Callcredit Blog

Closing the Loop With Campaign Analysis

Consumer Marketing Data

Having worked in analytics and insight for almost 20 years, I have had the privilege to work with a number of remarkable clients. Most have wanted to employ the services of the insight teams I have worked within to improve the success of their direct marketing activity. Hence I have been involved in the development of numerous targeting models, whether for acquisition, cross sell or retention; segmentation solutions to allow for more tailored communications and channel models.

Let’s be honest, developing solutions of this nature requires a significant investment on the part of the client, be it in the form of the insight services they employ to build the models, the planner to develop the contact strategies, the marketing agency to design the creatives or the implementation costs of putting it on the database. On top of this you need to include those painful days spent in meetings discussing it and agreeing the final plan!

After all that investment, many clients move to the execution of the campaign, where the real costs kick in – print and postage. Let’s assume a Direct Mail campaign of 1.5 Million in volume, this could easily equate to £500K, a massive investment. This huge investment certainly deserves all the insight, planning and fluffy (marketing) effort up front.

Getting to the point (finally I hear you say), while companies are willing to invest heavily in planning and executing a campaign, how many actually invest in analysing how well that campaign really performed. Sure, most companies produce top line statistics of the response rate, conversion rate, etc across the different cells of a campaign, but how many really get stuck in and find the key drivers of response, learn from the campaign and improve the success of future campaigns?

Campaign analysis is without doubt one of the most crucial, yet one of the most neglected parts of any campaign; indeed, of all the processes described above it is a tiny fraction of the cost.

As I said previously, by campaign analysis I don’t mean producing top line results for each mailing cell, but really getting into the detail, comparing the profile of responders vs non responders, converters vs non converters, accepts vs declines, across all of the characteristics available to you.

It is imperative to understand what makes a responder different to a non responder, why does creative A appeal to one person but creative B another, which audience was more likely to respond to each offer, are the responders different by channel. While I appreciate a model may have been built to predict some of these factors, the model may have aged, the market may have changed, models can be refined and improved and targeting must evolve.

In addition, when testing different creatives, you need to understand who and why one performed better than another, so you can focus your efforts in the right direction. All too often I see companies trying creative after creative, never learning and continually investing.

Obviously to do campaign analysis effectively you need to invest a little up front to ensure you have robust cell sizes for testing. A good planner will always have a campaign calculator to help you do this and it shouldn’t take long.

Next time you’re planning a big campaign, mail 10,000 less and invest that money in the next campaign, by really understanding what worked in this campaign – Close That Loop!

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