Use Voice of Customer Data to Improve Customer Experience Analytics

Voice of customer analysis provides insight into individual and segment motivations

When McDonald’s Corp. faced slumping growth and customer loss to competitors, marketers at the company listened for signals of customer preferences and needs. For years, diners clamored for the restaurant chain to serve breakfast during lunch and dinner hours. As a result of voice of customer (VoC) surveys, McDonald’s rolled out an all-day breakfast menu and promptly experienced a 5.7% jump in the fourth quarter 2015 same-store sales in the U.S.

“VoC analytics can serve as a useful addition to customer journey analytics, providing insight into the motivations and thoughts of individuals and segments,” said Lizzy Foo Kune, Senior Director Analyst, Gartner for Marketers.

According to Gartner CMO Spend Survey 2016-2017, customer experience is the top area of innovation being pursued by marketing leaders. Empowered with larger budgets and spend directed toward innovation efforts, marketing leaders look to analytics for proof that customer experience investments pay off. VoC analytics is often used alongside customer journey analytics to evaluate the customer experience across touchpoints and over time.

Personalized. People-based. Predictive.

The future of marketing is data and analytics. Are you ready?

Learn More

How to use VoC data

VoC data and insights inform many diverse marketing aspects across customer experience, brand, competitive analysis and product development. These include:

Customer experience: Understand consumers’ level of satisfaction at different touchpoints, motivations for engaging with the website or customer service team, or willingness to recommend the product or brand to others
Brand and reputation management: Monitor and manage brands and portfolios; improve satisfaction, retention and loyalty
Market and competitive intelligence: Understand consumers’ buying patterns and preferences; capture trends and social, political and environmental impacts on buying behaviors; discover what customers say about competitors
Product management: Gather feedback on new product ideas and features; understand price sensitivity; gather feedback on promotions; determine when to retire products

How to capture feedback

Analysts use VoC data for a range of purposes, including text mining for content themes, statistical analysis of feedback in surveys and analysis of the quantifiable data rendered from customer care phone calls. Before data analysis can begin, however, use one or more of three common survey capture methods:

Direct feedback: Feedback is given directly to the organization when the customer knows the organization is listening and may expect a response. This is typically through surveys, complaints, market research or panels.
Indirect feedback: The customer is speaking about the organization but not necessarily to the organization. Communications directly to the company may qualify if the VoC-related content is not related to the reason for the initial interaction. Indirect feedback includes social listening, review sites and text analytics applied to customer care interactions.
Inferred feedback: Operational, behavioral and transactional data is associated with a customer experience, such as website clickstream data, purchase history or contact center data.

To get started, first understand the business requirements for customer experience analytics and how the business intends to use the output. “Then communicate analytical outputs in the form of action steps and specific recommendations rather than general insights,” said Ms. Foo Kune.