At a glance
A useful marketing measurement plan starts with decisions, then defines the evidence, event rules, owners and review actions needed to make them. Dashboards come last, after the team agrees what each result can and cannot prove.
Before you add another dashboard, write down the decision it is supposed to improve. If the answer is “understand performance”, keep going. What would you actually change after looking at it?
A marketing measurement plan connects a business question to the evidence, definitions and people needed to answer it. It saves teams from collecting dozens of metrics and discovering later that none resolves the argument.
Choose three decisions worth measuring
A useful starting set might be: which campaigns deserve more budget, where enquiries lose momentum, and which customer groups are worth serving more deliberately. Each needs different evidence.
Campaign allocation may require an experiment as well as attributed results. Enquiry progression needs a shared definition between marketing and sales. Customer value needs revenue and delivery costs, not just acquisition data.
Our position is that measurement should be designed backwards from a decision. The dashboard is the last expression of that work, not the first.
Write the plan in plain language
| Decision | Evidence | Owner | Review |
|---|---|---|---|
| Increase webinar promotion? | Cost per attended session and qualified conversation | Demand generation lead | After the agreed follow-up window |
| Repair the enquiry form? | Starts, successful submissions and error reports | Web manager | Weekly during the test |
| Change target accounts? | Fit, opportunity progression and commercial value | Sales and marketing leads | Monthly account review |
For each row, add a definition, data source and known limitation. Keep enough detail that two people would calculate the same number from the same records.
“Lead” is rarely precise enough. Specify whether it means a form submission, a distinct person, an accepted enquiry or a qualified opportunity. A team can spend months improving the wrong number because everyone assumes the word means the same thing.
Use established event names where they fit
Google Analytics’ recommended events provide standard names for common actions. Using a recognised event can make implementation and reporting more consistent, but the team still has to decide exactly when it should fire.
For a lead event, record a successful submission rather than a click on the submit button. Test the failure case. If the same person retries, decide whether that represents another enquiry or a duplicate. These details influence the business report more than the colour of its chart.
Connect events to consistent campaign naming. A measurement plan cannot rescue source data split across half a dozen spellings of the same campaign.
Separate description from explanation
A report can show that revenue rose during a campaign. It cannot, by itself, establish how much of the increase the campaign caused. Changes in pricing, distribution, seasonality and sales capacity may also matter.
Use attribution, marketing mix modelling and incrementality testing for the questions they can answer. Do not force every business question into the tool that is already easiest to open.
For a small programme, a carefully defined comparison may be more useful than a complex model fed with weak data. Record what remains uncertain and what evidence would change the decision.
Agree the action before the review
Write a practical response for different outcomes. If attendance is healthy but qualified conversations are scarce, inspect the audience and offer. If registration is strong but attendance is weak, review the promise, reminders and timing. If the event attracts suitable buyers but follow-up is slow, the campaign may not be the bottleneck.
These are starting hypotheses, not automatic rules. The point is to enter the review with a way to investigate rather than a wall of numbers.
Keep the plan alive
Review definitions when products, forms or sales stages change. Record implementation dates. Assign someone to check that important events still work after website releases.
Retire metrics that no longer affect a decision. A useful measurement plan becomes clearer as the team learns. It should not grow indefinitely because nobody wants to delete a chart.
Better measurement begins when everyone knows what they are trying to decide. Better software can help after that.
