Data & Insights
Measurement that ties channels, products and customers to revenue and margin. GA4, server-side tagging, Looker Studio and SQL dashboards, built around the decisions your team makes each week.
Most online businesses have more data than they use. GA4 is installed, a dashboard exists, and the weekly decisions still run on instinct, because nobody connected the tracking to the questions that matter: which channels stay profitable after returns, which products bring people back, and which customer segments are worth paying to acquire.
We start by reconciling what the analytics say against what the platform and the bank say. Then we build the measurement plan backwards from the decisions, not forwards from the events a tool offers by default. We have done this for stores that sell in COP, AUD, USD and CLP at the same time, and we have kept attribution models usable through the iOS changes and the end of third-party cookies.
What we do
- Analytics setup
- Performance monitoring
- Data visualisation
- Conversion tracking
- Business intelligence
How we work
- 01Analytics audit and gap analysis
We go through your GA4 property, the GTM container and every existing dashboard. The output is a list of broken events, duplicate tags, missing server-side tracking and attribution blind spots, in priority order.
- 02Measurement architecture
A written measurement plan: which events to track, how attribution is modelled, and how analytics data joins your revenue and margin figures.
- 03Implementation and validation
GA4 event tracking, server-side GTM and enhanced e-commerce. Before any report is built on top, we validate the numbers against backend transactions.
- 04Dashboards and ongoing insight
Looker Studio dashboards or SQL reports shaped around weekly decisions, plus a monthly call where we turn what changed into what to do next.
Tools we use
- Google Analytics 4
- Google Tag Manager
- Looker Studio
- BigQuery
- Python / TensorFlow
- Metabase
Questions
Our GA4 is set up but we don't trust the data. Can you fix it?
Yes, and it is the most common reason we get called. We audit every event, compare it against backend transaction data and find where the gap comes from: usually misconfigured purchase events, duplicate tags or missing server-side tracking. We reconcile GA4 against your Shopify or platform revenue before building any reporting on top of it.
Can you build dashboards that combine several data sources?
Yes. Our Looker Studio dashboards pull from GA4, Google Ads, Meta Ads, Shopify and custom SQL databases. For clients who need long history or attribution modelling across large volumes, we have built BigQuery warehouses underneath.
What is your experience with inventory and demand forecasting?
We have built TensorFlow inventory models for cycling retailers that predict sell-through by SKU across seasons. For most mid-market stores we start with simpler SQL forecasting and only add machine learning when the data quality and the team's ability to act on it justify it.
How do you handle multi-currency and multi-market analytics?
We have set up GA4 and Looker Studio for stores operating in COP, AUD, USD and CLP at once. We normalise to a reporting currency with exchange-rate data and build market-by-market views, so contribution can be compared across countries on the same basis.
Related work
A dealer portal for Giant's distributor in Chile, covering the Giant, Liv and Momentum storefronts, with predictive inventory for a network of more than 250 dealers.
Our own Colombian cycling store, moved from Shopify Liquid to a headless Hydrogen, Remix and Oxygen stack with a rebuilt tracking layer. We run it, so every mistake and every fix costs us first.
A Shopify cycling store for Bicico with the Cannondale range, Suarez apparel and a WhatsApp advisory flow that puts an expert in the conversation before a high-value purchase.