Pipeline ROI Calculator

What does AI-handled follow-up add to your pipeline?

Speed-to-lead is the strongest lever on close rate. We model the lift agencies see when AI handles first-touch response and the multi-touch follow-up — using a conservative 2.0× midpoint sourced from HBR research and BTB AI client data.

Cold email + LinkedIn. Lift comes from AI handling replies fast and running the multi-touch follow-up cycle on autopilot.

Your numbers

Tell us what your funnel looks like today.

Speed-to-lead context

HBR found leads contacted within 5 minutes are ~21× more likely to qualify than those contacted in 30+ minutes. AI follow-up takes that response window down to seconds.

How we calculate this

Qualified leads × close rate × avg deal size = current monthly revenue. The AI projection multiplies your close rate by 2.0× — the conservative midpoint of close-rate gains BTB AI client agencies see when AI handles first-touch response and the multi-step follow-up sequence. Hours back assumes ~10 minutes per lead in manual follow-up sequencing (initial response, qualifier exchange, scheduling, 2–3 nudges).

Projection

Revenue with AI-handled follow-up.

Current monthly revenue from leads
$194,400/ mo
Projected with AI-handled follow-up
$388,800/ mo+100%
Annualized lift
+$2.3M
Hours back / month
30 hrs
Qualified leads / mo
180
Closed deals / mo
32.464.8
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Sources
Speed-to-lead contact effect
5-min response = ~21× contact rate

Leads contacted within 5 minutes are ~21× more likely to qualify than those contacted at the 30-minute mark. First-touch latency is the strongest single lever on conversion.

Lead Response Management Study, Harvard Business Review

AI-handled follow-up close lift
1.6 – 2.4×

When AI handles first-touch response + the multi-touch sequence after, agencies see 60–140% more closed deals on the same lead volume. Midpoint of 2.0× used in this calculator.

Aggregated across BTB AI client agencies (Q4 2025–Q1 2026)

Manual follow-up time per lead
~10 minutes

Conservative midpoint across initial response, qualifier exchange, scheduling, and 2–3 manual nudges. AI-handled flows reclaim 80–95% of this time.

Aggregated BTB AI client data

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