Designing an AI product that made $100,000 in enterprise sales in a week (Scalar)

What is Scalar?

I was doing sales discovery calls and most sales leaders I've talked to mentioned market information and lead generation for outbound as their biggest issues. Tools like ZoomInfo and Apollo only go so far - they don't solve the hard problem of finding good leads.

Scalar started out as a way to use generative AI to create a better ZoomInfo. ZoomInfo's data is outdated, enriched with the same generic properties and comes from sketchy sources.

We posted a pitch on Bookface and 70+ YC founders asked for a demo.

I was tasked with figuring out how the product would work.

What I did

We decided to build a list of 10 leads for each founder as a trial. Initially, my job was to figure translate ICPs into crawlable intent signals (e.g what on the web can let you know someone will raise a seed round soon? Spoiler: I figured that out).

During the process, it also became apparent that ZoomInfo's data needs to be validated twice to determine if the lead is a good fit and another time to check for data accuracy.

That's why every single lead has a “why a good fit” section explaining why the lead is there based on the criteria we aligned during our initial calls.

The results

All the founders said the product was a good idea and the overwhelming majority mentioned our "Why a good fit” section as the main thing behind their interest. We got $100,000 in ARR (with the avg. deal size being $15,000) at a pre-product stage.