How do you go from 25 customers to $110M ARR and a $500M deal? - Daniel Chait [Greenhouse]

Greenhouse bets AI interviews can fix broken hiring

Greenhouse sells hiring software to more than 7,000 companies, and its CEO argues AI has so far made hiring worse. Candidates flood employers with near-identical applications and AI filters screen them on the resume, so most applicants are never seen. The company's bet is to give every applicant a voice interview, and Chait says Greenhouse has to disrupt itself before someone else does.

Takeaways

• AI has made hiring worse so far. Candidates use AI to apply to far more jobs and tailor resumes, so companies receive hundreds or thousands of near-identical applications. Filters such as ChatGPT pick 25 people to call, and the other 975 are never seen.
• Greenhouse gives every applicant a conversation. Greenhouse Voice AI, built from the Ezra AI Labs acquisition, gives every applicant an automated voice interview. A 2003 study found 50% racial bias in resume callbacks, and giving everyone a conversation removes it. 90% of candidates rate it four stars or higher.
• Product-market fit meant 25 arm's length customers. Chait used Jason Lemkin's blog test. Greenhouse taped 25 numbered sheets to a whiteboard, adding a customer logo as each signed. The first customer took two months, then weeks, then days.
• The 2020 collapse reversed within a month. An April jobs report showed 13m people unemployed, so Greenhouse cut 30% of staff, mostly in sales and marketing. Growth resumed within a month, and the laid-off staff had already found jobs when it tried to rehire them.
• TPG's buyout cashed out the earliest backers. The growth buyout closed in the first quarter of 2021. It cashed out early shareholders, some of whom had put in $25,000 or $50,000 in 2012, and added tens of millions of dollars to the balance sheet.
• New products must matter to most customers. Chait's rule is that anything Greenhouse brings to market must be relevant to most of its 7,000 customers. Products only 5% of them need should be partner-led. That is how he frames the Ezra AI Labs acquisition.
• Software buying is shifting from seats to outcomes. Chait predicts pricing moves from seats to usage to outcomes, and compares the moment to the late-1990s internet revolution. Greenhouse must disrupt itself before someone else does, with the outcome being Blockbuster or Netflix.

How Chait got into the room

1. He built a technology consulting business for Wall Street and financial services, ran it for ten years, sold it in 2010 and left in 2011.
2. He started Greenhouse in 2012 and was dismissed by investors partly because he had never been to Silicon Valley.
3. For customer discovery he signed up as a candidate at a New York tech job fair, questioned recruiters in their lines and left with a stack of their business cards. The fair later made a rule against it because of him.