On this episode of Beyond the Billboard, hosts Charlie Riley and Greg Wise spoke with Pranav Piyush, Co‑Founder and CEO of Paramark, about why traditional marketing attribution has failed and how brands must evolve to get real impact.
Pranav’s bold claim? “Ninety percent of attribution tech is theater.” He argues that dashboards don’t move the needle and marketing teams must shift toward measurement rooted in data science and experimentation.
“You could take the marketing analytics at any large company and literally delete all the dashboards. Nothing would change.” — Pranav Piyush
Watch the full episode below.
Why Marketers Need Statistical Rigor
Pranav says the root of the problem is a lack of statistical understanding. Without grounding in probability and scientific reasoning, marketers are prone to relying on pseudo-evidence.
He says most CMOs need someone on their team with deep statistical training—or risk repeating bad measurement habits.
The Paramark Way: MMM Meets Incrementality Testing
Paramark combines marketing mix modeling (MMM) with geo-based incrementality testing, creating a unified solution that surfaces both correlation and causation.
- MMM: Analyzes historical data across channels to estimate contribution (ad stock, lag effects, seasonality, etc.) in a machine-learning model.
- Incrementality testing: Launch focused experiments (e.g., billboard campaigns in LA versus control cities) to prove causal lift.
Pranav sums it up:
“If you want causality in marketing you have just one option—and that is experimentation.”
Why This Matters for Out‑of‑Home and Podcast Campaigns
Even channels like OOH or podcast sponsorships can be measured scientifically. Pranav explains how marketers can run geotargeted tests or control groups to validate impact on traffic, search volume, or demo bookings.
This approach treats channels as hypotheses, not guesswork—and builds confidence in marketing budgeting.
Embrace the Failures Ahead of the Wins
Campaign-based testing reveals a hard truth: most new campaigns, around 70 to 80%, don’t succeed. What matters is creating an experimentation culture where failure is expected and iteration is the goal.
Pranav says marketing should model itself more like product development: test fast, learn fast, and scale what works.
Why Paramark Stands Out
Paramark’s goal is to simplify the complex: formerly siloed marketing mix modeling (MMM) and geo-testing solutions now live in one unified platform. The team supports setup, data integration, and continuous optimization—all with statistical rigor and white-glove support.
The company recently raised $6 million in seed capital, proving growing demand for AI-infused tools that build bridges between marketing and finance teams
Final Takeaway
If your marketing team is still leaning on last-touch meta reporting, it’s time to upgrade. Studios and dashboards are nice, but they don’t predict or optimize.
Pranav’s message is clear: run your marketing like a science, not a show. When MMM and incrementally testing work together—and live by experimentation—you get true measurement that the CMO or CFO can trust.
👉 Listen to the full episode of Beyond the Billboard featuring Pranav Piyush now.