RetailMarketing

How PetSmart Uses AI Decisioning to Boost Salon Bookings 22%

PetSmart is North America’s largest pet retailer, operating over 1,700 stores and serving 75 million Treats Rewards loyalty members. The company deployed Databricks Mosaic AI with Hightouch’s AI Decisioning Agents to move beyond static campaign calendars and deliver individualized marketing across owned channels. The result was a 22% incremental lift in salon bookings and a 13% improvement in autoship transaction rates.

Outcomes

22%Incremental lift in salon bookings
13%Lift in autoship transactions
75 millionTreats Rewards members benefiting from personalized outreach

Tools & Technologies

1DM
Databricks Mosaic AI
Suite of tools for training, fine-tuning, and serving custom large language models on a unified data platform.
2D
Databricks
Unified data analytics and AI platform built on Apache Spark for lakehouse architecture, ML, and generative AI workloads.
3HA
Hightouch AI Decisioning
AI-powered marketing tool that personalizes customer decisions in real time using predictive audience models.

AI Categories

Challenge

Traditional A/B testing and monthly campaign calendars could not deliver real-time personalization for 75 million loyalty members, leaving the marketing team unable to act on individual customer and pet data that lived in Databricks.

Solution

PetSmart deployed Hightouch AI Decisioning Agents on top of Databricks Mosaic AI, using reinforcement learning to personalize message content, offer type, and send timing for each customer across email and app push channels.

Full Story

PetSmart operates at a scale few retailers match — over 1,700 locations, 75 million Treats Rewards members, and 94% of sales tied to loyalty customers. With that concentration of loyalty data comes an immense responsibility to personalize: every customer has distinct pets, purchase patterns, and lifecycle moments worth recognizing. For PetSmart, generic campaigns were not just an opportunity missed — they were a strategic liability in a competitive market.

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Source

DATABRICKS
April 2026
Original case study

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