• Version 1.0 [2024-05-17]
  • Exact Matching Enhancement: Transitioned the matching logic for Event, Product, Churn, and User Property marketing objectives from regular expressions to exact matching. This refinement ensures precise targeting and accurate identification of relevant data points for analysis.
  • Random Timestamp Offset Implementation: For scenarios where new user properties have not yet been added to the BigQuery export table, the measurement protocol timestamp offset is now randomly set between 5 and 100 microseconds. This adjustment enhances the accuracy of audience refresh processes by preventing potential timestamp conflicts in new pipelines.

• Version 9 [2024-05-09]
  • Decoupled Event Data Processing: Segregated the logic for extracting the latest event table date, visitor IDs, session IDs, and timestamps. This adjustment boosts pipeline transparency and operational clarity. Accompanied by explanatory comments for an in-depth understanding of the functionality.
  • Advanced Timestamp Allocation: Introduced a dynamic calculation for the timestamp_micros field within the measurement protocol payload, leveraging an alphabetical ordering of user properties for offset determination. This enhancement ensures a more precise assignment of event timestamps, vital for the accurate refresh of audience segmentation membership.
  • Performance Insights: Implemented a new job to analyze conversion rates based on user property predictions, segmented into High, Medium, and Low categories. This enhancement provides valuable insights into the model's effectiveness in identifying high-value users.

• Version 8 [2024-05-03]
  • Enhanced GA4 Event Tracking: Incorporated session_id into the GA4 measurement protocol payload, enabling direct association of GA4 events with their session source/medium within the GA4 UI for improved data coherence and user journey analysis.
  • Refined Instant Vertex Pipeline Timing: Adjusted the timing of Instant Vertex pipelines by adding +2 microseconds to timestamp_micros, strategically designed to prevent data collisions with Instant BQML pipelines, thereby enhancing the reliability of audience refresh logic.

• Version 7 [2024-04-01]
  • Streamlined Event Propensity Pipeline: Eliminated the automatic generation of conversion events within the Event Propensity pipeline. This modification is intended to minimize confusion among users not engaged with Value-Based Bidding (VBB). The feature remains accessible and can be activated for tasks related to VBB as required.

• Version 6 [2024-02-29]
  • Introduced GA360 Fresh Daily Export Support: Added support for the GA360 Fresh Daily export option.

• Version 5 [2023-11-21]
  • Refined wildcard query logic to target 'events_20*' prefix, reducing the inclusion of views and enhancing query specificity.
  • Updated all date format specifiers in BigQuery queries from %Y (four-digit year) to %y (two-digit year) to align with the revised wildcard filter logic, ensuring accurate table selection and data querying consistency.
  • Implemented the boosted tree regressor algorithm for BigQuery Machine Learning models. Hyperparameters have been optimized, including setting BOOSTER_TYPE to DART and adjusting SUBSAMPLE to 0.7 for improved generalizability.

• Version 4 [2023-11-07]
  • Remove session_id and engagement_time_msec from GA4 measurement protocol payload.
  • Remove session_id calculations from Calculate Fields query.

• Version 3 [2023-10-24]
  • Updated the Event & Churn propensity training, prediction, and value-based bidding logic to include a regular expression filter. This filter omits events with names ending in '_iBQML' or '_vertex', which are associated with propensity score calculations, ensuring they are not included in the analysis.
  • Set data split method to `AUTO_SPLIT` in BigQuery ML training query hyperparameters.

• Version 2 [2023-08-07]
  • Updated audience boundaries job to define boundaries based on AUDIENCE_SEGMENTS variable, not user counts.

• Version 1 [2023-06-27]
  • Create Version Changelog to manage pipeline upgrades.
  • Remove conversion event creation from non-Event Propensity marketing objectives.