Popular Conversation Platform Accelerates Customer Engagement with AWS
A personalized, smooth, and pleasing customer experience has been growing in significance and many companies are ahead of the race in technology and innovation to create a unique and remarkable experience.
The innovative AI based marketing solutions platform was looking to achieve goals of customer retention and engagement with Data Engineering using AWS. They began their data transformation by building a data model that acts as a solid base for enhancing their customer journey.
The growing significance of customer insights
The AI business provides marketing solutions through conversation media marketing. 50 million+ users currently use the services in 100+ languages through intelligent keyboards, animated content, transliteration, and voice to text.
Enriching conversations with a variety of language keypads, GIFs, emojis etc is the core focus of the business.
The marketing platform collects a huge amount of data that primarily comes from customer interaction and engagement through predictive keyboards and helps determine customer segment and behaviour.
The business recognized the significance of this massive volume of data in understanding their customers, focusing on user preferences, accelerating customer retention, and enhancing the customer experience. However, they were dealing with extremely heavy data and the costs for transforming & generating data insights were very high. To leverage the data for customer insights and retention, the AI service provider required the right data transformation solution.
To leverage the data for insights into customer behaviour and retention, the client required an efficient data transformation solution, which would bring the ideal balance between performance & cost.
Achieving Data transformation with AWS
Data Insights Platform
Transforming customer engagement
With an efficient data transformation model, the business can embark on real time insights into customer behaviour for instant decision making, and scale easily to handle increasing data volume.