By Amanda Rubizhevsky
Shopper Insight is critical for having effective messaging, promotions, programs, and merchandise to drive returns and engagement – all particularly relevant for Retail RDs. Shopper insight can generally be defined as the unique, non-obvious data collected and analyzed in order to improve customer experience, gain competitive advantage, and thus influence the business decision-making process. Essentially it is an in-depth study of the influences and factors related to the retail environment that shape consumers' perceptions and buying behaviors. Here are five terms related to shopper insight all retail RDs should know.
Shopper Marketing is essentially directed marketing at those with spending power, someone looking for products to buy. The shopper is not always the consumer, think a mom (shopper), shopping for applesauce for her child (consumer). Shoppers are the largest group to reach and target.
Syndicated Data: Syndicated retail sales data comes from vendors like Nielsen, IRI and SPINS. This type of data provides a broad perspective by pooling across retailers and brands versus individual store data. Syndicated data enables stores to track competitors and compare. The user-base for this information is broad and includes retailers, brokers and distributors, direct sales and brand management teams, operations and supply chain forecasters, business journalists and more. Having a basic understanding of this data is key to planning successful events and promotions and for improved communication with your colleagues. Here is a great resource. From reports and analytics, to retailer specific tools, SPINS is the leading information and insights provider for the natural/organic and specialty products. Check with your marketing department to see if your store subscribes to this type of data.
Predictive Analytics/ Customer Intelligence takes data collected about customer behaviors (i.e. conversion rate, average order value, recency of purchase and total amount spent in recent transactions) and looks at overall trends like, historic sales, demand, seasonal fluctuations, price elasticity, lead times, and more to determine how to best plan for the next quarter, year, etc. Together, these measurements and more, provide greater insight into the behavioral tendencies of customers. When it comes to generating customer intelligence, three groups come together: retail experts, coders/data analysts, and predictive modelers/data scientists The data helps marketers, researchers, and business analysts paint a more complete picture of their customers.
Loyalty is often defined as a customer continuing to believe that your product/service is their best option. Loyalty means a customer wants to do business with you and does. Some of the important behaviors of a loyal customer include:
Beacons are small, unobtrusive objects designed to blend in with their surroundings. They can be used to track foot traffic, transmit Wi-Fi signals and can send special offers to customers via smartphone or tablet. Here is a great example of how a beacon can work: a shopper is walking past a retail store; if they have the retailer’s mobile app, the retailer can use beacon messages to entice the shopper to enter. Once inside, beacons can make personalized offers, share dietitian provided nutrition information or recipes, speed checkout processes, etc. According to Walker Sands Reinventing Retail, consumers say they are most interested in coupons (52 percent); additional information, including product content and reviews (36 percent); and indoor store mapping showing them aisle layouts and product locations (30 percent), from beacon technology. Yet many have not opted in to such tracking because of concerns about privacy (64 percent), message overload (64 percent) and security (55 percent).