Ecommerce Data Analytics Services

Look for ecommerce-specific proof: experience improving conversion and AOV with analytics-led decisions, the ability to connect storefront data with ERP/CRM/PIM and marketing platforms, and a delivery approach that turns insights into implemented changes.

Yes. If tracking is inconsistent, dashboards only amplify wrong conclusions. We validate event schemas, ecommerce events, consent mode implications, and channel attribution logic so performance reports reflect reality and experiments are measurable.

We define the system of record for each domain (orders, customers, products, inventory, pricing), then design robust pipelines and reconciliations so operational and marketing data match. This avoids the common failure mode where finance, ops, and marketing all report different “truths.”

We introduce data quality checks (validation rules, anomaly detection, reconciliation against source systems) and governance (naming conventions, metric definitions, access control). This creates confidence for leadership and prevents “metric debates” from blocking growth work

Bring clarity on business goals, target KPIs, key customer journeys, and the systems that influence orders (storefront, payments, shipping, ERP/CRM).

We typically start by aligning KPIs and measurement definitions, auditing tracking quality, and producing a prioritized insight-to-action backlog tied to revenue-critical journeys. The goal is to deliver measurable quick wins and a roadmap you can execute, not an abstract “dashboard project.”

Yes. We can build a reliable analytics foundation by centralizing data into a warehouse and connecting it to BI and activation tools, so reporting, segmentation, and personalization are consistent across teams and markets rather than fragmented by platform.

We link insights directly to optimization actions: funnel and cohort analysis identify where users drop, then we convert findings into UX, CRO, performance, and merchandising improvements and measure impact.

We design measurement to respect consent signals and data minimization principles, implement role-based access, and document what is collected and why. This keeps analytics useful while reducing compliance risk and protecting customer trust.