Checkr COO Lindsey Scrase on scaling from mid-market to enterprise
Key takeaways from a First Round Capital interview with Lindsey Scrase, COO of Checkr and formerly a Google Cloud go-to-market leader (July 2026):
From Google Cloud to a startup CRO. Scrase spent a decade at Google (joining Google Cloud at a few hundred people on the go-to-market side) before joining Checkr as CRO — a rare successful at-scale-to-startup transition she credits to a strong fit with what founder Daniel Yanisse needed: a data-driven, multi-segment operator.
Winning as a challenger. Competing against category incumbents (as Google Cloud did versus AWS/Microsoft) requires humility and focus — picking verticals you can win (staffing, gig, retail, hospitality) rather than trying to capture everything at once.
The mid-market-to-enterprise trap. Moving upmarket is far harder than the math suggests: multi-year sales cycles, long internal decision processes, low enterprise brand awareness, and an endless tail of last-mile product requests. Success needs the whole company — engineering, product, legal — committed, not just sales.
Outbound hunger is non-negotiable. Checkr won large accounts (e.g. Fortune 500 car dealerships) via granular, data-driven 'rich niche' takedown campaigns; Scrase won't hire sellers who have only had warm leads passed to them.
Events still work. Post-COVID, Checkr rebuilt an events motion because enterprise sales is a human trust leap — differentiated experiences and peer networking drive high ROI that AI won't replace soon.
Operating cadence. Checkr runs a document-culture business review, a first-team C-staff cadence, and aligns ~80 mid-layer leaders in person twice a year, cascading strategy before it reaches the whole company.
Data plus the customer. Scrase warns against managing purely by dashboard — the strategic push into fraud/identity (e.g. companies inadvertently hiring North Korean operatives) surfaced from customer calls, not metrics.
AI in production. Over 80% of Checkr's code is now written with generative AI; AI has lifted operations' resolution rates and support CSAT ~3x while scaling without added headcount, and the team is building an agentic outbound orchestration layer for reps.