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Badge PinWheel Analytics

Centralized Analytics Pipeline for Subscription E-Commerce Growth with Real-Time KPI Dashboards

Project Duration

Ongoing

Client Industry

E-commerce & Retail

Target Markets

North America

Technology Stack

Client Overview

We Understand Our Clients Best to Provide them the Best Solutions

Pinwheel Analytics is a consumer tech company that offers eCommerce products through platforms like Amazon, Stripe, and custom online stores. Focused on subscription-based revenue, Pinwheel needed better visibility into customer behavior, product performance, and churn trends to support growth and retention strategies across regions.

Solutions Delivered

End-to-end Data Engineering

ETL and Data Modeling

Business Intelligence Implementation

Subscription Commerce and Marketing Analytics

Team Composition

Data Engineering Specialists

BI Developers

Marketing Analytics Consultants

ETL & dbt Modelers

Engagement Type

Offshore Hiring

Key Challenges

Key Challenges

Eliminating Data Gaps, Inefficient Reporting, and Weak Customer Understanding

Disconnected

Siloed Data Infrastructure

Payment, sales, and engagement data existed in unconnected, inconsistent systems.

Inefficient Reporting

Manual, Delayed Reporting

KPIs were compiled ad hoc, limiting speed and accuracy of business decisions.

Limited Intelligence

Lack of Funnel Visibility

No ability to measure churn, LTV, or user behavior across cohorts.

Strategic Roadmap

The team architected a scalable analytics pipeline with Amazon Redshift at its core. Fivetran was deployed to ingest raw data from Stripe, Amazon, and e-commerce platforms. dbt was used to transform these disparate datasets into clean, analysis-ready tables. A semantic layer was built on top to standardize KPIs and empower self-serve reporting via Lightdash.

Custom dashboards were developed to address the most critical questions facing the business:

● How’s the churn rate trending by cohort, region, and product line?

● How are attach rates evolving across cellular product bundles?

● Where are drop-offs happening within the user funnel?

● How does mobile app engagement influence repeat purchases?

Each dashboard was designed for business users—simple to navigate, aligned with strategy, and refreshable in near real time.

Execution Approach

Unified Data Modeling and Dashboarding for Scalable, Consistent Insights Delivery

Using modular dbt models, the team stitched together data from all core platforms into a unified data model. This model powered a semantic layer that ensured metric consistency across departments, reducing reporting conflicts and unlocking faster iteration cycles.

Interactive dashboards were launched via Lightdash, tailored to specific teams: churn and cohort views for retention teams, attach rate and sales performance for product teams, and acquisition metrics for marketing. Stakeholders no longer had to wait for ad hoc reports—insights were available on-demand, at their fingertips.

The result was a powerful data ecosystem built for scale, accuracy, and decision velocity.

Execution Diagram
Business Impact

BUSINESS IMPACT

Real-Time Decision Support

Smarter Lifecycle Management

Accelerated Experimentation

Reduced Reporting Overhead

Business Impact Illustration

70%

faster dashboard build time

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98%

team-wide reporting access

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2.6x

improvement in retention

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100%

automation of key KPIs

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