StackAI found the bulk of enterprise revenue comes from expansion, not the initial deal. They operationalized this by creating a team of "AI strategists" who work with customers post-sale to proactively identify and build new use cases, driving deep account penetration and growth.
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Spreading efforts across startups, SMBs, and enterprises created confusing signals. A deep dive into metrics revealed enterprises, despite being a smaller revenue portion, showed the highest expansion potential, prompting a decisive focus that unlocked growth.
Most B2B SaaS companies stop ABM efforts after the initial sale, despite landing only about 30% of an account's potential revenue. The biggest growth opportunity lies in applying ABM strategies post-sale for customer expansion, which prevents a poor customer experience and captures significant untapped revenue.
Enterprises struggle to get value from AI due to a lack of iterative, data-science expertise. The winning model for AI companies isn't just selling APIs, but embedding "forward deployment" teams of engineers and scientists to co-create solutions, closing the gap between prototype and production value.
A system called AISOS was built to scale a small enablement team. It provides on-demand sales coaching, delivers just-in-time training content, and conducts pipeline analysis. This multi-function approach allows a small team to support a wide array of sales roles from BDRs to enterprise AEs.
While founder-led sales are critical, StackAI believes they waited too long to hire their first salesperson. Bringing in help earlier, around $500K ARR, would have accelerated their ability to test and refine their go-to-market strategy much faster.
Initially, being the "AI guys" led to endless custom requests across departments. The scalable breakthrough was shifting their model from doing the work to teaching customers how to use their platform to build agents, empowering them to solve their own problems.
Initially building a tool for ML teams, they discovered the true pain point was creating AI-powered workflows for business users. This insight came from observing how first customers struggled with the infrastructure *around* their tool, not the tool itself.
The sweet spot for their transformational AI platform wasn't the largest corporations, which are too rigid to adopt new tech. Instead, it was mid-market companies (100-1,000 employees) that had budget and pain but were agile enough to implement new workflows successfully.
As multi-year deals become less common, focus is shifting heavily to post-sales. Companies are investing in strengthening these teams' skills and rethinking their entire post-sales strategy, recognizing that retention and human relationships are more critical than ever.
Fal employs a product-led sales motion where enterprise deals originate from self-serve usage. The sales team is automatically alerted when a pay-as-you-go account's spending crosses a specific threshold ($300/day). This signal triggers outreach to convert the high-usage account into a larger, committed annual contract, creating an efficient and scalable GTM.
