• April 28, 2016

Put Customers to Work for You With Predictive Patterns

There’s no doubt mobile access, social media, and an abundance of apps that deliver price comparisons and more to your fingertips have tipped empowerment to the customer’s side. Customers have become so adept with these digital tools that they now dictate the terms of the exchange. They track down what they want, relentlessly compare features, offers, and prices, and select the terms of delivery. They rave or grouse about the experience in comments sections and through their favorite social media channels.

Enterprises have had to pivot rapidly, developing analytics and data management strategies to generate insight into their customers and recover footing. Successful execution of these strategies requires creative thinking and novel tactics. It means harnessing the power of collated data sets to generate predictive customer behavior patterns. The upshot? With the right tools and processes, it’s possible to create experiences so finely tuned to customer preferences that the customers become caught up in it.

Endless Capture

L’Oréal’s Makeup Genius app engages users by allowing them to virtually try products before buying. By transforming the front-facing camera on a mobile device into a virtual mirror, the app uses advanced facial mapping technology to overlay L’Oréal products and shade variances. It delivers rich real-time responses, learning customer preferences while refining the experience by incorporating the preferences of similar users. An initiative spawned from the company’s digital transformation strategy, Makeup Genius drives sales and loyalty across L’Oréal product lines.

By developing and deploying predictive customer patterns, enterprises can generate competitive differentiators and drive business value. It’s digital gold according to Bloom Reach, a digital marketing platform developer. As stated in a recent Bloom Reach study, 87 percent of consumers prefer to buy from companies that best predict their intent and provide rich, personalized experiences. In fact, these consumers favored these companies over all other competitors.

Engaging the Tools

How can the enterprise build an effective predictive pattern strategy? Start by clearly defining your objectives. Is it to understand the needs of your customers and prospective customers intimately? Ultimately increase customer satisfaction and generate brand loyalty? Launch a new product or service? Discover and leverage cross-selling opportunities? L’Oréal’s Makeup Genius app incorporates each of these objectives. For many enterprises, one or two of these goals may take precedence.

Next, collect data sets that include both internal (calls to customer support) and external (social media) information. Retailers like Wal-Mart leverage sales, pricing, demographic, and weather data to calibrate merchandising, inventory levels, and promotions for each store. Pattern detection engines, for example, can track how minute changes in weather influence customer preferences. Upticks in humidity can increase sales of smoothing hair treatments while dips boost sales of volumizing hair products. Online dating sites like eHarmony monitor user activity to tweak matching algorithms and tease out more accurate predictive patterns. By creatively generating these data sets, enterprises can build out the customer experience.

Consumers increasingly expect companies to engage them with rich, personalized experiences. With predictive pattern technologies, enterprises can markedly elevate their agile stance by learning and adapting to customer behaviors in real time. By optimizing the customer experience through multiple touch points along the engagement process, companies can build loyalty while they generate rich opportunities.

Like this story? Read more about predictive customer patterns.