Analytics-as-Code.

Analytics-as-Code is software that does the auditing, fixing, and monitoring work a web analyst would normally do — for about one two-hundredth of what hiring one costs. It does three things: it checks your Google Analytics 4 and Google Tag Manager setup for problems, it writes the actual fix code or configuration for you, and it keeps watching your setup after you log out so you find out the next morning when something breaks.

A traditional audit emails you a PDF of what is broken and then stops. You still have to find someone to fix every issue and remember to re-run the audit later. Analytics-as-Code does the audit, but it also generates the fix (the tracking code, the cookie banner, the corrected tag) and it keeps re-running every night so you find out the morning after something breaks — not three months later when revenue numbers stop matching.

No. The audit findings are written for marketers, not engineers — every problem comes with a plain-English explanation, the business impact, and the exact click-path inside the Google interface to fix it. The generated artifacts (cookie banners, tracking specs, naming rules) can be handed to a developer or a freelancer if you have one, or imported directly through Google Tag Manager if you do not. You do not write any code yourself.

Heads of Marketing, VPs of Growth, Directors of Performance Marketing, and Heads of Digital at companies doing $10M to $500M in revenue. Typically the analytics is set up (often badly) and there is no full-time web analyst on staff. The two alternatives are usually: hire a senior analyst for $80k–$250k a year, or pay an agency $3k–$10k a month. Both are slower and more expensive than the audit-and-monitor work actually warrants. We are the third option.

Three things changed at once. First, Google retired the old Universal Analytics in 2024, which forced every brand onto GA4 — an interface where the most expensive mistakes are hidden by default. Second, EU and UK cookie-consent rules tightened, which made the cookie-banner setup a real legal risk if you get it wrong. Third, AI got cheap and good enough to read tracking configurations and explain them like a human would. Together, the work that used to need a full-time analyst can now run as a subscription.

Not entirely. Roughly 80 percent of an analyst or agency role is the same recurring audit, fix, and monitoring cycle — that part is what software does well now. The other 20 percent — sitting in stakeholder meetings, designing the right dashboard for your CFO, picking the right attribution model, running experiments — still needs a human. Most marketing teams use Analytics-as-Code as the always-on layer underneath, and bring in a human only for the harder strategic calls.