Originally posted on DMNews
As consumers, we have purchasing opportunities through many channels at any time of day or night. We can buy online, track shipping or make subsequent orders via mobile, exchange in-store and review via tablet. And at every touch point, we’re giving up information about ourselves. Whether it’s our zip code at in-store checkout, our credit card, billing and shipping information online, or purchase history in an app store, we are leaving a robust breadcrumb trail for marketers.
Particularly with the rise in digital commerce, retailers now have access to more data than ever. Instead of a POS transaction, they now have information about which products the consumer looked at and didn’t buy, when they were scared off by a price or abandoned a cart and even what type of mobile device or browser they used. The task then becomes to use all this data to increase productivity and, ultimately, return on marketing investments. Here are some things to keep in mind while laying out your plan:
Happy customers are repeat customers.
Better data management has the potential to mean better customer service but ultimately, that depends on how well the retailer integrates all this information and how they leverage it to drive consumer behavior. Using data to drive campaign messaging will streamline your A/B testing and lead you to more accurate, timely results. Understanding customer data and driving that information throughout the organization will ultimately lead to better customer service and, you guessed it, customers who come back.
Mend the gaps.
For example, why aren’t retailers using browsing and other “non purchase” information to drive response or to upsell or cross sell offers in the call center? There’s an (often missed) opportunity whenever a customer calls, emails or visits a retailer’s website to check the status of, or change, an order. In the channel chosen by the consumer, the retailer has an option to provide an intelligent offer based not only on that consumer’s preferences but also using the vast data the retailer has about consumer behavior in general.
Optimize across channels.
The strategy to accomplish this is simple: provide all your channels (including customer care in this case) with more intelligence to support each customer contact. Give them access to more reliable, easier to use caller information and equip them with offers and messaging that are more likely to close a sale. But do this using advanced analytics and optimization – not the frustrating market basket approach pioneered by consumer goods firms in ‘70’s. Instead of simple correlations, we now have the data and the technology to create a more sophisticated portrait of a persona. Because you purchased gluten free bread you might also want to buy non-toxic detergent. Because you buy organic food, you’re likely more open to a yoga class.
Big data is getting a lot of press and 2013 is all about getting organized, making solid plans, executing and analyzing results – and staffing a team who knows how to handle cross-channel optimization using all this data.