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Minimum Viable Analytics for the Bottom Line

What is the least amount of data you require in order to make confident decisions right now? This amount might be called your “minimum viable analytics” (MVA), a concept that consultant Andy Carvell introduces in a post at Mobile Stack Growth. He describes what it will take to home in on the leanest analytics for a variety of different situations.

Min-Maxing

Initially, the main reason to seek out lean analytics is just to save yourself from all the risks that usually come with analytics: measuring the wrong things, trying to measure too much, not keeping current data, etc. However, MVA comes with risks of its own, and they are borrowed from the similar minimum viable product (MVP) principle. Namely, many MVPs in business are actually too minimal and end up not actually being viable. One reason is that MVPs invite all manner of sloppiness from the undedicated. Another reason is that people may fixate too much on keeping it small and lose sight of practicality. Both scenarios must be avoided when crafting MVA.

Carvell finds that there are roughly four core use cases for MVA:

  • Dashboards for executives
  • Marketing analytics for marketing
  • Investigative analytics for product teams/growth teams
  • Operational analytics for DevOps product managers

He writes at length about each of these cases, so you can peruse his article for the layer that applies to your situation. But for a snapshot, here is how he describes operational analytics:

If your product is not functioning, nothing else particularly matters except fixing it. The complexity of modern mobile products leaves ample room for server downtime, outages or API failures from critical 3rd party services, client-side crashes, DDOS attacks and other such drama.

Tracking some basic stuff like server availability, API response times, app crashes, etc. as well as setting up alerts, so that the people responsible for fixing these things get notified immediately when outages occur, may literally save the business, or at least mitigate the fallout considerably.

For additional insights, you can view the original post here: https://mobilegrowthstack.com/mobile-app-analytics-519f5719e283

About John Friscia

John Friscia is the Editor of Computer Aid's Accelerating IT Success. He began working for Computer Aid, Inc. in 2013 and continues to provide graphic design support for AITS. He graduated summa cum laude from Shippensburg University with a B.A. in English.

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