Brandformance

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.

Meta's advertising platform has become one of the most sophisticated machine learning systems ever built.

Yet most marketers still try to outsmart it.

In this live Office Hours session, Andrew Faris (CEO of AJF Growth) joins Pranav Piyush to break down how modern Meta advertising actually works—and why many brands are wasting time on outdated tactics.

What if the metrics your company relies on every day… are giving you the wrong answers?

In this episode, Pranav &  Sundar break down:

Why Uber cut $35M in Meta spend
The real meaning of incrementality
Why CAC swings can mislead entire organizations
How brand advertising actually works in saturated markets
Why marketers obsess over dashboards that don’t matter
And how AI is changing the future of analytics

This is a deep dive into modern marketing measurement, experimentation, brand strategy, and executive decision-making — designed for CMOs, growth leaders, and marketing operators navigating today’s increasingly noisy data landscape.

If you care about attribution, brand ROI, MMMs, incrementality testing, or performance marketing… this episode is for you.

In this episode of Brandformance, Pranav sits down with Vineet Mehra, Chief Growth Officer at Chime, to break down one of marketing’s biggest false choices: brand vs. performance.

Vineet explains why the best modern marketers are no longer choosing between storytelling and direct response. Instead, they are building integrated growth systems where brand, product, analytics, media, engineering, and lifecycle teams all work toward one shared business outcome.

The conversation explores Vineet’s idea of performance storytelling — combining the emotional power of brand-building with the economic discipline of direct response. He also explains the CAC Valley of Death, where companies exhaust existing demand, keep bidding on the same high-intent customers, and watch acquisition costs rise while growth slows down.

Pranav and Vineet also dive into how AI is reshaping marketing teams, from bringing more creative work in-house to increasing experimentation velocity, improving lifecycle communications, using synthetic research, and moving beyond traditional A/B testing.

For Vineet, this is not the end of marketing. It is the beginning of the golden age of marketing, where CMOs must become both growth architects and systems architects.

Is the AI agent bubble about to burst, or are we just using them wrong?

In Episode 24 of GTMN, Pranav and Austin break down the latest Gartner report predicting a massive failure rate for AI agent projects. They also discuss Meta's game-changing CLI launch, ChatGPT's staggering new ad performance, and why Pinterest is secretly dominating the social ad space.

In this episode, Samyutha Reddy shares what it was actually like to build messaging for a brand new category during the early days of generative AI at Jasper, including how the whole narrative had to change once ChatGPT showed up. She also gets into why press coverage has less to do with reporter relationships than most people think, why you can only really move the needle on one audience at a time, and what she got wrong about how fast enterprise would actually adopt AI.

About the guest:
Samyutha Reddy is a marketing and communications consultant who specializes in helping AI companies build trust with their users. She was head of product marketing, comms, and growth at Jasper, where she helped the company navigate its pivot from a consumer AI tool to an enterprise product. Before Jasper, she worked at WalkMe, which she helped take public. She now works with startups and consumer tech companies, including one of North America's fastest-growing dating apps, helping them figure out how to talk about AI in a way that actually lands.

In this episode, we dig into how Daniel Brady applies machine learning and neuroscience to a problem most email marketers underestimate: not what to say, but who is actually ready to hear it. He shares how Orita helped a brand make more money by emailing 40% fewer people, why deliverability is a high-stakes risk channel and not a cheap one, and why personalization only moves the needle in the middle of your CRM list. Along the way, Daniel makes the case that surprise and habituation are more useful marketing frameworks than most people realize, and shares where he wants to take ML next: data-driven decisions about billboards and sponsorships.

About the guest:
Daniel Brady is the co-CEO of Orita, an ML-powered platform that helps e-commerce brands get more out of their existing customer lists through smarter targeting and experimentation. Before Orita, he trained as a neuroscientist at Harvard and went on to work as a machine learning engineer in routing and logistics. He brings a hard science lens to lifecycle marketing, making sophisticated experimentation accessible to brands with no data science team.