A consumer visits an online or brick-and-mortar store for the very first time. Initially, the merchant knows nothing about this potential customer and thus treats all prospects the same. At some point, the consumer may click on a product or category, or make a purchase. This consumer behavior is likely to trigger a business rule that initiates an action by the retailer. Coupons might be printed for complementary products. An email might be sent offering a discount on a product in an abandoned online shopping cart.
In such instances, consumers are differentiating themselves by their behavior. The merchant, however, is still treating them the same because everyone who exhibits the same behavior receives the same offers. Inevitably the offers made will be more relevant to some recipients than to others, and responses will vary accordingly. Because the merchant doesn’t know anything more about these consumers beyond that they clicked on or purchased a product, there’s no reliable basis on which to make a more specific decision on a more relevant offer.
One of the greatest values of analytics is to provide decision points for determining how to treat customers differently. Analytics provide a reliable means, based on statistically valid data analysis instead of hunches or observational judgments, of deciding what actions to take with your customers. “Will it be profitable to offer free delivery?” “Are we offering a discount to customers who would buy this product anyway?”
Businesses who know their customers analytically make smarter strategic decisions about online/brick-and-mortar store design, merchandising and other investments. Analytics also enable them to implement these organizational-level strategies in individual-level offers. They aim for the “sweet spot” where customer behavior unites with what they need to accomplish.
Choosing the right analytics for the job is becoming a job in itself, however. Numerous vendors have crowded into the marketplace offering a jumble of similar-sounding solutions. Beneath the surface, there are actually significant differences in the analytic techniques being employed, the types of insights they provide and the business benefits they deliver. “One-size” definitely does not fit all requirements. To obtain a substantial return from your analytic investment, you need to choose the right technique for what you’re trying to accomplish.
Over the next several weeks we’ll provide an overview of analytic techniques that are most valuable and the kinds of targeted actions they’re enabling. If you can’t wait for the next post on this topic; check out our Insights white paper on the topic: "Which Retail Analytics Do You Need?" (registration required).