Analytics requirements translator for marketing and dev handoffs

The moment a marketing analyst needs to track a new user behavior, they open a Jira ticket, write something like 'track when users click the signup button,' and wait. The developer interprets this differently than intended, implements it inconsistently with existing naming conventions, and the analyst only discovers the problem two sprints later when the data looks wrong. Users describe this as a constant bottleneck: 'I constantly have to submit tickets to the development team to update tags' and 'companies often lack strong communication between marketing and IT teams to determine the necessary events to track.'

This friction is structural. Marketing analysts think in business questions ('how many users reach step 3 of checkout?'). Developers think in DOM events and data layer pushes. There is no shared language between them, and no existing tool is motivated to create one — analytics vendors want enterprises to buy implementation services, and project management tools are domain-agnostic and don't understand what a correct analytics spec looks like.

Every single new tracking requirement — a new button, a new funnel step, a redesigned form — triggers this same broken handoff process. At a company with active product development, this happens dozens of times per quarter. Each poorly specified ticket either gets implemented wrong (producing silent data corruption) or bounced back for clarification (adding weeks of delay). Neither outcome is acceptable, and both are currently the norm.

The business case is simple: a marketing analyst who can write an unambiguous, technically complete implementation spec without needing to understand JavaScript is worth more to their employer than one who can't. The tool that makes that possible gets bought by marketing ops teams who are tired of explaining what a dataLayer.push() is.

What to build

Build a web app where a non-technical analyst describes a user interaction in plain English, and the app generates a complete analytics implementation spec — including event name, trigger definition, variable mappings, and a sample dataLayer object — formatted as a ready-to-paste Jira ticket with acceptance criteria a developer can test against, using the customer's existing variable naming conventions as a constraint.

Where to start

Launch as a Jira plugin so the workflow lives inside the tool developers already use to review tickets — this removes the 'another tab to open' objection and means developers see the structured specs without the analyst having to convince them to adopt a new process.

The hard part

The value depends entirely on the generated spec being correct and consistent with each company's existing implementation conventions — which means onboarding requires ingesting their current schema, and any errors in the output will immediately destroy trust with the developer audience who has to implement it.

How it makes money

Per-seat subscription for analytics team members who create specs, around $30-50 per seat per month, with a free read-only tier for developers who receive and review specs. Grows as analyst headcount grows.