Every sales organization has them. You know, the sellers who seem to know which opportunities deserve their attention. They get the right people into the conversation. They know when to push, when to walk away, and how to keep a promising deal from quietly dying in the pipeline.
For years, sales leaders have tried to replicate that success through better training, better methodologies, better technology, and better hiring.
But what if the blueprint is already sitting inside your own revenue data?
That was one of the most compelling ideas to emerge from Guy Rubin’s presentation at GTM Live. Rubin, founder of Ebsta and Managing Director of Revenue Intelligence at Fullcast, presented findings from the 2025 Benchmark Report, based on an analysis of more than 650,000 opportunities representing nearly $48 billion in pipeline, alongside input from more than 2,000 revenue leaders.
The findings revealed an enormous—and growing—gap between top sales performers and everyone else.
According to the Benchmark Report, just 14% of sellers are responsible for 80% of new-logo revenue. The performance gap becomes even more dramatic when sales velocity enters the picture.
Rubin reported an 11X difference in sales velocity between top performers and average sellers, the largest disparity observed in the research. Top performers manage nearly three times as many deals while producing higher win rates, larger average deal values, and shorter sales cycles.
The important question isn’t simply why some sellers are better. What are they doing differently that the rest of the revenue organization could learn from?
More Pipeline Isn’t Necessarily the Answer
One of the easiest responses to disappointing revenue is to put more opportunities into the top of the funnel. The Benchmark Report suggests revenue leaders should look deeper.
Approximately three-quarters of opportunities worked by sales teams ultimately produce no revenue. Deals that close lost also spend roughly twice as long in pipeline as deals that close won. Rubin estimated that sellers consequently spend an average of just 15% of their time working on deals that ultimately generate revenue.
That creates a much larger efficiency problem. Bad opportunities don’t just waste a seller’s time. As they move through the pipeline, they begin consuming resources from solution engineering, finance, legal, leadership, and other teams.
The cost of a bad deal isn’t simply losing it. It’s everything the organization didn’t pursue while trying to save it.
Your Late-Stage Sales Problem May Have Started in Discovery
When a promising opportunity falls apart late in the sales process, teams naturally look at what happened near the end. What is pricing? The competition? Procurement? A missing executive sponsor?
Rubin argues that many supposed late-stage problems actually begin much earlier. When revenue intelligence analyzes historical sales calls and compares the quality of qualification against eventual outcomes, late-stage losses frequently trace back to inadequate qualification during discovery.
The Benchmark data reinforces the problem.
Only about one-third of opportunities leave discovery with structured qualification scores and written notes. In other words, many organizations are advancing opportunities before they have captured enough information to know whether those opportunities deserve to advance.
Slowing Down Could Actually Help Sales Move Faster
Salespeople are trained to create momentum. So when a prospect expresses interest, the instinct is understandable: move the opportunity forward. But stronger qualification doesn’t necessarily slow the sales process. It can accelerate it.
For the mid-market B2B SaaS sales processes Rubin discussed at GTM Live, the average sales cycle was approximately 91 days. Highly qualified opportunities closed in roughly 71 days.
That distinction matters.
Because it supports the belief that qualification shouldn’t be treated as paperwork standing between a seller and the next CRM stage. It should help sellers determine where their time has the greatest probability of producing revenue.
Top performers appear to understand this intuitively. They are more willing to disqualify poor-fit opportunities early rather than dragging them through the funnel. And that creates capacity for better opportunities.
Use Technology to Give Sellers More Time to Sell
Rubin offered an important distinction for revenue organizations investing heavily in automation. Technology is extremely useful when it removes administrative work from sellers. Qualification data, for example, can be extracted from call recordings and scored consistently rather than relying entirely on sellers to manually document every interaction. But technology shouldn’t become another distraction keeping sellers away from customers.
He noted that sellers are spending less than two hours a day talking with customers—time he believes should be dramatically higher. The objective should be straightforward: Let technology handle more of the repetitive work so sellers can spend more time doing what creates revenue—building relationships, understanding customers, and selling.
Your Best Sales Playbook May Already Exist
Near the end of the GTM Live discussion, Rubin was asked how organizations could begin closing the gap between their highest performers and everyone else. His answer came down to one word: Consistency.
Look at the opportunities you’ve won and lost. Look at which personas were involved. Look at engagement patterns. Look at qualification. Look at where deals stalled. Look at how your highest performers behaved differently.
As Rubin explained, once organizations have consistent data, they can identify the signals behind successful deals and show the rest of the sales organization what their best performers are doing differently.
That’s the bigger lesson behind the Benchmark Report. The goal isn’t to turn every seller into your top rep. It’s to stop treating exceptional performance like a mystery.
Your best sellers are already showing you what works. The opportunity is to turn those behaviors into a repeatable revenue system.