Consumers are craving greater relevancy, and increasingly using their power to disconnect from brands that don’t speak to them as individuals.
Marketers have greater powers than they realize to produce relevant, personalized communications. By using data and tools most already have in place, marketers can take a data-driven, content-rich approach to customer communications and achieve greater relevancy, evidenced by measurable returns.
This precision marketing process must begin by first deciding what problem you're seeking to address. Are you trying to reactivate dormant customers, for example, or achieve a greater response rate to a particular promotion?
Next, evaluate and leverage the data and campaigns you currently have in place. In many cases, your existing housefiles are sufficient to develop targeted segments for use in a test campaign. Begin small by establishing a customer segment with the desired level of engagement, then identify customers whose prior behaviors and engagement histories most closely match this first group. This new customer segment can then be divided into a target group and a control group.
Next, synchronize your campaigns and determine the best message for the channel. In a test case with Best Western International, the world’s largest hotel chain, we examined active reward members and identified 100,000 who were similar in their Best Western relationship to the most high-value customers with the propensity to either apply for a co-branded MasterCard and/or engage in the summer promotion of “More Rewards, Faster.”
Then we targeted half of the group with personalized messaging through monthly loyalty statements, leveraging the statement as a promotional document to inform loyalty program members of how much faster they could accumulate points during the promotional period.
Once a test campaign has been launched, the next step is to measure the results based on a wide range of criteria and, most importantly, bottom line measures. In less than eight weeks, Best Western enjoyed target group gains, including a 39 percent increase in number of stays and a 30 percent increase in revenue over the control group.