Problem Definition

Merchants using our SaaS ERP & E-commerce platform lack a unified and actionable view of their customers’ behavior. Current reporting is limited to basic order-level data, which prevents merchants from:

• Identifying top customers by revenue or activity.
• Monitoring customer acquisition and churn trends.
• Understanding shopping behavior, including product views, add-to-cart events, checkout drop-offs, and cart abandonment.

Without these insights, merchants must rely on external analytics tools or manual data exports, resulting in slower decision-making, less effective promotions, and lost opportunities to improve customer retention and conversion.

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Assumptions

• There is no existing customer Dashboard in the platform today; only fragmented or basic reports are available.
• Customer-level behavioral data (e.g., product views, cart actions, checkout attempts) is either not logged or not easily accessible.
• Merchants have expressed demand for actionable insights that can directly impact revenue and retention, but the scope and priority of their needs must be validated through research.
• Introducing this feature will require event-level instrumentation across the e-commerce journey to power accurate and reliable dashboards.
• Our internal team is getting multiple requests/tickets for extracting this data from the merchants. </aside>

Research & Validation Approach

Before designing the solution, we must validate technical feasibility and merchant demand through three key tracks:

1. Technical Assessment

• Audit current event tracking and confirm key events (product_view, add_to_cart, checkout_start, purchase) are logged.
• Validate data accuracy, latency, and storage design to support real-time or near real-time insights.
• Identify gaps (SDK updates, backend instrumentation, identity resolution).
• Assess infrastructure impact, runtime dependencies, and potential pricing implications (e.g., query costs, compute load).
• Establish monitoring & alerts for data pipelines/APIs to flag downtime, delays, or heavy resource usage.
• Define performance thresholds, caching strategies, and scalability requirements.
• Validation checkpoint: confirm if existing pipelines can support only a dashboard UI, only connectors (to push data out), or both simultaneously.

2. Competitive Analysis

• Benchmark leading platforms (Shopify, BigCommerce, WooCommerce) on:
  • Depth of insights (funnels, LTV, segmentation).
  • Processing type (real-time vs batch).
  • Pricing models (included, premium, or add-on).
  • Usability (drilldowns, exports, integrations).
  • Positioning (core differentiator vs upsell).
• Validation checkpoint: assess how competitors balance dashboards vs. data connectors, and where differentiation opportunities exist.