We've learned that companies go through these analytics maturity levels on their product journey:
Analytics debt becomes a pain when you start feeling that product market fit and your team starts scaling. When your product is available to users across platforms, and the tracking isn’t consistent across all of them. When more product managers join, that “any data is better than no data” starts becoming a blocker. People will make wrong decisions based on misleading data. Onboarding new developers becomes difficult. That “let’s just add this quick line of code to track this user action” is very easy to refactor out. Existing tracking breaks in every feature release, and it’s difficult for new developers know where to start when adding analytics for feature releases.
Analytics Debt is when you have incomplete, inconsistent, and bad data, and the only way to make data-driven decisions is to add more bad tracking because fixing what you have feels impossible.
At Avo, we’re here to help. Introducing the Avo Inspector.
The Avo Inspector helps you:
Inspect your current state of tracking:
Install the Inspector SDK for all your platforms, to start logging event names, shapes, types, volumes, etc. and get all current tracking in a single source of truth.
Analyze tracking issues:
The Inspector dashboard will summarize your current state of tracking and highlight current issues such as volume discrepancies between platforms and missing properties.
Prioritize what to fix:
You know your tracking is a mess, but where to start fixing it? Use the Inspector dashboard Filters to share direct issue links to colleagues. Make your tracking issues are something you can reason about.
Fix important tracking:
Define what events should look like. Build your tracking plan in using the Avo Event Library and Property Libraries to prevent inconsistencies that happen when data is designed manually in a spreadsheet
Future proof your analytics:
Avo is the state of the art for planning and implementing analytics, so you can ship faster without compromising data quality.
Collaboration: A GitHub-like branched workflow for Product, Engineering and Data to work together on multiple features at the same time.
Reliability: Type safe analytics code to implement faster without compromising data quality.
Transparency: Single source of truth tracking plan to empower the team to always know which events they can use to answer their questions.
Relevance: Unblock everyone to suggest data according to team guidelines.
The Avo Inspector helps Product teams understand their current state of tracking so they can make good decisions, Engineering teams ship faster without compromising data quality, and Analytics teams support their product teams in maintaining clean data.
So you can get back to making data-driven decisions.