Data & BI Dashboards for E-commerce & D2C
Platform ROAS, store revenue and bank deposits that never agree.
Business intelligence work consolidates data from ad platforms, CRM, your product and your accounting system into one warehouse, with agreed metric definitions, and presents it as dashboards. For a D2C or e-commerce brand, the work is judged on contribution margin per order, after shipping, returns and ad cost. One revenue definition, net of returns and COD failures, with spend joined against it by channel.
What is costing you money today
Platform ROAS, store revenue and bank deposits that never agree.
Optimising ads to purchase events reported by a browser pixel that ad blockers and iOS have already broken, then scaling on numbers that overstate revenue.
What changes once this is in place
One revenue definition, net of returns and COD failures, with spend joined against it by channel.
How e-commerce & d2c actually buys
Minutes to days for impulse categories, weeks for considered ones — and heavily concentrated into a few sale periods a year.
- The unit of value
- contribution margin per order, after shipping, returns and ad cost
- The common mistake
- Optimising ads to purchase events reported by a browser pixel that ad blockers and iOS have already broken, then scaling on numbers that overstate revenue.
- What we do instead
- Server-side tracking with order value and margin passed through, reconciled weekly against what the payment gateway actually settled.
What it has to talk to
A build for a D2C or e-commerce brand is mostly integration work. These are the systems we expect to exchange data with:
- Shopify / WooCommerce
- Payment gateway
- Logistics & courier APIs
- Meta CAPI & Google Enhanced Conversions
- Klaviyo / WhatsApp
The words your buyers actually use
Generic service copy loses to copy written in the vocabulary of the vertical. These are the terms that carry intent here, and the ones the pages we build are structured around:
- cash on delivery
- free shipping threshold
- return policy
- size guide
- abandoned cart
- average order value
The rules this sits under
India's Legal Metrology rules on displayed pricing and country of origin; consumer protection rules on returns; FTC substantiation for claims in the US; VAT display requirements in the UAE.
What you get
- Metric dictionary — Every metric that matters, defined in a sentence, agreed by the people who use it. The most valuable and least exciting deliverable here.
- Data pipelines — Automated extraction from ad platforms, CRM, store, product and accounting systems, with failure alerting.
- Warehouse — A modelled layer where the joins and transformations live once, so every dashboard reads the same numbers.
- Dashboards — Executive, marketing, sales and operations views, each built around the decisions that audience actually makes.
- Attribution model — Spend joined to leads joined to closed revenue, with the model's limitations stated rather than hidden.
- Automated distribution — Scheduled summaries to email or Slack, so the numbers reach people who will not open a dashboard.
- Alerting — Thresholds on the metrics that matter, so a problem announces itself rather than waiting for the monthly review.
- Documentation and training — How the data flows, what each metric means, and how to add a chart without breaking anything.