If you can’t measure it you can’t improve it
Metrics are the representation of user behavior and product success. Metrics values obtained by aggregation: addition, division, fraction, subtraction, multiplication, logarithm, etc. There are continuous metrics with values from minus infinity to plus infinity, or nominative, for example, 0 or 1, yes or no.
There is no one set of metrics fits any project. Of course, there are some big metrics you can meet almost at any product, but every product is unique. Behind every big indicator always is a set of micro metrics. Think about this as a metric hierarchy. Product metrics should be formed based on individual product characteristics and its business model. We call this process metrics mapping.
We can’t describe user behavior by this type of metric, but these metrics indicate product performance.
Some examples of growth metrics
- MAU — monthly active users
- DAU — daily active users
- Profit — how much does the product makes during the reporting period versus with the previous reporting periods
- User actions — numbers and ratios of sign-ups, purchases, services usage, etc.
Are metrics that indicate how users interacted with our product and based on this data, we can gather insights on whether the users interact effectively with the product or not.
Examples of behavioral metrics
- Task completion error ratio
- % of users who left a particular funnel step
- The time required to complete a specific scenario
- Relationships between actions and time
- CTR — interactions with the particular product elements
How to form relevant product metrics
Interviews with stakeholders
Stakeholders are aware of the strategic and business goals. The interview helps to understand the business and build a proper economic model as well as form growth metrics hierarchy.
Interviews with team
Customer success, support and dev teams are user-focused and can tell a lot about customer pains and gains. Also, the metrics and its structure must be clear, complete and useful for the whole team so that the team can use the metrics as a reference point.
The result of the interview should be a non-prioritized table with metrics that are relevant to different business units.
Though, not all metrics are equally important. Metrics should be prioritized and structured. Prioritized metrics help to understand how successful was an A/B testing or a new feature release. Also, metrics prioritization helps to focus on the most important things for the product and business. We will uncover more details on metric prioritization in the next article. Stay tuned.
Originally published at awsmd.com.