Analytics is the applied use of data in processes, and it’s something product managers need to learn to love because their careers are trending towards data. This is because data=fuel when making decisions and identifying goals. To achieve your product vision you need to segment customers by persona to identify high-value groups and use frameworks and key performance indicators (KPIs) to validate your decisions before setting the next set of goals. The video below outlines this process.
Why Data is Fuel For Product Mapping
Data is really just an efficient way to express information and is useful for making predictions. People who are good at predicting the future are usually flexible in their beliefs and can assess new information against what they already know. Analytics is used in this way because it is the open-minded cousin of statistics. It takes in all the information that statistics ignores like interviews, surveys, news, and even non-data like intuition. However, even the best data scientists can make errors and misinterpret results. So it’s important to be constantly validating, updating, and testing conclusions.
Data Types and Uses for Products
There are a few ways to define data and each interpretation requires a different approach. So it’s worth the time to check out the different types of data and understand what type you are dealing with. Broadly speaking, data can be information on customer characteristics like when they purchased last, how often, how much, and if they recommended the product. Using that information you can focus the product vision by segmenting customers, understanding their sensitivities, and using that information to develop features for your product.
Frameworks & KPIs With Impact
To get a good understanding of your customers use metrics that matter, such as Customer Lifetime Value (CLV) and Customer Retention Rate. Once you have decided how to organize your data, frameworks can then help you focus and create the story that you want to tell. Focusing that data helps you focus on things with high-impact such as CLV, directly marketing to your high-value personas, and Customer Journey. All of these things line up to create a data honed product vision.