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 program
Choosing the right success metrics for MMM
Why B2B marketing measurement is different from B2C
Geo holdout experiments and what they revealed
How to earn executive buy-in for experimentation
Common mistakes when building MMM models
Why uncertainty matters more than precision
When to build vs. buy a measurement platform

Whether 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-person
team 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 that
doing 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.

In this episode, Pranay Piyush and Sundar Swaminathan break down the most important concepts behind marketing mix modeling (MMM) and incrementality testing in plain English.

They explain:

•  What baseline and incremental sales really mean 
•  How control variables affect marketing models 
•  Adstock, carryover, and why advertising has lasting effects 
•  Saturation curves and diminishing returns 
•  Bayesian vs. frequentist statistics 
•  Why statistical significance isn't as objective as most marketers think 
•  Multicollinearity, endogeneity, and other commonly misunderstood terms 

Whether you're a CMO, VP of Marketing, growth leader, or performance marketer, this episode will help you understand the language behind better marketing decisions.

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 experiments
Why the model achieved an 0.88 R²
Whether AI can reduce the need for randomized controlled trials (RCTs)
What this means for Meta's incremental attribution
Why benchmarks can be misleading
Which companies can benefit from predictive incrementality today
Why RCTs remain the gold standard

If 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.

In this episode, Sheila Vashee — CMO of Figma and a former marketing leader at Dropbox, Opendoor and Ethos — breaks down how Figma turned its community into its most powerful marketing channel. She argues that great marketing comes down to three things: understanding your audience deeply, finding the channels that uniquely reach them, and building systems to optimize those channels. Sheila explains why brand and performance aren't opposites, how she measures both across short and long time horizons, and shares the Opendoor experiment where a brand campaign doubled market share in three months. She also gets into where AI genuinely helps marketers (and where humans still set the bar), how Figma rebuilt customer support around AI, and why she spends 30–40% of her time hands-on with the latest tools. Along the way: the CEO as the 'real CMO,' Friends of Figma's 240+ volunteer chapters, and the brand she admires most outside tech.

In this episode, Pranav Piyush sits down with Sam Allen, CEO of Iterable and former Chief Pipeline Officer at Salesforce, to discuss the evolving role of marketing leadership.

They explore:
Why CMOs often struggle in boardrooms
The tension between short-term pipeline and long-term brand building
What CEOs actually expect from marketing leaders
How the best CEO-CMO relationships work
Why marketing leaders must think like general managers
How AI is changing hiring, org design, and leadership
Why every company needs to build an AI-native culture

If you're a CMO, VP Marketing, founder, CEO, or growth leader, this conversation offers a rare executive-level perspective on leadership, marketing strategy, and the future of work.

What if the biggest thing holding back your marketing team isn't budget, attribution, or data...

What if it's your assumptions?

In this episode, Pranav and Sundar  break down some of the most common myths in marketing measurement, experimentation, and attribution.