The value we deliver
150 research hours.
One closed deal.
148.5 of those hours never had a chance.
In technical B2B verticals, an AE researching from scratch spends roughly 150 hours to land one closed contract[3][4][5] — and loses 95% of it before a single conversation happens. Below is the math, cited, followed by a calculator for your own numbers.
The math, laid out
Where 100 companies and 150 hours actually go
A rep working a technical vertical (developer tooling, infrastructure, security) spends about 1.5 hours per company researching tech stack, hiring signals, and org structure before ever making contact[3]. Roughly 5% of researched accounts convert to a first meeting, and roughly 20% of those meetings convert to a closed deal[4][5]. Working that funnel backward from one closed contract:
Bar widths are scaled for legibility (square-root scale, not linear) — the printed counts and hours are the actual figures.
99%
of the 150 research hours (148.5 hours) are spent on the 99 companies that never close.
95%
of total research time is lost before a single conversation happens — on companies that never reply at all.
What Kairo changes
Three layers of value, in order
KairoDynamics automates the research phase of that funnel — at measured expert parity (more on that below). What that unlocks compounds in three stages.
Layer 01
Reallocated hours
133 of the 150 research hours in a deal cycle move from research to actual selling — discovery calls, POCs, negotiation. That matters because B2B reps already spend only 30–40% of their week actively selling[1][2]; the rest is admin, internal meetings, and exactly this kind of research. Your AEs are salaried either way, so this isn't a payroll line item; it's capacity you already pay for, currently spent on companies that never respond.
Same 150-hour budget per closed deal, before and after — only the split changes. Reps are salaried, so this is reclaimed capacity, not a payroll line item.
Layer 02
Pipeline capacity
A rep bogged down in manual research caps out around 20 active accounts — there just isn't time for more. With research done before it hits their desk, a ranked, pre-researched feed supports 40–50 active accounts per AE, roughly double.
Layer 03
Revenue expansion
More reclaimed selling hours, spread across more active accounts, means more closed deals per AE per year — at your contract value, not an assumed enterprise number. That's what the calculator below is for.
87%
How we know
Measured against a human expert, not a demo
87% of our engine's top recommendations were judged good matches by a domain expert across three independent blind studies of sellers the system had never seen. Every study was pre-registered before any result existed, the expert labeled candidates blind to the machine's output, and results are reported per seller — a flattering average with hidden per-customer failures counts as a failure of the study. Every match a customer actually sees has also been individually approved by a human reviewer before it's revealed.
Run your own numbers
The calculator
Enter your team's actual median contract value, AE headcount, and cycle length. Every output below shows its formula — nothing here is a black box. The hourly value used throughout is $135, drawn from a $250–300k technical-vertical AE OTE[6].
Per deal
$17,955
reallocated capacity per closed deal
133 hrs eliminated × $135/hr = $17,955
Per year, whole team
$179,550
reallocated capacity per year, across 5 AEs
12mo ÷ 6-mo cycle = 2 deals/AE/yr
2 × 133 hrs × $135/hr = $35,910/AE/yr
$35,910 × 5 AEs = $179,550
This is reclaimed selling capacity, not payroll savings — your AEs are salaried either way. The value shows up as more selling time per AE, not a smaller headcount.
Added annual revenue, from that reclaimed selling time
Conservative
$200,000
+1 deal per AE per year
+1 deal/AE/yr × $40,000 × 5 AEs = $200,000
At full capacity gain
$600,000
+3 deals per AE per year
+3 deals/AE/yr × $40,000 × 5 AEs = $600,000
These are scenarios, not a forecast — the added-deal counts are illustrative bounds, not a modeled prediction for your team. Your own conversion rate and pipeline capacity will set the real number.
Sources
- [1] Salesforce — sales-forecasting & rep-productivity research
- [2] Ebsta-sourced sales time-allocation analysis, "Reps Only Sell 40% of the Time"
- [3] B2B technical pre-contact research-time benchmarks
- [4] Outreach — pipeline velocity & win-rate benchmarks
- [5] RevenueGrid — sales-cycle stage conversion benchmarks
- [6] Account Executive compensation benchmarks, technical-vertical OTE
Hours-reallocated and hourly-value figures above are KairoDynamics' own accounting, disclosed with their formulas rather than cited externally — see the calculator's formula readouts. The 87% match-quality figure is our own measured result, reported per the methodology summarized in “How we know” above.