Our history. Built for clarity. Driven by data. Designed to scale.

Trackity was founded with a single purpose: to give ecommerce brands full control over their attribution. No guesswork. No black boxes. We unify ad performance, order data, and analytics into one real time dashboard that is engineered for speed, accuracy, and action.

Powered by Kafka. Running on AWS. Trusted by scaling shops worldwide that want verified truth instead of stitched together stories.

Truth in, trust out Real time streams Engineered attribution

Engineering

Kafka powered, AWS native, built to scale

Data

Verify before you visualise your numbers

Teams

Built by operators who have lived broken attribution

This is who we are: a team that treats attribution as an engineering problem, not a reporting filter, so your growth decisions always sit on clean, defensible data.

Truth in. Trust out.

How we turned broken pixels into engineered attribution.

From frustration to foundation

Trackity began as a side project to fix missing orders, broken scripts, and fake ROAS reports, long before it became a product.
We rebuilt journeys using real time streams, verified IDs, and deterministic logic instead of relying on fragile pixels and shifting attribution windows.
The rule was simple. If we could not prove an event happened, we would not count it. No inflated metrics. No magic numbers.

Today that mindset still drives everything we ship, from server side tracking to dashboards your finance team can sign off on.

Our story

From broken tracking to engineered truth.

Trackity did not start in a boardroom. It started in Slack threads, midnight calls, and client reports that never quite matched the numbers in the bank account. Pixels dropped. Sessions disappeared. ROAS looked great until you realised it was counting things that never happened.

For over twenty years our founding team built SaaS platforms, analytics systems, and B2B cloud tools. We understood what clean data should look like. When we stepped deeper into ecommerce performance marketing, we saw how far attribution had drifted from that standard.

So we started over from zero

How Trackity took shape

01 · Prove We treated attribution as a problem to test first. Could we rebuild journeys with server to server hooks, webhooks, and UTM enrichment without relying on fragile pixels.
02 · Stream We moved to real time streams on Kafka, verified IDs, and layered fallbacks that turned scattered events into one consistent record of what happened.
03 · Scale Once we saw it work for our own accounts, we hardened the system on AWS and opened it to fast scaling Shopify stores and performance teams worldwide.

The principle never changed: verify before you visualise, architect before you automate, and always choose clarity before growth.

What this means for how we build Trackity today

We design every feature so that finance, founders, and media buyers can agree on the same number before they act on it.
We prioritise reconciliation logic, data integrity, and privacy safe collection before automation and dashboards.
We refuse to ship shortcuts that inflate performance. If Trackity shows a win it is because the underlying events prove it.
We build underneath the holes in tracking, not on top of them, so your attribution keeps working as privacy rules and devices keep changing.

Trusted like mission critical tech

Purpose built like core infrastructure.

We did not build Trackity as a typical marketing tool. We built it as a data engine. Under the hood there is a real time architecture powered by technologies such as Apache Kafka, Redis Streams, and AWS grade durability, carefully designed to verify, deduplicate, and scale attribution across your entire stack.

Your insights are not guesses. They are engineered events, measured in real time, tested under pressure, and backed by resilient pipelines from first click to final checkout.

Start free and see Trackity in action

No feature paywalls. Track your first 100 orders before you pay anything.

Real time streams Verified events Infrastructure grade reliability

The principles we build on

What “engineered truth” means in practice.

Our story explains where Trackity comes from. These principles explain how we ship today. They are the filters every feature, integration, and metric has to pass before it reaches your dashboards.

Verification first

100%

of orders must be reconciled against store data before appearing in attribution views.

Architecture focus

foundational layers are kept separate, so updates can happen smoothly without causing widespread issues.

Operator mindset

shared source of truth that founders, finance, and media buyers can all stand behind.

How this shows up in your day to day use

If a number looks too good to be true, we would rather flag it than let it silently inflate your ROAS.
We expose where each metric comes from. Stream, webhook and fallbacks, so your team can see how “strong” a signal really is.
We design for long term consistency over short term hacks, so your historical reports remain comparable as privacy rules evolve.
We think about attribution as infrastructure for decisions, not decoration for decks. Every change is judged by the clarity it adds.

In short: if Trackity says it happened, our systems have checked, stitched, and reconciled it first. That is the promise behind every chart on this page.