India's top ride-hailing firm engaged Codingmart to add personalization to its OTT platform.
In the competitive world of ride hailing companies where it has always been one-upmanship between the top two in terms of technological innovation & building products for consumer convenience and engagement.
The company had conceived a unique idea to engage with customers who are on board the cab to present them with relevant entertainment content that will help hook up to the service and retain customers. The content platform was already built and the aggregation of content has also been in place. The customers will get to consume content that has been curated on the platform during their ride.
Codingmart partnered with the brand and helped augmenting their existing engineering teams. The tech stack was predefined with the company’s existing stack that had seen scale. Java was used in the backend to build the platform while the front end was an android app optimized for tablets.
Customer segmentation played a key role in bringing in personalization where the cohorts were identified using various indices of customers. The customers will be suggested with relevant content during their ride.
1. Customer cohorting – build data analytics systems to identify the customer buckets
2. Content cohort mapping – a platform to map content with cohorts by both manual & automated methods
3. Analytics dashboard – to analyze post engagement data and finetune the mapping
These apps were built on mix of Java & Node JS to facilitate smooth integration between their existing systems that were running at scale. The front end consumer facing app was a native Android app which was built together by our engineers augmenting their team of engineers.
- Java 8
- React JS
- Node JS
- 1 Engineering Architect
- 1 Java Developer
- 1 Team Lead
- 1 Node JS Engineer
- 1 Node JS Engineer
- 3k member closed group
- 10k MVP
- 400M full launch
The roll-out has been extremely smooth and it scaled up very well. The brand received many positive feedback from the media and customers alike for improving their suggestions & increasing the engagement with the customers. Though the company did not scale it up beyond a certain level owing to business reasons, the engineering stack still remains a very robust & a scalable one.