The Customer: A Multi-Brand E-Commerce Operator
Our client operates five separate e-commerce stores across different product categories - each with its own Shopify or WooCommerce backend, its own Mollie payment gateway configuration, its own sales team, and its own set of performance metrics. The business had grown organically, with each store set up independently. The founder and central management team had no unified view of the group's performance - pulling a cross-store picture required logging into five separate dashboards, exporting data manually, and assembling everything in Excel. It was taking hours every week.
The Problem
Running multiple e-commerce stores without unified analytics is like flying five planes from five different cockpits.
- No Unified Performance View: There was no single place to see total revenue, order volume, conversion rates, or customer acquisition metrics across all stores simultaneously. Every business review meeting began with 30 minutes of data wrangling.
- Payment Data Fragmentation: Mollie was the payment gateway across all stores, but each store had a separate Mollie account. Reconciling payment data against order data was a manual, time-consuming process with regular discrepancies.
- Limited Admin Control: As the business grew, there was no central way to manage user access, store settings, promotions, or configuration across all stores from one place. Changes had to be made separately in each store's backend.
- No Actionable Insights: Raw data existed across the five stores, but there was no system to surface trends, compare performance, identify anomalies, or produce reports automatically. Management was always looking backward, never in real-time.
- Scaling Was Breaking the Model: Adding a sixth or seventh store to this setup would have made the problem dramatically worse. The operational model wasn't scalable.
How We Helped
We built eShop Analytics - a centralized analytics and management portal that aggregates data from all stores and payment gateways into a single, beautifully designed interface.
- Multi-Store Data Aggregation: The platform connects to each e-commerce backend via API and pulls order, inventory, customer, and traffic data on a continuous basis. All data is normalized into a unified schema so metrics are comparable across stores, regardless of the platform they run on.
- Mollie Payment Integration: A dedicated Mollie integration layer pulls payment transaction data for all store accounts, reconciles it with order data, and presents a consolidated view of revenue, refunds, chargebacks, and settlement timelines across the entire group.
- Real-Time Analytics Dashboard: The main dashboard gives management an instant view of the group's performance - total revenue today, this week, this month vs. last month; order volume by store; conversion rates; top-performing products; customer acquisition by channel; and payment method distribution. Drill-down into individual store data is one click away.
- Master Admin Control Panel: A unified admin interface allows a single administrator to manage all stores - user accounts and permissions, store settings, promotional configurations, and operational parameters - without logging into each store's native backend.
- Automated Reporting: Weekly and monthly performance reports are generated and distributed automatically to pre-defined recipients - management, store operators, and investors - in clean, branded PDF format.
- Anomaly Alerts: The system monitors for unusual patterns - sudden drops in conversion rate, payment processing errors, inventory shortfalls - and sends immediate alerts, enabling the team to respond before a problem compounds.
The Results: Five Stores, One Brain
What used to take 30–60 minutes of manual data assembly is now available in real-time, 24/7, from a single screen. Reporting accuracy improved dramatically as human-introduced errors from manual data pulls were eliminated.
The management team described the shift as going from "flying blind" to having a full instrument panel. They were able to identify that one store was significantly underperforming on mobile conversion - something that had been invisible in their previous process - and course-correct within days.
