Welcome to Part 4 of the “Mailing List Mistakes to Avoid” blog series. This blog series will be a lineup of major mistakes people make when buying a mailing list and how to avoid them. If you haven’t read our previous posts, you can find them here: Part 1: Introduction to Investing in a List, Part 2: Research List Providers, and Part 3: Compilers vs. Brokers.

Now that you know the difference between list compilers and list brokers and have a better idea of what kind of company you want to work with and the quality of leads you want, do you know what kind of data you need? Don’t worry if you don’t, I’m here to help. Many people feel that they have been misled by list companies and have lost faith in targeted mailing lists. This primarily happens because people think leads are lists, and lists are leads. Did I confuse you? Okay, let me explain.

Leads are people that have made proactive requests about your specific product.

Lists are individuals targeted as “those most likely to be interested” in your products and services.

Knowing the difference between leads and lists is vital. Many marketers have been misinformed to believe or assume that every person on the mailing list has requested your products and/or services and that lists and leads are one in the same, when clearly they are not.

Understanding what you are purchasing when shopping for your marketing list will help you come up with the right approach and marketing messages to the audience you hope will buy from you. Also, “leads lists” is another term use for “lists”.

Now that you’re familiar with the difference between leads vs. lists, it’s important that you understand the ways that lists are built. Here are 3 main categories for the types of data that you might come across.

Compiled data – Regularly updated information, pulled from public sources such as postal records, county recorder offices, government records, telephone directories, and credit bureaus. This type of data is best used when demographic criteria is the best method of targeting your most likely prospect.

Response Data – These are privately owned files that are collections of people who have had to take a specific action to get on the mailing lists such as: subscribing to a magazine, purchasing a product, filling out warranty cards, entering sweepstakes, and joining a club/organization/association.

Sales leads – These are proactive requests from a prospect indicating an active interest in purchasing a specific product or service.

Now that you know the difference in the main types of data that make up a marketing list, you should be aware that different types of data and the different ways they are used will have distinctive response rates. Response rates can vary greatly depending on the type of data that is used for your marketing list.

Every year, the Direct Marketing Association puts together an annual report that shows average response rates for various types of direct marketing. It may be worthwhile to familiarize yourself with the organization and their reports. This will help shed some light on what is otherwise a dark and scary corner, hiding a monster that can eat your money before you even get to pull it out of your wallet. Here are some key notes from their most recent 2015 report:

– Direct mail achieves a 3.7% response rate with a house list, and a 1.0% response rate with a prospect list.

– All digital channels combined only achieve a 0.62% response rate (Mobile 0.2%; Email 0.1% for a Prospect list and 0.1% for House/Total list; Social Media 0.1%; Paid Search 0.1%; Display Advertising 0.02%).

– Telephone had the highest response rate at 9-10%.

Understand that there is no one-shoe-fits-all solution. However, having the proper expectations will allow you to try various lists and marketing strategies and decide if anyone or a combination of these will do. If you have any further questions about this topic, please call US Data Corporation at (888) 578-3282.

Make sure to read other parts of the series: Part 1: Introduction to Investing in a List, Part 2: Research List Providers, Part 3: Compilers vs. Brokers, Part 4: Understanding Your Data, Part 5: Find a Trustworthy List Provider, Part 6: Be Open to List Suggestions.