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As personalization becomes more important to customers, marketers are searching for the holy grail of delivering individualized experiences to customers. Content, experiences, offers geared toward one person are significantly likely not only to increase customer spend, but their emotional bond with a brand.
Data collected through loyalty mechanisms are the key to making this happen, and machine learning tools help bring individualized loyalty to scale.
No person is alike, therefore no loyalty journey should be identical. Some brands are already guiding customers along their unique loyalty paths. CVS, for example, may use profile, location and transaction information to email a shopper about allergy medication based on the pollen count in their area that day. There are countless opportunities to action on comprehensive data collected by a versatile loyalty platform.
Hotel staff would no longer ask guests if they had been to that hotel before, they would simply provide that high value guest with a room filled with their preferences: down pillow, heavier quilt on the bed, fruit bowl with just apples vs generic fruit bowl with items you won’t eat.
Retailers could send loyal shoppers video of the latest red carpet event and match up the customer’s style (gathered from transactions, preferences, browsing history, etc.) to provide a one-click option to purchase the outfit or parts of the outfit as the video concluded.
Or, retailers could provide an individual pop-up store for a customer with items from her virtual closet on the dressing room with a seamstress. She tries on items, makes her final selections, then gets them tailored and delivered to her house within two hours.
Beauty brands could incorporate the VR experience for customers to virtually try on products, purchase and have them delivered to their home that day.
By enabling individualized journeys, loyalty can move beyond a programmatic structure that might consist of four to six tiers intended to motivate customers along their journey. But, as we’ve seen with content and offers, what appeals to broader segments doesn’t catch those outlying persons. In the very near future, each customer’s behavior will determine their own loyalty “program.” There may still be offers or points, but those would be specific to people who want them and are motivated by them. Brands can start using personality typing, psychological drivers and sentiment indicators to align with data collected on members to hyper-optimize their customer lifetime value to the brand. Such targeted journeys will build an emotional bond and keep customers hooked on the brand.
We’re seeing strong indications of individualized loyalty now, through targeted messaging and campaigns that continue to refine customer journeys. It won’t be long until machine learning allows us to bring this to scale and offer the very best of brands to their most loyalty customers.
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