Layers of Customer Analytics

Layers of Customer Analytics

Customer analytics includes the following layers of activities:

1.    Identify your current customers.

By identifying who your customers are, you will be able to have a clearer and deeper understanding of your customers. This can be done by gathering and combining the data from all the areas of customers’ journey. Segment them into subgroups, if any, to capture the real story better. By segmenting them, you make homogenous group. Each group provides distinct characteristics that will make the next step more thorough.

2.    Using modelling for analysis

This allows you to identify patterns and trends. As you go along reading this book, you will be oriented to the different challenging techniques that will help you how to get insights from raw data. Previous chapters have already taught you some.

3.    Looking for insights

Trends and patterns helps you find insights. Should there be changes in behavior, root causes can be easily identified. These causes can then be give proper remedies. Adjustments can be made at the present to have an impact in the future.

4.    Making predictions

Based on the data at hand, you can now predict the future. There are a number of prediction techniques that can be used. One technique does not fit all. It has its own unique features that answer certain questions. As a good manager or executive, it is always an edge to be acquainted with these techniques. As you go along with this book, you will learn some of the famous ones.

5.    Optimizing customer experience

This includes identifying features of products or experiences that are in not demand anymore given the change in trends. If it is a product, it is redesigning the features and repackaging. If it is a service experience, it is re-planning and re-evangelizing experiences. 

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