Case Study

Optimizing User Journey Measurement by Refining's Marketing Data is a visual software development platform. It enables both developers and non-developers to build dynamic content and seamlessly integrate with any backend, API, or platform.


Simplified event structures to boost conversions, retention, and business outcomes.

the challenge

Builder’s data analytics in Amplitude were unstructured, and events and properties were not properly organized. This led to several tracking issues such as redundant data, confusing event names, and key events not being tracked.

Reporting was not being done at the organization level. This meant that segmentation couldn’t be performed at the organization level and many group-level interactions were not being tracked.

Multiple teams were interpreting customer behavior using their own definitions of events and properties, leading to a non-standardized understanding of the user journey.

the solution

We realized that Builder’s marketing data needed a refresh. Here are five structural changes we brought to the data:
  1. Naming conventions: We standardized naming conventions for all collected events, adding clear and intuitive names and descriptions for all tracked data.
  2. Improved data granularity:We went over Builder’s data needs and made sure the structure showed the data granularity they needed.
  3. Flagged key events:We identified events that made up critical paths and added key data points to the user journey in Amplitude.
  4. Intuitive event names: Our team grouped events by organization and space level and also made event names more concise by introducing categories and properties.
  5. No duplicates: We removed duplicate events and properties to reduce data redundancy.

Next, we went in and checked if events were being triggered correctly and properties were stored as defined. For this, we created separate development and production projects to reduce test and erroneous data.

the result

At the end of this data restructuring, Builder’s team got access to a comprehensive and up-to-date tracking plan. This was strengthened by standardized naming conventions and company-wide taxonomy to help ensure that the incoming data is standardized and aligned with the company’s goals. We made sure Builder could count on this data by setting up automatic build-time QA and run-time validation. 

400+ eCommerce and SaaS brands are making better, data-driven actions thanks to MarketLytics
400+ eCommerce and SaaS brands are making better, data-driven actions thanks to MarketLytics