Are your users truly engaging with your product? How is their engagement trending and how can you convert this information into meaningful insights that inform your product strategy? Dive into this post for a method to go beyond vanity metrics that do little more than look beautiful.
After gaining an understanding of your user base, you will have context into key user segments along with the activities that they perform within your product. These insights guide you to focus on the product metrics that matter most amongst the dizzying array of available metrics. This will certainly bear fruit for evaluating top-line product performance. For deeper insights, however, you will need to shake the tree a bit more through further analysis. Otherwise, potential issues with user engagement could be masked by a spike in user growth and therefore go unnoticed. Let’s walk through a valuable tool you can use to mitigate this risk.
Create Your User Branches
One valuable approach to categorize your product’s users into branches is cohort analysis. To start, choose a type of attribute by which to create user cohorts. For example, choose a user attribute such as product sign-up date or customer segment. Attributes aligned with user behavior, such as those that downloaded a report, are another possible option. In this case, the report download might indicate that a user is actively interacting with the product. Utilize the selected attribute to divide your users into groups.
These cohorts can be created in several different ways depending upon the product analytics tools leveraged by your organization. A few of these tools were nominated at the 2021 Product Awards within the Operate Stage category and the winners can be found in the 2021 Guide to the Best Products for Product Managers. Product analytics solutions such as these are critical for measuring quantitative impact to determine product success. If one has not been implemented yet, then SQL queries pulling from the internal databases that store user event data can also be used.
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Analyze and Identify Trends
Next, consider how you would like to measure the performance of each branch. One best practice is to analyze the percentage of users that continue using your product. Digging into the number of users that logged in will also lead to interesting insights. Then, calculate the chosen performance measure for each cohort over time. Start with monthly time intervals to gain a bird’s-eye view into trends. As patterns emerge, drill down into weekly and daily increments to pinpoint key moments when up or downswings occurred.
Once this data has been compiled, leverage data analysis tools to apply color gradients over the performance measure values. This will help to visually highlight trends within the product’s performance. You can then uncover product intelligence such as which cohorts have the highest drop-off rates and after what time period does this typically occur.
Tell the Story
Engage an open and curious mindset as you investigate trends within the cohort analysis. If a certain cohort is performing better than others, develop hypotheses as to why that might be and explore further. Do exit interviews with your customers provide a glimpse into reasons for leaving your product. Was there a specific event or outage that could have resulted in users detracting? What are the key differences in how better retained users leverage your products vs. those that drop off?
This inquisitive lens will lead to you deeper insights into user engagement and help you hone in on product performance strengths and weaknesses by cohort. Employ cohort analysis with your products today to gain visibility beyond the smokescreen of vanity metrics.
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