AI case study

AvivaCustomer feedback analysis

Manual analysis missed trends in fragmented data. NLP now unifies feedback, cutting reporting time by 50% and saving £10k/mo.

Published|2 years ago

Key results

Monthly Savings
£10k
Time Saved
~50%
Faster Reporting
50%+

Result highlights

Unlock 3 result highlights

The story

Context

A multinational insurance company with a 'customer first' strategy, collecting vast amounts of feedback data across multiple survey sources and digital channels.

Challenge

Manual analysis of survey responses was time-consuming and error-prone, lacking the scalability to handle growing data volumes. The team missed...

Solution
Unlock full story

Scope & timeline

  • 98% reduction in deployment lead time
  • 75% faster time-to-market for data projects
  • Setup time cut from 12 months to 2 days
  • 2,250 internal data and AI users

Quotes

Unlock 4 more quotes

The company

Insurance, wealth, and retirement services provider.

IndustryInsurance
LocationLondon, England, UK
Employees10K-50K
Founded2000

The AI provider

AI and machine learning platform for enterprise data science and analytics.

IndustrySoftware & Platforms
LocationNew York, NY, USA
Employees1K-5K
Founded2013

The implementation partner

Helped Aviva build an ML-based sentiment analysis and topic categorization solution.

IndustryTechnology
LocationBengaluru, KA, India
Employees100K+
Founded1945

Similar Case Studies

Related implementations across industries and use cases

66 AI case studies in Insurance

268 AI case studies in Knowledge Management