In this podcast episode, Pranav Piyush joins the conversation to discuss marketing measurement and incrementality, with a focus on affiliate and influencer marketing. The discussion highlights Media Mix Modeling (MMM) and its growing accessibility through open-source tools and lower costs, positioning it as a key attribution method in the coming decade. The episode explains the difference between attribution and incrementality, contrasting the limitations of multi-touch attribution (MTA) with MMM's cause-and-effect approach. Pranav shares insights on how MMM can help brands assess the impact of various marketing channels, including those that are traditionally difficult to track. Listeners will also gain practical advice on implementing MMM, covering data needs, cost factors, common pitfalls, and real-world success stories. The conversation emphasizes the value of actionable insights and the importance of moving beyond basic dashboards to achieve meaningful business growth.
What is Always Be Testing?
Always Be Testing explores the experiments, insights, and growth stories shaping the future of affiliate and partner marketing in B2B SaaS. Hosted by industry veterans, the show dives deep into real-world lessons from the people driving measurable impact at companies like Google, HubSpot, Ramp, Webflow, G2, and beyond.
Each episode uncovers what happens when today's most innovative marketers challenge assumptions, run smarter experiments, and build programs that scale revenue through meaningful partnerships. If you’re in affiliate, partnerships, or SaaS growth — this is your front-row seat to how the best do it (and what they’ve learned along the way