Understanding CX analytics is a critical step in improving customer experience across the enterprise.
No matter what your company sells, its primary product is Customer Experience (CX). Customer experience is what attracts customers, influences what and how often they buy, and has a major impact on customer loyalty and lifetime value (LTV).
According to a Forbes Insights Report, 76 percent of business leaders believe customer experience is vital to their company’s survival
Strategizing and improving CX starts with measurement. Smart measurement and analysis of your customer data can help your brand improve customer experience and build lasting relationships. Here’s what you need to know.
What Is Customer Experience Analytics?
Customer Experience Analytics (CX Analytics) is the collection, processing, and evaluation of customer data to measure and ultimately improve CX. CX Analytics provide actionable data and offer verifiable measurements of marketing successes.
Customer Experience Analytics includes reporting on:
- The best customer market for your business and how to reach potential brand ambassadors and loyal customers
- Feedback, both positive and negative, from surveys, reviews and more
- A complete picture of the customer journey and pain points or roadblocks along the way
- Success rates of your current offerings and areas of potential for the future
Why Should Businesses Care About CX Analytics?
Creating a culture and structure that puts CX at the forefront of your business is the best way to understand your current customers, bring in new business, and build loyalty. CX is directly linked to customer engagement, purchasing, and LTV. CX Analytics produce actionable, measurable, and profitable insights.
CX Analytics touch every aspect of the business, from sales and marketing to customer retention. They’re crucial for proving the value of marketing strategies, surfacing pain points for customers, and making sure you’re meeting customers on the right channels.
Standard models based on broad metrics are not capable of deep insights and are often inconsistent throughout the business. Without CX Analytics, your most valuable insights about customer satisfaction, engagement, and purchasing habits are lost. Results from CX Analytics allow for measurable, data-driven decisions that get results.
How to Measure Customer Experience
Once the decision is made to concentrate on CX as the driving force of a business, the next step is to gather data and measure it using CX Analytics. CX data comes from offline and online sources such as:
- In-store sales and store traffic
- Customer surveys
- Social media interactions
- Site browsing patterns
- Mobile app usage
- Repurchase
- Coupon redemption
- Loyalty program enrollment
- Cart abandonment
Deep customer data analysis is only possible when you can bring together all these disparate sources to create a single source of truth. It’s a process that would be nearly impossible to do manually, but the right Customer Data Platform (CDP) can unify fragmented data sources and provide actionable, deep insights.
Unite Customer Data on a CDP for a Unified Customer View
CDPs centralize and unify fragmented customer data into accurate and complete single customer profiles. United customer data can be used to guide decisions about interactions with one customer and to create detailed views of all customers. There are three steps to performing CX analytics with a CDP:
- Collect, unify, and centralize data: CDPs stitch together all of your data sources into one centralized location so that it can be viewed as a whole picture, not just disparate snap shots of specific segments.
- Validate, clean, and update: The heart of the CDP is the Single Customer View (SCV). SCVs are a whole picture of a customer with all data from every touchpoint. The data is “cleaned” by removing duplicates, blank fields, incorrect or outdated information, and creating one profile for each customer. SCVs are essential for tracking current CX and informing future decisions.
- Produce deep insight: CX Analytics highlight channel preferences, touchpoint efficacy and engagement and inform forecasts around CLTV, loyalty and avenues for new business. CDPs and SCVs can guide communication and ad strategies for groups or individual consumers.
Spot Trends and Surface Insight Using Intelligent Data
Intelligent data processing not only produces a picture of current CX, it can provide valuable insight about trends, pain points and campaign successes or failures. Intelligent data processing also yields crucial information about how to gain new business, streamline and reduce costs for advertising and zero in on the most profitable strategies.
Executives get a bird’s-eye view of marketing activities, as well as ROI across regions and product lines. Strategists can quickly glean customer insights to build more effective plans. Lastly, campaign managers can see which audiences, channels, and messaging are driving the most revenue and ROI.
