Case Study:
Trulia Automates Tag Validation with QA2L Across Complex User Journeys
Industry: Real Estate / Internet
Business Use Case: Automated Data Quality for Marketing Analytics
Technical Use Case: QA2L Journeys, SPAs, CICD
Client: Trulia
Overview
Trulia.com is a home and neighborhood site for buyers and renters to find homes and neighborhoods across the United States through recommendations, local insights, and map overlays that offer details on commute, reported crime, schools, and nearby businesses. The site uses a variety of Marketing Technology vendors for the enablement of advertising, social media, privacy, and analytics capabilities.
The accuracy of MarTech data produced via tags is a critical component of the deployment of these technologies. Inaccurate or broken tagging can lead to misleading data, resulting in poor business decisions and undermining ROI.
Since deploying QA2L, Trulia has been able to achieve close monitoring of advanced tagging implementations across key conversion journeys. The long-lasting effects of improved data quality only add to the immediate time savings.
Highlights
A central component of the QA2L platform enables automated tag validation across complex conversion journeys. In the case of Trulia, one of the crucial site flows involves dynamically selecting new property listings and advanced form completions.
The final step of the journey triggers dozens of tags used by a variety of advertising, audience management, and attribution platforms.
The automated QA2L journeys run on a schedule, while the QA2L API enables Trulia to run user journeys as part of a CICD pipeline. If any discrepancies are detected, timely alerts are sent to the tag management and development teams ensuring that any tag deficiencies are flagged immediately and preventing extended data loss.
The QA2L API enables Trulia to run automated data validation tests as part of a mature CICD pipeline.
Challenge
Frequent manual validation of impactful journeys with this degree of complexity is resource-intensive and often impractical.
Even if performed just once a day, basic calculations show that it would require 20 man hours per day for the manual validation of just one such journey. Manual validation will also by definition be vulnerable to inconsistencies and human error.
The nuances of having several different variants, along with the added requirement of inspecting dozens of network requests, make the prospect of manual validation even more time-consuming and error-prone.
Solution
With QA2L Flow (a point-and-click interface for recording user journeys) the team at Trulia built a set of scheduled tasks, enabling the fully-automated validation of data firing on key journey steps, ensuring reliable data collection and improved data quality.
The tasks are capable of auto-sensing variants, ensuring that alerts are sent only when meaningful tagging changes are detected. Targeted alerts are sent to the team in charge of managing these tagging implementations.
[QA2L] is going above and beyond a typical vendor's responsibilities!
Sr. Data Analytics Manager
Talk to one of our data quality experts today to find out how QA2L can help automate tagging validation across your key conversion journeys.
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