Nature’s Energy

Client Background

The client operates within the healthcare and beauty & wellness sectors. They sell products through a Shopify website and offer appointment bookings via the Zenoti platform, available on the App Store.

Challenges

  1. Identifying Top-Selling Products: Understanding which products generate the most revenue.
  2. Revenue Contribution from Services: Determining which services are the primary revenue drivers.
  3. Repeat Rate Analysis: Assessing how frequently customers return for repeat purchases or services.
  4. Retention Rate Metrics: Measuring how well the client retains their customers over time.
  5. Service Preferences for Repeat Customers: Identifying which services are most popular among repeat customers.
  6. Demographic Insights: Analyzing age groups and gender demographics of visitors to the centers.

Before addressing these questions, a significant challenge was data collection. Accurate data tracking was crucial for effective marketing across multiple platforms, including GA4, Meta, TikTok, and Google Ads.

Strategy

An audit of the website and App Store revealed several issues:

  • Data Accuracy Issues: Duplicate data was being tracked in GA4, and no data was being collected for the Shopify website.
  • Improper Configuration: Purchase data points were not aligned with GA4 best practices, resulting in multiple events being recorded for the same action.

To address these issues, a comprehensive tracking plan was developed to monitor various events, including purchases, service bookings, and gift card purchases. It was determined that:

  • Purchase, Gift Card, and Booking Events: These were tracked both as individual events and as a combined purchase event in GA4. This approach was essential for accurate cohort analysis and calculating repeat and retention rates, as GA4 primarily tracks revenue through purchase events.
  • Separate Event Tracking: This enabled more detailed analysis, such as path analysis, which could not be performed with event parameters alone.

Transformation

Data transformation was implemented to standardize the data collection process:

  • JavaScript Functions: Given the limitations in modifying the data layer structure for the App Store, JavaScript functions like map were used to adapt the data layer. This approach facilitated the addition of necessary event parameters without the need for custom dimensions.

Outcome

Following the implementation of Google Tag Manager (GTM) and several months of data collection, the client was able to address key business questions effectively. The data was consolidated and visualized in a dashboard (note: specific metrics have been redacted to comply with NDA agreements).

The refined data tracking and transformation allowed for accurate insights into top-selling services and other critical metrics, enabling the client to make informed decisions and optimize their marketing strategies.