Two great posts on DAU/MAU and Measuring Power Users


Two great posts from Andrew Chen. Links below:

These posts were perfectly timed for me as we started thinking about Annual Planning for Alexa Voice Shopping org (Amazon) this week. As a part of my research of which metrics to use to measure things that our business cares most about and then setting the right benchmarks/goals for the org, the posts below were super helpful. So if you are in tech and if you care about 1) measuring frequency of usage 2) measuring the most engaged cohort then you should take some time to read these posts.

Power user curve 

DAU/MAU is an important metric to measure engagement, but here’s where it fails


Five actions that you can take if you measure your analytics/business-intelligence solution usage:



In this post, I am going to share five actions that you can take you if measure your analytics/business-intelligence solution usage:

Five actions!

I’ll highly encourage business stakeholders & IT managers to consider measuring the usage of their analytics/business-intelligence solutions. From a technical standpoint, it shouldn’t be a difficult problem since most of the analytics & business intelligence tools will give you user activity logs. So, what’s the benefit of measuring usage? Well, in short, it’s like “eating at your restaurant” – if you’re trying to spread culture of data driven decision-making in your organization, you need to lead by example! And one way you can achieve that is by building a tiny Business Intelligence solution that measures user activity on top of your analytics/business-intelligence solution. if you decide to build that then here are five actions that you can take based on your usage activity:

Let’s broadly classify them in two main categories: Pro-active & Reactive actions.

A. Pro-active actions:

1. Identify “Top” users and get qualitative feedback from them. Understand why they find it valuable & find a way to spread their story to others in the organization

2. Reach out to users who were once active users but lately haven’t logged into the system. Figure out why they stopped using the system.

3. Reach out to inactive users who have never used the system. it’s easy to find inactive users by comparing your user-list with the usage activity logs. Once you have done that, Figure out the root-cause – a. Lack of Training/Documentation b. unfriendly/hard-to-use system c. difficult to navigate; And once you have identified the root-cause, fix it!

B. Reactive actions:

4. If the usage trend if going down then alert your business stakeholders about it and find the root-cause to fix it?

Possible root causes:

– IT System Failure? Fix: make sure that problem in the system never happens again!

– Lack of documentation/Training? Fix: Increase # of training session & documentation

downward trend line chart

5. It’s a great way to prove ROI of an analytics/business-intelligence solution and it can help you secure sponsorship for your future projects!


In this post, you saw five actions that you can take if you measure your usage activity of your analytics/business-intelligene solution.

I hope this was helpful! I had mentioned user training in this article and so if you want to learn a little bit more about it, here are a couple of my posts: