Marketing & agency
Agency Email Conversion Rate Calculator
Works email conversion, where the action rather than the click is the measure.
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
Conversions divided by delivered messages, or divided by clicks depending on the question, with the value of the conversions shown. Measuring conversions rather than clicks is what connects email activity to results, since a click that goes nowhere is an engagement metric rather than an outcome.
What moves the number
- Landing experience after the click.
- Segment relevance to the offer.
- Timing and send frequency.
- List quality and deliverability.
Where this one goes wrong
A strong click rate with poor conversion points at the landing page rather than the email, because the email did its job in generating interest and the page failed to convert it, and that is a common misdiagnosis that leads to rewriting emails that were working. Check the page. Frequency is the other factor, since over-sending produces short-term clicks and long-term unsubscribes, and the damage shows up later than the benefit.
Before you quote
- Check the landing page when clicks are strong and conversions are not.
- Measure unsubscribes alongside conversions.
- Segment to the offer rather than sending broadly.
Questions
About this calculator
Good clicks and poor conversions, what is wrong?
Usually the landing page rather than the email, since the email generated the interest and the page failed to convert it. That is a common misdiagnosis that leads to rewriting emails that were doing their job perfectly well.
Does sending more emails produce more conversions?
In the short term sometimes, and it produces unsubscribes and reduced engagement over time. The damage appears later than the benefit, which is why frequency decisions should be judged over months rather than campaigns.
What should be measured alongside conversion?
Unsubscribes and spam complaints, since both are the cost of pushing frequency or relevance too far. A campaign with good conversions and a spike in unsubscribes has borrowed from future performance.
The formula
each step = that step / the step before it; overall = jobs / enquiries
Put this calculator on your site
Free to embed. Paste this where you want it to appear. It stays up to date automatically because it loads from BDEVY.
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.