Feb 14, 2025 · 42m · saastr
Going Long: How Procore’s Founder Tooey Courtemanche Built a Billon-Dollar SaaS Empire Over 23 Years
gold bands on the timeline = statements, start to end. Hover to read, click to jump. CC turns on captions
In this SaaStr interview, Procore founder and CEO Tooey Courtemanche reflects on his 23-year journey scaling a vertical SaaS empire, navigating economic downturns, expanding into enterprise markets, and integrating AI to transform the global construction industry.
How this conversation actually went
Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Jason holds 32.9% of the talking time here. How this is scored →
speaking balance: gold is Jason, purple is the guest (3 minute bins)
Tooey forcefully rejects the idea that aggressive enterprise reps can bulldoze construction prospects, recounting how buyers kick arrogant sellers out of their offices.
Hardest push from Jason ▶ 21:03 Questioning generalist sales rep valueJason pushes back on whether standard B2B sales reps provide any real value in complex vertical sales conversations without deep domain knowledge.
Biggest teaching moment ▶ 16:00 Debunking construction industry stereotypesTooey corrects conventional misconceptions about construction, explaining that it is a highly sophisticated, data-intensive, low-margin industry rather than simple manual labor.
Jason holds their own ▶ 26:20 Comparing vertical TAM strategies to KlaviyoJason demonstrates SaaS expertise by contrasting market concentration in ecosystem verticals like Klaviyo on Shopify against Procore's multi-trillion global construction TAM.
the scores for every segment, with the reasoning behind each
| Chapter | Topic | Jason as informed peer | Guest teaching | Guest disagreement | Jason pushing back | Why |
|---|---|---|---|---|---|---|
| Procore's Early Architecture and Capital Efficient Foundations | 5 | 5 | 1 | 2 | Jason probes Procore's early unit economics and customer profile, comparing early SaaS pricing models. Tooey details how serving custom home builders with absentee high-net-worth owners laid the foundation for project management workflows across all construction verticals. | |
| Navigating the 2008 Financial Crisis and Near-Death Survival | 6 | 4 | 1 | 1 | Jason compares his own 2008 experience at EchoSign with Procore's near-total market wipeout in residential construction. Tooey shares how pivoting to mixed-use commercial projects and surviving with an angel bridge loan eliminated their competitive field. | |
| Breaking into Enterprise and Leveraging Construction Word-of-Mouth | 6 | 5 | 1 | 2 | Jason asks about customer retention pressures versus word-of-mouth expansion in modern SaaS. Tooey explains the hyper-local nature of construction and how transient project managers naturally champion the platform across firms. | |
| Managing Multi-Stakeholder Workflows and Sales Enablement | 6 | 6 | 2 | 3 | Jason questions whether sales reps need deep domain expertise or if generalist B2B reps suffice. Tooey clarifies that generalist reps fail without structured enablement and pairing with former field project managers acting as sales engineers. | |
| Multi-Trillion TAM, Disciplined Capital Allocation, and Coding | 7 | 5 | 2 | 2 | Jason contrasts Procore's multi-trillion TAM dynamics with Klaviyo's 80% market share in Shopify. Tooey reframes the goal from obsessing over market share percentages to solving customer problems and managing capital allocation across massive R&D budgets. | |
| Transitioning from Point Solutions to an Integrated Data Platform | 6 | 5 | 1 | 2 | Jason notes that modern vertical SaaS companies go multi-product far earlier than Procore did. Tooey agrees that the era of point solutions is over because construction requires a unified data corpus rather than fragmented siloed apps. | |
| Artificial Intelligence, Labor Shortages, and Value-Driven Pricing | 6 | 6 | 1 | 2 | Jason asks whether AI features justify additional monetization or should be bundled to drive 10x customer value. Tooey outlines severe industry labor shortages and explains how autonomous agents and reasoning models eliminate costly construction mistakes. |