The Cost of No-Decision — A Fearless Buyer / JOLT ROI Model
Most lost deals aren't lost to a competitor — they're lost to indecision. This model puts a number on what "no decision" is costing your pipeline today, and what closing part of that gap is worth. Every input is yours to change.
1Your Pipeline Today
2The Improvement You're Testing
3Investment
How We Did the Math — every formula
Assumptions & Sources
| Input | Default | Where it comes from |
|---|---|---|
| % of deals lost to no-decision | 50% (midpoint of a 40–60% range) | Widely cited industry research on B2B win/loss patterns finding a large share of "in-progress" forecasted deals ultimately close as no-decision rather than lost to a competitor (The JOLT Effect, Dixon & McKenna, 2022 — a study of 2.5M+ sales calls). Treat this as a starting reference point, not a guaranteed figure — replace with your own win/loss data whenever it's available. |
| Reduction in no-decision rate (Conservative / Moderate / Confident) | 5 / 10 / 15 points | Grounded in JOLT Effect research: sellers who apply JOLT skills close deals identified as indecisive at 59%, versus 26% for sellers who don't — a 33-point, 2.3x swing. That's a win rate on a specific subset of deals (those already flagged as indecisive), which is a narrower lens than the aggregate no-decision rate above, but it's the best available evidence for how large a swing is achievable. The slider is capped at 33 points so the model can't claim more than the published research shows — and all three presets sit well below that ceiling: even the Confident case (15 pts) assumes less than half of the documented swing. |
| Year 1 ramp factor | 50% | As part of the program, sellers apply JOLT and Fearless Buyer skills directly to deals already in their pipeline — and we frequently see sellers close deals using these skills during the program itself, so the impact can be immediate. We still build in a ramp to account for the fact that not every seller will be able to apply it to a live deal right away. Turn off if you want to assume full impact from day one. |
| Average sales cycle (payback only) | 3 months | Because sellers apply these skills to deals they're already working, impact can show up well before a full sales cycle passes. Payback still uses your average cycle length as a conservative floor, to account for the fact that not every seller will close a deal with these skills right away. Replace with your actual average cycle length. |
Why This Model Is Conservative
- It only counts deals you already have. No new pipeline, no new logos, no lead generation is assumed — recovery comes entirely from deals already sourced, qualified, and worked.
- The presets ask for a fraction of the documented swing. Published JOLT research shows a 33-point difference on indecisive deals; the Confident preset assumes less than half of that, and the default Moderate case less than a third.
- Year 1 is discounted by 50% by default, even though sellers often close deals with these skills during the program itself.
- No second-order benefits are counted — cleaner pipeline and forecasts, faster cycles on won deals, higher win rates against competitors, or improved seller retention.
- Impact is held flat after Year 1 — no compounding from coaching, manager reinforcement, or team-wide adoption.
How This Return Compares to Other Ways to Grow Revenue
What a new logo actually costs. KeyBanc's 2025 SaaS Survey (400+ companies) found the median company now spends $2.00 in sales & marketing for every $1.00 of new ARR — a "Magic Number" of 0.90 — with a median ACV of $62K and a 20-month median payback period. At that efficiency, winning $800K in brand-new-logo revenue costs roughly $1.6M in fully-loaded S&M spend to generate it.
Acquisition vs. retention. Bain & Company's widely-cited research (Harvard Business Review, 2014) found acquiring a new customer costs 5 to 25 times more than retaining an existing one. JOLT isn't a retention play, but the logic transfers: revenue you already have influence over — a deal already in your pipeline — is far cheaper to capture than revenue you have to manufacture from zero.
The acquisition cost on pipeline is already sunk. Bridge Group's SDR Metrics Report puts fully-loaded SDR cost at $98K–$173K per year. That spend — the marketing, the SDR hours, the AE cycle time to qualify a deal — has already happened for anything sitting in your pipeline today. JOLT's job is to stop that sunk investment from evaporating, not to go generate a new one.
The baseline you're actually comparing against. Gartner (Hank Barnes) and Matthew Dixon's research puts no-decision losses at 40–60% of the average pipeline, and Forrester's 2024 State of B2B Revenue data found 86% of B2B purchases stall at some point in the buying process. Without intervention, the revenue modeled above isn't "a modest return" — it's revenue that was already headed to zero.
Put together: the ROI on JOLT looks different from the ROI on new pipeline generation for three reasons. Cost basis — the acquisition cost on a pipeline deal is already sunk, so this investment is incremental on top of money already committed, not a new customer-acquisition outlay. Speed — new-logo revenue requires a full sales cycle (a 20-month median payback per KeyBanc, and cycles have stretched further since), while pipeline already in motion converts faster. And the counterfactual — 40–60% of that pipeline is heading to no-decision regardless, so the real comparison isn't "$0 invested, $0 returned," it's "fully-invested pipeline, mostly headed to a loss." A recovered dollar against that counterfactual tells a very different story than a dollar measured against a blank slate.
- 50% no-decision default — midpoint of the 40–60% range in published B2B win/loss research (The JOLT Effect, Dixon & McKenna, 2022; 2.5M+ sales calls analyzed). Replace with your own win/loss data where available.
- 5 / 10 / 15-pt presets — JOLT sellers closed indecisive deals at 59% vs. 26% for average sellers, a 33-pt swing. Every preset sits well below that documented ceiling.
- 50% Year-1 ramp — sellers apply the skills to live pipeline during the program, but the model discounts Year 1 anyway.
- New-logo comparison — $2 of S&M per $1 of new ARR and ~20-month payback: KeyBanc SaaS Survey 2025 medians (SaaS-weighted; treat as directional outside software).
- Only counts deals you already have — no new pipeline, logos, or lead generation assumed; the acquisition cost on these deals is already sunk.
- Asks for a fraction of the documented swing — the Confident preset assumes less than half of the published 33-pt difference.
- Year 1 discounted 50% despite in-program deal wins.
- No second-order benefits counted — cleaner forecasts, faster cycles, competitive win rates, seller retention.
- Impact held flat after Year 1 — no compounding assumed.