It’s well–known and well–documented that as the relevancy of a given marketing campaign increases, so does guest engagement. For example: a vegan is more likely to respond to a message promoting the new Impossible Burger than one for cheese fries.
This is why successful segmentation is so critical. For a campaign to be as effective as possible, it needs to be targeted to the right group of guests, based on their behavior; but traditionally, segmentation tools were limited to a single factor, like visit frequency, average spend, or commonly ordered items.
While this is better than a one-size-fits-all approach, these old methods of segmentation leave marketers with a one-dimensional view of their guests and provide little insight into what various segments have in common, or where they overlap.
Now, Advanced Segmentation with artificial intelligence – part of the Paytronix AI to IA(sm) solution – is revolutionizing the way marketers segment guests by taking multiple factors into account at once. The proprietary algorithm, trained using 20 years’ worth of data collected across restaurant and convenience store segments nationwide, considers each guest’s total visits, average check size, average days between visits, and their likelihood to lapse.
The result is a detailed set of 12 categories, recalculated weekly based on guests’ behavior.
These hyper-specific segments help shape the strategy for targeting the different types of guests. Those in the green segments could be enticed to cement their brand loyalty by a visit challenge or other small reward. Those in the orange segments will need a richer reward to be drawn back in. Potential Loyalists and New Members could be coaxed into joining the green or gold tiers with a nurture campaign.
These segments can be leveraged to minimize cannibalization, identify and prevent potential lapse, and strategically foster greater brand loyalty.