Direct mail offers the benefit of an immediate measure of success - your response rate. Another benefit of direct mail is that you can test and measure the variables before committing all your resources to a single approach. Here are some of the possible variables and metrics to consider.
List Performance
It is generally understood that the biggest factor in the success of direct mail is the quality of the list. Once a target audience has been well defined, general best practices call for utilizing multiple lists from multiple sources (no one vendor has a list that contains all of your key, target audiences). A simple merge/purge/de-duping process will refine the list.
Coding the list source in your data base is a simple and effective way to evaluate the performance of any specific list.
As responses are generated, credit the response to each list. This isn’t “over counting”, but it will provide an accounting of which lists provided the best relative response rates.
Without this basic procedure, you lose the most valuable feature of direct marketing – the ability to see where your potential customers are and where you can find more of them.
Testing Variables
While it is best to test one variable at a time, few marketers have the luxury of time or budgets to isolate variables this way. However, when done properly, variables such as messages, offers, and packages can all be tested in one mailing by developing a test matrix. Below is a sample 2x2 matrix that shows a variety of variables that can be used in a direct mail campaign.
With a matrix like this, records from the database are randomly assigned to each of the groups (P1 – P4). Make sure the assigned group is coded into each record in the database.
As responses come in, you can perform statistical significance tests to determine which variables performed above expectations. In subsequent mailings, eliminate underperforming variables until you end up with the winning combination.
Media Lift
While direct marketing has evolved over the years it continues to be the most widely used medium in direct marketing.
However, to improve your response rates and surpass the industry standard of 1% or less, you may want to consider integrating other media with your direct mail campaign.
For example, by selecting the most appropriate online or offline media prior to and during the mailing, you can raise brand awareness and positively affect response rates. By using different media mixes in different markets, you can evaluate the overall media lift rate, as well as segment lift rate by medium.
Metrics Planning
The most common error in measuring direct mail performance is the failure to identify the key metrics and parameters as part of the advanced planning process. Marketers should consider historical or industry standards and prepare Performa response models to determine which metrics to measure and anticipated results.
Tracking responses over time will provide longitudinal data to make better decisions for improved campaign-over-campaign performances.
List Performance
It is generally understood that the biggest factor in the success of direct mail is the quality of the list. Once a target audience has been well defined, general best practices call for utilizing multiple lists from multiple sources (no one vendor has a list that contains all of your key, target audiences). A simple merge/purge/de-duping process will refine the list.
Coding the list source in your data base is a simple and effective way to evaluate the performance of any specific list.
As responses are generated, credit the response to each list. This isn’t “over counting”, but it will provide an accounting of which lists provided the best relative response rates.
Without this basic procedure, you lose the most valuable feature of direct marketing – the ability to see where your potential customers are and where you can find more of them.
Testing Variables
While it is best to test one variable at a time, few marketers have the luxury of time or budgets to isolate variables this way. However, when done properly, variables such as messages, offers, and packages can all be tested in one mailing by developing a test matrix. Below is a sample 2x2 matrix that shows a variety of variables that can be used in a direct mail campaign.
With a matrix like this, records from the database are randomly assigned to each of the groups (P1 – P4). Make sure the assigned group is coded into each record in the database.
As responses come in, you can perform statistical significance tests to determine which variables performed above expectations. In subsequent mailings, eliminate underperforming variables until you end up with the winning combination.
Media Lift
While direct marketing has evolved over the years it continues to be the most widely used medium in direct marketing.
However, to improve your response rates and surpass the industry standard of 1% or less, you may want to consider integrating other media with your direct mail campaign.
For example, by selecting the most appropriate online or offline media prior to and during the mailing, you can raise brand awareness and positively affect response rates. By using different media mixes in different markets, you can evaluate the overall media lift rate, as well as segment lift rate by medium.
Metrics Planning
The most common error in measuring direct mail performance is the failure to identify the key metrics and parameters as part of the advanced planning process. Marketers should consider historical or industry standards and prepare Performa response models to determine which metrics to measure and anticipated results.
Tracking responses over time will provide longitudinal data to make better decisions for improved campaign-over-campaign performances.
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