PODi REPORTS
Brought to you by Caslon, a PODi Affiliate
January 2009
  
Strategic Solution Sales

What Does Personalization Do For Response Rates?

How much can personalized, relevant direct marketing increase your response rates over static direct marketing? This is not an easy question to answer as response rates depend on several variables including: the relevance of the message, the offer, the list, the creative and the timing.
Often the process is as much art as science.


Most marketers know instinctively that personalization can increase response rates for direct mail. But there are very few concrete examples available that can tell a marketer how big the increase will be. And yet, having some idea of what to expect is critical if you want to decide whether personalization is worthwhile-or if you have to defend your personalized campaign against criticism.

If you are a print provider proposing a personalized campaign to a customer, or if you are a marketer championing personalization within your corporation, you are likely to run into people who think that personalization won't pay for itself. To overcome their objections, you need to be able to estimate how much more profitable your personalized campaign will be than the corresponding static mailing. A key piece of information you will need is the increase in response that personalization brings.

The Caslon Response Rate Report has recently been updated with information from new case studies that have been added to the PODi case study database in the past 14 months. This has resulted in changes in many of the statistics. (The data on fundraising is an exception: there were no new fundraising case studies with sufficient detail added to the database, so we have re-published last year's data without any change.) We have also replaced some of the cases discussed in the text of the report with newer ones.

Although the overall results in this year's report are similar to those in our last report, there are some differences that are worth mentioning. The biggest difference this time around was the widespread use of personalized URLs (PURLs). The majority of the new case studies used them, whereas relatively few did in the past. In cases where lead generation was the goal, the typical campaign consisted simply of a mailing that directed the prospect to a PURL. (Of course, a PURL by itself is not a reason to respond, and these campaigns had to be both relevant and interesting to achieve good response rates.)

Response rates vary by the campaign objective and in this report we considered five main types:
  • Direct order (including fundraising)
  • Lead generation/traffic generation
  • Lead nurture/follow-up
  • New customer experience
  • Loyalty
Two other key variables that arise from analyzing PODi case studies which you can use to help predict response rates are:
  • House list vs. Outside (rented) list
  • Size of the campaign

By analyzing PODi case studies and taking into account those PODi case studies are atypical we are providing a set of recommended response rates to use if you don't have access to historical data. Or you can take the results of a previous static campaign (if you don't have those, the corresponding average from the DMA report) and get an estimate of what to expect from a relevant VDP campaign by applying the PODi factor to the static results.

Here are the values we recommend using in planning your campaign:

Direct order - sales to consumer
Typical static response rate (DMA) 1.75%
Typical personalized response rate 3.2%
Factor increase for personalization vs. static 1.8
For a good house list add 1%  
For a large (>1000) rented list subtract 1%  
Table 1: Suggested response rate targets for direct order - sales to consumer campaigns

Fundraising
Typical static response rate (DMA) 4.46%
Typical personalized response rate 7%
Factor increase for personalization vs. static 1.5
For a good house list add 1-3%  
For a large (>1000) rented list subtract 1%  
Table 2: Suggested response rate targets for fundraising campaigns

Lead generation
Typical static response rate (DMA) 3.2%
Typical personalized response rate 5%
Factor increase for personalization vs. static 1.5
For a good house list add 1%  
For a large (>1000) rented list subtract 1%  
Table 3: Suggested response rate targets for lead generation campaigns

Nurture
Typical static response rate (based on DMA data) 2%
Typical personalized response rate 6%
Factor increase for personalization vs. static 3
For a good house list add 1-2%  
For a large (>1000) rented list subtract 2%  
Table 4: Suggested response rate targets for nurture campaigns

Loyalty
Typical personalized response rate 5.4%
Table 5: Suggested response rate targets for loyalty campaigns

This data is taken from Caslon's Response Rate Report which was updated in December of 2008 with the results from 114 new PODi case studies. The full report can be purchased at the Caslon Store. PODi members can login and download the report for free.

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