Our work / Case study

Online Shopify Sales & Marketing Analytics

We built nightly sales and marketing reporting for a Shopify merchant—giving clear ROI tracking and faster growth decisions.

E-commerce · Retail

Shopify sales data analysis

Clear ROAS visibility

Nightly sales scorecards

Faster growth decisions

Reported outcomes from this engagement; not projected results for a new pilot.
Channel profitabilityExample

Revenue after advertising and fees

ChannelSalesMargin
Search$18.4k28%
Social$12.6k19%
Email$9.8k36%

Review spend alongside earned margin

Concept illustration with sample data.

Results

After go-live, the merchant delivered:

  • Clearer ROI tracking with nightly reports leadership actually used.
  • Faster growth decisions because channel and product performance stopped living in silos.
  • Higher conversion focus from fixing the highest-impact funnel leaks.
  • Smarter ad allocation toward campaigns that earned, not just spent.
  • Stronger retention targeting for high-value customer segments.

The Challenge

A Shopify merchant was scaling spend without a trustworthy view of what actually drove profit. They faced:

  • Unclear Marketing Effectiveness: Hard to attribute sales to channels and campaigns with confidence.
  • Conversion Leakage: Drop-offs in the funnel were visible too late—or not at all.
  • Cart Abandonment: Checkout friction cost sales without a clear diagnosis.
  • Retention Blind Spots: Lifetime value and repeat behavior weren't guiding spend.
  • Scattered Data: Shopify, analytics, and ad platforms never reconciled into one daily picture.
  • Product Mix Uncertainty: Revenue leaders weren't always the profit leaders.

What We Built

We delivered a unified sales and marketing analytics system:

  1. Multi-Source Integration: Automated pulls from Shopify, Google Analytics, and major ad platforms.
  2. Centralized Warehouse: Modeled conversion, AOV, CAC, LTV, and channel ROI in Microsoft Fabric.
  3. Sales & Marketing Dashboards: Built Power BI views for funnel health, campaign performance, segments, and product profitability.
  4. Funnel Diagnostics: Surfaced drop-off points so the team fixed the highest-friction steps first.
  5. Customer Segmentation: Implemented RFM-style segments and LTV views for retention campaigns.
  6. Attribution Visibility: Compared first-touch, last-touch, and multi-touch views so budget decisions got sharper.

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