- Analytics & Modeling - Machine Learning
- Analytics & Modeling - Real Time Analytics
- Consumer Goods
- Equipment & Machinery
- Logistics & Transportation
- Quality Assurance
- Experimentation Automation
- Last Mile Delivery
- Testing & Certification
OYO is a global platform that aims to empower entrepreneurs and small businesses with hotels and homes by providing full-stack technology products and services that aims to increase revenue and ease operations. OYO offers 40+ integrated products and solutions to patrons who operate over 157,000 hotel and home storefronts in more than 35 countries including in India, Europe, and Southeast Asia, as of March 31, 2021. With a unicorn valuation and a pan-India presence, OYO is one of the most well-known and popular hospitality brands in the country. Known for its technology-driven process and a deep emphasis on customer experience, OYO naturally prioritizes customer engagement above all else.
OYO, a global platform that empowers entrepreneurs and small businesses with hotels and homes, was facing challenges in maximizing the impact of their customer interactions across various campaigns. The company runs different campaigns with triggered journeys based on customer action on their app, and it was crucial for them to understand which message variant was performing the best. The results of effective engagement campaigns would reflect in the incremental CTR (click-through rate) improvement, which ultimately adds to the bottom line in terms of new and repeat hotel bookings. However, the process required a lot of manual intervention to configure the better performing variation and maximize its use. This was particularly difficult with automatic trigger and period campaigns that run for longer durations. Additionally, it resulted in the loss of CTR during the initial stage of experimentation.
To overcome these challenges, OYO implemented Sherpa, MoEngage’s proprietary machine learning engine, which allowed the team to complete the testing and optimization quicker and in real-time. Sherpa automatically maximizes campaign performance by predicting the right message and optimizes the percentage distribution in the variations to maximize the CTR from the campaign. With this machine learning-based feature, the message variation with chances of highest interaction is intelligently predicted on the fly and sent to customers to maximize engagement. Post the implementation, Sherpa automatically assigned message variations to the customer segments who qualified for a campaign and optimized the distribution across the variations based on their performance, for the duration of the campaign. The team at OYO predominantly used Sherpa’s content optimization capabilities for triggered campaigns.
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.