How I Grew This is a podcast hosted by Amanda Vandiver and Adam Landis exploring the real stories behind digital growth. Each episode features candid conversations with leaders in marketing, product, and tech about how they built, scaled, and navigated challenges in an ever-changing digital landscape. From breakthrough strategies to hard-earned lessons, guests share what actually worked—and what didn’t—along the way.

How I Grew This: Real Stories of Digital Growth

What if the key to mobile campaign success wasn't just about driving installs? In this episode, host Amanda sits down with Erica Johnson, Director of Global Platforms at Publicis Collective, to explore why thinking beyond the install matters, how to build seamless cross-device experiences, and the critical role measurement plays in modern mobile advertising, alongside AI's growing influence. Whether you're navigating measurement challenges, managing complex global migrations, or preparing for 2026's mobile landscape, this conversation is packed with actionable strategies from the Publicis Mobile Summit. Tune in to uncover how a holistic approach to mobile campaigns drives real, measurable growth. 
What You’ll Learn:
How to move beyond install-focused metrics and measure long-term value 
Why the web-to-app journey deserves immediate attention 
The crawl-walk-run framework for executing large mobile campaigns 
How to approach MMP migrations strategically 
Why AI in ad operations requires teaching the technology your standards rather than fearing it 
How to accelerate into leadership roles 
About the Guest(s):
Erica Johnson is Director of Global Platforms at Publicis Collective, bringing deep expertise in digital marketing, media technology, and ad operations. With a career spanning mobile advertising, mobile measurement partners (MMPs), and campaign execution across social, search, programmatic, and CTV channels, she has become a recognized MMP power user and advocate for holistic campaign strategy. In this episode, Erica shares insider perspectives from the Publicis Mobile Summit on emerging trends shaping 2026, including the shift beyond install metrics, the transformative role of AI in ad operations, and strategies for seamless cross-device experiences. Her work migrating global clients across platforms and implementing sophisticated measurement infrastructure has positioned her as a thought leader for brands seeking to optimize mobile performance and measurement in an increasingly fragmented ecosystem. This conversation is essential for marketing professionals and growth strategists looking to navigate mobile advertising complexities and build sustainable, data-driven campaign foundations. 
If you enjoyed this episode, make sure to subscribe, rate, and review it on Apple Podcasts, Spotify, and YouTube Podcasts. Instructions on how to do this are here.
Episode Highlights:
[00:06:17] Think Beyond the Install to Drive Long-Term Mobile App Value 
[00:16:06] Prioritize Postback Events and Partner Configuration in MMP Migrations 
[00:17:27] Prioritize the Web-to-App Journey as a Critical Campaign Foundation 
[00:21:00] Adopt the Crawl-Walk-Run Framework for Large Campaign Execution 
[00:32:02] Lean Into AI Rather Than Fear It—Build Standards and Drive Quality Assurance 
[00:36:45] Pursue Challenging Projects to Build Leadership Credibility and Expertise 
Episode Resources:
Erica Johnson on LinkedIn
Publicis Collective on LinkedIn
Publicis Collective Website
Amanda Vandiver on LinkedIn
Branch on LinkedIn
Branch Website
How I Grew This on Apple Podcasts
How I Grew This on Spotify
How I Grew This on Simplecast

Beyond the Install: Erica Johnson on Building Smarter Mobile Campaigns

What if the most intimate device in your pocket could understand exactly what you need—before you even search for it? In this episode of How I Grew This, hosts Amanda and Adam sit down with Harish Thimmappa, SVP and GM of Discovery Ads at Branch, to explore an on-device solution revolutionizing app discovery. Learn why first-party data is becoming the ultimate competitive advantage, how Branch powers search experiences on half a billion devices worldwide, and the counterintuitive strategies that balance user privacy with advertising performance. Whether you're a marketer looking to diversify beyond Meta and Google, an app developer navigating a crowded ecosystem, or an AdTech enthusiast curious about the future of personalization, this conversation reveals the technology and thinking that's reshaping mobile commerce. Tune in to discover why the next generation of advertising isn't about who bids the most—it's about who understands the user best. 
What You’ll Learn:
How to build trust by prioritizing user experience over ad load
Why on-device bidding and ad selection outperforms cloud-based systems
The power of behavioral pattern recognition beyond search intent
How to align supply and demand in ad tech marketplaces
Why first-party data is now the competitive moat in advertising
How to position experimentation as table stakes for modern marketers
About the Guest(s):
Harish Thimmappa is the SVP and GM of Discovery Ads at Branch, leading a standalone business unit that has grown into a major force in mobile advertising. With over two decades of experience in adtech, Harish has built a reputation for scaling technology and advertising businesses, previously holding key roles at InMobi, Supersonic Ads, Kensho, and Unboxed. In this episode, he reveals how Branch Discovery leverages on-device machine learning and first-party data to deliver contextually relevant search results and ads to over 500 million devices globally, while maintaining user privacy and trust. Harish shares actionable strategies for marketers on experimenting with emerging ad platforms, demanding performance-based results, and diversifying spend beyond Meta and Google. His work in developing privacy-first, performance-driven advertising solutions makes this conversation essential listening for digital advertisers and adtech professionals seeking to understand the future of mobile discovery and app monetization. 
If you enjoyed this episode, make sure to subscribe, rate, and review it on Apple Podcasts, Spotify, and YouTube Podcasts. Instructions on how to do this are here.
Episode Highlights:
[00:07:50] Maintain a 90/10 Organic-to-Ad Ratio to Build OEM Trust
[00:12:32] Capture Non-Intuitive Behavioral Patterns to Unlock Deeper Targeting
[00:17:03] Move Ad Selection On-Device to Overcome Connectivity and Privacy Constraints 
[00:19:58] Align Supply, Demand, and Product Teams to Prevent Monetization Failures 
[00:22:56] Win Advertiser Confidence Through Performance Rather Than Features Alone 
[00:33:20] Marketers Should Experiment Beyond Meta and Google to Find Information Asymmetries 
Episode Resources:
Harish Thimmappa on LinkedIn
Amanda Vandiver on LinkedIn
Adam Landis on LinkedIn
Branch on LinkedIn
Branch Website
How I Grew This on Apple Podcasts
How I Grew This on Spotify
How I Grew This on Simplecast

Shifting the Search Paradigm: How Branch Discovery Powers On-Device Intent for Half a Billion Users with Harish Thimmappa

What if you could turn creator content into your most cost-effective acquisition channel? In this episode of How I Grew This, Amanda and Adam sit down with Nic Weber, Co-Founder and Chief Product Officer of Noise, to explore why creator-powered marketing outperforms traditional ads, how to build viral campaigns at scale, and the strategies that transform unknown creators into growth engines for your brand. Whether you're a mobile app founder struggling with user acquisition costs or a marketer looking to unlock authentic engagement, this conversation reveals actionable frameworks on relatability, need, and novelty—plus real examples of brands achieving pennies-on-the-dollar CPMs. Tune in to discover how to leverage 950,000+ creators and tap into the future of performance marketing. 
What You’ll Learn:
How to build a two-sided marketplace that aligns creator incentives with brand performance
Why the interest graph has replaced the social graph
The three-lever framework for viral content: relatability, need, and novelty
How to reverse-engineer virality by finding existing successful content in your niche, iterating on it with multiple creators, and then scaling the winning variation
Why users acquired through short-form content are higher-intent than traditional paid ads
How to leverage organic platform algorithms as a free ad network
About the Guest(s):
Nic Weber is Co-Founder and Chief Product Officer at Noise, known for his expertise in creator-powered marketing and viral content strategy. With a background spanning graphic design, mobile publishing, gaming, and consumer apps, Weber has built scalable growth systems that transform how brands acquire customers through short-form content. At Noise, he has pioneered a two-sided marketplace that connects creators with brands, enabling acquisition costs as low as 8¢ effective CPM through viral video campaigns—a model Weber himself validated by building a consumer app to 2 million downloads. In this episode, Weber reveals the psychology behind viral content, the formula for creating trends, and how brands can leverage an army of everyday creators to dramatically reduce customer acquisition costs while maintaining authentic brand messaging. His insights on relatability, need, and novelty provide actionable frameworks for marketers looking to move beyond traditional influencer partnerships and tap into the most addictive social platforms in the world. 
If you enjoyed this episode, make sure to subscribe, rate, and review it on Apple Podcasts, Spotify, and YouTube Podcasts. Instructions on how to do this are here.
Episode Highlights:
[00:09:07] Why Human Creators Beat AI for Social Media Marketing –
Nic reveals that despite AI videos achieving 20 million views, human creators remain essential because they understand audience psychology and can adapt messaging in real-time. The challenge for brands is that algorithms favor authentic human connection, which AI cannot replicate, making creator-led campaigns fundamentally more effective at driving conversions. While AI can generate volume, it lacks the contextual awareness needed to resonate emotionally with viewers, causing audiences to immediately recognize and skip synthetic content. To leverage this insight, brands should prioritize recruiting diverse creators over investing in AI video generation, even when scaling campaigns across multiple platforms. A concrete example: Noise saw dramatically better performance when they had thousands of creators post variations of a concept rather than relying on a single AI-generated video, because the human variations naturally included hooks and messaging tweaks that resonated differently with different audience segments. For brands looking to maximize ROI on short-form platforms, this means building creator armies that can iterate in real-time based on performance data, not betting on automation.
[00:10:49] The Formula for Viral Content: Find, Iterate, Scale –
Nic breaks down virality into a repeatable three-step framework: find existing viral content in your niche, iterate on it with multiple creators to test variations, then scale the winning formula across your entire creator base. Most brands fail because they try to create original viral content, ignoring the fact that the internet has already validated what works—making "not being smarter than the internet" the key to success. The real work happens in the iteration phase, where real creators bring their own creativity to hooks, text overlays, and presentation styles, naturally producing variations that hit different audience segments. Brands should start by identifying viral videos in their category with 1+ million views, then brief 50-100 creators to create their own versions with slight modifications, tracking which variations generate the highest views and conversions. For example, if a competitor's cleaning product video went viral, a brand selling a mop should create dozens of variations showing different mom personas, different pain points, and different product demonstrations—then double down on whichever version outperforms. This approach transforms viral success from a lottery into a predictable, scalable system.
[00:14:18] CPM-Based Creator Partnerships Outperform Flat-Fee Influencer Deals –
Nic explains that paying creators a fixed amount per post ($500–$10,000) creates misaligned incentives, while CPM-based pricing ensures both brand and creator profit when content performs well. When a brand pays a creator a flat fee for a single post that underperforms, the creator has already been paid and has no incentive to improve, while the brand absorbs the loss—this is why traditional influencer marketing often fails to deliver ROI. With CPM pricing, creators are incentivized to post repeatedly, test variations, and double down on high-performing content because their earnings scale with views and conversions. A creator earning $3,000 from a viral post that converted well will stay committed to that brand and continue optimizing, whereas a creator who received a one-time $10,000 payment that didn't convert will move on to find another client. Brands should set CPM targets ($0.50–$2.00 depending on category) and let creators decide when and how to participate, creating a continuous flywheel rather than one-off campaigns. This approach also filters for creators who genuinely understand audience psychology, because only skilled creators can consistently deliver high-view, high-converting content at scale.
[00:35:13] The Three Pillars of Viral Content: Relatability, Need, and Novelty –
Nic identifies three non-negotiable elements that drive engagement and conversions on short-form platforms: relatability (audiences must see themselves in the content), need (addressing a real problem), and novelty (offering something unexpected or improved). Without relatability, content fails to stop the scroll; without addressing an actual need, viewers won't take action; and without novelty, the message blends into the noise of competing products. Brands can audit their content strategy by asking: Does my audience see themselves in this? Am I solving a real pain point? Am I showing something they haven't seen before? The most powerful products combine all three—like the self-wringing mop that's relatable to busy parents, solves the frustration of manual wringing, and delivers a novel product feature. To apply this framework, start by researching viral content in your category that already demonstrates these three elements, then craft your creator briefs around how your product amplifies each pillar. This transforms vague creative direction into a measurable framework that creators can execute against, dramatically improving the odds that content will gain traction.
Episode Resources:
Nic Weber on LinkedIn
Noise on LinkedIn
Noise Website
Amanda Vandiver on LinkedIn
Adam Landis on LinkedIn
Branch on LinkedIn
Branch Website
How I Grew This on Apple Podcasts
How I Grew This on Spotify
How I Grew This on Simplecast

The Viral Growth Blueprint: How Nic Weber Turned Creators Into a Scalable Acquisition Engine

What if you could transform your app's revenue without sacrificing user experience? In this episode of How I Grew This, hosts Amanda and Adam sit down with David Leviev, Chief Revenue Officer and Co-Founder of Nimbus, to explore how publishers can build custom monetization solutions, why user experience directly impacts long-term revenue, and the key strategies to leverage AI and first-party data in a post-IDFA world. Whether you're a mobile app publisher looking to optimize ad performance or an ad tech enthusiast curious about the future of auction mechanics, this conversation is packed with actionable insights on balancing monetization with retention. Tune in to discover how the right decisioning layer can unlock premium CPMs and sustainable growth. 
What You’ll Learn:
Why building a custom monetization stack makes sense
How to identify the magic retention threshold through testing
The decisioning layer framework for auction optimization
Why omitting proprietary demand creates competitive advantage
The three-pronged approach to overcome signal loss post-IDFA
How to structure dedicated publisher support for sustainable growth
About the Guest(s):
David Leviev is Chief Revenue Officer and Co-Founder of Nimbus, a full-stack mobile ad monetization platform. With a background in ad tech spanning companies like Pubgears and pivotal experience monetizing the popular Timehop app, David brings deep expertise in programmatic advertising, auction mechanics, and publisher-first monetization strategies. In this episode, David shares practical insights on building sustainable ad experiences that balance revenue optimization with user retention, providing actionable strategies for app publishers looking to maximize their monetization without sacrificing user experience. His work at Nimbus—where he champions transparency, direct demand relationships, and AI-driven auction optimization—has helped publishers reclaim control over their ad stacks and significantly increase CPMs, making this conversation essential for anyone interested in mobile app monetization and ad tech innovation. 
If you enjoyed this episode, make sure to subscribe, rate, and review it on Apple Podcasts, Spotify, and YouTube Podcasts. Instructions on how to do this are here.
[00:14:21] Find Your App's "Magic Number" for Ad Duration Through Retention Testing - 
David discovered that Timehop's optimal ad display duration was 1.3 seconds—far shorter than industry standards—by systematically testing retention metrics rather than relying on generic benchmarks. Publishers often assume longer ad exposure equals higher revenue, but this approach overlooks the silent user churn that happens when friction increases without generating app store complaints. By monitoring uninstall rates alongside clickthrough rates and viewability scores, you can identify the exact threshold where user experience breaks down. Start with incremental testing, pushing duration limits while watching for organic drops in daily active users or session length. This precision-based approach protects lifetime value and prevents the revenue decay that comes from aggressive ad placements. Smaller publishers can apply this same framework to their own apps, treating retention as the north star metric that balances monetization with sustainable growth.
[00:18:56] Assign Dedicated Cross-Functional Teams to Each Publisher Instead of Generic Support Channels - 
Nimbus provides each onboarded publisher with a dedicated team of five people—an account manager, customer success representative, solutions engineer, technical account manager, and demand facilitator—plus a shared Slack channel for streamlined communication. This stands in stark contrast to industry-standard support models where publishers email a generic address and receive responses from rotating staff across multiple time zones, leading to unresolved issues and missed optimization opportunities. The cost of dedicated support is offset by the ability to deeply understand each app's unique monetization challenges and implement tailored strategies that generic solutions cannot address. These teams proactively monitor ad performance, recommend market trends, and evaluate inventory quality—transforming support from reactive troubleshooting into strategic partnership. For publishers evaluating ad tech partners, demand dedicated support structures as a non-negotiable contract requirement. This investment in human infrastructure becomes a competitive differentiator that directly impacts your ability to optimize revenue while protecting user experience.
[00:24:04] Use Machine Learning to Optimize Auction Costs by Predictively Throttling Bid Requests - 
David explains that applying ML and agentic AI to auction mechanics allows publishers to reduce cloud infrastructure costs (AWS bills) while simultaneously improving bid prices by selectively inviting only demand partners likely to win at premium rates. Traditional waterfall and open-auction approaches waste compute resources by running bids from all demand partners on every impression, even when specific partners have historically shown no intent or ability to compete on that inventory. By analyzing historical bidding patterns, buyer behavior, and performance trends, you can predict which demand partners will generate winning bids on specific user segments and throttle unnecessary bid requests accordingly. This "offensive" strategy preserves DSP budgets for higher-value inventory, encouraging demand partners to bid at their true ceiling rather than low-ball testing bids designed to learn your auction models. Publishers implementing this approach report both lower AWS costs and higher effective CPMs, turning infrastructure expense into a revenue optimization lever. Start by reviewing your last 60-90 days of auction data to identify which demand partners win most frequently on which user segments, then implement bid throttling rules that reflect those patterns.
[00:28:39] Build First-Party Data Packages by Identifying User Behavioral Patterns in Auction Data - 
Instead of relying solely on third-party identifiers like Trade Desk UID or LiveRamp Ramp ID, publishers can reverse-engineer their own audience segments by analyzing which advertisers consistently bid on specific users and what creatives they deliver. For example, if user "John Smith" repeatedly sees BMW and Mercedes ads across multiple auction windows, you can confidently tag him as an "auto enthusiast" and package millions of similar users into curated deals that command premium pricing. This first-party signal approach gives smaller publishers leverage with SSPs and DSPs without requiring massive scale, as SSPs now bundle mom-and-pop apps into curated packages based on performance KPIs rather than audience size alone. Start by tagging users with authenticated credentials (Gmail login, phone number), then analyze 30-60 days of auction data to identify behavioral clusters and their historical CPM performance. Once you understand your audience segments and can quantify their value with performance data, you can confidently pitch curated packages to demand partners. This transforms raw auction data into a proprietary asset that protects against signal loss and increases your negotiating power.
[00:32:40] Set Competitive CPM Floors Based on Historical User Monetization Patterns - 
Publishers without access to third-party identifiers or SSP curation tools can still reclaim significant revenue by implementing dynamic CPM floors that reflect how valuable specific users have historically been in auctions. Rather than using a flat floor across all inventory, analyze your auction history to understand whether a particular user consistently generates $5+ CPMs or $0.50 CPMs, then set asymmetric floors that prevent valuable users from being sold at commodity rates. This approach requires no external partnerships or complex data infrastructure—just historical performance data and the discipline to say "no" to low-priced bids on premium inventory. Even mom-and-pop publishers with limited scale can gain a competitive edge by ensuring their most engaged or high-LTV users don't see cheap remnant ads, which directly impacts long-term revenue and user retention. Start by segmenting your user base into quartiles based on historical CPM performance, then set floor prices that reflect each segment's actual market value. This simple lever can increase effective CPM by 10-20% without requiring audience data partnerships or sophisticated ML infrastructure.
Episode Resources:
David Leviev on LinkedIn
Nimbus on LinkedIn
Nimbus Website
Amanda Vandiver on LinkedIn
Adam Landis on LinkedIn
Branch on LinkedIn
Branch Website
How I Grew This on Apple Podcasts
How I Grew This on Spotify
How I Grew This on Simplecast

The Ad Monetization Paradox: How User Experience Drives 3x Revenue Growth with David Leviev

What if your MarTech stack was actually working *for* you instead of against you? In this episode of How I Grew This, hosts Amanda and Adam sit down with Rebecca Nackson, CEO of Notable, to explore why most companies fail at implementation after buying tools, how to enlist salespeople as strategic partners in your buying process, and the key strategies to build a system of continuous testing and iteration. Whether you're drowning in marketing software or trying to make sense of your growth stack, this conversation is packed with actionable insights to help you move from tool chaos to strategic clarity. Tune in to discover why the best-performing teams aren't using more tools—they're using them smarter.
What You’ll Learn:
How to reframe your career as intentional pattern recognition rather than random luck
Why the sales process is broken and how to fix it as a buyer 
The critical implementation gap no one talks about
How to act as "connective tissue" across distributed teams
The test-learn-scale framework that separates high-growth teams from stalled ones
Why build vs. buy decisions are about to shift dramatically with AI and low-code tools
About the Guest(s):
Rebecca Nackson is the CEO of Notable, a marketing consultancy specializing in helping companies navigate and optimize their marketing technology stacks. With a background spanning Audible, iHeartRadio, Bandsontown, and Prolific, Rebecca brings deep expertise in digital transformation, marketing operations, and cross-functional alignment. In this episode, she shares candid insights on bridging the gap between buying marketing tools and successfully implementing them—a critical pain point for modern marketing teams. Her philosophy centers on understanding the "job to be done" rather than defaulting to solutions, and her work has helped numerous companies avoid costly MarTech missteps while building sustainable growth systems. This conversation is essential listening for marketers and product leaders seeking to maximize ROI from their technology investments and create alignment across distributed teams.
If you enjoyed this episode, make sure to subscribe, rate, and review it on Apple Podcasts, Spotify, and YouTube Podcasts. Instructions on how to do this are here.
Episode Highlights:
[00:01:45] Embrace "Career Squiggles" Over Linear Planning - 
Rebecca Nackson reframes career success not as following a predetermined path, but as recognizing patterns across seemingly random opportunities—what she calls "career squiggles." Most professionals assume their early roles must align with their end goal, but Rebecca's trajectory through Audible, iHeartRadio, and Bandsontown shows that adjacent experiences compound into unexpected expertise. The pressure to have a five-year plan can actually blind you to emerging patterns and opportunities that only make sense in hindsight. Instead, focus on developing deep skills in each role and staying alert to common denominators across different industries and companies. By the time you've worked across multiple verticals, you've gained a superpower: seeing what others miss because you recognize repeating patterns. This approach transforms career uncertainty into a competitive advantage, especially when building businesses or advising others through similar challenges.
[00:15:45] Fix the Implementation Gap Between Buying and Using MarTech Tools - 
The largest missed opportunity in enterprise software purchases happens after the contract is signed—the step from buying to actually using the tool is routinely skipped, leaving companies paying for solutions they can't operationalize. Most vendors invest heavily in the sales process but provide little support for the critical transition to implementation and integration. Instead of treating your tool evaluation as a final decision, use it as an opportunity to simultaneously inform both your sales process and your implementation strategy by clearly articulating what's broken today and what success looks like for your specific business. This forces vendors to be specific about cost, resource requirements, and phased rollout timelines—information you'll desperately need the day after signing. By reversing the typical process and enlisting salespeople as partners who understand your real constraints, you create a feedback loop that strengthens both the evaluation and the execution. Companies that front-load this discovery work dramatically improve their ability to extract ROI from new tools rather than letting them gather dust.
[00:21:31] Become the "Connective Tissue" Across Siloed Internal Teams - 
One of the most underrated services agencies provide—and one any leader can replicate internally—is acting as connective tissue between teams that rarely interact, especially in remote-first organizations where marketing, product, and engineering don't naturally cross paths. Without deliberate bridging, these teams often become adversarial, with acquisition blaming retention and retention blaming acquisition quality, when in fact they're two sides of the same customer lifecycle coin. The first step is documentation: ask each team to share their current processes, then synthesize and redistribute this information so teams understand how their work feeds into the next stage. Next, facilitate conversations where product marketing shares customer acquisition data with the retention team, and lifecycle marketing shares churn patterns with product, so each team gains visibility into the upstream and downstream effects of their work. When teams understand the complete journey and see how customer data flows from acquisition through retention, they stop treating each other as obstacles and start collaborating on shared metrics. This internal connective work often generates as much value as the external consulting itself because it permanently changes how teams operate together.
[00:28:24] Build Compounding Growth Through Small, Tested Loops Instead of Big Swings - 
The clearest separator between high-growth teams and stalled ones is whether they operate within a system of continuous, small experiments with clear success metrics and predetermined scaling/kill decisions, or whether they take periodic large bets with no learning mechanism. Successful teams treat growth like compound interest—each week they test a hypothesis (if we onboard in this way, will retention improve?), define what success and failure look like before launching, and have a pre-committed plan for scaling if it works or killing it if it doesn't. This approach generates incremental wins that compound throughout the year, so these teams consistently end the year higher than they started, even if individual experiments fail at a normal rate. In contrast, teams taking big swings often see dramatic results one way or the other, but because they didn't isolate variables or document the test conditions, they can't extract learnings or replicate success. The framework is simple: form a hypothesis, run a test, measure against pre-defined success criteria, scale what works, kill what doesn't, and repeat weekly. This systematic approach transforms growth from a series of desperate gambles into a predictable, compounding process that any team can operationalize.
Episode Resources:
Rebecca Nackson on LinkedIn
Notable on LinkedIn
Notable Website
Amanda Vandiver on LinkedIn
Adam Landis on LinkedIn
Branch on LinkedIn
Branch Website
How I Grew This on Apple Podcasts
How I Grew This on Spotify
How I Grew This on Simplecast

Why Your MarTech Stack Is Broken—And How to Fix It Without Starting Over with Rebecca Nackson

What if your messaging could be the infrastructure powering growth instead of just surface-level copy? In this episode of How I Grew This, hosts Amanda and Adam sit down with Chris Silvestri, Founder of Conversion Alchemy, to explore why research and strategy matter more than writing, how to craft messaging that cuts through AI slop and sameness, and the key strategies to balance point of view with value-driven messaging. Whether you're building a brand, launching a product, or navigating the creator economy, this conversation is packed with actionable insights on positioning, personalization, and preparing your messaging for the future of AI agents. Tune in to discover how to make your brand truly stand out.
What You’ll Learn:
How to Reframe Copywriting as 70% Research and Strategy, Not Writing
The Point-of-View + Value Messaging Framework
How to Extract Voice-of-Customer Language Before AI Touches Your Copy
Why Message-Market Fit Matters More Than Message-Product Fit
The Three-Layer Research Blueprint
How to Recognize and Avoid AI Slop in Your Brand Communication
Why You Need to Validate Messaging Before Launch
How to Adapt Your Messaging for the AI Agent Economy
About the Guest(s):
Chris Silvestri is the Founder of Conversion Alchemy, a strategic messaging consultancy that helps B2B and B2C companies clarify their positioning and craft compelling copy that drives conversions. With a unique background spanning over a decade as a software engineer in industrial automation and UX design, Chris brings a technical, infrastructure-focused approach to messaging strategy that goes far beyond surface-level copywriting. In this episode, Chris shares how to balance point of view with value-driven messaging, leverage AI without falling into generic "slop," and adapt your communication strategy for an increasingly attention-scarce market. His methodologies for research, positioning, and testing provide actionable frameworks for organizations looking to stand out authentically and connect meaningfully with their audiences in a crowded digital landscape.
If you enjoyed this episode, make sure to subscribe, rate, and review it on Apple Podcasts, Spotify, and YouTube Podcasts. Instructions on how to do this are here.
Episode Highlights:
[00:05:46] Reframe Copywriting as 70% Research and Strategy, Not Writing - 
Chris reveals that in today's AI-driven world, the mechanical act of writing now represents only 10% of his copywriting work, while research comprises 70% and strategy comprises 20%. This shift is critical because most companies and marketers assume copy is the primary deliverable, missing the foundation that makes copy effective. Without thorough research into internal alignment, customer needs, and competitive positioning, even the most eloquent copy falls flat. The process begins with internal research across product, marketing, support, and customer success teams to identify messaging inconsistencies that undermine brand coherence. Next, external research examines how customers experience transformation through your product, combined with market research analyzing competitor positioning and messaging approaches. This strategic foundation ensures that when copy is finally written, it emerges naturally from deep customer and market understanding rather than guesswork.
[00:09:37] Balance Point-of-View with Value-Driven Messaging to Generate Genuine Attention - 
Chris explains that most companies excel at either showcasing a strong industry perspective or communicating customer value, but rarely balance both effectively—and this imbalance is precisely why they sound generic and forgettable. To create distinctive messaging, ask your team provocative questions like "What misconceptions in your industry drive you crazy?" and "What lies do you want to expose with your product?" These insights form your hook—a unique point of view that makes prospects think "You understand me." However, a strong opinion alone won't convert; you must pair it with clear value messaging that answers "What's in it for me?" When both elements carry equal weight, your messaging becomes a seesaw in perfect balance, generating the attention and engagement competitors cannot replicate. For B2C brands, this point of view shifts from industry-focused to customer-experience-focused, using vivid examples of how your product transforms daily life.
[00:17:08] Absorb Customer Language Before Feeding Data to AI Tools - 
Chris emphasizes that the most common mistake brands make when using AI for messaging is feeding customer data directly into AI models without first deeply absorbing that voice themselves. Before running 500 customer reviews through AI, Chris personally reads every single one to internalize the authentic language, emotions, and concerns customers express naturally. This human-first approach creates an intuitive foundation that allows him to edit and refine AI-generated copy with confidence and accuracy, ensuring it reflects real customer voice rather than generic AI patterns. You can apply this by reconstructing vivid "day-in-the-life" narratives of your customers—either through real interviews or AI-assisted synthesis grounded in actual data—to capture the specific language, pain points, and desires that define their experience. When AI tools then generate variations or enhancements to your copy, you'll recognize immediately whether they've preserved the authentic voice or drifted into corporate jargon and hollow sentiment. This intuition-building phase is non-negotiable if you want AI to amplify your brand's voice rather than replace it.
[00:22:12] Validate Messaging Before Launch Using Usability Testing and Synthetic Research - 
Chris stresses that launching copy without validation is a costly gamble; instead, conduct pre-launch message testing using platforms like UserTesting, UXTweaks, or Winter (for B2B) to observe how real prospects respond to your messaging in context. Usability testing requires carefully crafted test questions that prompt genuine reactions rather than leading responses—track prospects from landing through the entire conversion journey to identify where messaging resonates or confuses. For B2C brands with tight budgets, synthetic research using AI personas yields approximately 50-60% accuracy on its own, but jumps to 80% accuracy when grounded in real customer research data and transcripts from actual interviews. Chris recommends using synthetic research to expand limited interview data—if you've interviewed only three customers, use AI to generate richer voice-of-customer variations that make your copy more vivid and resonant without relying solely on synthetic insights. Post-launch, run A/B tests on value propositions and email subject lines, then conduct quarterly research refreshes to stay aligned with shifting market dynamics and competitive positioning.
[00:28:04] Prepare for AI Agents by Making Copy Crystal Clear and Jargon-Free - 
Looking five years ahead, Chris warns that AI agents and bots will increasingly browse websites and make purchasing decisions on behalf of humans, forcing companies to rethink how they communicate across all channels. These AI agents extract the core essence of what you do and who you serve to determine relevance and fit—meaning vague language, marketing fluff, and industry jargon that confuse bots will also confuse or repel human visitors. Your copy must become radically clear about your positioning, value proposition, and ideal customer, using plain language that both humans and AI systems can parse and recommend to others. This doesn't mean abandoning brand personality; rather, it means building clarity as the foundation upon which personality and voice sit. Begin now by auditing your website copy for unnecessary jargon, softening language, and vague claims, replacing them with crystal-clear statements of what you do, who benefits most, and how you're different—the same clarity that will help AI agents recommend you to the right customers. 
Episode Resources:
Chris Silvestri on LinkedIn
Conversion Alchemy on LinkedIn
Conversion Alchemy Website
Amanda Vandiver on LinkedIn
Adam Landis on LinkedIn
Branch on LinkedIn
Branch Website
How I Grew This on Apple Podcasts
How I Grew This on Spotify
How I Grew This on Simplecast

Reclaim Your Brand Voice and Rise Above the AI Slop with Chris Silvestri

What if the future of performance marketing wasn't about controlling every detail, but about measuring what matters and experimenting beyond the obvious channels? In this episode of How I Grew This, Amanda and Adam sit down with Ionut Ciobotaru, CEO and Co-founder of Hypd.ai, to explore why measurement is the foundation of marketing success, how AI agents are reshaping advertiser workflows, and the untapped channels that savvy marketers should be exploring next. From building PubNative into an ad tech powerhouse to launching a pretzel bakery in Berlin, Ionut shares hard-won lessons about pivoting, scaling, and knowing when to double down. Whether you're optimizing a single channel or managing complex multi-platform campaigns, this conversation is packed with strategic insights to help you allocate your budget smarter and stay ahead of the curve. Tune in to discover why your next competitive advantage might lie in channels you haven't considered yet.
What You’ll Learn:
How to identify and capitalize on emerging technology waves
Why pivoting your core product based on market realities is essential for survival
The "international advantage" of digital-native businesses
How to structure acquisitions and integrations for maximum value
Why measurement and attribution must come before experimentation in performance marketing
How AI agents will unlock access to fragmented, non-programmatic channels
About the Guest(s):

  
Ionut Ciobotaru is a serial entrepreneur and AI-driven performance marketing innovator, currently building Hypd.ai, an AI agent platform designed to streamline marketing operations across multiple advertising channels. With a distinguished career spanning mobile ad tech, programmatic advertising, and strategic business scaling, Ionut co-founded PubNative—a native mobile ad network that was acquired by MGI (now Verve Group)—where he served as Co-CEO overseeing significant M&A integration and product development. In this episode, Ionut shares hard-won insights on building successful ad tech ventures, navigating complex acquisitions, and leveraging AI to solve real-world challenges facing modern performance marketers. His deep expertise in channel innovation, measurement attribution, and emerging advertising platforms provides actionable strategies for entrepreneurs and marketers looking to stay ahead in an increasingly fragmented digital landscape. Whether discussing the evolution from mobile-first advertising to today's omnichannel environment, or the future of AI-powered marketing automation, Ionut's perspective offers invaluable guidance for those seeking to drive measurable business growth.
If you enjoyed this episode, make sure to subscribe, rate, and review it on Apple Podcasts, Spotify, and YouTube Podcasts. Instructions on how to do this are here.
Episode Highlights:
[00:01:06] Recognize Technology Inflection Points Before the Market Saturates - 
Ionut's early career demonstrates the power of identifying emerging tech waves—he moved from web to mobile specifically because he recognized the iPhone represented a fundamental shift in how users would access digital experiences. Rather than starting his mobile venture in Romania where the infrastructure didn't support it, he strategically relocated to Berlin to position himself at the center of mobile innovation. This insight reveals that successful founders don't just follow trends; they **position themselves geographically and professionally where new technologies are being adopted first**. For performance marketers and entrepreneurs, this means **continuously scanning the horizon for the next wave** before it becomes obvious to everyone else. The timing advantage of being early allows you to build expertise, relationships, and credibility that compound over years. Ionut's entire career—from native ads to AI agents—reflects this principle of finding emerging channels before they become commoditized.
[00:05:11] Pivot Your Product When Market Forces Demand It, Not When Your Vision Says Otherwise - 
PubNative began as a native-only ad network designed to replace banner ads, yet by the time Ionut sold the company, it had pivoted to selling primarily banners and programmatic formats—the exact formats he originally opposed. Rather than viewing this as failure, Ionut explains that **sometimes you cannot push against the market itself as a single company**, and larger advertisers demanded standardization across channels. This teaches a crucial lesson: **your founding thesis matters less than your ability to serve what customers actually need**. Large brands wanted consistency, so PubNative adapted rather than die on principle. For performance marketers building products or services, this means **staying obsessed with solving real customer problems** rather than being married to your original feature set. The companies that survive are those flexible enough to follow customer demand while maintaining their core mission of creating value.
[00:06:33] Leverage the International Advantage of Digital-Native Businesses to Accelerate Growth - 
One of the most surprising insights from Ionut's mobile era was how fundamentally different digital distribution was from traditional media—a developer in Belarus could launch an app globally and compete with anyone, whereas traditional media (radio, TV, print) remained localized and gatekept. **This international scalability is unique to digital products** and represents a structural advantage that didn't exist in previous eras. Small publishers like Voodoo could launch a game from France and reach users worldwide instantly. For modern performance marketers and entrepreneurs, this principle remains vital: **your product's ability to reach a global audience from day one means you should think internationally from the start**. Rather than optimizing for one geography first, consider how your offering can serve multiple markets simultaneously, learning and iterating across regions. This fundamentally changes how you approach customer acquisition, product development, and fundraising—you're not building a local business that might go international; you're building an international business from inception.
[00:29:37] Master Measurement and Attribution Before Experimenting with New Channels - 
Ionut articulates a hierarchy of priorities for performance marketers that directly contradicts conventional startup wisdom: **small brands should focus obsessively on maximizing single channels before attempting to optimize across multiple channels**, while **large brands competing for the same keywords need sophisticated measurement and attribution to identify where to shift budget**. Small brands often haven't exhausted Google or Meta; they're leaving money on the table in known channels rather than needing new ones. This framework reveals that **the biggest mistake small brands make is channel proliferation before channel mastery**. For performance marketers at any stage, this means **building robust measurement infrastructure is prerequisite to intelligent experimentation**—without knowing which channels and segments actually drive value, any new channel you add is essentially a guess. Large brands report shifting their measurement cadence from annual to quarterly reviews, meaning they're now making reinvestment decisions every three months rather than annually. The implication: **measurement is no longer optional or low-priority; it's the operational heartbeat of modern performance marketing**.
[00:37:23] Use AI Agents to Access Fragmented, Non-Programmatic Channels That Were Previously Unscalable - 
The future opportunity Ionut identifies with AI agents isn't automating existing workflows (platforms like Meta and Google are already doing that)—it's **lowering the barrier to entry for retail media, out-of-home, CTV, and other channels that aren't easily traded on impressions**. Before AI agents, buying billboard space or shelf space required upfront commitments of tens of thousands of dollars; agents can simplify both buyer and seller operations enough to allow smaller budget commitments. **This unlocks a massive untapped inventory of advertising channels that were previously inaccessible to most brands**. For performance marketers, this represents the next frontier: **once you've optimized Google and Meta (which AI within those platforms will handle automatically), the competitive advantage shifts to discovering and scaling in emerging, less-optimized channels**. The workflow looks like: establish measurement, optimize existing channels, then systematically experiment with new channels using agentic automation. This represents a fundamental shift from "which ad formats perform best" to "which unexploited channels contain audiences we haven't reached yet."
Episode Resources:
Ionut Ciobotaru on LinkedIn
Hypd.ai on LinkedIn
Hypd.ai Website
Amanda Vandiver on LinkedIn
Adam Landis on LinkedIn
Branch on LinkedIn
Branch Website
How I Grew This on Apple Podcasts
How I Grew This on Spotify
How I Grew This on Simplecast

Building Through Every Ad Tech Era: AI, Attribution, and What’s Next with Ionut Ciobotaru

What if AI could actually amplify human creativity instead of replacing it? In this episode, Amanda and Adam chat with Jen Taylor, Director of AI Strategy and Integration at Capacity Interactive, about how arts and culture organizations can adopt AI thoughtfully and strategically. From building ethical frameworks and training teams to unlocking practical use cases that drive real business results, Jen shares how to position AI as a thought partner rather than a shortcut—and why keeping humans in the loop is essential to avoiding "AI slop." Whether you're a marketer looking to level up your strategy or an arts administrator curious about where AI actually fits into your workflow, this conversation is packed with actionable insights on how to use these tools to work smarter, not just faster.
What You’ll Learn:
How to position AI as a thought partner for strategy, not just a workflow optimizer—unlocking deeper thinking on target audiences, messaging, and campaign refinement
The three-phase adoption framework: establish clear organizational policies, invest in training and prompting literacy, then identify business outcomes tied to measurable results
Why ethics matter differently in arts organizations: address ownership concerns, environmental impact, and imitation risks by making active, intentional choices about tool use
How to build consistency across departments using branded AI tools that understand your voice, style, and mission without sacrificing human oversight
The "human-driven AI" principle: keep humans in every loop—from prompting strategy through verification—to avoid "AI slop" and ensure quality output
How to use AI for audience insights and personalization by testing messaging across multiple audience segments, then letting AI surface unexpected audience opportunities
About the Guest(s):
Jen Taylor is Director of AI Strategy and Integration at Capacity Interactive, bringing over 15 years of experience building and engaging audiences across streaming and digital platforms. With a background in theater marketing and digital audience growth at A&E Networks—where she managed strategy for both ad-supported and subscription streaming businesses—Taylor has become a leading voice in helping arts and culture organizations adopt AI responsibly. In this episode, she shares practical strategies for arts administrators looking to leverage AI for operational efficiency while preserving human creativity and artistic integrity. Her work bridges the gap between cutting-edge technology and the arts community, offering actionable frameworks for organizations seeking to enhance their marketing and administrative workflows without compromising their values.
If you enjoyed this episode, make sure to subscribe, rate, and review it on Apple Podcasts, Spotify, and YouTube Podcasts. Instructions on how to do this are here.
Episode Highlights:
[00:20:14] Use AI to Elevate Strategy, Not Just Speed Up Tasks - 
Jen Taylor emphasizes that while AI excels at automating repetitive tasks, its real power lies in serving as a thought partner for strategic thinking. Many organizations get excited about efficiency gains, but miss the opportunity to use AI for deeper strategic work like audience analysis and campaign refinement. The distinction between "making a plan" and "making a strategy" is critical—AI can help you move beyond constant tactical execution into thoughtful, intentional strategy development. Ask AI to stress-test your plans, identify misalignments with specific audiences, and explore angles you might have missed. This approach transforms AI from a time-saving tool into a strategic advisor that elevates your entire marketing function.
[00:07:11] Implement a Three-Phase AI Adoption Framework - 
Rather than rushing to use AI tools, Jen recommends a structured, phased approach: establish clear organizational policy first, invest in training and prompt literacy second, then identify business outcomes tied to specific results. Many arts organizations worry about ethics and values alignment, so beginning with policy ensures AI adoption stays true to your mission. The nuance matters deeply—approving ChatGPT is just the start; you must then decide what features and capabilities team members can actually use. Following this framework prevents scattered adoption and ensures your organization gains consistent, measurable value from AI investments.
[00:12:26] Address AI Ethics Head-On by Making Active, Intentional Choices - 
Jen identifies three critical ethics concerns for arts organizations: ownership and fair compensation for artists whose work trained AI models, environmental impact from computational demands, and the risk of imitation and copyright violation. Rather than paralysis, she advocates for making deliberate choices that mitigate these risks. For example, opening a new chat when changing topics reduces computational load, and applying the same ethical standard you'd use offline—don't ask AI to do what you wouldn't steal manually—keeps your use aligned with your values. This active, thoughtful approach prevents "AI slop" and ensures the tool enhances your work rather than compromising your integrity.
[00:34:13] Build AI Tools for Audience Consistency and Personalization - 
Jen demonstrates practical use cases where AI drives measurable business impact: building custom tools that ensure consistent brand voice across departments, and creating systems that identify which audience segments will respond to specific messaging. By feeding AI your target audiences and ad copy, you can discover unexpected audience overlap and generate new messaging variations tailored to incremental segments. This approach treats AI as a discovery and personalization engine, helping you move beyond assumptions about who your audience is. The result is more sophisticated, data-informed audience targeting that increases conversion and resonance.
[00:40:15] Keep Humans in the Loop at Every Stage of AI Use - 
Jen's philosophy of "human-driven AI" means your strategy, judgment, and oversight remain central throughout the AI process—from crafting the initial prompt through validating the output. Rather than fully automating decisions, use AI to generate options and insights that you then critically evaluate, refine, and ultimately decide upon. This hands-on approach requires you to maintain skills across your area of expertise, occasionally doing work manually to keep your thinking sharp. The difference between this active collaboration and fully automated, unreviewed AI output is visible to your audience; quality emerges when humans and AI work together intentionally.
Episode Resources:
Jen Taylor on LinkedIn
Capacity Interactive on LinkedIn
Capacity Interactive Website
Amanda Vandiver on LinkedIn
Adam Landis on LinkedIn
Branch on LinkedIn
Branch Website
How I Grew This on Apple Podcasts
How I Grew This on Spotify
How I Grew This on Simplecast

AI won’t replace your artists, but it will free them to create more with Jen Taylor

What if your health tech marketing strategy is actually holding you back from growth? In this episode, Amanda and Adam sit down with Saul Marquez, founder and CEO of Outcomes Rocket, to explore why most health care companies are missing critical strategy before tactics, how to navigate HIPAA without fear while personalizing your marketing, and the key opportunities in influencer marketing and AI integration that your competitors are sleeping on. Whether you're a health tech founder, marketer, or growth leader, this conversation is packed with actionable frameworks—from the three D's of marketing (discover, define, deliver) to leveraging custom GPTs for team alignment—to help you cut through the noise and focus on execution in 2026. Tune in to uncover why strategy comes first, always, and how the convergence of health tech and medical device playbooks is creating unprecedented opportunities.
What You’ll Learn:

The "Three D Framework" (Discover, Define, Deliver)
How to leverage micro-influencers (10K–50K followers) in B2B health care
Why "tactics are the noise you hear before the war is lost"
How to implement a custom GPT as your team's "source of truth"
The convergence of health tech and medical device marketing playbooks
Why HIPAA compliance fears are overblown
The 2026 execution imperative

About the Guest(s):
Saul Marquez is the Founder and CEO of Outcomes Rocket, a healthcare-exclusive marketing, media, and advisory firm specializing in helping health tech and medical device companies accelerate growth. With over 20 years of experience in the medical device industry—including a tenure as Vice President at Medtronic and field experience as a medical device representative—Marquez brings deep operational and market insights to healthcare marketing strategy. A prolific podcast host with over 2,000 episodes across multiple shows, he has interviewed hundreds of healthcare leaders and identified critical market trends at the intersection of health tech and medical device innovation. In this episode, Marquez shares his proprietary three-D framework (Discover, Define, Deliver) for healthcare marketing success, explores the convergence of health tech and medtech, and provides actionable guidance on leveraging AI as a strategic tool rather than a distraction. His insights on regulatory compliance, personalization within HIPAA constraints, and the future of healthcare marketing make this conversation essential listening for health tech professionals, CMOs, and entrepreneurs looking to execute with precision in an increasingly complex market.
If you enjoyed this episode, make sure to subscribe, rate, and review it on Apple Podcasts, Spotify, and YouTube Podcasts. Instructions on how to do this are here.
Episode Highlights:
[00:16:14] Apply the Three D Framework: Discover, Define, Deliver - 
Saul's proprietary Three D Framework provides a simple yet comprehensive structure for building effective health care marketing programs that eliminate decision paralysis. The **Discover phase** involves asking hard questions about your goals, target audiences, key metrics, and overall go-to-market strategy, ensuring alignment on what success looks like. In the **Define phase**, you crystallize your go-to-market strategy, establish frameworks and roadmaps, and set KPIs that will measure success or failure throughout your campaign. The **Deliver phase** encompasses executing tactics across three buckets—owned, earned, and paid media—with the advantage that your earlier discovery and definition work eliminates wasteful noise and focuses spending. Once you've delivered and gathered data, you iterate continuously based on KPI performance, doubling down on what works and adjusting what doesn't. For health care companies struggling with fragmented marketing efforts, this framework provides the clarity needed to move from scattered activity to coordinated, measurable growth.
[00:19:35] Micro-Influencers (10K–50K Followers) Represent an Underutilized B2B Health Care Opportunity - 
Saul identifies that B2B health care marketing is "asleep at the wheel" on influencer marketing, particularly leveraging micro-influencers in the 10,000 to 50,000 follower range across platforms like LinkedIn. These niche creators show higher willingness to collaborate with brands, deliver more targeted audiences, and produce measurable impact that often exceeds traditional email or paid advertising methods. Health care marketers can identify relevant micro-influencers by using ChatGPT to search for niche voices in their specialty—whether that's cardiology, orthopedics, or health tech innovation—and approaching them directly with collaboration proposals. Measurement of influencer campaigns can focus on brand awareness (site visits, click-through rates) or mid-to-bottom funnel metrics (conversions from qualified personas), depending on your campaign goals. Since most health care companies haven't yet systematized influencer outreach, first movers in this space gain significant competitive advantage and can build authority before the channel becomes crowded. This channel represents genuine "green space" where health care brands can achieve outsized returns on modest investment.
[00:26:14] Create a Custom GPT as Your Team's Unified Source of Truth for Messaging - 
Rather than allowing team members to generate marketing content through random ChatGPT conversations, Saul recommends building a custom GPT trained on your brand house, target personas, proven content examples, and communication guidelines. This custom GPT becomes an AI copilot that ensures messaging consistency across email, social media, web, and paid advertising—critical in health care where regulatory compliance and brand trust depend on aligned communication. You establish a non-negotiable rule that all content creation flows through your custom brand GPT, not external tools, preventing the fragmentation and inconsistency that currently plagues many health care marketing teams. You can extend this approach by creating specialized GPTs for each persona or product line—a "Virtual Care GPT," a "Cardiology GPT," etc.—enabling both customization and consistency simultaneously. The upfront work of documenting your brand strategy, messaging frameworks, and successful content patterns pays dividends in team alignment, faster execution, and reduced brand risk. Teams that implement this discipline report that their marketing becomes "music"—a unified, harmonious effort that amplifies impact rather than creating conflicting signals.
[00:31:03] Study Convergence Between Health Tech and Medical Device Marketing Playbooks - 
Saul observes that health tech companies (algorithm-based, capital-light, rapid iteration) and medical device companies (hardware-heavy, FDA-regulated, slow cycles) are increasingly colliding and acquiring each other, creating a historic moment where both industries must learn from each other's marketing approaches. Health tech companies should adopt medical device's playbook for enterprise integration, regulatory navigation, and building trust with institutional buyers—capabilities that unlock major revenue opportunities when health tech solutions integrate with legacy incumbents like Stryker. Conversely, medical device companies must embrace health tech's playbook for speed, direct-to-consumer marketing, AI-enabled personalization, and agile iteration—capabilities increasingly necessary to compete against nimble health tech entrants. The Care AI acquisition by Stryker exemplifies this convergence: Stryker brings distribution, regulatory expertise, and institutional relationships, while Care AI brings spatial AI, fast iteration, and consumer-centric product thinking. Health care marketers in either camp should study the other's go-to-market strategies, partnerships, and messaging to identify new growth vectors. This convergence is happening across industries globally—hardware and software are merging everywhere—making this insight universally valuable for technology marketers seeking competitive advantage.
Episode Resources:

Saul Marquez on LinkedIn
Outcomes Rocket on LinkedIn
Outcomes Rocket Website
Amanda Vandiver on LinkedIn
Adam Landis on LinkedIn
Branch on LinkedIn
Branch Website
How I Grew This on Apple Podcasts
How I Grew This on Spotify
How I Grew This on Simplecast

Personalization vs. Privacy: How Healthcare Marketers Can Win Both with Saul Marquez

What if your mobile app strategy was holding back your entire company's growth? In this episode, Amanda and Adam welcome back Matt Hudson, founder of BILDIT, to discuss why mobile-first thinking isn't just about technology—it's an organizational imperative. From breaking down the real ROI of app investment and the myth of channel cannibalization, to preparing your ecommerce business for AI discovery optimization, Matt shares hard-won lessons on aligning teams, personalizing customer experiences, and staying ahead of LLM-driven search trends. Whether you're scaling retail, launching a mobile strategy, or wrestling with how to compete in an AI-first world, this conversation cuts through the noise to deliver actionable insights that will reshape how you think about customer engagement across all channels.
What You’ll Learn:

How to determine if your ecommerce business actually needs a mobile app
Why organizational alignment across teams matters more than technology
The critical difference between SEO and AI discovery optimization
How to immediately implement AI-ready data on your site today
Why React Native and cross-functional web-and-mobile teams accelerate app growth
How AI personalization works at scale using embeddings and vectors

Episode Highlights:
[00:05:35] The Five-Point Framework for Determining If Your Business Needs a Mobile App - 
Matt Hudson shares a strategic framework to help ecommerce businesses evaluate whether a mobile app investment makes sense for their company. The framework addresses a critical question many retailers face: with limited resources, is building an app worth the effort and cost? Rather than assuming all businesses need apps, Hudson identifies five specific criteria: having 50,000+ SKUs, operating physical stores, running loyalty programs, generating $100M+ in revenue, and understanding that app users are your most loyal customers—not necessarily younger demographics. For example, a retailer with nearby physical locations sees 50% higher app usage within a 25-mile radius, proving that apps convert loyal, high-value customers who trust the brand. This framework helps ecommerce leaders make data-driven decisions about mobile strategy instead of following industry trends blindly.
[00:11:36] Organizational Alignment Over Technology: Why Mobile App Growth Requires Company-Wide Buy-In - 
Matt Hudson reveals that mobile app success depends far less on technical excellence and far more on getting every department—from stores to marketing to IT—genuinely invested in the app's growth. The challenge most retailers face is that mobile and web teams operate in silos, compete for attribution credit, and prioritize their own channel's metrics over total revenue. Hudson explains that when the marketing team sees improved ROAS (return on ad spend) from app traffic, and when stores actively promote downloads, the app grows exponentially; without this organizational alignment, even a perfect user experience fails. A key tactic is seating app and marketing teams physically next to each other and tying bonuses to overall company revenue rather than channel-specific metrics. This organizational shift removes the false notion of "cannibalization" and ensures every team pushes customers to their best experience—whether web or app.
[00:21:19] Optimize for AI Discovery (AIO) Now or Lose 90% of Your Search Traffic - 
Matt Hudson warns that traffic from AI-powered discovery is already replacing traditional Google search, with click-through rates dropping from 15% to as low as 8% (or lower), and the trend will only accelerate. Unlike Google's SEO, which indexes everything and rewards backlinks, AI discovery prioritizes authoritative sources—Reddit, Quora, FAQs, podcasts, and trusted voices—and cares about giving correct answers, not just showing available links. Retailers must shift strategy immediately: stop relying on keyword rankings and start building authority through FAQ-formatted content, detailed product descriptions, JSON-LD schema markup, and getting mentioned in trusted communities where real people validate your answers. The good news is that unlike SEO, this content doesn't need to be visible to users—you can hide FAQs below product pages specifically for AI consumption. For any retailer serious about discoverability in the next 2–3 years, implementing AIO optimization today is non-negotiable for maintaining visibility.
[00:32:38] Layer Personalized Customer Data into Product Pages Today So LLMs Reference It Now - 
Matt Hudson advises ecommerce companies to immediately begin adding customer-specific, personalized data to product pages—not just generic descriptions—so that large language models start consuming and referencing this information in recommendations today, rather than waiting for "perfect" AI features. LLMs use three-dimensional embeddings and vectors to predict which tokens (words) come next based on a user's entire conversation history; if you provide personalized data about who a product suits, the AI naturally generates personalized answers. For example, instead of just "Red Plaid Shirt," include FAQ-style answers like "Is this great for trendy ladies?" or "Will this fit someone with a small frame?" so the AI understands the product's full audience and context. The data doesn't need to be visible on the page—it can be hidden in structured markup or FAQ sections—but its presence trains the AI to make smarter, more personalized recommendations when customers ask about your products in ChatGPT or other LLMs. This practice compounds over time as models learn your data patterns and become more effective at positioning your products.
Episode Resources:

Matt Hudson on LinkedIn
BILDIT on LinkedIn
BILDIT Website
Amanda Vandiver on LinkedIn
Adam Landis on LinkedIn
Branch on LinkedIn
Branch Website
How I Grew This on Apple Podcasts
How I Grew This on Spotify
How I Grew This on Simplecast