Allergan Aesthetics Enhances Consumer Rewards Program Using Machine Learning to Deliver Personalized, Actionable Offers to Patients In-Office

THE NEW ALLĒ FLASH PILOT RETURNED A 44% REDEMPTION RATE 

Allergan Aesthetics, an AbbVie company announced an intelligent, new and industry-first experience available via its consumer loyalty program, Allē: Allē Flash. This new, in-office offer delivery system is powered by cutting-edge technology to deliver highly personalized offers to the platform’s 3.7 million active loyalty program members in real-time while at their participating dermatologist, plastic surgeon, or med spa.

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With the aesthetics industry on the rise, meeting consumer needs and helping make   aesthetic treatments more accessible is a primary goal at Allergan Data Labs, the Digital and Consumer Marketing Group at Allergan Aesthetics.

According to internal research, in 2021, 65% of JUVÉDERM Collection of Fillers visits were either on the same day or within 30 days following a BOTOX  COSMETIC (onabotulinumtoxinA) treatment. The goal of Allē Flash is to surprise and delight patients with personalized offers while they are in their health care providers’ office. The offer could be for the treatment they are scheduled for, and they can redeem on the spot, or for another future Allergan Aesthetics treatment.

“Since launching Allē in late 2020, our providers’ have driven its utilization in office, significantly exceeding our expectations. We are eager to take our ‘much loved’ loyalty program another step further with Allē Flash,” said Jasson Gilmore, Senior Vice President, Global Digital and Consumer Marketing, Allergan Data Labs.  “Our Allē Members lead busy lives, and we know aesthetic regimens are not one-size-fits-all. We believe there is further opportunity to support them with personalized offers delivered to them when they are in the position to redeem.”

THE TECHNOLOGY
Allē’s home-grown AI-powered recommendation engine combines consumers’ affinity to specific brands, purchase propensity, and past treatment patterns to generate a customized offer that has a high likelihood of redemption. The platform uses machine learning to predict brand affinity and purchase propensity for each patient. In two pilot programs conducted in 2021 in more than 60 aesthetic health care provider practices, Allē Flash delivered a 44% redemption rate and informed the design of the offering.

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Allē is committed to supporting strong connections between consumers and the Allergan Aesthetics portfolio of brands. Through smart technology solutions, Allē elevates and democratizes access to aesthetic products and treatments for the consumer.

Allē’s predictive model uses an ensemble approach combining both supervised and unsupervised learnings leveraging collaborative filtering, propensity models, the teams’ own flavor of market basket analysis, and
Participating Allē practices will have Flash QR codes on display in their offices and consumers will scan the QR code provided using the camera function on their mobile phones. Once scanned, Allē’s machine learning algorithm will determine which personalized offer, if any, will be provided to the consumer. If the consumer is eligible for an offer, it will automatically be deposited into their Allē Wallet. While all scans may not return an offer, many will.  By scanning at check-in or while waiting, offers can be redeemed in the same visit, schedules permitting and if the patient is an eligible candidate for treatment. Offers may be general Allē offers or brand-specific, with varying time frames to redeem.

Core to the Allē ethos is its ability to help consumers access aesthetics treatments via technology.  Allē Flash is the latest innovation from Allē designed to reward and support members. At launch, offers will be for a range of Allergan Aesthetics treatments at varying values and windows to redeem. Some scans might return bonus points for more than one treatment, while others might see dollars-off filler, neurotoxin, or even their favorite skincare product. The offer inventory will constantly evolve and adapt to consumer purchasing patterns.

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