hi, i’m amr — deals rarely die on a single day. they age. and the data suggests the longer an opportunity sits without movement, the less likely it is to close.
what the deal-age data shows
one vendor analysis from Optif.ai looked at 47,548 deals across 938 b2b companies between Q2 2025 and Q1 2026. it reported win rates by days stalled: 43.2% at 0-14 days, 32.1% at 15-28 days, 19.8% at 29-42 days, 14.3% at 43-56 days, and 8.7% at 57 days or more.
the steepest drop in that dataset sits between days 21 and 35. whatever the exact numbers are in your own pipeline, the shape is the useful part: win probability does not fall evenly, it falls fast in the first month of silence.
why this changes how you review pipeline
most weekly pipeline reviews ask what stage a deal is in. the better question is how many days since the last real buyer action. a deal in stage 4 with no buyer activity for 30 days is closer to stage 1 in practice.
what to check this week
- add a days-since-last-buyer-activity field in your crm
- set an alert at 14 days, a review at 28 days, and a close-or-requalify call at 42
- run your own win rate by age bucket from your closed deals before trusting any benchmark
- remove stalled deals from the forecast, or weight them down by age
- look for the pattern behind stalls: single-threaded contacts, no next step, no champion
how this connects to the rest of the stack
stalled deals are often a multi-threading and sales enablement problem, not a rep problem. if only one contact is engaged, the deal ages the moment that person gets busy. it also feeds pipeline coverage: stale deals inflate the number while adding almost no expected revenue.
start scaling — if you want a pipeline plan built on your real win rates instead of a borrowed rule, let’s connect.
sources: figures come from a published vendor study (Optif.ai, Pipeline Failure Early Warning Index) and have not been independently verified. they are not results from my client accounts. check them against your own closed deals.