Customer feedback is key to success to retailers. According to PwC’s recent Consumer Intelligence Survey, three quarters of consumers cite customer experience as an important factor in their purchasing decisions, behind product quality and price.
Delivering a good experience requires retailers to listen to their customers, and act on what they’re saying. Indeed, Morrisons’ chief executive recently suggested that customer feedback was an important factor in the supermarket chain’s three consecutive years of multichannel growth, saying that “listening to customers, responding, and improving the shopping trip are as important now as when we started this turnaround three years ago.”
By monitoring and measuring customer feedback, brands will be better able to respond to customer demands in a timely manner, improve their products and services, protect their reputation, and predict any trends that might impact their business in the future. The challenge lies in measuring customer feedback and interactions across multiple channels in real time.
Opportunities and challenges
For generations, retailers have been listening to the demands and bugbears of their customers. Today’s multichannel environment, however, requires a deep-reaching, digitally focused solution. Voice of Customer (VoC) analytics provide valuable intelligence on how consumers perceive a particular brand. By capturing everything a customer says about a retailer and its products – their expectations, their preferences, their dislikes – VoC data can help that retailer shape its offering, and present it at a price that customer is most prepared to pay. What’s more, by combining VoC data with product data, of which most retailers have many years’ worth, it becomes easier to predict trends in demand and sales.
However, while a recent survey revealed that the majority of retailers consider VoC to be important, fewer than three in five actually plan to invest in it. Given the variety of data that must be acquired and evaluated for VoC to be effective, this is perhaps unsurprising. While it’s relatively straightforward for software to aggregate and analyse structured data such as pricing information, product ID numbers or quantitative data from opinion surveys, it’s considerably less easy to analyse unstructured data which, unfortunately, is where the real insights lie.
Customers of a truly multichannel retail operation will use phone, email, instant messaging and social media to give feedback, make requests or lodge complaints. This information is largely unstructured and written in natural language, which makes it incredibly difficult to merge and analyse, particularly when it is drawn from multiple different sources.
Handling the sheer volume of data produced by VoC analytics can prove challenging for any retailer.
Efficiently and effectively analysing, understanding and gaining value from this information can only be carried out by a machine using a process known as ‘text mining’. This process is particularly important given its ability to read unstructured textual data. As we’ve seen, this data contains more valuable context and insights than its structured, transactional counterpart, by reflecting the opinions, intentions, emotions and conclusions of its authors.
Through the application of AI technology, these machines can learn to read written text and not only identify any mentions of people, places, things, events and time-frames that occur, but also assign emotional tone to each of these mentions. It’s even possible for machines to determine whether a document is based on fact or fiction.
By acquiring and processing thousands of documents and articles every second, these machines are capable of reading at the pace required for VoC analysis to be effective. It’s important, therefore, that as the volume of data generated by VoC analytics will only increase over time, retailers should invest in an AI solution that is able to process immense amounts of data efficiently and that can scale as necessary.
The customer is king, and always has been. According to KPMG, they are also telling retailers how to run their business. The problem is “many brands aren’t listening. They may collect reams of data about what customers do and what they buy, but they’re not paying enough attention to what customers actually want or value most.”
However, by implementing powerful AI-enhanced technology in conjunction with text mining capabilities, it’s possible for retailers to unlock the valuable intelligence provided by VoC analysis, and more clearly understand how their customers feel, what they like, what they don’t like, and how much they’re prepared to pay. This understanding will then, in turn, allow them to better engage with their customers, offering them what they want when they want it, and delivering the experience so important to guiding their purchase decision.
In an increasingly complex and competitive multichannel digital environment, the voice of the customer is the most important guide for any retailer, and one that they should pay close attention to if they hope to not just survive but thrive.