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Find what buyers say before a deal stalls, then have AI alert the seller with the follow-up that works
Picked and checked by Olga Pearson, SalesUpLevel
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Reported in Gong's write-up: PayPal's team saw 22% faster time to revenue and a 17% increase in forecast accuracy. Eitan Saban, in the same session, described it as an increase of "a little shy of 20%" in forecast accuracy and a 20% revenue increase.
Some deals do not die. They stall after the signature, and your forecast slips with them.
Case study: PayPal (customer) and Gong (vendor). Eitan Saban's North America SMB team had deals stalling between the merchant signing and starting to process payments, which is where PayPal's revenue starts. The team used Gong's AI to spot the moments in conversations that came before a stall, like a merchant expressing hesitation. They set it up to send automated deal alerts and guide sellers with best-practice follow-ups.
By Eitan Saban (PayPal), in a Gong article, Head of North America SMB Sales, PayPal · Gong blog, from a Gong Celebrate panel ↗ · Jan 28, 2026
Run it before your 10am
- Name the point where your deals stall. For PayPal it was between signing and the first processed payment.
- Pull calls and emails from deals that stalled there and from deals that moved on.
- Have AI list what buyers said in the stalled deals that they did not say in the others (hesitation, a new person, a delayed date).
- Turn the top signals into alerts that reach the account owner the same day.
- Attach the follow-up that worked best for each signal, so the alert comes with a next step.
- Track time from signature to revenue and how close your forecast lands, before and after.
Below are notes and transcripts from [N] deals that stalled after signing and [N] that went live on time. [paste] List the things buyers said or did in the stalled deals that show up much less in the on-time deals. For each one, quote an example, say how early it showed up, and suggest one follow-up the seller could send within a day. Rank them by how often they appear in stalled deals.
If you lead a team
- Measure time from signature to revenue, not just signatures.
- Every alert should come with the follow-up that worked, not just a warning.
Watch out for
- Vendor case study; Gong is describing its own product, and PayPal's numbers come from a Gong-hosted session.
- The article gives two slightly different forecast numbers (17% and "a little shy of 20%"); we show both.
- A small sample of stalled deals can produce signals that are just noise; check them against new deals before you trust them.
- Check your company's rules before you put customer calls into an AI tool.
- What I'd have my team try first: pull your last 20 stalled deals and 20 on-time deals and run the prompt once.
Source: Gong blog 'Leading from the front: How revenue leaders at PayPal, Wayfair, and Twilio drive transformational change using AI' by Craig Hanson, Jan 28, 2026 (updated Mar 4, 2026), from a panel at Gong's Celebrate event. Case study: customer PayPal, vendor Gong. Results are as reported; we did not measure them.
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