucinations.
If you work in user acquisition, CRM, or lifecycle marketing, this is a practical look at how AI workflows actually get built, what they deliver, and where the guardrails go.
The panel’s topics include:
AI as a UA operating system - automating the repetitive, rules-based work of a media buyer, from data aggregation and payback projections to bulk creative uploads with no naming errors, while the model never decides on its own
How to build it - a detailed product spec with clear scope and boundaries, research into which platforms have an MCP or API, and plenty of back-and-forth with Claude to get to an MVP
AI agents for CRM - build and QA agents that take a ticket from Airtable to working code, simple campaigns shipped in 30 minutes instead of one to four weeks, and the hidden cost of extra peer review
Monitoring broken automations - a Monday Slack alert that flags any campaign with a 25%+ week-over-week drop in sends, and the SDK update that broke key triggers and pulled GMV down 11% until it was fixed
Personalization at scale - AI-generated login screens based on cart and browsing data, rolled out from 1% to 15% of users through A/B testing, with conversion up 26%, about 42% retention increased, and NPS holding steady
Data readiness, guardrails, and culture - structuring your data before you connect it, keeping humans in the loop, getting finance and accounting teams on board, and feeding company policies and culture into the model, not just marketing guidelines

Six statements about app growth, a room full of marketers voting live on their phones, and a panel that doesn’t always side with the room.
The audience agreed with almost everything: that AI is creating sameness, that growth is now a product problem, that retention beats acquisition. Only one statement got flipped. Hearing why the panelists push back, hedge, or go all in is where it gets interesting.
This episode was recorded at Business of Apps NYC, with a panel hosted by Nicole Weiss, Founder of Brass Finch/Mintgrove, featuring:
Kate Palmer, Senior Director of Growth and Lifecycle Marketing at TouchTunes
Christopher Bagtas, Senior Manager, App Marketing at The Economist
Vincent Eterlet, VP Marketing at Fubo
Alisha Kabir, Senior Growth Strategy Manager at Audiomack
The panel splits on AI creative, with one side saying viewers can spot an AI-made ad straight away, and the other saying ads all looked the same long before AI arrived. They explain why brand has caught up with performance now that installs come from repeated exposure across TikTok, Meta, YouTube, and CTV rather than a single ad. Kate draws a clear line between product and marketing problems: if the right users are churning, it’s product; if you’re bringing in the wrong users, it’s marketing. And on channels, the panel weighs a wide mix you can shift budget into against the beta access and guidance that come from deep partnerships with a few platforms.
If you work in app marketing, user acquisition, or lifecycle marketing, this is a candid look at which growth strategies deliver measurable results today, and which trends are overhyped.
The panel’s topics include:
AI in creative - why AI-generated scripts and statics are easy to spot, and where AI helps by making animated ads that would be too expensive or slow to produce in-house
Brand vs. performance - performance spend across many platforms adds up to brand building, and in crowded categories users need a story and a mission before they commit
Product vs. marketing - signal engineering as shared work between growth and product, and why marketing teams still need access to App Store Connect and Google Play
Short-term ROAS vs. long-term growth - early experimentation to find the right optimization events, knowing your unit economics, LTV, and payback periods, and why ad-supported apps behave more like gaming
Retention vs. acquisition - ad platforms now optimize for in-app events and revenue rather than installs, but in emerging markets grabbing market share first can still win
Fewer channels vs. more - keeping alternate channels ready for when costs rise, starting with Apple Ads plus one channel, and why a mobile team of two to five people can’t manage 20 partner relationships

This time we're digging into connected TV as a performance channel for mobile apps - and how to prove it actually drove an install.
TV has always been good at building brands. The hard part is showing it led to a conversion. As a top-of-funnel channel, CTV often loses the attribution credit to whatever touched the user last, and that's where incrementality testing comes in.
To cover all this, we've got Connor Kernochan, Head of Apps and Games at Vibe, talking to tech journalist David Murphy at Business of Apps New York about measuring CTV campaigns and running them the right way.
Connor explains what counts as connected TV, why it's now a performance play as well as a branding play, and how MMP data shows which strategies are working. He also covers how incrementality works in practice, including geo lift tests and ghost bids.
If you work in user acquisition, app marketing, or mobile measurement, this is a clear look at how to measure CTV and fit it into your existing media mix.
Today’s topics include:
What connected TV is - Hulu, Peacock, HBO Max, Roku, and ESPN on the biggest screen in the house
Brand and performance - targeting viewers like any other digital channel and measuring well enough to optimize
Measuring a CTV campaign - plugging into AppsFlyer, Adjust, or Singular as the source of truth
Why CTV loses attribution credit - many touch-points before a conversion, and CTV sits at the top of the funnel
Incrementality in practice - comparing exposed and control groups through geo lift tests and ghost bids
Doing CTV the right way - direct publisher relationships, and CTV data alongside your other channels
Links and Resources:
Connor Kernochan on LinkedIn
Vibe.co website
Business Of Apps - connecting the app industry
Quotes from Connor Kernochan:
The real value is that it is a branding play, but it is also a performance play."
"CTV often loses out on attribution credit because of the nature of being a top of funnel channel."
"Whatever any of our clients are using as their source of truth for how they look to measure and report on their KPIs is what we plug into."
Host
Business Of Apps - connecting the app industry since 2012

Today's topic is where app marketing budgets should go - and why creative now does the work that audience settings used to do.
Ad platforms are increasingly machine learning-led, and the industry is increasingly privacy-led. Put the two together, and the creative you run decides who sees your ad. A couple of hero videos won't cut it anymore.
To cover all this, we've got Jonathan Yantz, Managing Partner at M+C Saatchi Performance, talking to tech journalist David Murphy at Business of Apps New York about budget allocation, creative strategy, and retention.
Jonathan explains why budget planning starts with a robust testing plan, how to be ready for new channels like ChatGPT ads before they arrive, and what a creative strategy built on a large number of variations looks like. He also covers why retention matters more when every dollar is under scrutiny.
If you work in app marketing, performance media, or creative strategy, this is a clear look at how to plan, test, and spend when the algorithm does the targeting.
Today’s topics include:
Budget allocation - a testing plan thought through in advance, especially going into the end of the fiscal year
New channels - having a plan ready and making sure you can measure any extra dollar
Creative is the new targeting - how machine learning-led platforms and privacy changes moved the job to creative
A robust creative strategy - many variations, with the next batch ready to go
From A/B to A-to-Z testing - tying creative back to the overall testing strategy
Budget scrutiny and retention - acquiring a user is costly, so keeping them is the easiest way to grow
Links and Resources:
Jonathan Yantz on LinkedIn
M+C Saatchi Performance website
Business Of Apps - connecting the app industry
Quotes from Jonathan Yantz:
"We always said creative is king. And now we're saying creative is the new targeting, which is absolutely true."
"Any extra dollar is going to be the most important one to measure."
"Every dollar has to drive something."
Host
Business Of Apps - connecting the app industry since 2012

Performance CTV is the phrase of the year - and today we're looking at what's actually behind it.
For years, connected TV did one job: awareness. It was bought on reach and frequency, often upfront at fixed rates, with no way to tie an impression to an outcome. Now measurement has caught up and supply has flooded in, so the same channel can be linked to installs and conversions.
To cover all this, we've got Matilda Lindström, Associate Sales Director at Dataseat, talking to tech journalist David Murphy at Business of Apps New York about connecting CTV with mobile user acquisition.
Matilda explains what changed to make performance possible on CTV, why so many CTV tests look like failures when they aren't, and how MMP attribution settings can decide a campaign before it starts. She also covers second-screening and where to begin if you've never run CTV for performance.
If you work in user acquisition, app marketing, or brand media, this is a clear look at how to run CTV and mobile as one strategy.
Today’s topics include:
What performance CTV means - still a great brand channel, but now measurable and optimizable in real time
Measurement and supply - MMPs support CTV attribution, and free ad-supported streaming has pushed inventory ahead of demand
Programmatic buying - bidding into inventory, shifting budgets mid-campaign, and capping frequency across publishers and placements
The organizational challenge - CTV sits with brand teams, UA with mobile teams, each with different KPIs
Attribution settings - probabilistic IP matching and MMP defaults that can make a working campaign look like it isn't
A unified CTV and mobile strategy - second-screening, and a Sunday-night TV ad that pays off with a Monday-morning install
Where to start - keep direct brand buys, scale programmatically, and check your MMP's CTV windows and prioritization
Links and Resources:
Matilda Lindström on LinkedIn
Dataseat website
Business Of Apps - connecting the app industry
Quotes from Matilda Lidström
"I don't think that we should shy away from the fact that it's a great brand channel. That part hasn't changed. What changed is the ability to measure and optimize in real time."
"You might look like the performance is not working at all, but it's actually not a performance issue. It's a settings issue."
"I think that the most disappointing CTV tests are the ones that were decided by settings that no one looked at."
Host
Business Of Apps - connecting the app industry since 2012

This time, we're talking about the practical impact of AI on app store optimization - and why LLMs aren't about to pull app discovery out of the stores.
LLMs are changing how people search the web. But app discovery has stayed inside the App Store and Google Play for 16 years, and the stores are now adding AI layers of their own.
To cover all this, we've got Dave Bell, Co-Founder and CEO of Gummicube, about how AI is reshaping ASO on the App Store and Google Play.
Dave explains why winning in-store search is what earns an app a place in Apple's and Google's AI recommendation layers, and why reviews, Custom Product Pages, and Android vitals now count as AI signals. He also covers the risk of "AI cannibalization" when competing apps use generic prompts to write their metadata, the store policies and copyright issues around AI-generated content, and why your website, social, and store listing need to tell the same story.
If you work in app store optimization, app marketing, or app growth, this is a clear look at what AI actually changes in the stores - and what it doesn't.
Today’s topics include:
App discovery stays in the stores - web downloads remain in the single digits, and LLMs will take share from web search, not from the App Store
Search feeds AI - the organic signals that power in-store search also fuel Siri, Spotlight, personalized collections, and Ask Play
New AI ranking signals - ratings and reviews, Custom Product Pages linked to organic terms, and Android vitals all affect how AI positions your app
AI cannibalization - generic LLM prompts produce identical listings, lower conversion, and risk store penalties under Apple and Google Play spam policies
Content cohesion - aligning your website, social, and structured content with your store listing so LLMs find one consistent story
Links and Resources:
Dave Bell on LinkedIn
Gummicube website
Business Of Apps - connecting the app industry
Quotes from Dave Bell
“LLMs are absolutely going to eat search.”
"AI is great for research, but it's not great for creation."
“You don't want to have a web page that communicates one thing, and a store listing that communicates another.”
Host
Business Of Apps - connecting the app industry since 2012

Today we're talking about influencer marketing - and about the point where creator content stops being a brand play and starts being a performance channel.
Creator-led ads run four times better on click-through rate than the same brand's own ads. So the question is no longer whether to use influencers. It's how to scale them without losing the ROI.
In this episode, we bring you a live panel hosted by Lucia Aguilar, CEO and Founder at TATAM Digital, featuring:
Joanna Malecka, Partnership Director at Numan
Esma Ebnu, Influencer Marketing at Flo Health
Lia Darozhkina, Senior Influencer Marketing Manager at Trade Republic
Stephanie Terziyski, Growth Influencer Marketing Manager at HelloFresh.
The panel works through four trends. YouTube as the new TV - 13% of all US viewership and more ad revenue than Paramount, Disney, Universal, and Warner combined - and why long-form still converts for products that need explaining. Creator and partnership ads, where content boosted from the creator's own handle beats anything posted from a brand account. Regulation, with only 57% of UK paid posts tagged correctly, and how teams in health, Pharma, and banking build compliance into the brief instead of bolting it on at sign-off. And AI, from sourcing and brief writing through to forecasting campaign results, plus the case for human creators in a feed filling up with avatars.
If you work in influencer marketing, user acquisition, or performance marketing, this is a practical look at where creator budgets are going in 2026 and what it takes to scale them profitably.
The panel’s topics include:
AI in growth teams — which tasks it already replaces, and why humans still own strategy
Performance marketing's limits — why trust-driven categories like fintech need brand channels too
Web-to-app funnels — near-double conversion rates and skipping the 30% app store tax
Channel strategy for 2026 — fewer channels done better vs. always testing new ones
Data and targeting vs. creative — where each wins, and the 96% CPA reduction story

In this episode, we're talking about app store visibility - and about the fact that organic and paid aren't two separate budgets.
Every channel you run, no matter where it starts, ends up on the same product page. And the platforms are watching what happens there.
To cover all this, we've got Stephanie Ino, Client Services Manager at Gummicube, about how ASO and paid search feed each other on the App Store and Google Play.
Stephanie explains why ASO is the home base every channel returns to, how Apple Ads and Google Ads send relevance signals back into the organic algorithm, and why the right split between the two depends on budget, app maturity, and how much relevance you've already built. She also covers Custom Product Pages and Custom Store Listings as a way to align paid traffic with the right creative, and why a younger app should build its ASO foundation before pushing paid spend through.
If you work in app store optimization, user acquisition, or app growth, this is a clear look at how the paid and organic sides of the store actually connect.
Today’s topics include:
ASO as home base - metadata and creative work together because almost every channel routes users back to the product page or store listing
Paid feeding organic - Apple Ads SERP placements and Google Ads Play Store placements both send relevance signals into the algorithm for the terms you're targeting
Striking the balance - there's no blanket answer, it comes down to available budget, app size, and maturity in the storefront
Younger apps first build relevance - get the ASO foundation and keyword rankings in place, then push paid traffic through at a lower acquisition cost
Custom Product Pages and Custom Store Listings - matching store assets to each paid campaign's strategy so the traffic you buy actually converts
Links and Resources:
Stephanie Ino on LinkedIn
Gummicube website
Business Of Apps - connecting the app industry
Quotes from Stephanie Ino
“ASO is where everything comes back to, kind of home base. Most of any channel will come back into that product page or that store listing.”
"When we're running Apple Ads, particularly for those SERP results, it gives that boost in relevance so that Apple understands that we have better potential to then rank organically for those terms."
“If we're working with a younger app in the storefront, we don't have that relevance built out yet within the algorithm. So we really want to focus on our organic and our ASO performance first.”
Host
Business Of Apps - connecting the app industry since 2012

Today we're talking about mobile A/B testing - and about the moment the app store hands you a winner.
Because that result is directional, not the truth. And if most of your traffic is paid, you may have measured the wrong users entirely.
In this episode, we speak with Scott Masters, Director of Strategy and Partnerships at Gummicube, about why mobile A/B testing is never set-and-forget.
Scott explains why most developers and marketers under-invest in testing, what a sensible cadence looks like - once or twice a month, with each test running at least two weeks to reach statistical significance - and why changing one element at a time is the only way to know what actually moved the needle.
If you work in app store optimization, user acquisition, or app growth, this is a practical guide to testing your product page properly.
Today’s topics include:
Why testing is never one-and-done - trends, user preferences, and app features all shift, and a static product page goes stale
Cadence and statistical significance - test once or twice a month, run each test at least two weeks, with traffic volume determining how long
One variable at a time - change the screenshot copy and the imagery together and you won't know which one worked
What to test beyond screenshots - title, subtitle, short and full descriptions, icons, and feature graphics all feed the strategy
Measuring what's real - platform confidence intervals are directional, so validate with pre- vs. post-deployment conversion rates across every channel
Links and Resources:
Scott Masters on LinkedIn
Gummicube website
Business Of Apps - connecting the app industry
Quotes from Scott Masters
“If you're not A/B testing at least once or twice a month, you're leaving users out there for other competitors to take from you.”
"It's not a one-and-done. You can't set it and forget it. It's just like with any other brand - you create a package for your product and you put it on the shelf. If it doesn't change over time, if you're not attracting those users with new materials or new approaches, it's going to get stale."
“The platforms will give you an estimated conversion impact and confidence interval for each test you run. But that data is directional. True validation of performance really comes from launching a test winner into the store and then measuring the pre-deployment conversion rate versus the post-deployment conversion rate.”
Host
Business Of Apps - connecting the app industry since 2012

In a world built to fragment your attention, one news app made the opposite bet: fewer ads, trusted sources, and users who actually stay.
In this episode, we speak with Ramesh Ramalingam, VP of Product at SmartNews, about how a Japanese news app was rebuilt — not ported — for American users.
Ramesh explains why SmartNews users spend 20 minutes per session, why 79% of them don't switch to another screen while reading, and how that focus turns into brand recall for advertisers. He also covers contextual targeting without cross-web tracking, why the product looks different in Tokyo than in Los Angeles, and how a revenue-share model keeps publishers in the loop.
If you work in product, app growth, or media monetization, this is a conversation about building for engagement quality rather than scale.
Today’s topics include:
Engagement over scale — 20-minute average sessions and why 79% of users stay undistracted
Monetization model — native brand and performance advertising, programmatic where it fits, plus SmartNews+ subscriptions in Japan
Brand safety and privacy — contextual targeting, first-party data, and third-party validation instead of invasive tracking
Japan to US expansion — high-density vs. clean-white-space design, local publisher partnerships, and building credibility from scratch
Centralized vs. decentralized product development — core platform in Japan, market teams close to local users
Links and Resources:
Ramesh Ramalingam on LinkedIn
Smartnews website
Business Of Apps - connecting the app industry
Quotes from Ramesh Ramalingam
“What is interesting about SmartNews is it's not about the scale. We're talking about 50 million, but it's more about the user engagement. Our users spend on average 20 minutes in our product, which is very high.”
“From an advertiser perspective, yes, they do care about the reach, but trust is the most important aspect. We don't rely on invasive tracking across the web like other platforms do. What we built is a privacy-first, brand-safe environment.”
“We didn't take the Japanese app and plug it into the US. We made sure that it is customized to the user preferences in the US, and it's built for American users.”
Host
Business Of Apps - connecting the app industry since 2012