How to Prepare a Successful Integrated Digital Marketing Program, Part 3
In this three-part series, we've been exploring what an integrated digital marketing program is, why having one is important and how to make it successful using four foundational tools. In part one, we discussed the basics around an integrated digital marketing program. Part 2 focused on the first two of four foundational tools required for a successful integrated digital marketing program: the ability to recognize customers across channels and smart data. In today's part three, we identify and examine the last two foundational tools required for a successful integrated digital marketing program: the ability to personalize communications and how to do attribution correctly.
Let's face it: If you have smart data but no plan for fusing that insight into your communications, then the data isn't really doing you any good. Personalization used to mean "Dear [FirstName]." That's no longer the case. While adding a customer's name to a communication, especially an email, does add a measurable amount of familiarity, it merely hints at the powerful capabilities of true personalization. Simply put, true personalization involves using relevant data about the customer to address their needs, both expressed and implicit. Let's look at the two categories separately here:
- Expressed personalization includes offers or content selected based on information that the consumer has provided to the marketer. Typically, consumers make this information available through a preference or subscription center on the marketer's website. To summarize the many good articles written on preference centers, these pages allow consumers to signal their interest in specific content or offers (or, in the case of subscription centers, specific emails), including types of products or other areas of interest. Expressed personalization works well because consumers say what they want then get what they want.
- Implicit personalization refers to offers or content served up based on inferences that a marketer can make from customer information, both expressed by customers themselves or observed through interaction. An apparel retailer, for example, can infer that a consumer who lists her residence as Milwaukee will want information on heavy coats in the winter and swimsuits in the summer. Meanwhile, a shopper from Miami might only want information on light sweaters in the winter and swimsuits year-round. (Hey, it's Miami!)
Most implicit personalization comes from observed behavior such as purchases or web browsing behavior. To return to our Milwaukee consumer, a marketer might observe that she's browsed swimsuits in February since she plans to visit her sister in Miami. A smart email program would interpret that behavior as interest in swimsuits and swap out heavy coats in its next email to her and replace them with swimsuits.