“You’re Just an Ad Tech Person” — How Advertising Produces Great Product Managers

Demanding Users, Rapid Innovation, and Data Saturation in a Polarizing Field

  • Users of ad tech are technical, analytical, and skeptical, with many software options at their fingertips. Core to my vision of Product Management as a discipline is the well-known idea that users want and will pay for software to make their lives/jobs/tasks easier, and with ad tech the key is being able to build tools for each of the personae that will engage. Buyers, Traders, Campaign Managers (all coming in both internal and external flavors for ad tech with a managed service and self service business), along with the usual SaaS requirements for executive sponsorship, are all part and parcel with user engagement for ad tech. Ad tech product managers deal with some of the toughest users AND buyers around, and they need to have a significant amount of empathy while knowing how to push back against each persona. It isn’t an easy tight rope to walk.
  • Because ad tech users have so many options for their software, every company needs to innovate rapidly. By the time you release your latest features, your competitor puts out their v2. The pace of innovation is breakneck. Your customers’ customers operate quarterly (vs the multi-year contracts of typical enterprise SaaS), so you can’t afford to have a 12 month roadmap that is immutable within 6 months. This forces ad tech product managers into all the experimentation techniques and metrics analysis that typically accompany high growth consumer products, with all of the stability, security, and business requirements of steady enterprise technology.
  • Ad tech is full of data. Billions of queries per second flow through bidders, and each one needs to be parsed, checked against campaign parameters, discarded if mismatched, bid on if matched, and it all needs to happen in ideally under 50ms. How do we store this data? How does it inform our bidding logic? How much control do we give our users over targeting? What happens if a parameter is missing — skip or use machine learning to predict? Can we use machine learning to forecast availability? What about pricing? Ad tech product managers get a crash course in data science and machine learning when starting to look at precisely what makes the software easy to use and innovative for our technical, analytical, and skeptical stakeholders.
  • Advertising is a polarizing field. There are a whole lot of people who think that advertising has destroyed the internet, and whether that is true is out of scope of this discussion. But working in a semi-controversial field gives product managers the opportunity to step outside of themselves and understand how what they’re building impacts the world beyond their users and their company. It is scary and humbling, and makes for more thoughtful decision making when building future products and features.

--

--

Lover of Product Management as a discipline, software as a service, data science as a hobby, and Iron Maiden as a band.

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
Adam Hecht

Lover of Product Management as a discipline, software as a service, data science as a hobby, and Iron Maiden as a band.