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(From Forbes, October 3, 2012) To reach the customer today, retailers need to be effective multichannel organizations. Plenty of articles will tell you that, and it’s true. But what’s often missing is a level of detail and specificity that actually helps retailers understand what it means to be multichannel today. Retailers need to analyze all the data their customers create, and then translate the insights into targeted communications/offers across a range of touchpoints.
Given the near real-time nature of many of these interactions, companies need to embrace predictive analytics so they know not only whom to target but also where and when so that they can will drive sales and loyalty. We’ve seen three flavors of offers that have been very effective in reaching the right customer in the right place at the right time:
■ Location-based offers: Vendors such as Visa have introduced highly targeted location-based offers to consumers as they make purchases at a set of partner retailers. Scan your Visa at a Gap, and get offers for retailers within walking distance. Google has rolled out applications that enhance shopping on-the-go including indoor maps as well as mobile coupons and targeted local search with rich data such as inventory, store hours, and consumer reviews.
■ Behavioral trigger-based offers. Consumer-facing companies have an opportunity to reduce reliance on some third party vendors by getting clear on the ‘triggers’ that ignite an offer and making the offers highly personalized. For example, one retailer has tagged its consumable products with lifecycle purchase patterns and then sends reminders to consumers prior to purchase time. These reminders get enhanced if they identify the consumer browsing online either on their sites or on other sites to make sure they don’t lose the moment of purchase. Other retailers use “comeback offers” for lapsed high-value customers, especially store loyalists whose loyalty has lapsed as they move online. Or online only coupons to encourage consumers to “cross the channel” from store to online.
■ Event or seasonal triggers. This involves mining data for lifecycle events to generate targeted messaging based on an automated trigger engine.Sears, for example, has developed a response model based on weather, e.g. targeted emails on window AC units during a heat wave targeted at relevant zip codes 3-5 days after a heat wave.
What actions have you seen that have been effective for retailers to target their customers?