How is data used to create a personalized piece?
At this point I have preached a few times about data and goals. Now the question is how to use the data to actually create a personalized marketing campaign?
And you should know by now that one question begets another…what data is it that you have?
That is the critical question – if you have a limited data set then the piece cannot be too customized. An example of limited data is if you only have first name, last name, and mailing address. For a limited data set, the piece can be customized with the individual’s first name – such as “Hi Eric” or “Hi Katie.”
If you have a robust data set then the piece can be entirely customized. An example of a robust data set would be first name, last name, mailing address, age, date of last purchase, total of last purchase, store most frequented. For a robust data set, the piece can be customized with the individual’s first name – again used in the same manner and then a thank you about their last purchase (“Thank you for visiting our store in Waldorf’s Festival Center last month. Below is a coupon for your next visit!” You really can get in depth, even customizing the coupon for an amount or discount based on total purchase price set at a threshold close to their last purchase.
Why do it though? Because using variable data can make the marketing campaign relevant to each customer. And, more importantly, it can increase the return on investment (ROI). It does this because the campaign message is speaking to the individual (tailored to them and their needs).
According to the Response Rate Report: Benchmark information for relevant marketing programs, June 2007(available to members of PODi) from Caslon / PODi, adding personalization that leverages customer history/data to mail can impact response rates anywhere from 3% to 13% based on vertical market. Seems to me personalization is worth the time and efforts since standard direct mail response rates are typically 1% to 2% (if you’re lucky).