I know many people switch from different backgrounds to Product Management. It is no doubt that Product management has its charm and that you can learn a lot from engineering, design, and branding to analytics. However, it is indeed still very ambiguous how to start.
Shifting from depth-to-breadth
In my case, I had years of working on Fraud and Payment analytics particularly. Hence, I start to learn about products by looking widely into product analytics.
Key metrics are the most simple and straightforward way to check the product's health, to know if you are building an impactful product. This article would benefit anyone who works in the product management space!
Let’s cut the chase, there are the top 3 Product metrics categories I love the most:
This is the most important stage in your product funnel.
If you are not being aware that the product is existing, you would never use the product.
So how to measure this? The fundamental formula is equal to the number of customers who know about your product per total population you advertised or total customers you have. We commonly see it in the campaign reports. However, I personally think it is very important for anyone who builds the product to know this. There is some common metric to use in this case
Active User (DAU, WAU, MAU): Defined as the number of users who use the product in the specific given time
- DAU: Daily Active User
- WAU: Weekly Active User
- MAU: Monthly Active User
Also, in some cases, you can expand the concept of Active users in calendar time or rolling time.
WAU Calendar: Number of Users who uses the product in a specific week from Monday to Sunday
WAU Rolling: Number of Users who use the product within the last 7 days (No matter which current day is this)
It would narrow down the scope of the population who possibly knows about the change in your product. This metric is also used for the marketing campaign to advertise to the top users about the change since they have better engagement with your product.
For example: If you want to release a button in your app. To know how many people are aware of your button existing, they would need to go to the app first. Active user metrics are the direct metric to measure this.
Product adoption, or user adoption, is the moment when users start to use your product or features. At a basic level, adoption can be defined by the percentage of users who take the action on your product or feature for the first time
For example: Follow up with your new button in the app from the previous example, now you would like to know how many users tap into the button the first time.
Some of the key metrics in this category would help:
- Product Funnel Conversion Rate: The ratio in each step is the straightforward way to measure the feature/product adoption. Tips are simple: Understand your funnel and when a user would use CTA (Call to Action)
- Speed of Adoption: Defined as how long the user takes from the moment, they are aware of the product to the moment they act. This metric is very helpful to identify:
(1) The product problem: If your product has a technical challenge that prevents the customer from acting
(2) Product market fit: If the product does not bring benefits or is not helpful to the customer in this market
After the customers used the feature/product, the important and sustainable business lies in how well we can retain customers over time.
There are 2 key metrics in this category:
- Retention: this metric is defined as the percentage of customers from the moment they used the product (adoption) and still use the product over time.
- Churn: One of my favourite metrics. This is a commonly used metric for measuring product engagement. It is defined as a percentage of customers that stopped using the product during a certain period. In most of the companies I worked at, this is a very important metric because we do not want to lose the customer. Churn metric usually raises multiple high concerns about the business.
For example: If you see a company with 80% growth rate from month 1 to month 2, it sounds like an amazing result. But if the churn rate is 90% of the month after, then the question is:
> “Is the company really growing?” The churn is fast as it grows.
There are tons of other metrics we should look into when building a product feature. It is definitely case by case. I hope these top product metric categories would help you approach the problem faster as a reference
I am always up for an open discussion if you have different ways and I love to learn from others too!