Know your real numbers, then know what to do next
Store Intelligence computes accurate revenue, profit, and inventory metrics from your store's raw order data — with the exact definitions documented — then layers on forecasting, reorder points, and risk alerts. It is in active development; we're building accuracy in from the first line of code.
The problem
Most analytics dashboards are easy to build and hard to trust. Numbers disagree with Shopify's own reports, refunds land on the wrong day, and profit is a guess.
- Metrics drift between pages because each screen computes them differently.
- Line-item joins silently inflate revenue; refunds aren't attributed to the day they were issued.
- Without reliable COGS, margin and ROI are approximations at best.
How Fitly helps
Store Intelligence treats accuracy as a hard requirement. Every metric has one canonical definition, computed the same way everywhere.
- All deterministic metrics are computed at request time from raw synced tables — one definition, one implementation.
- Refunds are attributed by issue date and revenue is refund-adjusted, matching Shopify's own analytics.
- Numbers are checked against a golden dataset and reconciled with Shopify Admin analytics before release.
Features
Key features
Everything Store Intelligence does, in one focused feature set.
Revenue & profit
Gross and net revenue, AOV, discounts, tax, shipping, COGS, and gross profit — computed by the shop's own timezone, with cost completeness surfaced honestly.
Product performance
Units sold, refund-adjusted revenue and margin, sales velocity, inventory value, turnover days, ROI, and reorder points that don't understate new products.
Customer insights
RFM segments, lifetime value, new-vs-returning, and a transparent recency/frequency churn-risk formula — labelled as a formula, not a black box.
Bundle intelligence
Co-purchase support, confidence, and lift to find which products sell together — with data guards so small samples don't mislead.
Sales forecasting
Per-product forecasts selected by backtest, with empirical confidence bands and accuracy gates that suppress a forecast when there isn't enough history to trust it.
Risk & alerts
Lifecycle stage, dead-stock probability, and stateful alerts for margin, discount, and inventory risk — each recommendation cites the exact inputs behind it.
A closer look
Inside the app
A preview of Store Intelligence's interface.
Interface previews from an in-development build; final UI may change.
How it works
Set up in three steps
From install to insight — no heavy lifting required.
Install & connect
Add the app to your store and grant read access. Store Intelligence syncs your orders, products, inventory, and customers into its own tables.
We compute, accurately
Metrics are calculated from that raw data on demand, using documented definitions and verified against Shopify's own analytics.
Explore & act
Read your dashboards, forecasts, and alerts — and use the simulators to test capital, bundle, and pricing decisions before you make them.
Who it's for
Made for the right stores
Where Store Intelligence makes the biggest difference.
Growing DTC brands
Stores past the early stage that need profit clarity, not just top-line revenue.
Inventory-heavy stores
Merchants who live or die by turnover, reorder timing, and dead stock.
Multi-product catalogues
Stores with enough SKUs that per-product velocity and bundle insights actually move the needle.
Data-serious operators
Owners who want numbers that reconcile with Shopify — and definitions they can audit.
A good fit for
Trust & compliance
Built to be dependable
The operational details that matter once it's running on your store.
Accuracy as a requirement
Every metric has one canonical definition, implemented once and asserted by a golden-dataset test suite.
Reconciled with Shopify
Numbers are compared against Shopify Admin analytics for the same periods before any release.
Read-only analytics
The analytics API only reads your data — it never modifies your store.
Honest about limits
Where a number has a caveat (e.g. current vs historical unit cost), the app says so instead of hiding it.
FAQ
Common questions
Not yet — it's in active development. The data model and accuracy definitions are in place and the analytics engine is being built. Get in touch if you'd like early access or to follow its progress.
Store Intelligence is on the way
We're building Store Intelligence now, with accuracy as the hard requirement. Get in touch for early access or to follow along.