Case Study: Customer Segmentation

Driving Digitalization With AI-enabled Analytics

  • Inspirient analyzed CRM data for Nitro, a public relations and marketing communications consultancy
  • The system automatically identified customer segments, which were previously unknown
  • The detected patterns helped deliver a more focused marketing communication strategy to their client
  • This shows how Inspirient enables marketing agencies find valuable insights for their clients faster
Customer interaction
Key use case figures:
  • 5 tables extracted from client CRM
  • 2.2 million customer records
  • 3.9 million communication transactions
Sample insights
Major insights derived by Inspirient:
  • Summarized client’s loan portfolio
  • Segmented loans by categories such as age and gender
  • Conducted analysis of marketing channels

Innovation and Benefits for the Customer

Nitro was enabled with a ‘quick look’ into the data and report on interesting patterns, outliers and trends, so that, from the get-go, they can start generating and prioritizing data-informed hypotheses about their clients. This AI-supported process enables a leaner and more agile approach that cannot be achieved with regular business intelligence tools, meaning that Nitro can begin their projects with a better understanding of their client and can iterate through prioritized hypotheses at a faster rate. The result — higher value insights and reduced risk of missing the obvious!

Enablement through AI-enabled Analytics Workshops

Inspirient's Automated Analytics Engine was used to automatically process and analyze 5 sets of raw data extracted from a CRM database of an international lending company. Two of the datasets were substantial in size, containing 2.2M customer records and 3.9M communication transactions from 2010 to 2017. Together with Nitro's team of data scientists, we reviewed and prioritized the automatically discovered patterns in the data to help Nitro come up with a more optimal marketing communication strategy for their client. As a result of this workshop, Nitro's team of experienced data scientists were able to spend 80% more time on targeted deep-dives, since the data exploration process was fully automated with Inspirient's Automated Analytics Engine, which equated to more value for the client.

Conclusion

The presented case is an example of how Inspirient’s insight discovery worksop can be used by marketing agencies to help deliver more valuable insights to their clients. The use case described here demonstrates how Inspirient's Automated Analytics Engine can be used as an additional team member on a consulting-based project to surface hidden insights when it matters most — at the very beginning! With this service, Nitro were able to generate data-driven hypotheses rather than relying on assumptions before having their team of data scientists carry out the deep-dives, which resulted in lowering the risk of missing the obvious and spending less time on wrong assumptions.

If you would like help discovering strategically critical insights for your business, please do not hesitate to get in touch!