The optimal time to send a message differs by user segment. Data Eagle automatically chose segments of a customer’s mobile app by algorithm and determined a best time to contact for each, running over 40 A/B tests in total across segments. Different segments benefitted from different timings. While timing without segmenting increased the impact of messages by 48%, timing with segmenting increased message impact by a full 214%--more than triple the impact.
When testing for the impact of different changes in your product or marketing you usually run A/B tests. If you're not careful to check the effect these different changes have on each other you may ultimately end up doing something that has no positive and some cases worse customer engagement. Read on to find out how this issue occurs and what you should do.
See that messaging has optimal timeframes. Too soon or too late can decrease efficiency, and careful analysis can uncover the best moment to send a message. As shown in the case study a message sent out after an optimal delay of 5 days versus a suboptimal one day could triple the effectiveness of your messaging.