Writing analytics specs that developers can build

In UK government digital teams I wrote the specifications for my own team's analytics work, as user stories with acceptance criteria. The rule I took from it is easy to state: an analytics request is ready for development when someone other than the analyst can test it.

The situation

I worked as an analyst in UK government digital teams, at GDS and the Department for Education, often in several teams at the same time. The teams were multidisciplinary and worked in Agile, with product and delivery managers, developers, designers and user researchers on the same service.

Part of the work was digital identity. In the UK that is harder than in many countries, because there is no national identity card to check people against, so a service has to build confidence in who someone is from several weaker pieces of evidence. Government is still working on it: in February 2026 HMRC started signing up new customers through GOV.UK One Login, which GOV.UK said was then available for over 200 government services.

In a team like that, an analytics request competes with everything else on the board. If it arrives as "can we track the identity check?", the developer has to guess what to send, when and with which values. The guesses come back at user acceptance testing (UAT), when changing them is expensive.

What I did

For my own team, I wrote each analytics task as a user story with acceptance criteria. The story said who needed the data and which decision it supported. The criteria said what the developer had to build and how we would check it in UAT.

The example below is invented for this post and has no detail from a real service, but it has the shape I used.

As a performance analyst, I want an event when a user leaves the identity check step, so that we can report completion by step and see where people drop out.

• When the user leaves the step, one event named identity_check_step_end is sent.
• The event has an outcome parameter with one of these values: passed, failed, exited.
• The event sends no name, date of birth, document number or free text.
• In UAT, one attempt with each outcome produces exactly one event per attempt in the test property.

The privacy line sat in the criteria on purpose. In an identity service the safest personal data is the data the event never carries, and a written criterion can be tested in UAT like any other.

Writing the check first also moves the questions earlier. Edge cases come up while the story is being refined, when an answer is a comment on the ticket.

The team also automated its recurring reporting with Python and ETL pipelines. That cut the analytics effort on reports by around three quarters, and weekly reports went out on time to more than 30 stakeholders. It was a team achievement, built in Agile with everyone on the team.

What I learned

Acceptance criteria that cannot fail are a wish list. Each line has to describe something a tester can see happen or not happen. The analyst is the best person to write those lines, because the analyst knows what the data will be used for and which mistakes would make it useless.

What I would do today

The GOV.UK Service Manual already asks teams to have a performance analyst from the start of discovery and to work out their measurements while the service is built (Service Manual). I would keep that and add four things.

1. Link the tracking plan to the stories, so each event points to the story that created it and to the metric it feeds.
2. Check event names and allowed values automatically in the test environment, so a typo fails before release.
3. Agree once with the privacy team a list of fields that never go into analytics, and paste it into every story.
4. Write acceptance criteria for AI features in the same way. A feature built on a large language model also needs written cases it must pass before release, and someone other than its builder should be able to run them.