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DIRECT MAIL DATA & TARGETING SERIES
PART 1: The Two Key Types of Data
If you’re a growth marketer who is using the mail channel to generate leads, then you are very aware of the power of targeting. The most relevant message sent with the greatest offer is lost on a mistargeted recipient. This series of blogs is to help anyone using direct mail to understand the different types of data available, along with some thoughts on how we decide which data to test on behalf of a client’s direct mail campaign.
The data world is constantly changing. New data sources come online. Existing ones are enhanced. Even the analytics we use to select best prospects are changing, thanks to the use of artificial intelligence and improved reporting.
The Two Types of Data
This first blog kicks it off with the most basic data consideration: Not all data is created equal. Depending on how your data was derived could have a lot to do with how it performs. At the highest level, there are two types of data available to marketers:
- House data: This is your internal database of prospects. They know you and, in some way, have raised their hands to do business with you, even if it did not result in a sale. It includes a company’s active customers, inactive customers, dropped phone calls, inquirers and more.
- Prospect data: These are consumers from the general population of roughly 128 million US households. They may or may not know you, but, by definition, they have not done business with you because they are not in your house database. These names are procured from a number of different outside databases.
In general, house data performs better than prospect data because the target has already expressed interest in, or even purchased, your product or service. If a company can mine their own customer data for cross-channel marketing, and/or reactivation of prior customers to meet business objectives then that data should play a role in your direct mail strategy.
However, most marketers are charged with growth marketing. In fact, often the next level of funding for new businesses and start-ups is tied to showing rapid growth in terms of net new customers acquired. Acquiring net new customers via direct mail requires exploring audience targeting with prospect data outside a company’s current in-house database.
Keep in mind that there are about 128 million households in the US (as of 2019), so the largest consumer databases will have close to that number of households in their databases. What separates these large data sources from each other is what we call the “view” they have into those households. How can the particular information in a list source’s consumer view contribute to fulfilling a company’s unique DM targeting needs?
Up next in this series will share the types of prospect data sources that can be optimized to create a successful direct mail prospect audience targeting strategy. We’ll review the largest databases along with smaller, specialized ones that deliver small, highly targeted segments. Along the way, we’ll present the pros and cons of what different list types have to offer. Although we’ll be focusing on B2C prospect data sources, many of the same principles apply in the B2B arena.
Read the entire series on data types:
DIRECT MAIL DATA AND TARGETING PART 1: The Two Key Types of Data
DIRECT MAIL AND TARGETING PART 2: Compiled Databases
DIRECT MAIL AND TARGETING PART 3: Transactional Databases
DIRECT MAIL AND TARGETING PART 4: Trigger Data Sources
DIRECT MAIL AND TARGETING PART 5: Intent Data
ABOUT GUNDERSON DIRECT
Gunderson Direct is one of the largest independent full-service direct marketing agencies, providing strategy, data, creative and production expertise to B2C and B2B clients across the U.S.
Gunderson Direct does not own or compile data. We have a deep knowledge of data sources and the tools used to analyze their effectiveness. The goal is always the same: Deliver the optimal mix of prospect files to cost-efficiently test, learn and rollout programs to meet our clients’ business needs.
All our data sources are members of the ANA (Association of National Advertisers). As such, they are required to respect data privacy laws, have proper data privacy certifications and maintain a solid reputation in the direct marketing industry.