Recognizing the Potential in Digital Retail
Digital tools help retailers improve business performance, transform the consumer experience and speed decision making.
by David Woodhead
Retailers have come to realize that customer experience is a moving target. What worked in the past — brick-and-mortar stores with high-touch service — no longer meets the needs of today’s highly networked and time-strapped consumers. And the demands of tomorrow may be different from the expectations of today.
How can companies adapt in the ever-evolving world of retail — one in which they must continually find new ways to serve customers? They can start by using digital tools to revolutionize their front-end technology and their back-end infrastructure. And they can go a step further by investing in data management services that transform the organization to engage in new ways of doing business.
The new customer journey
By deriving insights from recognition and analytics technologies, as well as natural language processing from call center records (see sidebar), retailers can improve business performance, transform the consumer experience and speed decision making.
And speed is important. Convenience is a driving factor in purchase decisions today. Customers expect a retailer’s products to be consistent and visible across multiple channels, and they embrace interactions that promote real-time, personalized attention to their buying needs. They will even share personal data to enable this conversation.
This type of consumer requires a completely different approach to the day-to-day business of retail. And not all retailers have successfully adapted.
The way forward
Picture a solution that delivers multifactor customer identity authentication (combining biometrics such as face and voice recognition) on the go — and even, potentially, in the store — to speed up the checkout process. This convenient and secure tool can help retailers close the deal more often on items put in a shopper’s cart.
By linking this system to a powerful, segmented in-store and online analysis of consumers’ behavior, we can unlock limitless opportunities to improve the customer experience. Retailers can use these actionable insights to improve their marketing and other efforts, and they can help shoppers — embracing the convenience and personalized attention — further invest in their relationship with the company.
The solution can improve decision making across a whole spectrum of important areas. Companies can use customer preferences to better predict assortment needs, stock and labor demands, for instance, which can lead to reduced costs, as well as margin and revenue improvements.
While best practices are emerging, there is no one-size-fits-all approach. Companies need to evaluate their current processes and decide which steps will lead them to the digital future.
Whatever the starting point, retailers need to take advantage of digital investments that can produce a truly omnichannel approach.
‘How Can I Help You?’
Many companies have invested in sophisticated omnichannel contact centers that allow customers to reach them by phone, email, social media or other means. But because many of these interactions are unstructured, companies gain little insight into what customers really need and how they behave.
By applying natural language processing to customer emails, tweets and interactions with contact centers, businesses can tap into a wealth of new insight.
CSC recently performed this work for a large water utility. Although contact center records provided an excellent source of data, they were difficult to work with and did not always capture the full reason for a client call.
CSC addressed this with a data scientist-led customer intelligence project. The method required four steps to analyze call center communication:
Stop-words elimination. This consists of taking out common words such as “the,” “Mr.” and Mrs.” that do not contribute to the meaning of a sentence.
Stemming and lemmatizing. These are linguistic techniques for organizing the data; for example, recognizing that “payment,” “payments,” and “pmnt” likely mean the same thing.
Tools and algorithms. These include natural language processing, text analytics and visualization tools.
Benchmarking, analysis and resolution. This includes benchmarking success and then targeting calls that fail to meet this mark. By assessing the calls and alerting the business to take immediate and informed action, the company can prevent negative customer satisfaction in the future.
An effective analytics strategy guided by this process has the power to transform customer satisfaction, highlight opportunities for upsell and cross-sell and increase operational efficiency. It can truly take customer response to the next level.
DAVID WOODHEAD is a partner in CSC’s consulting organization.
DR. NINA WEINA JIANG, a senior consultant with the consulting organization, contributed to this article.