Customer Analytics Software Providers for CX

How Customer Analytics software can help your business

Whilst the exact definition of customer analytics seems to differ, the overall sentiment refers to using technology and data to understand customer behaviour better and then using that information to improve business outcomes.

And if there is part of a business that swims in data, it's typically the contact centre and marketing teams! 

By using customer analytics as an example, you can: 

  • Understand customer's habits and preferences
  • Predict future behaviour and use that data to influence the outcome
  • Identify high-value customers

There are a range of different customer analytics 'types' including descriptive analytics, predictive analytics and prescriptive analytics.

Customer analytics uses a range of techniques, including predictive modelling, data visualization, information management and segmentation, which can sound complicated, but thankfully, customer analytics software solutions make it much easier to unlock the power of your data using easy-to-use software that can automate reports, provide useful dashboards and more.

In discussing customer analytic solutions with suppliers, it can be helpful to know there are four 'types' of Data Analytics:

  1. Descriptive Analytics - used to help answer questions about what happened.
  2. Diagnostic Analytics - used to help answer questions about why things happened.
  3. Predictive Analytics - helps answer questions about what will happen in the future.
  4. Prescriptive Analytics - helps answer questions about what should be done.


What is Big Data?

When it comes to customer analytics software, you may hear the term 'big data'.

Big Data refers to extremely large data sets that may be analysed computationally to reveal patterns, trends, and associations, especially relating to human behaviour and interactions.

When you combine big data with high-powered analytics in a call centre or CX setting, you can accomplish tasks such as:

  • Determining root causes of failures, issues and defects in near-real-time.
  • Determining which customers are more likely to purchase a particular product or response to telemarketing calls (equally much higher sales conversions).
  • Determining which customers are more likely to leave your organisation so you can develop a retention strategy to keep them with your business.
  • Generating coupons at the point of sale based on the customer's buying habits increases spend.
  • Detecting fraudulent behaviour before it affects your organisation.

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