Measure the Time Between a Local Marketing Enquiry and a Sale

A marketing report that compares this month's leads with this month's sales can mislead a business whose customers take weeks to decide. The sale may be the result of an earlier enquiry, while new leads have not had time to progress. A time-lag analysis makes that delay visible and reduces pressure to judge incomplete cohorts as failures.

Use the enquiry date as the starting point

Record the first known enquiry timestamp and the date of each later milestone, such as first response, appointment, quote, deposit, and completed sale. Choose one consistent starting event. If a person contacts the business several times about the same job, use a documented rule for identifying the original enquiry rather than restarting the clock with every follow-up.

Build cohorts instead of mixing calendar totals

Group enquiries by the week or month in which they first arrived, then observe how many progress after a consistent elapsed period. This differs from comparing all sales recorded in a month with all leads recorded in that month. Cohorts reveal whether older enquiries are maturing and whether recent groups have had enough time to be evaluated.

Calculate elapsed time carefully

For each matched lead, calculate the interval between the first enquiry and the chosen outcome date. Use consistent time zones and decide how to handle reopened enquiries, cancelled jobs, and records with missing dates. Report a median or distribution alongside an average when a small number of unusually delayed cases could distort the mean.

Illustrative example

A fictional kitchen renovation firm receives enquiries throughout April. Some projects close in May, while others require site visits, design changes, and financing before a decision in July. Counting only April sales would understate the progress of that cohort. A report should show how many April enquiries remain open, how many were disqualified, and how many reached each milestone by the observation date.

Avoid premature conclusions

A young cohort naturally has fewer completed outcomes simply because it has had less time. Compare cohorts at the same age, such as 30 days after enquiry, only if that window is suitable for the business. If the sales cycle varies substantially by service type, analyse those services separately rather than forcing a single timeline onto unlike purchases.

Separate marketing delay from sales-process delay

Long elapsed time may reflect customer consideration, but it may also reflect slow callbacks, scheduling capacity, quote preparation, or stock availability. Add operational timestamps where possible. A pattern of delayed first responses suggests a different follow-up question than a pattern where customers receive quotes promptly but decide much later.

Present incomplete cohorts honestly

Mark the date through which outcomes were observed and show open records explicitly. Do not project final sales from an immature group unless the forecast method has been validated and its assumptions are explained. A useful report can say that the cohort is not yet mature enough for a final conversion comparison.

Questions readers often ask

Should unfinished leads count as failures?

Not automatically. A lead that has not had enough time to progress should remain open or immature under a defined rule.

Which summary statistic should I use?

Choose one suited to the decision. A median can describe a typical elapsed time when long delays skew the average; also show the observation window and sample size.

Decision note

Use an explicit observation cutoff for every cohort. Without it, two charts may appear to compare equal groups even though one group has had several more weeks to reach an outcome.

Questions to resolve before interpreting the cohort

Which date starts the clock? Does a reopened opportunity retain its original date? How are cancellations and no-shows represented? What is the cutoff for calling a lead mature? Are response times measured? Write the rules once, apply them consistently, and revise them only with a dated note so a later analyst can explain why a cohort's outcome differs from an earlier report.