Creating Data-Driven Customer Profiles

pexels-photo-219003

The customer profile is the whole “data picture” of a customer. Customer profiles contain personas that allow companies to target the clients they want to reach. These can be beneficial to anyone wanting to know their customers and it’s nice to understand the reasons companies choose to profile customers. Profiles contain the individual information of customers and paint a clear picture of them! It’s also a good idea to familiarize yourself with the metrics you can use because it will make analysis a breeze. Once your data knowledge is sealed up the data you have can be used to make predictions that boost your companies advantage in the market.

Benefits of Profiling

Customer profiles give you all the information about an individual customer in one place. An average customer can be synthesized from multiple customer profiles, that hypothetical customer is then called a Persona. Companies choose to profile their customers to offer the personalization their customers want within segmentation.  Profiling should not stop at just your own customers it’s useful to understand your competitor’s customers and the people who never will be customers. Frameworks can help you organize that load of data and later interpret that data so you can capture all the sweet benefits of customer profiling. That analyzed data helps focus customer experience (CX) by informing you of the direction your most valuable customers would like. Helping the company increase their Customer Lifetime Value (CLV). People are always changing, so remember customers preferences are in flux and need to be updated, validated, and reassessed regularly.

Metrics For Profiling

Net Promoter Score (NPS) has become a tyrant in CX methods even though its scope is lacking.  So use some caution when using NPS and avoid using it as a lone metric. A lot of people suffer from NPS dependency. Breaking away from that can help you understand your data at a deeper level. That data you collect for Customer Profiles will often fit into 4 data dimensions, (Product Usage Preferences, Price Sensitivity, Marketing Engagement, and CX Research) which all fit into the similar but different, Customer Journey Framework. Knowing the preferences of customers helps us understand what they like about our product, how much they will pay for it, which ads work, and what our customer base would like to see in the future. Customer Lifetime Value itself is the single most useful metric for determining the underlying patterns of your customer base.

Analytics For Profiling

The goal of your analytics should be to understand the complete customer profile across the 4 data dimensions. It’s why you profiled and it will allow you to personalize without being a creeper. Starting out, you may not be able to build complete profiles on every customer and you will always be sampling. Creating powerful customer profile tools called personas can help you run simulations with your data. Personas can also be used as a framework to describe the data and provide a face for the grouping. That can lead to the ability to predict individual customers and create actionable persona profiles to maximize your business efforts. When you’re steadily on the road to profile perfection consider automating any process you can and remember to share your new insights with the rest of your organization.
Why stop here? Move on to the next lecture in our series and understand how to use your new Customer Profiles to Data-Drive Better Sales Conversations!