For digital analytics teams
70% of your analytics capacity goes to work that never makes it into the dashboard: verifying data, maintaining implementations, diagnosing issues, debugging what breaks. It rarely gets seen, but every number depends on it.
This work is non-negotiable. Doing it yourself is.
Data checks
Every event, property and value verified on real traffic, around the clock: coverage, types, casing, consent — before the number lands in a dashboard.
Implementation maintenance
A living schema of your tracking, kept current with every release: what appeared, what disappeared, what changed shape, and who owns it.
Diagnosis
A drop, a spike, a gap between platforms: Trackingplan investigates before it answers and tells you whether it’s demand or tracking.
Debugging
Real sessions and payloads, from the dataLayer to the destination, with the tag, the trigger or the variable that caused it.
“Before Trackingplan, we spent around five to six hours per project every month just debugging and ensuring data accuracy.”
Sounds familiar?
None of them really needed your judgment. But they still need your time. So the work that actually does need an analyst keeps waiting.
And everyone else waits with it.
Trackingplan takes care of repetitive questions, reports, and data checks, giving analysts their time back — and everyone else an answer.
Analytics capacity, regained
You’ve got better things to do than manually auditing tags, maintaining outdated spreadsheets, or scrambling to fix tracking issues only after they’ve already broken your tracking.
Since 11:02, each purchase goes out to TikTok twice from the same tag: once on the Purchase Confirmation pageview and once on the purchase DataLayer event. TikTok’s bidding has been optimizing on a doubled signal for three hours. GA4 and the other pixels are unaffected.
Cause: the 11:02 publish added the purchase DataLayer trigger to TikTok – Purchase without removing Purchase Confirmation, so both match on every order. One trigger to remove in GTM.
Answers, on demand
Let our agent answer the questions you get asked every day — grounded in your data, directly in the channels they already use, and without adding another request to your to-do list.
Pinterest conversions fell off a cliff — is the campaign dying?
The campaign isn’t. The tag is. Since Tuesday at 16:40 the Pinterest tag fires without order_id on 100% of checkouts, and Pinterest discards those. Clicks and landing sessions are flat versus last week.
Cause: the variable DL – order_id was renamed in GTM release v92. One change, no budget decision needed.
The layer where data breaks
Most AI analytics starts with what’s already in the warehouse. Trackingplan starts where your data is actually produced — the hit, the dataLayer, the SDK, the pixel, the CAPI payload, the consent state, the GTM release. That’s where a number becomes true or false — and where Trackingplan AI actually looks.
Can I send these numbers to the board?
Revenue and purchases: yes. Server-side and GA4 agree within 0.4% for the quarter, consent coverage is stable, no open implementation warnings.
Sessions: not yet. Since the cookie banner update on the 20th, 9% of EU sessions land without a consent state and GA4 drops them. The quarter is undercounted by roughly 6%. Send the revenue slide as is; footnote sessions or wait for the banner fix I’ve drafted.
24/7 Monitoring
Stop waiting for a dashboard to look weird — or for someone to complain – to realize two weeks later that tracking is broken. Trackingplan monitors your implementation 24/7 and alerts you as soon as something stops firing, starts sending unexpected values, or silently disappears.
Since yesterday morning, sessions landing from Google Ads and Meta arrive with utm_source and utm_medium but no utm_campaign: 11,400 sessions so far, across the 14 landing pages of the Back to School campaigns. GA4 is reporting them as direct / (none). Organic and email traffic are unaffected.
Cause: the new ad sets went live yesterday with a tracking template that never fills utm_campaign. The old ad sets still do. One template to fix in the ad accounts.
Automated debugging
And when an error appears, ask Trackingplan to automate its debugging — from finding the cause to routing it to the right person. With full visibility into what was sent, what wasn’t, and why. No emulators. No need to replicate the issue or the user’s environment. Just actual data from real users navigating your sites or apps, with all the context you need to fix it fast.
Cause found. Every purchase without currency comes from the new express checkout: it builds its own purchase payload and never sets the property. The regular checkout still carries it, so 78% of orders are fine.
Fix: add currency: order.currency to the express checkout’s dataLayer push, next to value. One line. Sent to @ashley (last editor of the tag) in #implementation_analytics with the 40 sample hits and the diff. I’ll confirm here on the first clean purchase.
Trackingplan is your digital analytics agent. It works the way a digital analyst works: it sees the data as it is produced, monitors it continuously across 80+ providers, investigates what happened before it answers, and shows the evidence behind its conclusions.
Ask it a question, give it a task, or let it run an automation. It works from your actual traffic — not from assumptions — and can deliver the answer where your team already works: Slack, Teams, email, your app, or your IDE.
Every request your website, iOS and Android apps, and server-side endpoints send to 80+ providers — including GA4, Meta, Google Ads, TikTok, Bing, Mixpanel, Segment, Amplitude, Snowplow, your CDP, and your consent stack — plus the dataLayer underneath them.
Trackingplan captures the schema, values, providers, consent signals, timing, and implementation context as data flows through your stack. The agent reasons over your actual traffic and its history, rather than filling gaps with a model’s guess.
Because an AI agent can only reason about what it can see.
A warehouse tells you what data eventually arrived. It doesn’t tell you whether the pixel fired correctly this morning, whether a consent state changed, whether a GTM release dropped a parameter, or whether Meta started receiving a different payload after a deployment. By the time the problem reaches the warehouse, the evidence about how the number was produced may already be gone.
Trackingplan starts at that layer. It observes the hits, dataLayer, pixels, SDKs, server-side payloads, consent signals, and implementations that determine what eventually reaches your analytics stack. It automatically builds the schema and semantic context around your real traffic, so the agent can understand what happened, what changed, where it happened, and whether the resulting data can be trusted.
No. Trackingplan is designed to start observing without asking you to build a data model first.
Add one tag, pixel, server-side connection, or our iOS/Android SDK. No tables to expose, no relationships to define, no semantic layer to build, and no tracking plan to configure before the agent can start working. As data flows in, Trackingplan automatically infers your schema and semantic model from what is actually happening.
We are fully committed to respecting user privacy and maintaining compliance with global privacy regulations such as GDPR and CCPA. Trackingplan only observes the data your site or app is already sending to analytics or marketing tools — and only for the purpose of monitoring tracking quality and detecting implementation issues.
In short: Trackingplan never introduces new tracking mechanisms, never stores personal data, and never builds user profiles. We act only as a passive observer of the data you’re already sending to your vendors, with strict safeguards against access to personally identifiable information.
If you want to review the decompiled script under NDA, contact our support team. For a complete overview, visit our Privacy & Security documentation.
It should cannibalize the work nobody wants to bill for.
For agencies and consultants, the value isn’t in spending hours manually checking pixels, chasing broken implementations, or answering the same tracking question for the tenth time. It’s in being able to take on more sophisticated work, serve more clients without adding proportional headcount, and spend your time where expertise actually matters.
Trackingplan automates the repetitive operational layer. Your expertise stays in the loop where judgment matters.
Book a demo
This isn’t a sales call. It’s a chance to understand what matters most to you, discuss any data quality concerns you may have, and share practical ways Trackingplan could support your goals, if it makes sense.