What Shows Up in a Closed-Won Deal
Gong Labs analyzed 1.8 million B2B deals closed in 2024 and found that deals which close have roughly twice as many buyer-side contacts as the deals that do not. Closed-won deals also average 6.7 people from the seller’s own team engaged across the deal, a selling team 67% larger than the team on comparably staged deals that end up lost. On large strategic or enterprise opportunities specifically, the average climbs to 17 buyer-side contacts.
None of that is what a raw logo count measures. A logo counts as one win whether it took a single contact or seventeen, which means logo count alone hides exactly the engagement depth Gong’s data ties to closing.
A Modern Buying Group Is Already Bigger Than One Logo Implies
Gartner research finds 87% of B2B buying groups now include four or more stakeholders. A single logo, in other words, is rarely a single decision-maker. It is a group of at least four people who each have to be reached, convinced, or at minimum not actively opposed, before that logo turns into a closed deal at all.
Chasing more logos without accounting for that group size means spreading the same limited outreach capacity across more four-plus-person buying committees, a straightforward way to under-resource every single one of them.
Why Depth Beats Breadth in the Data
Multi-threading, engaging more than one buyer-side contact instead of relying on a single point of contact, is associated with an average 130% win-rate lift specifically in deals over $50,000, per Gong’s same 1.8-million-deal analysis. Looping in a sales engineer or other technical specialist for demos or technical questions is associated with up to a 30% win-rate lift on its own. Both numbers describe depth of engagement within an account, not the number of accounts being pursued at once.
What an ICP Fit Score Is For
An ICP fit score is a numeric or tiered rating that measures how closely a specific target account matches an ideal customer profile, industry, size, structure, and sometimes behavioral signal, so a targeting list can be filtered and prioritized instead of treated as one flat, undifferentiated pool of possible fits. That scoring concept only pays off if the accounts it surfaces then get the multi-threaded, technically supported engagement Gong’s data associates with closing. A high fit score paired with a single rushed contact wastes the targeting work that produced the score in the first place.
What This Means for How We Book Meetings
Five companies engaged the way Gong’s data describes, multiple contacts, technical support where it matters, real multi-threading, produce more closed revenue than five hundred companies each touched once. That is not a claim about effort, it is a claim about where 1.8 million real deals ended up closing.
Booking Demos Built Around Fit, Not Volume
A targeting list built around ICP fit score is only as good as what happens after the first meeting gets booked. Chasing raw logo count optimizes for a number that Gong’s own dataset shows has little to do with what closes.
Human + AI SDRs book demos against the specific ICP criteria a SaaS company sets, prioritizing account fit over how many companies get touched in a given week.
Sources
The external data in this article draws on the sources below. Figures described in the text as estimates or industry triangulations are directional and are not attributed to a single dataset.
- Gong, Data Shows Top Reps Don’t Just Sell, They Orchestrate (With AI)
- Landbase, 35 B2B Sales Statistics, citing Gartner’s Buying Groups research