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The similarities between “scan-and-go” and self-search are striking. Shoppers like self-search, and it offers the type of shopping experience they want. It drives revenue through enhanced shopper loyalty and increased basket size. And it improves the bottom line through labor cost savings. No wonder that front-runners like Target and Walmart in the US and Albert Heijn in Europe already offer self-search in their mobile apps.
To make self-search happen, retailers need to get four things right.
The self-search function needs a carrier that allows for seamless integration into the shopping trip. This means either a mobile phone with the retailer mobile app installed and/or a personal shopping device with a dedicated app. Both approaches have unique advantages.
Integration into the retailer mobile app means that self-search can be leveraged and linked to a broad set of available functions, such as product catalogue access, product lookup, shopping list creation, and promotions. Self-search makes the app more attractive and pulls in users, creating new monetization opportunities.
Retailers must take care of a so-called “Store Mode,” though. This means that when the app is opened in a store, it must adapt to that store, feature the available in-store functions at that location, and display the correct store map.
The advantage of using a retailer-owned device for self-search is that shoppers regard it as a practical and safe device to use while shopping and scanning. Not all shoppers are comfortable using their own phones for scanning, searching, and paying.
Self-search requires that both shopper and products are accurately located. Retail chains can consist of thousands of stores, with each store carrying up to 40,000 unique products (SKUs). Given that floorplans differ per store, and that promotions, campaigns, and second placements make stores change their face every day, this clearly is an important but hard nut to crack for retailers. Realograms, depictions of how shelves actually look in any given store at any given time, are notoriously different from planograms—how the shelves were supposed to look.
In our experience with Interact at Signify, product locations can be calculated by smartly combining the available planogram and floorplan data. In order to succeed, retailers must exercise discipline in deploying centrally optimized planograms in the store, as well as in closing the loop when local changes are made. The good news is that self-search can kickstart a virtuous cycle, in which an accurate sync between planograms and realograms enhances self-search, and self-search demands an accurate sync. When planograms and realograms are in sync, planogram optimization will truly maximize sales, and no penalties need to be paid to CPG brands for misalignments.
Effectively navigating a grocery store requires a map that offers an accurate visual representation of reality. This means that retailers must create digital store maps that are launched as soon as a shopper requests direction. Often, these maps already exist as either technical drawings of the building or floorplans that retailers specifically use to plan the layout of gondolas and shelves.
Retailers should partner with suppliers that know how to build simplified and beautified maps from these inputs. In many cases, map specialists go overboard with map features, confronting users with 3D maps that show extraneous information and annotations. When it comes to product finding, simplicity should be the rule. All that’s needed is a simple map showing the shopper’s location, a product’s location, and an accurate, navigable route between the two.
To get self-search implemented, shoppers should be able to accurately position their smartphone or retailer-owned device in real time, such that they can receive directions while on the move. This is where indoor positioning systems come into play. Commonly used systems leverage the radio signals from Wi-Fi access points or Bluetooth low-energy beacons to triangulate the location of a smartphone. Others use earth magnetic field information.
The problem with these systems is that both radio and magnetic field signals tend to bounce, bend, and weaken depending on the number of people in a location or a building’s properties. In other words, they might work for generic wayfinding applications like the ones used in public places such as airports, stations, museums and offices. But they are simply not accurate enough to be used in self-search where shoppers must be guided precisely to one of 40,000 SKUs in a store, each residing in a space only a few centimeters wide on the shelf.
Regardless of the benefits that self-search brings, retailers will have to look for scalable and affordable solutions to implement the four essential building blocks. Where indoor positioning and maps are concerned, lighting can show the way. Signify has developed an indoor positioning system that leverages store lighting enhanced with visible light communication (VLC) to locate smartphones and retailer-owned devices with very high accuracy (<50 cm).
Lighting is everywhere in the store and VLC comes at very limited additional cost, so retailers can make their lighting infrastructure do double duty as an indoor location infrastructure, solving the serious scalability and cost concerns that come with deploying indoor location technologies. In addition to indoor positioning hardware and software, Signify offers software to render and control digital maps and routes as well as the services to create and maintain them.
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This is the second in a series of three articles on the profit potential of self-search in big box retail. The next article will explore how to make self-search happen. For the full read, download our whitepaper, “The profit potential of self-search in big box retail.“
Learn more about how Signify can help you to implement self-search in a scalable and cost-effective way.
