How PMs can measure the success of their Product — Improving Product journey
Every interaction of users with your product is a unique journey. The aim of the user is to accomplish their goal. It leads to a few questions :
- Are users able to achieve their goals?
- Are they dropping out without achieving their goal?
- Are they confused and ended up following an inefficacious path?
As a result, PMs must dedicate time to defining trackable events, making them part of the product backlog, & carefully analyzing the trends depicted by the data.
The product manager should analyze the below areas :
- Bounce Rate 👥— The bounce rate is a single-page session. Often it indicates the user did not find what they came looking for and left after scanning only one page or screen. A high bounce rate for your product suggests the product manager needs to work on improving the first-time experience and communication. Also, they should experiment with multiple landing pages and personalization algorithms to make different traffic sources more relevant and make an attempt to cater to the unique requirements of that user. Bounce rate should be analyzed with a caveat — if the product offers core value in a single pageview then this metric can be skipped.
- Dissect journey🎋— Product journeys are seldom straight. Multiple options on a screen/page logically showcase different paths a user can take, which branch out to achieve different goals and link back to previous pages. Excessive options amplify cognitive load & eventually confuse the user in achieving their goal.
- Trend Analysis 📊— Heat maps are useful tools to analyze clicks, mobile gestures, and scrolling behavior. Tools such as hotjar, UserZoom, etc can even analyze what users are scanning, reading, or hovering over. We might assume that the screen/page is clearly laid out with visible CTA for the user and still user is taking time to figure out the next logical action ( Maybe they are searching for the help section or wanna go back to edit previous details )
- Error handling🚫 — PMs are championing in analyzing happy flows but the maturing lies in tracking & determining frequently observed error conditions which are stumbling blocks for the users. Those errors might be an outcome of the poor screen design / incomplete or unclear messaging. Approach such situations with a hypothesis that the user is always true and then you will be able to work towards improving their experience through your product offerings and get rid of all the possible errors.
- Engagement time ⌛— It depends on the product. If an e-commerce app has a high engagement time then it might imply that the user is not able to make the decision and thus not able to place the order. In such a case time spent on the app should be less and the conversion rate should be higher. However, in the case of gaming apps, time spent on the app is a key metric to measure engagement over a long period of time.
- Step enhancement🪜 — PMs should aim to increase or decrease the number of discrete steps critical to accomplish a task. Each step is an opportunity for the user to drop out — to ditch your product before task completion, maybe be because of feeling overwhelmed, confusion, impatience, or regret that they aren’t able to generate expected value out of the product. Your P0 should be to eliminate or enhance the steps with a high drop-off ratio. P1 will encompass focusing on the remaining steps, displaying feedback throughout the journey so that the user can observe proximity towards task completion.
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