IndiaTravel and aviation2020 – ongoingMakeMyTrip
Machine learning for personalized proactive campaigns
MakeMyTrip's click-through rates on proactive campaigns rose 20% with machine learning personalization
Problem
MakeMyTrip, an Indian online travel company, wanted to send travelers more relevant messages across the customer lifecycle. Building and training the models for this took time.
Approach
The company built an internal feature store on Databricks to simplify feature preparation and model training. Machine learning models target customers and drive micro-segmented messages such as fare alerts and hotel room availability countdowns.
Results
Takeaway
Targeted, event-based messages gave a measurable lift in clicks over generic campaigns. The page does not say what baseline the 20% was measured against.
Categories
- Industry
- Travel and aviation
- Business function
- Marketing and sales
- Innovation type
- Process innovation
- Adoption
- Off-the-shelf tool or platform
- Evidence
- Vendor case study
Sources
Source summaries
Databricks describes how MakeMyTrip uses machine learning and an internal feature store to personalize communications. It reports a 20% increase in click-through rates of proactive campaigns.
Full details are in the original sources.
