Brandformance

David Fallarme, VP of Marketing at Owner.com, joins this week's episode of Brandformance with Pranav Piyush to break down how Owner.com built a brand and organic media machine to diversify away from paid social, and why it all started with a decision, not an attribution model.David joined Owner.com as a fractional advisor when the company was around 60 people. Today it has 700+ employees and just announced its Series D.In this episode, we cover:Marketing to Restaurant Owners: Why blue-collar, non-tech buyers decide on vibes and what their local community says, not white papers and webinars, and why their phone number is right on their Google Business Profile.Sweating the Details: How high-quality case study videos, with the restaurant owner as the star, helped convince one of Owner.com's investors.AI for Small Businesses: Why restaurant owners embrace AI despite the broader anti-AI sentiment: thin margins mean they'll take every advantage they can get.Organic as a Testing Ground for Paid: How a business breakdown of In-N-Out's growth hit 200,000 views, and why organic hits can become top performers on paid.The Content Engine: Why video editors are the scarcest resource in marketing, and what it took to recruit media talent from the MrBeast and Hormozi world.Brand Is a Decision: Why leadership has to treat brand as an imperative, why a cold start takes at least two quarters, and how 20–30% of early deals traced back to organic channels.Hiring for Taste: David's interview method, from a 30-minute "vibes" chat to a design-crit review of a candidate's five best pieces of work.AI Without Losing Quality: Hiring people with strong editorial taste, and building a shared context layer of positioning, voice and tone underneath everyone's AI work.Follow David:LinkedIn: https://www.linkedin.com/in/dfallarme/ Website: https://owner.com/Follow Pranav:LinkedIn: https://www.linkedin.com/in/pranavp/ X: https://x.com/pranavpiyushInstagram: https://www.instagram.com/pranavmktg/TikTok: https://www.tiktok.com/@pranavtalkWebsite: https://www.pranavpiyush.com/Follow Paramark:YouTube: https://www.youtube.com/@ParamarkHQ X: https://x.com/paramark_hqWebsite: https://paramark.com/Chapters:00:00 Intro01:11 Why David Joined Owner.com02:40 How Owner.com's Marketing Team Is Structured04:30 Marketing to Restaurant Owners06:26 Sweating the Details: Case Study Videos07:25 AI for Small Businesses08:38 The Vision Beyond Restaurants10:28 Organic as a Testing Ground for Paid13:07 The Content Engine15:46 Hiring From MrBeast's World16:54 Brand Is a Decision19:47 Hiring for Taste22:03 Being Terminally Online24:22 AI Without Losing Quality25:39 Campaigns David Admires27:20 Fire Round: Marketing Myths & Dream Campaigns

Arthur Leopold, CEO and Co-founder of Agentio, joins this week’s episode of Brandformance with Pranav Piyush to break down why the world’s largest advertisers are moving away from traditional digital ads and going all-in on creator media. With half of all digital attention now focused on creator content, legacy marketing plans are becoming increasingly difficult to defend in the boardroom.In this episode, we cover:• The Trust Deficit: Why consumers trust creators 70% more than traditional brands, and how industry giants like Unilever are aiming to shift 50% of their marketing spend directly to creators.• Creators vs. Influencers: The fundamental difference between legacy, one-off #ad campaigns and partnering with niche authorities who act as effective micro-creative agencies.• Partnership Ad Efficiency: A look at Meta’s internal data showing that dual-handle partnership ads deliver 19% better efficiency compared to business-as-usual brand ads.• YouTube Integrations: Why 90-second, host-read YouTube integrations remain the most effective and underpriced ad inventory on the market, driving 85% to 87% view-through rates.• 0-to-1 Strategy for Brands: The importance of setting up strict measurement infrastructure, automating the buying process to achieve scale, and targeting mid-tier creators rather than nano-influencers or mega-stars like MrBeast.• Unexpected Niches: How algorithmic platforms help brands discover highly converting audiences outside their core demographic, such as a men's grooming brand finding top-tier performance by sponsoring a Maine lobster fisherman.Follow Arthur:• Instagram: https://www.instagram.com/artiegrams/• Website: https://www.agentio.com/Follow Pranav:• X: https://x.com/pranavpiyush• Instagram: https://www.instagram.com/pranavmktg/• TikTok: https://www.tiktok.com/@pranavtalk• Website: https://www.pranavpiyush.com/Follow Paramark:• YouTube: https://www.youtube.com/ ⁨@ParamarkHQ⁩  • X: https://x.com/paramark_hq• Website: https://paramark.com/Chapters:00:00 - Introduction & The Power of Creator Trust01:40 - Agentio’s Growth & Unilever’s 50% Shift to Creators04:14 - Why Legacy Advertising is Losing to Creator Media09:39 - AI-Generated Content vs. Authentic Creator Trust13:18 - The Evolution from "Influencer" to "Creator"16:24 - Why Meta Partnership Ads Outperform Standard Ads19:32 - Step-by-Step: Taking a Brand from 0 to 1 in Creator Marketing25:08 - Solving Data Friction & Building Trust with Creators28:03 - The Arbitrage Opportunity in YouTube Integrations31:36 - How to Price Creator Media: CPMs vs. Ad Spend35:17 - The Future of the Creator Tech Ecosystem38:42 - Closing Thoughts & Where to Find Agentio

Why do most A/B tests fail to produce any meaningful improvement—and what separates a useful experiment from another inconclusive result?In this episode of Brandformance, Pranav Piyush speaks with Casey Hill, CMO at Do What Works, about what thousands of real-world website experiments reveal about conversion rate optimization.They explore:Why most A/B test variants fail to move the needleThe three checks to make before launching an experimentWhy specific messaging consistently beats generic benefitsHow reassurance copy can remove conversion barriersWhat marketers misunderstand about benchmarks and confidenceWhy customer logos alone may no longer build trustHow to position AI products without relying on empty languageWhether websites still matter in a world of AI agents and LLMsFor CMOs, growth leaders and B2B marketers looking to make smarter website and experimentation decisions, this conversation offers practical lessons grounded in actual testing data.

How do you change what people think about an established brand—without throwing away everything that made it valuable?In this episode, Pranay Piyush sits down with Meiling Tan to unpack lessons from two very different brand challenges: helping Care.com evolve beyond childcare and building the Waymo brand when self-driving cars still sounded like science fiction.Meiling shares why the best brand transformations go far beyond a new logo or campaign. They require alignment across product, customer experience, communications, leadership, and marketing.They discuss how Care.com repositioned itself from a childcare utility to a broader caregiving brand—and went on to deliver its first quarter of new membership growth in nearly four years. Meiling also takes us inside the early days of Waymo, explaining how the team built trust in self-driving technology by focusing on the human problem it could solve.Plus, they explore why brand and product are inseparable in the customer's mind, how to get CEOs and CFOs to invest in brand, why leading indicators still matter, and the marketing experiment Meiling would run with an unlimited budget.For CMOs, brand leaders, and marketers trying to connect brand building to real business growth, this episode is packed with practical lessons.

Has performance marketing reached its limits?In this episode, Pranay Piyush sits down with Peter Sengenberger, who has spent more than 25 years in direct response, infomercials, consumer marketing, and B2B demand generation.Together they explore why today's best marketers are looking beyond digital channels to build long-term brand growth.

In this Office Hours episode, Pranay Piyush sits down with Raunak Kumar to discuss how he built incrementality testing and marketing measurement systems at companies like Stripe and Intercom.Together they cover:How to build an in-house incrementality programChoosing the right success metrics for MMMWhy B2B marketing measurement is different from B2CGeo holdout experiments and what they revealedHow to earn executive buy-in for experimentationCommon mistakes when building MMM modelsWhy uncertainty matters more than precisionWhen to build vs. buy a measurement platformWhether you're building your first MMM model or scaling an experimentation program, this episode is packed with practical advice for marketing leaders and analytics teams.

In this episode, Kristin Fracchia — Head of Marketing at Gamma, the AI presentation and website platform with nearly 100 million users — breaks down what it takes to run marketing inside a hypergrowth AI startup where the playbooks expire every quarter. She explains why an AI, product-led company still needs salespeople and human trust, how she staffs a ten-personteam of generalists who each spike on brand, growth, or product marketing, and why she plans in a “narrative arc” rather than annual plans. Kristin digs into Gamma's creator engine — 300 to 400 influencer posts a month — and the thinking behind stunts like the nation's first large-scale drone-and-projection show in San Francisco, planned in five weeks. She makes the case thatdoing things faster with AI isn't the point (the job to be done is), and that the real edge is soul,taste, and solving real problems. She closes on the trait she now hires for above all else: plasticity.

Sundar Swaminathan, a marketing measurement practitioner and data scientist, breaks down MMM and incrementality testing in plain terms. He explains baseline vs incremental sales, adstock and carryover, saturation and diminishing returns. He also covers Bayesian vs frequentist ideas, multicollinearity, endogeneity, and how to assess model quality.

In this episode, Tye DeGrange — founder and CEO of Round Barn Labs — makes the case that affiliate and partner marketing, done right, is a trust-building channel rather than the “bottom feeder” its reputation suggests. He explains why the modern trust gap creates an opening for authentic third-party partners, why affiliate is better understood as a multi-channel lever with 15+ partner types than a single channel, and how incentives quietly determine outcomes. Tye digs into the measurement problems that plague the channel — why server-to-server tracking beats pixels, why last-click rewards the wrong partners, and how to feed impression data into marketing mix models. He shares standout campaigns (eBay Motors’ multi-year Bring a Trailer build; an 81% traffic lift from a single mid-tier YouTube creator for Atlassian) and the misconceptions that keep brands from managing affiliate like the real channel it is. It's a practical tour of a channel most performance marketers underrate.

Can AI accurately predict marketing incrementality without running a randomized controlled trial?In this episode, Pranay Piyush and Sundar Swaminathan break down a new marketing science paper introducing Predicted Incrementality by Experimentation (PI) and discuss what it means for marketers, ad platforms, and measurement teams.They cover:How PI predicts incrementality using historical experimentsWhy the model achieved an 0.88 R²Whether AI can reduce the need for randomized controlled trials (RCTs)What this means for Meta's incremental attributionWhy benchmarks can be misleadingWhich companies can benefit from predictive incrementality todayWhy RCTs remain the gold standardIf you're a CMO, growth leader, marketing scientist, or performance marketer, this episode offers a practical breakdown of one of the most interesting developments in marketing measurement this year.