Marketing & agency
Agency Conversion Rate Calculator
Measures an agency's own funnel, where the proposal stage is expensive.
Result
Splitting the funnel matters because the fix differs at each step. A poor answer rate is a staffing problem, a poor booking rate is a scripting problem, and a poor win rate is usually a price or trust problem.
Get a Free Business AuditHow the calculation works
Each stage divided by the one before: enquiries to qualified, qualified to proposals, proposals to signed clients. The proposal stage matters disproportionately because producing one takes real strategic time, which makes a low win rate a capacity problem as well as a revenue one.
What moves the number
- Qualification before a proposal is produced.
- Win rate on proposals.
- Whether the agency is competing against many others.
- Fit between the enquiry and the agency's actual offer.
Where this one goes wrong
Producing proposals for poorly qualified opportunities is the most expensive habit an agency can have, because each one consumes senior time that could have served existing clients, and a low win rate frequently reflects which opportunities were pursued rather than how the proposals were written. Qualify harder. Asking how many agencies are being considered is a fair question and a useful one, since a wide competitive process has a low expected value for everyone in it.
Before you quote
- Qualify before committing senior time to a proposal.
- Ask how many agencies are being considered.
- Track why proposals were lost, not just the rate.
Questions
About this calculator
Why is a low proposal win rate expensive?
Because each proposal consumes senior strategic time that could have served existing clients. A low win rate is a capacity problem as well as a revenue one, and it frequently reflects which opportunities were pursued rather than how the proposals read.
Should an agency ask how many others are pitching?
It is a fair and useful question, since a wide competitive process has a low expected value for everyone in it. Knowing the answer lets the agency decide how much to invest rather than treating every opportunity identically.
What should be tracked on lost proposals?
The reason rather than the count. Losing on price, on fit, on credentials and on responsiveness need completely different responses, and a single win rate tells you something is wrong without telling you which.
The formula
each step = that step / the step before it; overall = jobs / enquiries
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Please keep the attribution line. It is the only thing we ask in return.
How to use this calculator
- Enquiries. Enter your own figure; the page starts at 100.
- Answered or returned. Enter your own figure; the page starts at 82.
- Booked an appointment. Enter your own figure; the page starts at 55.
- Became paid jobs. Enter your own figure; the page starts at 33.
- Average job value ($). Enter your own figure; the page starts at $3,800.
The result updates as you type, so you can try a figure, see what it does to enquiry to job, and change it back. Nothing you enter is sent anywhere or saved.
A worked example
These are the figures the calculator opens with. Every number in the results column below is produced by the same calculation the page runs, so you can follow it through before putting your own figures in.
What goes in
| Input | Value |
|---|---|
| Enquiries | 100 |
| Answered or returned | 82 |
| Booked an appointment | 55 |
| Became paid jobs | 33 |
| Average job value | $3,800 |
What comes out
| Result | Value |
|---|---|
| Enquiry to job main result | 33.0% |
| Answered | 82.0% |
| Answered to booked | 67.1% |
| Booked to won | 60.0% |
| Value of what fell through | $254,600 |
33.0% of enquiries become jobs. The biggest drop is worth finding: 82.0% get answered, 67.1% of those book, 60.0% of those buy. The ones that fell through were worth $254,600.
How sensitive the answer is
Holding everything else steady and changing only average job value, this is what happens to enquiry to job. It is worth knowing which of your inputs the answer actually hinges on, and which barely move it.
| Average job value ($) | Enquiry to job |
|---|---|
| $1,900 | 33.0% |
| $2,850 | 33.0% |
| $3,800 example above | 33.0% |
| $5,700 | 33.0% |
| $7,600 | 33.0% |
Every other input is held at the example value while this one changes, which is not how a real job behaves. Treat it as a guide to which number matters most, not as five separate quotes.
What each figure means
- Enquiries
- A number, between 0 and 100000, starting at 100.
- Answered or returned
- A number, between 0 and 100000, starting at 82.
- Booked an appointment
- A number, between 0 and 100000, starting at 55.
- Became paid jobs
- A number, between 0 and 100000, starting at 33.
- Average job value ($)
- A money amount, starting at $3,800.
What the results tell you
| Result | What it is |
|---|---|
| Enquiry to job | The headline result. A percentage. |
| Answered | A percentage. |
| Answered to booked | A percentage. |
| Booked to won | A percentage. |
| Value of what fell through | A money figure. |
Attribution is the weak link
Return and cost-per-lead figures depend on knowing which enquiries came from which source, and most home-services businesses do not track that reliably. If the source data is guesswork, so is the return.
Estimating is the easy part
The jobs you never hear about cost more than the ones you mis-measure. BDEVY builds the marketing, systems and automation that bring them in.