Use Case: Customer Segmentation

Driving Digitalization With Cognitive Analytics

  • Inspirient analysed 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:
  • Summarised 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 is now enabled with a system that can provide 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 prioritising data-informed hypotheses about their clients. This process enables a leaner and more agile approach to data-driven consulting, meaning that Nitro can begin their projects with a better understanding of their client and can iterate through prioritised hypotheses at a faster rate. The result – higher value insights and reduced risk of missing the obvious!

Usage of Automated Analytics

Inspirient automatically processed and analysed 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. Inspirient was able to automatically scan the data for relevant patterns, which Nitro’s consultants were able to use in combination with their team of ‘human’ data scientists to help them come up with a more optimal marketing communication strategy for their client. The use of Inspirient along with a team of data scientists proved successful, since the system could provide the consultants with a summary of key insights within minutes, whilst the data scientists were able to carry out the deep-dives after the consultants had prioritised their initial hypotheses.


The presented case is an example of how Inspirient’s Artificial Intelligence for automated data analytics can be used by marketing consulting agencies to help deliver more valuable insights to their clients. The use case described here demonstrates how Inspirient can be used as an additional team member on a project to surface interesting insights when it matters most – at the very beginning! With this capability, 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.

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