E-commerce · Product analytics · React Native
For e-commerce brands, retailers, and D2C stores with serious mobile traffic, the app is not just a sales channel - it drives decisions on conversion, campaigns, and assortment. Whether you are building from scratch, launching mobile for the first time, or modernizing an existing app, shape it around data from day one.
Below: what to measure in a mobile store app, which tools to use, and how it translates into brand revenue.
Without analytics you only see the last column. With analytics you see every point where you lose customers - and can win them back.
Sample funnel for illustration - not a promise of results for your store.
00 / Why now
In larger stores and retail brands, app data often sits beside web analytics, CRM, ads, and ERP - without a shared event language. The mobile app is sometimes built "fast": a few events added late, unnamed screens, marketing measured separately from sales. On a greenfield build, first mobile channel, or modernization you define every screen and customer action anyway - so the tracking plan can be designed properly from the start instead of patched in after launch.
For e-commerce and marketing teams where every conversion point matters, the difference is simple: instead of an app you only know "works", you get a product that suggests what to improve to sell more - and lets you validate in days instead of guessing for a quarter.
Our approach
We do not bolt analytics on at the end. We treat it like payments or login - part of the app planned from the start.
01 / Philosophy
Data can be read on three levels. Most e-commerce organizations stop at the first. The insights that move margin and LTV appear two levels up.
Level 1, description
What is happening?
How many users, what revenue, which screens. A starting point, not the goal.
Level 2, diagnosis
Why is it so?
Where and who drops off, which product variants block purchase, what separates buyers from the rest.
Level 3, action
What do we do next?
Tests, personalization, and timely reminders. What moves conversion and basket value.
02 / Foundation
Before we measure anything, we design a tracking plan - an agreed dictionary of events and attributes (e.g. product_viewed, add_to_cart, checkout_started). App, web, and marketing data then speak the same language.
Why this matters at e-commerce scale
With a large catalog, seasonality, and many campaigns, consistency matters: the same metrics in the app, web store, and ad reports. You add new tools quickly without digging into code each time.
03 / What we can measure
04 / Tools
For brands with high traffic and many channels there is no single “best” stack. Below are categories we work in, with example tools - from MVP to stacks handling hundreds of thousands of sessions per month.
Market standard, strong Google Ads integration. A sensible starting point at no extra tool cost.
Advanced funnels, cohorts, and paths without developers for every question.
Analytics, session replay, A/B tests, and feature flags in one, with self-hosted option and full data control.
Your own data warehouse for deep custom analysis and tailored reports.
One event source, routed to all tools. Less code, easier vendor swaps.
Accurate, ad-blocker-resistant measurement of key conversions on the server.
See which campaigns bring buyers, not just installs. Less wasted ad spend.
Ads land on the right product in the app, not the home screen.
Live A/B tests and gradual rollouts. Decisions from results, not opinions.
Change copy, promo prices, or layout without an app store release.
Watch real sessions and see exactly where customers get stuck and leave.
Automatic detection of repeated taps - a signal of bugs or unclear UX.
Automated, personalized push and messages based on real behavior, e.g. abandoned cart.
Lightweight, cost-effective start with push notifications and audience segments.
Catch errors and crashes before customers report them. Every checkout crash is lost revenue.
We track screen load times. A slow app simply converts less.
Listed tools are examples. The final stack is chosen for your business goals, traffic scale, and budget.
05 / From data to revenue
Analytics alone does not sell. What you do with it does. A few moves that usually pay back fastest:
funnel optimization
We find the step with the biggest drop-off (often delivery or checkout registration), simplify it, and measure impact. Analytics shows which change to ship first - and with React Native we usually deploy in days and see results immediately.
cart recovery
Customers who added items and left get a timely reminder, sometimes with an incentive. One of the fastest-payback automations in e-commerce.
personalization
Recommendations and home feed tailored to history and behavior raise basket value and shorten the path to purchase. More data means better suggestions.
retention and LTV
Acquiring new customers is expensive. Data-driven segments let you reach at-risk users before they churn and reward your most valuable ones.
experiment culture
Every major change (product page layout, copy, promotion) is tested on part of traffic and shipped only when it improves results. Less risk, faster growth.
Honestly
We do not promise magic growth percentages - every brand, catalog, and season is different. We promise data-driven decisions, fast hypothesis tests, and steady improvement of revenue metrics.
06 / React Native advantage
More on the stack: React Native
07 / How we roll it out
Phase
0
Right after kick-off we define the tracking plan and collection layer - in parallel with a greenfield build, a first mobile channel, or modernizing an existing app in React Native. We treat analytics like payments: part of the product from the first release.
Phase
1
We launch funnels, dashboards, and session replay. For the first time you see the full picture: where and why you lose customers.
Phase
2
A/B tests, cart recovery, push automations. We systematically lift conversion and basket value.
Phase
3
Recommendations, predictive segments, churn prediction. The app starts acting proactively.
08 / Roles
We build the foundation: tools, integrations, clean data, ready dashboards. We own that entirely. But wiring alone does not sell - your team does, because they know customers, seasonality, promotions, and brand policy.
In larger e-commerce organizations that is usually performance marketing, CRM, or the mobile product team - the people who already own campaigns, push, and offer tests. We install the cockpit; they fly, because they know customers, assortment, and the retail calendar.
On our side
On your side
We do not leave you alone
At launch we hand over dashboards, an event dictionary, and short team onboarding so the barrier to use is as low as possible.
What happens after you sign
Right after signing we run a Discovery workshop (DDT) to agree key events and pick an analytics stack - whether we are building from scratch, launching mobile, or modernizing an existing product. It is part of the app project, not a separate IT workstream.
Have an app idea or need technological support? Write to us — we'll prepare a preliminary analysis and estimate within 48h. Projects that go through our DDT process (Discovery, Design & Technology) come with a price guarantee and a fixed-price agreement — a key differentiator for us.