Tag audit and change management for Adobe Analytics

The moment arrives when a marketing analyst realizes a campaign has been firing against a misconfigured eVar for six weeks and there's nothing to do about it — the data is gone, the report is wrong, and fixing it requires a developer ticket that will take two sprints to clear. This is not an edge case. Users explicitly call out that 'if you incorrectly implement it, you cannot retroactively fix your data' and that 'custom events demand development and QA skills, but companies often lack strong communication between marketing and IT.'

The gap persists because Adobe's incentive is to sell implementation consulting and enterprise contracts — a cleaner self-service layer would cannibalize agency revenue that Adobe partners depend on. The buyer (CMO, VP Marketing) rarely sees the day-to-day ticket queue, so the pain stays invisible at the purchasing level until a major campaign fails.

What's missing is not another tagging UI — it's a change control layer that sits between a marketing analyst's intent ('track clicks on this button as Event 42') and the developer's implementation. Today, that translation happens in Slack threads, Jira tickets, and spreadsheets with no audit trail, no validation, and no rollback. A single miscommunication produces silent data corruption that compounds for months before anyone notices.

This recurs every time a new campaign launches, a site redesign happens, or a tracking requirement changes — which at any active company is every few weeks. The cost of getting it wrong isn't just bad data; it's bad budget decisions made confidently on corrupted numbers.

What to build

Build a web app that lets analytics managers define tracking requirements in plain-language spec cards (event name, trigger condition, expected variable values), auto-generates the corresponding Adobe Analytics implementation code and Data Layer spec, flags conflicts with the existing variable schema, and maintains a versioned change log tied to deployment dates so data anomalies can be traced back to specific implementation changes.

Where to start

Start with the spec-to-ticket workflow only: a Jira-integrated card format that standardizes how analytics requirements are written and handed off to developers, so the first value is faster, cleaner tickets — not code generation. That gets adoption before the harder technical layer is built.

The hard part

Adobe's implementation patterns vary wildly between companies — some use DTM, some Launch, some hardcoded JavaScript — so the code generation layer has to handle enough variation to be useful without becoming a full-blown tag management system that competes with Launch directly.

How it makes money

Monthly subscription per analytics workspace, tiered by number of tracked properties. Starts around $200/month for a single property, scales to $800/month for teams managing 5+ properties with approval workflows.