True profit per order
Revenue minus product cost, ad spend, shipping, COD fees, discounts and returns, by product, channel and campaign.
Data Analytics · E-commerce
Ecommerce Data Analytics & Retail Demand Forecasting
Bring store, marketplace, ad, courier and POS data into one place, then forecast demand, find your best customers and see true profit per order before the month closes.
Overview
Ecommerce data analytics that shows profit, not just revenue
Your store dashboard tells you revenue. It doesn't tell you what you kept after ad spend, courier charges, COD returns, discounts and refunds. That data lives in Shopify or Salla, Meta and Google Ads, the courier's portal, Google Analytics 4 and an ERP or POS, and pulling it together takes a week of spreadsheets at month end. Ecommerce data analytics joins it into one model, so you can see profit by product, channel, city and campaign while there's still time to act.
On top of clean data we add forecasting. Retail demand forecasting uses your sales history, seasonality and promotions to predict how much of each SKU you'll need for Ramadan, Eid, White Friday, 11.11 or Black Friday, and where to place it if you also run physical branches. AI sales forecasting gives finance a monthly outlook that updates as orders arrive. Customer analytics for ecommerce groups shoppers by value, frequency and return behaviour, so you know who to win back and which cities or couriers drive refused COD orders.
Retail BI dashboards are delivered in Power BI, Looker Studio or a custom admin panel, built for the people who use them: founders, buyers, marketers and operations. We have built analytics panels before, including the admin analytics panel behind AA JoyLand's WhatsApp support and lead-qualification chatbot. Customer data is handled with role-based access, encryption and hosting in your chosen region, designed to support GDPR, the UAE PDPL and Saudi Arabia's PDPL.
Use cases
AI Data Analytics use cases in E-commerce
Retail demand forecasting
SKU-level forecasts by week and channel, adjusted for Ramadan, Eid and sale events, to guide buying and replenishment.
AI sales forecasting
Rolling revenue and order forecasts for finance and investors, with ranges instead of a single guess.
Customer analytics for ecommerce
Cohorts, repeat rates, lifetime value and churn risk, with segments you can send straight to Klaviyo or WhatsApp campaigns.
COD and courier performance
Refusal and return rates by city, courier and product, so you can change payment rules or switch couriers where it pays.
Store and channel comparison
Online, marketplace and branch sales side by side, with stock positions to spot transfers before items go out of season.
How it works
How it works
- 01Connect your sourcesPipelines pull data from your store, marketplaces, ad platforms, GA4, couriers, POS and ERP.
- 02Clean and matchOrders, customers and SKUs are de-duplicated and matched across systems so numbers agree.
- 03Build dashboardsRole-based dashboards for leadership, buying, marketing and operations.
- 04Add forecastsMachine-learning models predict demand, sales and churn on top of the clean history.
- 05Push insights outAlerts and scheduled reports reach the right person by email, Slack or WhatsApp.
Capabilities
Key features
Unified commerce data model
One source of truth for orders, customers, products, spend and shipping.
Role-based retail BI dashboards
Each team sees the metrics it owns, with drill-down from total to single order.
Forecasting models
Demand, sales and stock-out forecasts that account for seasonality and promotions.
Natural-language questions
Ask "which products lost money in Lahore last month?" and get a chart back.
Customer privacy controls
Masked personal data, row-level security and audit logs for every query.
Automated alerts
Low-stock warnings, unusual refusal rates and ad spend spikes sent as they happen.
Integrations
Works with your E-commerce stack
- Shopify
- WooCommerce
- Salla
- Google Analytics 4
- Meta Ads
- Google Ads
- Klaviyo
- Odoo
- SAP Business One
- Power BI
- BigQuery
- Looker Studio
Using something else? If it has an API, a database or a webhook, we can connect to it.
Outcomes
Benefits for E-commerce teams
Buy the right stock
Forecasts reduce both stock-outs on bestsellers and dead stock after the season ends.
Spend ad budget on what profits
See which campaigns bring profitable orders, not just revenue that comes back as returns.
Fewer refused deliveries
Courier and city analysis shows where to require prepayment or change delivery partners.
One set of numbers
Founders, finance and marketing stop arguing over whose spreadsheet is right.
Our work
Related Work
FAQ
AI Data Analytics for E-commerce: FAQs
What is ecommerce data analytics?
It's the practice of combining store, marketing, shipping and customer data to understand what is profitable and predict what happens next. Typical uses are profit reporting, demand forecasting, customer segmentation and ad spend analysis.
How accurate is AI demand forecasting for retail?
It depends on how much history you have and how stable demand is. We test each model against past seasons before you rely on it, and show a likely range for each SKU rather than a single number.
Can you combine Shopify, Meta Ads and courier data?
Yes. We build pipelines from your store, ad accounts, GA4 and courier reports into one warehouse and match them at order level, so you see real profit per order.
How much data do we need to forecast demand?
Ideally more than a year, so the model sees each season at least once. With less history we combine your data with product-level patterns and widen the forecast range accordingly.
Can we keep using Power BI or Looker Studio?
Yes. We deliver dashboards into the BI tool your team already opens every day, or build a custom panel if you need something tailored to your store.
Is customer data safe in an analytics setup?
Yes. Personal details are masked where they aren't needed, access is limited by role, every query is logged and data stays in your chosen cloud region.
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Stop guessing how much to buy for peak season.
Tell us the three numbers you wish you had every Monday. We'll show you the dashboard and forecast that delivers them.