The Outbound Forecast Calculator.
Plug in your numbers. See exactly how much outbound volume you need - and how much revenue it should produce - to hit your goals. Built on real campaign data.
Your inputs
Any reply, including auto-responders + OOOs. Industry avg: 1–4%
% of all replies that show genuine interest. Industry avg: 20–50%
Industry avg: 20–40%
Industry avg: 90%
Avg for cold outbound: 20% (higher with experience)
Your forecast
Monthly revenue from outbound
Emails / month
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Emails / day
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Meetings booked / mo
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Meetings held / mo
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Deals closed / mo
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Pipeline value / mo
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Infrastructure you'll need
Forecasts assume well-built infrastructure, real copy, real ICP targeting, and active reply handling. Yours likely won't hit these unless all four are in place. That's where we come in.
What 12 months of outbound looks like vs. doing nothing.
Using the inputs from the Calculator tab. Assumes a 3-month ramp: month 1 builds infrastructure, month 2 hits ~30% of steady-state, month 3 ~70%, month 4+ runs at 100%.
Everything you earn today from referrals, inbound, repeat business - not from cold outbound.
Year-over-year growth from your existing motion. Converted to monthly compounding internally.
These are the numbers when the system runs clean. In practice, results almost always come in lower because of operational constraints (fulfillment capacity, onboarding bandwidth), closing variance (one bad month tanks the average), limited ability to onboard consistent business without breaking things, changes in outbound efforts (offers that stop landing, audience shifts), message fatigue (segments that worked in month 3 stop in month 9), seasonality, hiring gaps, deliverability turbulence, and a dozen other variables a slider can't model. Treat this as a ceiling - the math of what's possible - not a guarantee. Use it to decide if outbound is worth investing in.
How these numbers are calculated
No fluff. Every number on this page is derived from the inputs above, using transparent math. Defaults reflect medians from our portfolio - not best-case scenarios.
The funnel math
emails_per_month= total_replies ÷ reply_ratetotal_replies= interested_replies ÷ interested_rateinterested_replies= meetings_booked ÷ booking_ratemeetings_booked= meetings_held ÷ show_ratemeetings_held= deals_closed ÷ close_ratedeals_closed= revenue_goal ÷ deal_size (revenue mode)
or directly entered (meetings mode)
Infrastructure sizing
- 20 business days / month
- 20 emails / inbox / day (safe steady-state cap)
- 3 inboxes / domain (max we run per domain)
inboxes= ceil(emails_per_day ÷ 20), min 1domains= ceil(inboxes ÷ 3), min 1
Ramp curve (12-month)
- M1: 0% - infra build, copy + lead lists
- M2: 15% - first sends, warm-up still active
- M3: 40% - copy iterations starting to land
- M4: 70% - campaigns dialed in
- M5: 90% - setters refined, deliverability stable
- M6+: 100% - steady state
Baseline + growth
baseline_M[m]= current_monthly_rev × (1 + monthly_growth)^mmonthly_growth= (1 + annual_growth)^(1/12) - 1- Do-nothing line = sum of baselines M1-M12
- With-outbound line = do-nothing + sum of ramped outbound
- "Pure gain" = with-outbound - do-nothing (= outbound contribution alone)
Default sources: Reply rate 2.5% (industry 1-4%), interested rate 35% of all replies (industry 20-50%), booking rate 30% of interested (industry 20-40%), show rate 90% with active setter follow-up, close rate 20% on cold-sourced leads. All defaults are user-adjustable - override with your own data if you have it.
The ramp assumption is the median across our portfolio - some agencies hit 100% by week 6, others take longer. Compounding starts the day you ship copy and doesn't stop while the system runs.