The Importance of Data-Managed Product Managers
If you have no experience in Data Science, Data management as a product manager can seem like a daunting task. However, this is what you need to pay attention to. And that’s why:
- The data allows you to get important feedback from users about your product;
- Data helps you develop the right products and solve problems faster;
- Data is a powerful communication tool between teams and stakeholders.
The good news is that while being guided by data is crucial, it’s not as difficult as it sounds. Today we’ll talk about the basic metrics that great Product Managers use to create even greater products.
Metrics that are important to a Product Manager
Not a single metric in itself can give you all the necessary information, there are a lot of them, and you need to follow them all. What metrics you follow depends on your business strategy, the industry in which you work, and on what stage of growth you are at. Sometimes metrics will be determined for you, because it is imperative that the KPIs and OKRs of your product meet the other metrics of your company.
Here are the main metrics that will be of great importance for almost all Product managers:
1. MAU / DAU
Monthly Active Users (MAU, the number of unique users per month) and Daily Active Users (DAU, the number of unique users per day) are excellent indicators of the health of your digital product as a whole. If you are interested in long-term growth, then these are indicators that you must not forget about! They help keep track of whether the user base is growing or not, and how sticky your product is to end users.
Understanding how to calculate DAUs is determined by the specifics of your product. Often this is just an indicator that counts people who have opened the application and closed it. Most managers are still trying to determine the minimum action taken to get value from the product. For a music streaming service, for example, it can be a song playback. For a messenger application, this may be sending a single message.
Likewise, how often a user must use your product to get into the MAU metric will also vary depending on your offer. Does the user need to use your application once a month or twenty times to increase the MAU?
Setting the bar too high can be as catastrophic as setting the bar too low. The question that you should ask yourself is: “How do I ensure the value of the product for the user?” You should base your metrics on it.
2. Conversion Rate
How many people coming to your site do what you want from them? Whether it’s signing up for the freemium version of your new tool, uploading photos, or streaming your content. A low conversion shows that people go to your application / website and don’t find why they came, or are disappointed in your product.
Why is it important? First, this metric will help you identify key user dropout points and features that may not work correctly. Of course, they will be able to find your new function, but it is difficult to understand what value it carries for users if they do not use it.
Similarly, if you understand that a relatively small percentage of your users find your new function, but the conversion rate is high, you will understand that the problem is not in the function, but that it is difficult to find. Instead of abandoning the function, add onboarding to help users find it.
3. Churn and Customer Retention Rate
You already know what a drill is … How to count the churn of customers will depend on your product!
Customers are great, and new customers arriving every day look great on growth charts. But if these same customers leave in a few days (or in a few seconds in this unstable world of applications!), Then you have, in fact, a holey basket, not a product. It makes no sense to fill the basket with new users until you learn how to hold them. You need a high Customer Retention Rate or customer retention rate – this is when more people return to your product than leave.
As Growth Product Manager from Airbnb, companies that did not understand the concept of retention and too sharply increased the cost of attracting a client, then very quickly lost all their users. Without users, your product is nothing.
If you have too high a speed of outflow of users, then your product does not deliver the promise. On the other hand, the low outflow rate shows that your user base is loyal and, at least, loves the product enough to stay with you.
Do not forget that outflow is not always bad! For example, dating apps like Badoo and Tinder are sometimes deleted because they have fulfilled their purpose and the user is now in a relationship. Not all products are intended to be used throughout the user’s life! Perhaps your product is a job search tool that the user will remove as soon as they find the job of their dreams. The entire history will be shown to you by the outflow speed, and it is precisely for it that you need to follow.
4. NPS and CSAT indices
Net Promoter Score (NPS) and Customer Satisfaction Score (CSAT) are a great way to measure the mood of your users.
In short, your NPS will tell you how much users like your product. It will help you divide users into 3 categories depending on how many points out of 10 they will rate your product.
1-6 = Critics
Such people use your product, but only if necessary / due to the lack of alternatives, and would not recommend it to a friend.
7-8 = Passive clients
These people like your product, but they did not impress them.
9-10 = Promoters
Such people are a gold mine. They are your first fans and will actively promote your product in their circles.
Once you have such promoters, you can use them in your product development strategy and marketing.
CSAT is a simpler assessment and can be used to understand how users are satisfied with individual processes or functions. NPS is more often used to measure how users are happy with their User Journey, while CSAT will give you more specifics. For example, you can ask users to rate the experience of onboarding on a scale of 1 to 10, as soon as they finish it. This issue is resolved with one touch, and is a common method of collecting feedback as part of customer service.
Managing Your Product Data
Managing your product data can seem like a daunting task if you are not an expert in Data Science. There are a few key thoughts to help you succeed:
- Centralize your data. Tracking metrics becomes more difficult if you have multiple data sources. When different teams / team members are guided by data from various sources, you run the risk of getting misunderstandings in the team.
- Share data. Shared data is a very powerful thing. Give all team members the opportunity to make the right data-based decisions, giving them access to the necessary metrics.
- Visualize your data. Using tools data visualization turns complex numbers into simple visual elements. This makes them understandable for all team members, and not only for those who are familiar with this data.
Choosing the right metrics and understanding how to align a team with the same metrics is not easy! Fortunately, this skill can be obtained at the product management training. What other indicators would you include in this list? Tell us about it in twitter!