I’ve been fighting a KPI (key performance indicator) battle recently. Setting appropriate KPIs is an…
Iterative testing leads to constant optimization and also protects you from a declining response rate.
Direct mail is all about ongoing, iterative improvement. Establishing a control mailing — one that yields dependable, predictable response — is an essential step for any mailer.
But controls wear out over time and become less effective. This is especially true if you depend on remailing a particular target, which may be exposed to your mailings multiple times over a given period.
That’s why building a testing and learning mindset into your direct mail program is essential.
A/B testing, also known as split testing, is a method of comparing two versions of a direct mail piece to determine which one performs better.
In practice, you create two versions of your direct mail campaign, each with a variation in a single element, such as the offer, the headline, or the design. You then randomly divide your target audience into two groups. One group receives Version A and the other group receives Version B.
By tracking the response rates of each group, you can determine which version is more effective in driving the desired response.
A/B testing helps you make data-driven decisions about your direct mail campaigns, allowing you to optimize your campaigns for better results. Here are some tips for conducting effective A/B tests for your direct mail campaigns:
- Define your goals: Before conducting an A/B test, it is crucial to define your goals and the metrics you will use to measure success. This could be the response rate, conversion rate, or any other relevant metric. Make sure you are testing variables that affect your specific goals.
- Test one variable at a time: To get accurate results, it is essential to test only one variable at a time. This will help you determine the impact of each variable on the response rate.
- Test discernible differences: Changing a line of copy or font size is less likely to lead to discernible response differences. New offers, new value propositions, and new designs are more likely to make a difference. Once a new package is a winner, you can massage the details in subsequent mailings.
- Use a large enough sample size: Make sure your test cell sizes are large enough for readable differences. The size of your sample will depend on the size of your target audience and the anticipated response rate. Generally, the larger the sample size, the more reliable the results.
- Ensure you make data-driven decisions: Use unique tracking codes or package-specific URLs and QR codes to track responses from each test group. A match-back process to match the mail file to the customer file during the test period is the most accurate method to confirm results.
- Retest to validate: Roll out new findings in stages to ensure test results hold up over time and to larger audiences.
- Don’t stop testing: Optimizing a campaign is an ongoing process. Continue testing new variables to improve results and to keep your creative fresh.
By following these tips, you can conduct effective A/B tests for your direct mail campaigns and optimize your campaigns for better results.
In conclusion, A/B testing is an essential tool for direct mail marketers. By testing different variables in your direct mail campaigns, you can continually optimize your campaigns for better results and avoid scrambling if the response to a control mailing weakens.
Gunderson Direct has long-lasting relationships with some of the country’s largest corporations, helping them to lower their customer acquisition costs and increase profits using address-based integrated direct marketing programs.
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