Hear the Voice of the Customer in Retail: Why Use VoC in Retail Analytics

Traditionally, retailers have focused more on brand experience and customer experience (CX) to understand customer relationships. Commonly used metrics, such as CSAT and NPS, have allowed businesses to gauge how shoppers feel about certain brand products or services. However, as time progresses, these metrics become not enough. Retailers that really want to succeed today need more. They need data. 

“The future belongs to those who can collect, aggregate, segment, integrate, visualize and interpret data.”

– Vint Cerf, American Internet Pioneer

Let’s begin with the meaning of “retail analytics.” It involves a company’s discovery, collection, and analysis of retail information or data. Such a process utilizes data specifically related to inventory, supply chains, consumer demands, marketing, sales, and more, to make the right marketing and procurement decisions. 

Retail analytics is not just about having the data; it is also about knowing how to leverage big data and realizing its potential.

Your shoppers are constantly leaving their product or service ratings and reviews. Let it be sharing feedback over the phone, within conversations with a customer service chatbot, in emails, surveys, on your eCommerce product pages, etc. In turn, tons of feedback (voice of the customer) data accumulates daily, most of which is unstructured.

However, VoC data helps businesses gain a detailed understanding of customers’ demands and expectations. Aside from the NPS and CSAT, VoC data is an additional resource for capturing the full ‘customer experience’ picture. Unbeknownst to many retailers out there, VoC data contains a wealth of potentially valuable insights, and it is the retailers that strive to dig deeper through the untapped gold mind – those who seek to properly utilize VoC – will capture the end-to-end customer journey.

VoC insights, if and when properly leveraged, can help transform the retail process – from sales to delivery and service – and improve both brand and customer experience. Advances in technology have made it all possible, particularly with artificial intelligence. With the right retail analytics tool to listen to the customers, retailers can see that VoC empower business in the following ways:

Involving the voice of the customer can help you better understand your end-to-end retail campaign impact and deliver more effective marketing and sales strategies. In turn, higher revenue. For instance, through artificial intelligence technology and natural language processing, you may discover that many of your shoppers have been talking positively about a certain in-store display that they like. Based on this key knowledge, you and your teams are able to replicate the success of the results and improve on the existing displays while generating new and similar ideas for future productions. 

The massive volume of retail data may be intimidating for most analysts, especially when they need to consistently mine through the unstructured data without errors and deliver accurate results every time. However, retail analytics technology driven by artificial intelligence can save various departments time and money. For instance, your R&D team can spend less time crunching the numbers since the AI is designed to automatically collect, sort, and analyze data round the clock. Instead, market analysts can spend more time drawing conclusions from the insights (also generated by machine learning and fully accurate). Meanwhile, product marketers have all they also need at their fingertips to improve existing campaigns rather than re-doing them, saving time and costs.  

What significant reasons or factors keep your customers returning or even from returning? Which in-store product rollout was most effective, and why did a certain product not meet sales goals? How about other retail competitors? What are your customers saying about them? Modern text analytics tools, such as Wonderflow, can help companies identify those small yet impactful details mentioned among the ever-growing number of online reviews. Such details are often missed by the human eye. These insights may relate to the logistical and operational side of things, plus others, to help retailers deliver a better customer experience.  

Retail analytics is here to stay. Between 2019 and 2025, the global retail analytics market is forecasted to grow at 18%. Within five years, it will be valued at more than $9.5 billion. 

In a 2022 press release, Gartner predicts that 60% of organizations will supplement traditional market research methods with analysis of customer interaction data like voice and text data.

In our continued and strong partnership with a multinational retailer, we have a leading example of how the client was able to save its first (TV) product launch by leveraging analytics. The retailer used our unified and AI-based text analytics platform to uncover several key consumer preferences. Not only did they experience sales increasing by 12% for the second rollout and a 23% increase in conversions, and TV ratings scored near 4.3 stars on average. Read the full success story here.