Profiling Your Customer Improves Marketing Potential

This is part 1 of the series “Targeting The Customer“, a 5-part series on using marketing automation to target customers and improve marketing effectiveness.

Sending off blind email blasts without regard to the end recipient is like a sales rep using the same sales pitch for a product, regardless of the customer’s specific needs. While email marketing as a commodity is inexpensive, the value proposition of marketing a company’s products and services via email would be far higher if the content was targeted to the individual. In order to effectively target a message to the individual, one first needs to know information about that individual.

Profiling involves capturing information about customer behavior and customer preferences to obtain a more complete picture of the customers interests, needs, and wants. A good profile database can allow for more targeted marketing, and lead to more effective marketing campaigns and improved ROI. If a customer or prospect is seeing content that is directly targeted to their needs, interests, and wants, the customer or prospect is more likely to respond favorably and take action.

Profiling involves both perceived customer preferences as well as customer behavior. Since a person’s interests, wants and needs exist at both a conscious and a subconscious level, both preference-management and automated behavior tracking are critical to building an accurate profile for any given customer. The more data one can obtain about a customer, the better able a marketing department can provide the customer with relevant content. While the danger exists of information overload, providing too much information for a marketing department to effectively digest and utilize, there are automated tools that allow the marketing team to analyze the data and respond with triggered and dynamic content automatically based on a user’s profile.

Profile management systems can be as simple as measuring specific interest categories (sending customers who have shown interest in product A information about products related to A, and customers interested in product B products related to B, etc.) or can utilize complex weight formulas, giving customers a score in multiple categories based on behavior and analytics of that behavior (customer has shown interest in products of type A, has bought product of type B, and has ignored any attempts at marketing type C, causing a customer to get a higher weighting on products of type B than on type A, etc.). Knowing these facts about a customer and organizing them in a way that makes sense is the key to a robust Marketing Automation solution.

Profiling can take many forms, included automated web activity profiling, profile preference forms, surveys, and social network profiling. In part 2 of this series, we will review the first three methods of this profiling (social network profiling will be covered in part 5 of this series).