CASE STUDY
How D2C Beauty Brand Improved Retention by 15% with Unified Analytics Dashboard
AT A GLANCE
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Client: Shopify D2C Beauty Brand
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Industry: E-commerce (Beauty & Lifestyle)
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Location: Global Operations
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Solution: Customer Retention & Revenue Analytics
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Key Impact: 14% retention improvement, 40% faster reporting, optimized discount strategy
Background
This fast-growing direct-to-consumer beauty brand operates on Shopify, serving customers globally with premium skincare and lifestyle products. The company had invested in WebEngage for customer engagement and marketing automation, generating substantial data about customer behavior and campaign performance.
As the brand scaled rapidly, leadership recognized that fragmented analytics across multiple platforms was constraining growth opportunities and preventing data-driven decision making about customer retention and revenue optimization.
The Challenge
The e-commerce brand faced critical visibility gaps that prevented optimization of their retention strategy and revenue growth. Leadership lacked a unified view to answer fundamental business questions about performance trends. They couldn't effectively track how revenue, orders, and average order value were trending over time, nor could they identify which products, coupons, and marketing channels were truly driving sales and repeat customers.
The value distinction between new and repeat customers remained unclear, with no visibility into purchase intervals or customer lifetime value development. Without cohort-based retention analysis by acquisition month, source channel, or geography, the company couldn't identify which customer segments were most valuable or at risk of churn.
Existing reports were scattered across Shopify, WebEngage, and various marketing platforms, creating a fragmented view of business performance. This disconnected approach led to delayed insights and reactive decision-making, with teams often working from conflicting data sources. The manual compilation of reports consumed significant resources while still failing to provide actionable intelligence for retention improvement.
The Solution
GrowthBI built a comprehensive Power BI dashboard powered by an automated Fivetran to BigQuery to Power BI pipeline, integrating Shopify order data with WebEngage engagement metrics. The solution created a unified data model in BigQuery, optimized for cohort analysis and retention tracking.
The automated data pipeline used Fivetran to extract Shopify orders and WebEngage campaign data into BigQuery, ensuring real-time data availability. The centralized schema unified orders, customers, and coupon data, enabling sophisticated retention and value analysis.
Key capabilities included:
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Performance KPIs Dashboard: Real-time tracking of revenue, AOV, orders, new versus repeat customers, and discounted order share
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Product & Coupon Analytics: Identification of top 10 revenue-driving products and ROI analysis of coupon codes
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Customer Value Cohorts: CV tracking over 1, 30, 60, 90, and 180-day periods segmented by channel and discount code usage
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Retention & Repeat Analysis: Detailed interval analysis between 1st, 2nd, 3rd, and 4th orders with repeat purchase percentages
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Channel Benchmarking: Comparison of marketing channels including CashKaro, Instagram, Google, and SEO across AOV, retention, and 90-day customer value metrics
Results
The unified e-commerce dashboard transformed the brand's ability to understand and improve customer retention. The analysis revealed low repeat purchase rates, leading to immediate implementation of targeted re-engagement campaigns that drove measurable improvement in customer retention.
Discount optimization based on clear ROI visibility enabled the company to eliminate underperforming promotional schemes while doubling investment in top-performing coupon codes. Product performance insights enabled strategic inventory allocation, with concentrated investment in top-selling items reducing stockouts while minimizing slow-moving inventory.
Key performance outcomes included:
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15% improvement in customer retention through targeted campaigns
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Reporting cycles cut to half with automated data refresh
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Optimized discount strategy with clear coupon ROI visibility
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Improved inventory planning based on product performance insights
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Enhanced channel allocation through acquisition source benchmarking
The dashboard revealed critical insights about customer behavior patterns, including average intervals between purchases and lifetime value development by acquisition channel, enabling more sophisticated marketing strategies.
Looking Forward
The brand continues to enhance their analytics capabilities with plans to integrate predictive modeling for customer churn and lifetime value forecasting. The company is developing automated marketing triggers based on behavioral patterns identified through the dashboard.
The success of this implementation has positioned the brand as a data-driven leader in D2C e-commerce, with plans to expand analytics into product recommendation engines and personalized pricing strategies.
Want to see the technical details behind this implementation? Read our technical deep-dive to learn how we integrated Shopify and WebEngage data using Fivetran, BigQuery, and Power BI.