At its core, artificial intelligence-driven marketing aims to communicate with guests on such a personal level that it’s as if each campaign were crafted specifically for them. Using the Paytronix AI to IA(sm) tools Advanced Segmentation and Predictive Analytics together, campaigns can be automated to target guests on an individualized and recurring basis.
Two of the most common of these one-to-one campaigns are the Missed Visit Campaign and the Visit Challenge.
Missed Visit Campaign
Because guests visit at their own pace, choosing the right time to send a “We Miss You” campaign can be challenging. While one guest visits daily, another visits just once a month, meaning that each will be considered “lapsed” at different times.
Using the Missed Visit Score, a marketer could send a message to all guests who had missed a visit according to their personal visit cadence. The AI would identify weekly guests who hadn’t visited in more than seven days, monthly regulars who hadn’t been in for more than 30 days, and everything in between. With the Missed Visit Score, creating this dynamic group would be as simple as clicking a button.
The same approach can be used when preparing a visit challenge. An ideal one will feature goals that incentivize guests to visit more than they typically would; but the challenge needs to be attainable for each guest based on their typical behavior. A bi-weekly regular, for example, is unlikely to be persuaded to visit four times in a week.
AI helps identify the optimal guest segments to receive a given challenge and makes it simpler to design multiple challenges, enabling all guests to be targeted by the campaign. The AI can optimize for the right number of visits and a promotion timeframe that will challenge each guest appropriately, and machine learning can be used to determine, over time, which rewards are best at driving guest behavior.
Looking for more ways to revolutionize your loyalty strategy with AI? Download Unlocking the Power of Data with Artificial Intelligence: Take the Guesswork Out of Marketing.
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