Ensuring data quality with Adobe Analytics Alerting

Data quality is key for companies to generate valid and valuable insights from their data collection and also an important factor to drive user adoption. Maintaining high data quality from any existing tracking implementation demands constant monitoring of your setup and KPIs. This is where alerts come in as a monitoring tool to ensure that everything is running smoothly and to catch any issues early. Together with our client who is in charge of a global tracking setup (incl. different platforms and apps for multiple markets) we implemented and run an alerting system, where alerts are set up in Adobe Analytics, forwarded to Slack, checked daily by a team responsible for documenting the detected issues, determining their respective sources and sharing them with relevant stakeholders.

Digital analytics with daily monitoring

As a first step, we defined the most important tracking points in terms of critical technical functionality as well as business relevance for a global analytics setup across multiple websites and applications. We then set up the alerts function in Adobe Analytics to monitor the respective variables and metrics (find out more about alerts in Adobe Analytics here).

Once the alerts were up and running, we set up an automatic forwarding to a dedicated Slack channel, a function that also works with MS Teams. Slack makes it easy to retrieve an email address for the respective channel, which then can be used as an email address for the Adobe Analytics alerts. This way, all team members retrieve alert notifications in one place, and are able to discuss issues and take actions quickly if necessary. Another advantage of this setup is that alerts don’t get lost in email inboxes.

 The next step was to form a team in charge of checking incoming alerts every day to identify any tracking issues occurring. A team member is named on a weekly rotating basis to check the incoming alerts and mark them with respective signs (e.g. false alarm, further investigation needed, critical alert etc.). In case of critical tracking issues, immediate action is taken to solve the problem as soon as possible. This approach enabled us to ensure that our data collection was running smoothly and KPIs were being tracked accurately. Tracking issues are now detected and solved immediately.

In addition, documentation allows us to see which issues have been detected, when the problem has been solved, which variables, metrics or (virtual) report suites were affected and – in cases that take longer to fix – the period in which data collection was not valid. One way to do this is to use a shared confluence page where all known tracking issues are documented. A further possibility is to implement it directly within Adobe Analytics by means of Annotations.