#33 - Pranav Piyush
Pranav Piyush is the CEO of Paramark, a marketing measurement company helping brands cut through attribution noise and understand what is actually driving business results. Paramark works with companies on measurement fundamentals like marketing mix modeling and incrementality testing, bringing more scientific thinking to one of the messiest questions in marketing: how do we know if this is working? He tells us all about why traditional attribution models are mostly broken, what smaller teams should pay attention to before they have enough data for real measurement, and how marketers can think more scientifically without overcomplicating the work. We also get into why product and marketing are more connected than most companies realize, how he thinks about building Paramark’s own content program, and why the best content in the AI era has to come from real conversations, real experiences, and real life.
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Hey all,
This week I sat down with Pranav Piyush, the founder and CEO of Paramark. He ran growth at Dropbox, marketing at Build.com, and is now building a measurement company that helps major brands determine what marketing activities are moving the needle.
He’s also been a Good Content client for the past 18 months, and the benefits of working together have been mutual; I learn something new every time I talk with him.
Pranav’s business is built around solving the age-old problem facing marketers everywhere.
How do we know what marketing activities work?
I kicked off the podcast asking this question and Pranav’s answer was two-pronged: it depends on the size of your company.
For the big dogs
If you’re spending $20M+ across marketing channels, Pranav’s recommendation is technical—but it’s not about touchpoints. He’s staunchly against multi-touch attribution, because most spend doesn’t directly generate clicks.
Pranav’s perspective is that modern media works by planting a memory. Someone sees your ad while they’re doomscrolling and, six months later, has the problem you’re solving. They go to your site because the name was sitting in their head.
MTA will not tell you that story.
The answer to real attribution is in the math marketers used before the Internet: mixed media modeling, regression analysis, and scientific testing.
For example, launch a campaign in two of your top ten cities and see if those two lift compared to the other eight.
It’s not a new idea. These methods were pervasive in the Mad Men era of the ‘70s. Pranav even references Claude Hopkin’s bookScientific Advertising that was written in the 1920s. But it’s been a bit of a dying art in our digital age.
TLDR for big brands: you have the scale to measure marketing accurately. But you need to use tried and true metrics. Do not succumb to the tempting mirage of multi-touch attribution.
For the rest of us
For younger brands with tighter budgets, Pranav’s answer is completely different.
He believes that, at subscale, you don’t really need attribution. Because you’re only on a few channels running a handful of plays, Pranav says the signal should be obvious.
- Watch your DMs. Are ICPs reaching out after seeing your posts? Are they referencing specific things you said?
- Read your comments. Look at who’s engaging over engagement metrics. Comments from inside your ICP are going to make a bigger impact on your bottom line than hundreds of random replies.
- Check Google Search Console. Are your organic impressions and clicks moving up and to the right? If they aren't, your content isn't landing. This is free and most teams don't look at it.
Pranav believes that attribution is particularly garbage at this stage. Teams fall into the trap of overthinking and overengineering. He gave me an example from a team that defined the credited channel as the first touch among all the last touches in the 90 days before a conversion. What does that even mean?! Garbage.
If real people in your ICP are responding to your stuff, it's working. If they aren't, no dashboard is going to save you. As Pranav put it:
"Don't dance around metrics and hide behind fake precision."
You should be able to feel if it’s working (or not).
How Pranav grew his own program
Despite being a marketing measurement company, Paramark is a startup. That means it falls into that second, more subjective category.
When Pranav came to us in mid-2024, he’d been posting on LinkedIn himself for over a year. He’d spend four or five hours every Sunday writing his own content, and saw some positive signals.
So Pranav came to Good Content confident that LinkedIn could work for Paramark. He was curious to see whether a sturdier content engine could compound what a few Sunday hours were already producing.
We took the voice he’d already developed and built a system around it, increasing post frequency, honing in focus, and sharpening hooks and structure.
Six months in, when Pranav could feel it working. Prospects were DMing him. People were bringing up posts in sales calls. ICPs were citing LinkedIn directly as the reason they took the meeting. He wanted to double down. Over the following year, we built a whole content program;
- A newsletter that expanded the POV in his LinkedIn posts
- Podcast amplification that pulled clips from interviews back into LinkedIn and email
- Live monthly Office Hours, where his audience could ask him and his guests questions directly
- A quarterly magazine, highlighting key marketing players and reaching his ICP in a novel way
- Case studies boosting social proof
When I asked Pranav how he knew the bigger program was working, he gave the same answer he gives all subscale founders. He looked for human feedback at every step.
"Marketing is a human game. If you're not getting that human feedback, your metrics mean nothing."
And yes, Pranav’s gut reaction translated to results: Paramark’s grown 3-4x over the course of our engagement.
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