Most go to market plans fail on arithmetic
long before they fail on effort
A plan is not wrong in month nine when the number is missed. It was wrong on the day it was approved, and about twenty minutes of division would have shown it. We publish that division: coverage maths, channel selection tests, budget splits and the gates that decide what gets killed.
No signup. Nothing stored. The model runs in the page.
Four readings decide
what lives and what dies
These are applied per sequence, per segment, after warm up, over a window agreed before launch. Three of them divide positive replies by emails sent. The fourth divides all replies by emails sent, which is a different fraction, so it sits apart rather than next to them.
Kill line, positive replies on sends
Below this the sequence is finished. Iterating on it costs more than replacing the segment and starting again.
Scale line, same fraction
Between 0.5% and 1% you iterate. At 1% you fund more volume. At 2% you pour everything you have into it.
Fleet baseline positive rate
Derived from two published segment multiples, not read off a dashboard, and labelled derived every time it appears. It is the conservative planning input.
Reply rate, one week, largest account
44,649 emails producing 377 replies. How many of those replies were positive is not a figure we hold, so this page does not print one.
Four calculations decide
whether a plan is possible
Everything here runs from a revenue target backwards to a volume of activity, then checks that volume against the two ceilings nobody looks at: what your team can physically send and how many qualified companies exist to send it to.
Pipeline coverage
Coverage is the inverse of your own win rate, adjusted for deals that slip out of the period. A fixed 3x is the correct answer for a 33% win rate and nobody else, which is why teams hit every activity metric and still miss the quarter.
What each rate divides by
Reply rate, positive reply rate and positive reply ratio, each written as a fraction with its sample and period. The same campaign can honestly be described as 40% or as 0.4%, and a planning meeting that mixes the two approves a budget two orders of magnitude too small.
Channel selection
Four tests decide whether outbound earns budget before inbound does: how many companies could plausibly buy, whether deal size supports a human sales process, how long the cycle runs, and whether the team can actually hold the meetings it books.
Budget allocation
Splitting spend across capacity, experiments and compounding assets, modelling a true cost per meeting held rather than per meeting booked, and deciding in advance what gets cut first. We teach the model. You supply your own costs.
Revenue backwards to activity,
then a capacity check
It is deliberately boring. The sophistication is not where the value sits. Refusing to skip a step is, because every error compounds downwards and the two most commonly skipped steps are the last two.
Deals, then opportunities
Revenue target divided by your own segmented closed won average, then divided by your opportunity to close win rate. A blended company average that mixes a pilot with an enterprise renewal produces a plan for a customer you do not have.
Derive the coverage ratio
One divided by your win rate, multiplied by a slippage allowance for deals that push out of the period. A 25% win rate with 20% slippage needs 5x, not the 4x the inversion alone suggests, and certainly not a borrowed 3x.
Convert to meetings, including no shows
Opportunities divided by your meeting to opportunity rate, then divided again by your show rate. Where calendar discipline is broken, booked meetings die at roughly a 50% show rate, which silently doubles every activity number below this line.
Check the volume against two ceilings
Meetings divided by the positive rate per channel gives required sends. Then compare that against your real sending capacity and against the count of qualified companies in the market. If it exceeds either, the plan has stopped being aggressive and started being impossible.
Set the gates before launch
Kill, iterate, scale and pour thresholds agreed in writing before the first send, along with the review window. A threshold agreed after the first bad week is whatever the loudest person in that meeting wanted, and everyone will remember it as a decision.
We publish the number
that disqualifies our own service
This property is owned by an outbound agency. That is the first thing you should know about it, because the most useful argument on the site is that outbound is the wrong instrument for a large share of the companies who ask for it.
The argument against outbound needs its own address
On an agency website, a page explaining that the arithmetic collapses below roughly $10K in deal size reads as false modesty, and the reader discounts it. On a property whose entire subject is the maths, the same sentences read as the maths. The credibility difference is real, not a trick.
Every rate ships its denominator
Including the correction we owe. Comparing a positive reply ratio to a per send industry average is the standard claim in this category, our own earlier marketing made it, and it overstates the result by an order of magnitude. That comparison appears nowhere on this domain.
Part of the Outbound Pros group
Disclosed in the footer of every page, and worth reading as a credential rather than a disclaimer. The kill thresholds above are ones we act on with our own clients, when killing a sequence costs us revenue. A consultant with no execution arm has better optics and worse data.
The questions that come up
before the budget is signed
What is allbound, and how is it different from multichannel?
Allbound is a go to market model where inbound and outbound are planned, budgeted and measured as one system against a single pipeline number. Multichannel describes how many channels touch one prospect. You can be multichannel without being allbound, which is the common case: an SDR team running email and LinkedIn while marketing runs content on a separate budget with a separate target. Sequencing touches against a prospect is orchestration. Deciding which motion earns the next unit of budget is allbound, and it only works if both motions are measured with the same fractions.
What is a healthy pipeline coverage ratio?
Healthy coverage is one divided by your own opportunity to close win rate, multiplied by a slippage adjustment for deals that push out of the period. A 25% win rate lands near 4x before slippage and near 5x after a realistic allowance. The famous 3x is the derivation for a 33% win rate and no slippage, repeated until it lost its origin. There is a second trap underneath it: if your sales cycle is longer than the period you are covering, some of that coverage is arithmetically incapable of closing inside it, no matter how good the deals are.
Should we fund inbound or outbound first?
Outbound first if you can name fewer than about a thousand companies who could buy, your deal size supports a human sales process, and you need pipeline inside one quarter. Inbound first if buyers are already searching for the category, deal size is too low to support per prospect outreach, or the market is too large to prioritise without demand signals showing you where to look. Most companies above roughly $10K deal size and below roughly 50,000 target accounts should run outbound first and start the inbound asset build in parallel, because inbound compounds and cannot be started retroactively.
How long before a new outbound motion tells you anything?
Longer than most plans allow for. Onboarding runs around 21 days and domain warm up takes 4 to 6 weeks before volume is real, so the first two months of a bad programme look identical to the first two months of a good one. That gap is also where the industry loses people: monthly client churn across this category runs in the 3 to 5% range, and a meaningful share of it is buyers cancelling during the ramp they were told about and did not price in. Set the review window past the warm up or do not start.
What positive reply rate should I model for a channel I have never run?
Model conservatively at the derived fleet baseline, roughly 0.05% positive on sends, and treat 0.5% to 1% as the target you are trying to reach rather than the rate you plan around. Then run the model at both ends and look at the spread. If the plan only works at the optimistic end, the plan does not work. This is the single most common correction we make to a go to market model, and it usually moves required volume by a factor of ten.
Who should not use this site?
Pre revenue companies with no closed deals, because every model here needs a win rate and an average deal size, and estimated inputs produce false precision that gets quoted in a board meeting. B2C, e-commerce and low ACV self serve, where per meeting cost overwhelms the deal economics and the whole framework misleads you. Anyone who wants one benchmark number for a slide, because you will get a range, a denominator, a sample and a caveat instead. And teams that will not instrument show rate, meeting to opportunity conversion and positive replies by segment, because that is not a maths problem and this site cannot fix it.
Do the division
before you fund the motion
The calculator takes a revenue target, deal size, win rate and channel mix, and returns required pipeline, opportunities, meetings, replies and sends. It runs at a conservative and an optimistic rate at the same time, so you see the spread before you commit to either.
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