Optimize Your Contact Strategy for Higher Response Rates

(List and Data Strategies) Contact strategy is a balancing act: Approach your customer multiple times in a short timeframe and you could either improve your results or experience list fatigue by contacting the same audience one too many times.

Finding the right balance can be challenging because the best approach is different for every marketer. In fact, approaches differ greatly from industry to industry and, not surprisingly, from company to company.

Fortunately, you can optimize your contact strategy–and your campaign performance–by taking a look at your audience selection approach. Optimizing contact strategy is particularly critical for direct mailers in industries such as insurance, telecommunications, and financial services that due to highly competitive market conditions and other factors, heavily target their prospect and customer universe with a large number of direct mail pieces within a short time.

In determining the best balance in your contact strategy, consider the following variables:

• Contact frequency – This is the number of times an audience will be targeted within a specific timeframe to drive the maximum response rate.
• Contact recency and resting period – Together, these determine the optimal duration for “resting” a prospect to drive the highest response rate. Marketers must find the length of time that a target audience must rest in order to avoid response degradation.
• Creative and offer rotation – A fine line exists between building awareness and boring a prospect with the same creative or offer. Marketers must determine the optimal rotation sequence to drive the maximum response rates from a prospect.

But where can marketers begin? Start by following these recommendations:

• Store collection promotion history data in a centralized data environment. Access to contact strategy data is the number-one requirement to optimize your contact strategy. Invest in a relational database with the capacity to store the details of every campaign or in a lower-cost data processing-based solution.
• Develop a contact strategy that includes your business rules related to contact frequency, resting period, and creative/offer rotation. Create a continuous testing environment to test various dimensions of your contact strategy. Use multivariate testing techniques to maximize what you learn from your test designs. Repetitive multivariate testing through randomized tests is usually the best method to get to the best answer.
• Use contact history data as a predictor in your response models. For example, for a leading credit-card issuer, contact history data generated a 20%-25% lift in response.

Improving – and ideally optimizing – your contact strategy is a key factor in successful marketing. But far too many marketers ignore proven best practices and instead follow their gut instinct and house their data in multiple locations. A systematic, data-driven approach holds the answer and helps marketers find the right balance in their contact strategy.

Ozgur Dogan is senior director of database marketing solutions for Lanham, MD-based database marketing company Merkle (www.merkleinc.com).