Investments in Advanced Analytics Tools Drive Customer Experience Transformation | Teleperformance
Investments in advanced analytics tools drive customer experience transformation

I recently read a great article focused on the process of capturing value from customer data by the COO of customer experience (CX) consulting firm Praxidia, Ian O’Donnell, This is an important topic because I am often asked about how to justify the investment in advanced analytics tools. Executives see that there are CX benefits, but they often find it hard to create a direct link between fantastic CX and the investment in analytics.

Ian’s article draws on research by McKinsey, highlighting several key areas of data analytics that executives need to understand. One of the most important points was how to capture value from the data that has been captured. Of course, the ways in which data can be used to create value are limitless and depend only on your business area and your imagination, but Ian gave ten excellent examples that I’d like to repeat:

  • Fraud prevention. With data available on genuine customer behavior, it is easier to flag up genuinely unusual behavior as potential fraud, rather than relying on very rigid or fixed rules, such as customers not being in their home country.
  • Make the customer’s life easier. By knowing more about what they like you can make their path to the product easier and more streamlined.
  • Increased loyalty. An easier experience with better personalization leads to increased customer loyalty.
  • Automated feedback from social networks. Instead of relying on surveys, you can use a Big Data approach to constantly monitor anyone saying anything about your brand or products.
  • Personalization. Ensure that your interactions are shaped by knowledge of the purchase history and former behavior of this customer.
  • Recommendations. Create new sales opportunities by recommending additional relevant items.
  • Improve retention. Reducing churn is important for many subscription businesses and an ability to predict those customers who may soon leave allows for interventions.
  • Test new products. A detailed knowledge of your customers allows you to choose ideal beta testers for new products.
  • Improve the customer journey. A combination of streamlining the path to purchase and offering relevant products and advice creates an overall improved customer journey and experience.
  • Predict customer behavior. The ability to predict customer behavior based on data is extremely powerful because it allows you to constantly improve the customer journey based on what the customer is likely to do.

The clear point from this list is that it should be possible for any executive to draw a line from the process of data collection and then analysis to specific business actions that either increase sales and revenue, promote customer loyalty, or promote customer retention.

Recent research by Harvard Business Review Analytic Services features some fascinating insights into the trends in spending on data analytics and exactly how many companies are making a link between improved analytics and improve CX. The HBR research features highlights such as:

  • 70% of enterprises have increased their spending on real-time customer analytics solutions over the past year.
  • 58% of enterprises are seeing a significant increase in customer retention and loyalty as a result of using customer analytics
  • 60% use real-time customer analytics to improve customer experience across touchpoints and devices is extremely important today
  • 44% of enterprises are gaining new customers and increasing revenue as a result of adopting and integrating customer analytics into their operations
  • 39% of enterprise execs consider IoT an important technology today for improving customer experiences increasing to 55% in two years, making it one of the fastest growing systems for customer analytics.

The HBR research indicates that 60% of enterprise business leaders say customer analytics is extremely important today. If you project out to 2020 then that same statistic is 79%, with one of the key drivers being the ability to personalize CX at large scale. This intention to personalize CX at scale by fine-tuning all customer interactions based on the preferences of the individual is often used in high-achieving enterprises to offer recommendations, upsell products, and adjust prices or create offers based on what the customer is likely to respond to.

In my mind, the message is clear. As Ian’s article noted, there are a large number of different areas where your business can improve CX through investing in data analytics. The HBR research shows that most enterprises are focusing on personalizing their service and also that most executives can now see the connection between data analytics and great CX.

Let me know what you think about the connection between great CX and data analytics by leaving a comment here or get in touch directly via my LinkedIn.

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