Money-saving consumer-driven media with a time-saving self-service scan-and-bag solution

With 40% of all shoppers using self-service checkout, customers want a fast and easy shopping experience, from scanning and bagging their own items in the aisle to quickly paying at the front of the store.

They also want the best price on the products they choose. According to industry surveys, 40 -70% of all shopping decisions are made in the store. And while there is a staggering 40% decline in in-store coupon redemption (1996 – 2006), 88% of shoppers would use coupons if they were personally relevant and available in-store. Shoppers want and receive instant gratification from in-store from money-saving offers.

Retailers and brand marketers can influence in-store shopping behavior at critical moments of decision with Modiv Shopper. Modiv Shopper offers truly relevant consumer-driven media and retail through a time-saving scan-and-bag handheld for shoppers.

Consumers who use Modiv Shopper have:

Twice the basket size,
16% higher store frequency rate and
18% higher coupon redemption rate than that of general grocery shoppers

With Modiv Shopper,

Brand marketers bring real-time, measurable, coordinated and relevant media targeting to an in-store experience. Offers and content can be contextualized based on a number of factors, including shopping history, redemption history, in-store location tracking and just-purchased items in aisles.
Consumers receive a superior shopping experience, allowing them to save time and money with intuitive self-service scan and bag, running total and fast check-out functionality — all combined with personally relevant savings and offers without manual coupon clipping.
Retailers increase sales, customer loyalty and operational efficiencies through self-service convenience and relevant marketing solutions.

Watch the Demo (Flash)

Download Modiv Shopper Datasheet (PDF; 2 MB)

Find a Store

Watch a CBS Profile

View the IBM/Motorola Modiv Shopper White Paper (PDF; 661kb)

How does Modiv Shopper work?

Shoppers dentify themselves at the self-service kiosk that includes a large display rack with handheld scanners at the front of the store. One cradle blinks, signifying them to remove the unlocked MC17 handheld. The MC17 was developed and designed with state-of-the art Symbol/Motorola technology. As customers shop, they select an item, scan its barcode and place the item in their shopping bag. Customers are encouraged to bring their own reusable bags as a recycling measure.

As shoppers walk through the aisles, they receive targeted offers and advertisements in real time based on their past, present and anticipated buying choices. Since Modiv Shopper is zone-based, the information is coordinated and delivered to customers at the time and location they are ready to make a decision. Modiv Shopper delivers experience-enhancing functionality such as running totals, relevant offers tied to loyalty card shopping history and extra savings. Shoppers can remove an item by re-scanning its bar code. Because Modiv Shopper integrates with POS systems, customers use the self-checkout area to scan the "end of order" barcode, which records the full shopping trip. After paying, the customer quickly leaves with a cart of already-bagged goods and their special savings.

Modiv Shopper includes:

Self-service kiosk that integrates with loyalty card data if available
Cradles containing Symbol/Motorola's MC17 handhelds, which are 9.5 ounces and have high-contrast color 2 1/4-inch high by 1 3/4-inch wide LCD displays
Thumb-oriented key navigation pad, allowing shoppers to scroll through all advertisements and offers as well as view price, regular price, savings, "extra savings," total amount in cart
Campaign management that coordinates and delivers the right targeted offers based on event triggers and relevancy to the right shoppers at the right time
Wireless zone tracking based on specific department and aisle
Media enablement for advertisements and offers:

Trigger, trait and contextual targeting based on purchase history, external events such as weather-related promotions, brand preferences, previous offer-type effectiveness, current activity and current location, etc.

Post-hoc analytics, including store trip reports, impression rates, redemptions rates, customer savings percentages and more