Location Intelligence (LI) solutions for the retail industry have been selling like hotcakes. The increased usage of mobile phones and IoT devices has further accelerated the use of LI for retail. The utilization of LI in the retail industry is seen via a number of applications like retail site selection, customer demographics, and targeted advertising. LI is defined as the ability to draw business from the use of location data. A research report published by Wipro suggests that 80% of all data maintained by organizations has a location component. GIS-based tools help in drawing insights from demographic data, which reveals the relationship between location and people.
Foot traffic, aka footfall, is defined as the number of visitors to a site. Footfall analysis helps brick-and-mortar stores gain insights about their customers just like the e-commerce brands. Foot traffic analysis works on the basic principle of foot counts that enter a store. Insights like clusters, the conversion rate from entry to purchase, and time spent inside a store (dwell time) are a few examples. These insights can be compared with the competitors to gain an edge.
Competitor’s footfall can be analyzed by using anonymous mobile location data and detected visits which may not be accurate but will provide an overview. Many retailers use services from companies like Safegraph, Gravy Analytics for their foot-traffic data.
Human mobility analysis
Human mobility is not just limited to footfall to a store but how humans move in general. Analysis of human movements offers solutions like location-based marketing, both online and offline. The targeted advertising specifically aims at increasing the consumer base and retaining the current customers. Methods like print advertisements, flyers, and billboards may still work but to optimize the advertisement campaigns, retailers are investing in building location-based advertising capabilities. This technology integrates location with mobile phones, which provides advertising in real-time.
Mobile location data analysis
Mobile location data defines a relationship between the anonymous user’s location and their activities on their mobile phones. Mobile-based applications usually have permission to track the activities of users across other apps. This enables advertisements based on their location and interests. Firms can get mobile location data via cell phone carriers who provide the data when consumers choose ‘allow’ when prompted if an app or website can use their location. The analytic firms use algorithms to draw insights from the mobile movements and use of applications. Insights like what the customer is searching for, whether the customer is returning to a store, and how often does the customer return are few cases.
Retailers have taken mobile location data to the next level by providing push notifications to consumers when they are in proximity through promotions and ads sent to mobile phones.
Out-of-home (OOH) advertising has been taken a step forward with digital out-of-home (DOOH) advertising. DOOH provides more flexibility for advertisers as it is a channel that can easily be updated online and is not affected by weather changes. There are strong links between mobile locational marketing and DOOH as mobile location data markets itself as an extended brand experience with DOOH. For example, proximity-based marketing tactics revolve around offering promotions and offers based on a person’s location, weather, search history, and time of the day.
IoT and indoor mapping
Internet of Things (IoT) devices help in monitoring, collecting, and disseminating information. IoTs are the hardware that enables the collection of foot traffic data, mobile location data. IoT sensors enable tracking consumer data and sending push notifications based on the location and proximity of devices.
The IoTs work hand-in-hand with geofencing, which can be defined as creating a virtual boundary using GPS or RFID technology which can prompt a reaction if a consumer enters or exits. These devices contribute towards creating and providing a personalized experience for consumers based on their activities. By sending IoT-enabled push notifications, passers-by can be attracted to visit the retail store.
GPS and RFID technology enables brands to track their inventory to each item through the entire delivery process, these technologies allow automatic track inventory and stock levels. Brands like H&M, Decathlon are providing consumers with the flexibility of scanning the QR code on tags of the products to know more and self-checkout. Another upcoming feature is locating a product in the brick-and-mortar store based on indoor mapping and the use of IoTs to navigate to a specific product. This provides greater convenience to the consumer and makes their experience at the store feel seamless.
The ability to track products from one end to another gives a lot of room to wiggle – different delivery routes can be tested. Hence, it is safe to say that IoTs are an umbrella under which there are many application areas.
Retail store location analysis
Location Intelligence also helps in driving businesses as it helps in narrowing down a location for the brick-and-mortar store. It takes into consideration different factors like consumer demographics, consumer behavior, interests, and competitive analysis.
When setting up a store, it is crucial to find an apt location. Earlier practices revolved around relying on broad census and assumptions based on competition for decision making. LI provided a revamp to this legacy process with its analytics backed up by relevant data. Demographic information helps in gaining insights into the consumer’s demand. For example, a market near a society with a larger young population will have a demand for stationery. Consumer behavior can be analyzed via analyzing foot traffic data. This type of analysis can help in figuring out if the store should be inside a mall or easily accessible from a road, LI can help in such an analysis by offering the power to look where and how people shop. LI can be used to gauge competitor’s strengths, market penetration, and share.
By leveraging the use of LI, retailers can make spatially aware decisions, based on both location and market. LI can help in choosing the best location based on the extent of analysis which may be unavailable with other types of data.
Trends in retail space
The retail industry has seen quite pioneering trends in the past few years. These include trends like the rise of social media-based commerce which covers the role of influencers. Stores are coming up on platforms like Facebook, Instagram which makes it easier for brands to tap into a larger customer base.
A trend has been seen where homegrown brands have kickstarted with an online presence and work-from-home model and went on to have physical offline stores. Technology is transgressing leaps and bounds, making advances in augmented reality gives more room for retailers to market their product in online fashion.
Another trend that is being observed presently is the rise of values-based brands and their USP is their ethics and morals as a business. More emphasis is being put on sustainability and the carbon footprints of brands. As more such names are coming up, existing conglomerates who are not so transparent about their brands are unable to get away with concealing any information about their product.
Retail space is continuously changing as technology keeps evolving and makes the consumer’s life more comfortable. New trends are arising in the post-COVID-19 world which will reshape the industry and how retailers work.
Explore more about how location intelligence is transforming the retail industry at Location World Retail digital series, scheduled on 4th March 2021, from 8 AM to 10:30 (PST). At this event, speakers from various countries including U.S., Canada, U.K., Belgium, and Singapore will deliberate on major trends the retail industry is expected to witness in 2021 as well as the role of location intelligence for this industry.
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