Capturing a Single View of the Customer
One of marketing’s biggest challenges is having the ability to capture disparate customer data, which is dynamic and ever-changing, then analyze it and make it actionable. The ultimate goal is to leverage that data to create a single view of the customer.
Let’s look at some of the types of customer data that is available:
Declared, or self-reported data is what our customers tell us through welcome programs, questionnaires, landing page forms, or customer surveys. This type of data can be as basic as a name and email address, or also include more specific information, preferences, and opinions.
Past purchase, or transaction data provides information on purchase history can help marketers target more effectively. Past purchase data has three aspects to it:
- Recency indicates when a customer last placed an order.
- Frequency shows how many orders a customer placed in a period of time.
- Monetary value indicates how much money the customer spent.
RFM targeting, as it’s called, relies on the premise that someone who recently bought something, who shopped often, and who spent a lot is more likely to respond to your next campaign than some one who bought something a long time ago, shopped infrequently, and spent next to nothing.
And finally, behavioral data represents a separate category of information that is based on what customers demonstrate through their actual actions or behaviors. This includes, for example, how they responded to emails, social posting behaviors, mobile behaviors, or which pages they visited on our websites.
There are other types of data available to marketers including customer sales and service interaction data recorded in Customer Relationship Management, or CRM, and other enterprise systems. Use them all together to create a dynamic customer profile that enables you to deliver superior customer experiences.