Data Infrastructure · Server Side Tracking
Why BooleanMaths is the best tracking setup for your D2C Brand
Standard tools like GA4 are missing more of your data than you think. Here's exactly why, and what we do differently.
1. Server-side tracking
100% events captured,
unaffected by Ad blockers & privacy browsers
BooleanMaths is a server-side tracking setup that plugs directly into the Shopify data layer. This ensures we are not missing any user events on your store's domain. Every Page view, Add to cart, and Checkout initiation is tracked accurately.
Because all events are captured server-side, we are unaffected by iOS restrictions, cookie blockers, Ad blockers, and privacy browsers like Brave and Safari.
We stay compliant with all privacy policies while maximising data capture.
2. Third-party checkout accuracy
99.3% session merge accuracy across 3rd-Party Checkouts
We have custom merge algorithms for each third-party checkout including GoKwik, Shoppay, Paypal, Shopflo, Shiprocket, and others. These ensure there is no data loss when the user journeys switches sessions from Shopify to the checkout page.
GA4 can only do this with 85–90% accuracy. We do it at 99.3%.
3. Identity graph
Cross-browser journeys and the attribution gap most brands don't see
This is the problem that most trackers completely ignore and their accuracy falls completely part behind the scenes.
When you click on an ad in Meta's ecosystem, it opens in an In-App browser - inside Instagram or Facebook itself.
When you click a Google ad, it opens in your phone's native browser.
A YouTube ad opens in Chrome or Safari.
What this means is that the same user who clicked on both Meta and Google ads ends up coming to your store from two completely different browser sessions.
Most trackers cannot merge these multi-browser sessions into one unified user journey. BooleanMaths can.
We do this using an identity graph that combines
Deterministic identifiers : fingerprint, email, phone number &
Non-deterministic signals : device ID, IP address, location, and browsing behaviour,
Our algorithm scores each candidate session with a confidence score for how likely is is that it belongs to the User Journey. We only match a session with a user journey if the confidence score is above 95%.
Without cross-browser enrichment, brands typically only see around 5% of the actual overlap between Meta and Google. If the real overlap is 300 out of 1,000 orders, a brand without enrichment will surface just 25–30 of those - under 3%.
With our identity graph, we are able to identify ~200 of those 300 journeys. Because we want to maintain a 95%+ confidence, we choose not to merge the remaining ~30% of the journeys. Lowering our confidence would capture those sessions but introduce a lot of noise to our data.
65%
of real cross-channel journeys identified, vs. under 3% without enrichment
4. Anonymous visitor identification
Identifying anonymous visitors through Shopify logins and historical data
Our deep integration with Shopify's data layer lets us track Shopify logins and account updates to identify anonymous visitors the moment they log in.
Beyond that, the extended data history we have across all sessions lets us build a much richer identity graph. This identity graph enables us to even identify anonymous traffic that visited your store two or three months ago and has now returned.
25%
Most tools write that traffic off. We identify 25% of it.
To recap
1. Server-side tracking that captures 100% of events and is unaffected by ad blockers, iOS restrictions, or privacy browsers.
2. Custom algorithms for each third-party checkout, so there is no data loss at the session handoff.
3. A rich identity graph that resolves cross-browser complexity with a 95% confidence threshold.
4. Shopify login integration and historical data depth that retroactively identifies 25% of anonymous visitors.
All of this together means our tracking has better visibility, more accuracy, and is able to identify far more of your anonymous traffic than any standard tool.