Adoption Metrics for Product Managers

An essay about feature adoption or product adoption metrics. We know they are essential, but how do we go about it?

Metrics are quantitative landmarks that guide you toward your goal. You can only reach your product goals by defining, tracking, and constantly optimising metrics throughout the product lifecycle. Consequently, metrics become one of the most important things for almost all stakeholders, from the product team to the broader stakeholders.

Metrics << Product Goals << Customer Needs + Company Vision

When we define product goals, we keep them simple. So that it is humanly possible for someone to understand even if they do not belong to the team or organisation.

Example — We would like to improve product engagement with this feature. Internal goals can be something like 'by 25%'.

The definition of product engagement is spelt out, or it might be common knowledge in some circumstances. Example — Liking, re-tweets, & comments are engagement parameters of a tweet. Let us say we are talking about increasing the length of tweets, and then our engagement baseline before the implementation of change will be a weighted average of all three.

But, in our product goals, we do not write it as a lawyer would write a contract. Example: (😉)

Our product goal is to increase usage of the comment button by 25% within 12 months. Still, it cannot affect the churn negatively, it cannot affect revenues negatively, it cannot affect time spent on our website negatively, and it cannot lead to the de-growth of any of the following # of likes or re-tweets or comments.

In other words, when we define a product's goals and do not define its drawbacks, it is often assumed that the intended impact is only positive.

Our friend, 'metrics', and its cousin,' counter metrics', will look out for unintended negative consequences on certain system parts.

Practical Challenges:

Product managers are generally in a hurry to deliver product features that work for the customers, look good, and impress the seniors that sometimes, the necessary development needed to track the metrics, analyse them and act on them needs to be included.

In many organisations, the senior product management is interested in something other than product metrics; they are only interested in a few revenue metrics discussed in important meetings. It is only later, many quarters later or years later, the lack of proper tracking of customer feedback, number of adoptions and usage, which leads to customer churn and negative feedback on social media, that senior management realises the issues of baked products with zero analytics. By then, it is too late. Suppose the organisation needs to believe in or understand data-driven decision-making for a singular product manager. In that case, pushing and getting the resources necessary to ensure that all adoption or product metrics are built into the system is tricky.

What can a product manager do when management needs to support investment in adoption metrics?

Way forward:

As a product manager, you need to build an incredible relationship with the engineering team and then use the flexibility that a product manager enjoys in terms of bandwidth, work closely with the engineering team/manager and build a crude analytics model that you can look for data points that will help you take good decisions. This may not be prioritised in a given organisation, but soon enough, you will land up in an organisation where these things matter greatly.

Remember, at the end of the day, you are a leader and lead your product. You have to stand your ground, fight for the space to have the analytics module built into your products and use the data generated by the product analytics to improve your product. This analytics is key to helping you satisfy the customer's needs, and you must always keepng with ideating and implementing finer data points to hone your product.

I have created a list of the top 10 metrics to help you with your case.

1. Product Adoption Rate (New engaged User/Total Signups * 100)
2. Feature Adoption Rate (New active user of that feature/Total Signups * 100)
3. Time to the first essential action (Average time taken for a necessary action to be completed — for Example, OTP verification of email or phone)
4. DAU/MAU — The bread and butter of product managers — daily and monthly active users.
5. Average time spent using your product/feature (This shows how much customers use/like your product and is an important metric to help you improve.)
6. Churn Rate (This tells you why some customers are deserting you. Where are they deserting you regarding the exact place of your customer journey and allowing you to figure out ways to reduce the churn, if not stop it completely? The silver lining is that this constant struggle with the churn rate is the one thing that will enable you to constantly bring improvement to your product, albeit a bit forcefully. But, sometimes, high churn teaches product managers lifelong lessons that make them fantastic. )
7. LTV of Customer (Your ability to earn revenues from your customer through your product, specifically a very sticky product, will make you stand apart from your peers. Understanding the lifetime value your customers provide to your company and leveraging it to increase the lifespan or the value being exchanged by the consumer/customer and the company is a sure-shot way to improve your product.)
8. Cost Per Acquisition (You ought to know how your product is acquiring customers and how your product can fuel organic acquisition. Cost of acquisition per cohort is a powerful tool that can tell you as a leading indicator about the possible growth of your product and also the churn of your product.)
9. Average Revenue Per User (The ARPU is a high-level metric; as a product manager, you need to decide which other metrics or cohorts are driving the ARPU up or down and then direct your energy on improving your ARPU through your product changes.)
10. Cohort Analysis (Segregate your user base by various parameters per your business — For example, high paying or medium paying, geographical distribution or type of acquisition, etc. Now run revenue metrics or usage metrics on these cohorts to figure out which is the most engaged cohort, the most profitable cohort or the opposite.)

Numerous other metrics will tell you the health of your product; many of them are technical or system design metrics, but they are invaluable to you as a product manager.

An example of just 'active users' can be tracking the following:

• Reach
• Activation
• Engagement
• Retention
• A specific action, depending on your company's needs.

Similarly, 'revenue metrics' can be tracked across multiple areas to help you find the most profitable cohort where all your energies should be focussed and the least essential cohort from which you can withdraw your resources.

You will have to track your company and product goals and finally track them through the appropriate metrics.