Allergan Aesthetics generates over $1 billion in direct-to-consumer sales by embedding CLV into Allē loyalty program
Using Snowflake, Segment, and machine learning, Allergan Aesthetics relaunched its Allē loyalty program, generated over $400 million in new revenue in 2021, and reduced JUVÉDERM cost per acquisition by 10%.
Background
Allergan Aesthetics faced intensifying competition in the aesthetics market and could no longer rely solely on its physician-facing marketing strategy. The legacy loyalty program had low user awareness and poor ratings. Fragmented data prevented personalized engagement with patients and made it impossible to understand or model the customer journey.
What Was Implemented
- Rebuilt loyalty program (Allē) replacing Brilliant Distinctions
- Segment CDP to collect, unify, and create single customer profiles
- Snowflake as centralized data platform and ML model environment
- Machine learning models (built by Allergan Data Labs, a team of 100+ data scientists and engineers) to predict relevant offers, products, and content per customer
- Twilio Programmable Messaging for real-time transactional texts to loyalty members
- Reverse ETL via Segment to push ML predictions into Braze and other marketing tools
- Allē Flash: highly personalized offers delivered to members in real time at the point of care (dermatologist offices, med spas)
Results
- Over $400 million in new direct-to-consumer revenue generated in 2021 alone - Over $1 billion in total DTC sales driven since 2021 by the new data platform and loyalty program - 10% reduction in JUVÉDERM "completed a purchase" cost per acquisition through ML-optimized social media advertising campaigns - 3M+ actively engaged Allē loyalty users (Snowflake case study) - 6M+ total Allē members across 19,000 practices as of 2024 (AbbVie press release)
Lessons
- B2B2C companies can unlock significant DTC revenue by building direct patient/consumer data capabilities even when the primary commercial relationship is with intermediaries (physicians)
- A unified customer data platform is a prerequisite for effective CLV modeling at scale
- Machine learning for offer personalization and campaign optimization delivers measurable cost-per-acquisition reductions alongside revenue gains
- Legacy loyalty programs with poor UX can be transformed by pairing re-architecture with real-time personalization