Mitesh Chandorkar, Data Science Architect, with:
Aviva Team - Simon Sinfield
Wipro Team - Richardson Jebasundar, Narinder Saini, Nitesh Panda, Sohel Kadir
Country: United Kingdom
Aviva is a British multinational insurance company headquartered in London, England. It has customers across its core markets of the United Kingdom, Ireland, and Canada. In the United Kingdom, Aviva is the largest general insurer and a leading life and pensions provider. Aviva is also the second largest general insurer in Canada.
Customer reviews or feedback are significant part of online journeys of the customers in large organizations with digital capabilities. With growing competition and increased customer expectations, businesses face major challenge in effectively harnessing and analyzing the vast amounts of feedback data generated across various touchpoints.
As a leading insurance provider in UK with millions of customers, Aviva always strive for "Customer First" approach. It was imperative that Aviva understand the customer pain points to make informed decisions and enhance the customer online experience. Traditional methods of manual analysis are usually time-consuming, error-prone, and lack scalability. This can lead to missed opportunities in understanding feedback themes, identifying emerging trends, and thus addressing pain points for improving customer satisfaction.
The key challenges with manual processing were:
Wipro's “AI & Automation” leverages its industry and business-focused solutions to solve the above problems using Machine Learning. The ML solution was built to:
The Machine Learning Solution was built using the Dataiku platform. Aviva has been using the Dataiku platform for many years to build variety of use cases in data and ML area. The key features of this solution include:
The journey to build the solution was challenging due to:
The Dataiku platform played a crucial role in the NLP preparation, model trainings experiments, and deployment processes using built-in recipes and custom python code. Dataiku enabled us to perform:
Below is a high-level process flow diagram illustrating how solution works on Dataiku platform.
The Machine Learning solution built using Dataiku had a significant impact on day-to-day business processes. It transformed the way customer feedback data was analyzed and utilized. Below are the keyways in which the solution impacted the business:
Below are few examples of valuable insights and dashboards. Sensitive information is masked for privacy and security purposes.
The following dashboard presents weekly overview of top ten contributors into positive and negative themes.
The trend below shows the weekly comparison of positive contribution percentage for years 2022 and 2023.
The heatmap below offers valuable insights into the weekly percentage change for each theme, enabling stakeholders to focus on the most significant fluctuations across different weeks.
Business Area Enhanced: Marketing/Sales/Customer Relationship Management
Use Case Stage: In Production
The ML solution built using Dataiku generated both tangible and intangible value for the business.
Dataiku provided additional valuable to this Machine Learning solution in various aspects. Below are listed some of these key aspects:
Overall, Dataiku brought value to the solution by enhancing team efficiency, flexibility, no-code and low-code using built-in recipes and models, as well as scaling the solution quickly and insightful analytics capabilities.
We are excited to leverage Dataiku’s enterprise grade development tool for Generative AI to further enhance this solution.
Hundreds of thousands of $