Ditch the Silos to Better Serve Your Customers

Nearly 200 customer experience experts shared their knowledge for CX Network’s annual report, The Big Book of Customer Insight and Analytics. Here’s a snapshot of the major trends developing around the use of data in CX. Data Silos as a Challenge: Data silos are identified as the most significant challenge regarding customer data, cited by 46% of respondents.

These silos can lead to internal inefficiencies. Scott Draeger, a customer experience officer at Quadient, suggests that unifying the business around personalized experiences can break down these data silos and lead to cost savings and increased Customer Lifetime Value (CLV). Feedback Data and Personalization: According to the survey, for the second year in a row, 41% of respondents consider process improvements based on customer feedback data as a significant source of personalization efforts in their businesses.

This highlights the importance of feedback data for enhancing customer experience. It also indicates that more than half of businesses don't share this perspective. Gathering customer feedback without using it for CX improvement is counterproductive.

Challenges with Feedback Data Usage: Draeger suggests that the lack of visibility and communication across departments could hinder businesses from effectively using customer feedback data. He recommends interdepartmental sharing of feedback to avoid data protectionism, which impedes accurate reporting of CLV and profitability. Predictive Analytics Adoption: The adoption of predictive analytics to enhance customer experiences is not widespread, with 77% of businesses stating that they haven't implemented this technology yet.

However, 38% of those not currently using predictive analytics have it on their radar for potential future adoption. Advantages of Predictive Analytics: Draeger highlights the benefits of predictive analytics, which categorizes customers into personas and aids in targeting marketing and sales adjustments for optimal outcomes. The dynamic nature of predictive analytics allows for real-time responses to changes in the market, leading to effective customer onboarding and guiding future customer journeys.