For the last two years, brick and motor stores have been targeted by a new, customer led shopping strategy called showrooming. The idea is as follows: customers browse through merchandise at a store to touch and feel the products, go home empty-handed, and then head online to find the products they like at a cheaper price. As in-store sales slumped, large chains like BestBuy responded to the challenge with price match guarantees. If consumers could find products at a cheaper price online, BestBuy would match the price and sell you the product right then and there. This of course lead to some headaches, one such example occurred recently where customers were using fake third-party Amazon listings to get Playstation 4 bundles at $90, $310 off the normal listing of $400.
Price matching only addresses one pain-point in the battle against eCommerce. Giants like Amazon are able to use data analytics to track their customers and create personalized marketing strategies that drive sales. With their “item-to-item collaborative filtering”, Amzaon can track what products customers viewed, what they purchased, and the reviews they left. This allows Amazon to create user profiles that then allow them to make highly targeted email and advertising campaigns. Amazon also has a powerful recommendation engine that refers new products based on past purchases. These powerful algorithms gave eCommerce platforms a large advantage over their brick and motor counter-parts. To fight back, physical stores are rising up to the challenge with their own in-store analytic platforms that seek to be just as powerful and effective in driving personalized in-store experiences.
This article will begin with an introduction into location based analytics (LBA) and its use case in retail. Then I will go on to identify other consumer facing industries that can benefit from LBA, and how LBA can be the foundation to building smarter cities. Finally I will drive some thoughts and insights on how the industry for LBA will evolve over the next five years.
Location Based Analytics in Retail
The new craze that is sweeping retailers is the idea of Location Based Analytics (LBA). LBA is an analytics platform that rests on-top of a Wi-Fi or beacon access point. Smartphones are continuously on the look out for new Wi-Fi access points. As customers come close to a store, their smartphones automatically make communication with the store’s access point to find out more information about it. During this communication process, the smartphone itself also gives out a unique MAC address that helps the access point identify the smartphone. A MAC address does not identify personal information such as a customer’s name, email, or address, but with the help of an analytics platform, retailers can now track the smartphone as customers move within the radius of the access point. By tracking the hundreds, or even thousands, of shoppers who move through the access point in the course of a day, retailers are privy to several metrics that they can use to help create better customer experiences:
- How many customers walk by their stores
- How many customers stop to look at their store displays
- How many customers come into the store (Store conversion ratio)
- How long do those customers stay inside the store?
- Where in the store do they go? What do they look at? (Traffic flow)
- How often do customers come back?
The above list is non-exhaustive, retail analytics can be sliced and diced in many different ways to provide a wide breadth of information. These data points are then used to influence operational decisions to improve business. For example:
- Change inventory/merchandise
- Align in-store staffing with traffic
- Alter in-store layouts
- Run A/B testing for different promotions and events
- Influencing purchase decisions by pushing product information (via the retailer’s app) to customers based on the product(s) they are looking at in store. Examples include:
- Pricing and feature comparison
- Product reviews from the store or even from Amazon
- Youtube videos or documentation on how it works
- Options to find a product at another location (for larger chains with multiple stores)
Some retailers take this a step further by using location-based analytics to redefine their marketing strategies. By allowing customers to log-in to the Wi-Fi access point using their Facebook or preferred social network, customers have access to free data usage while retailers can analyze a customers’ social media profile. Combining the analytics collected in-store with interests and behaviors extracted from Facebook, retailers create customer profiles that can allow them to target customers more precisely with offers and promotions that will yield a higher conversion rate.
Applications Beyond Retail
In understanding how useful LBA is to retail, it’s easy to envision how this can apply to other industries. Some examples of other industries and segments that are exploring the use of a location-based analytics service include quick-serve restaurants (QSR)/coffee shops, hospitality, and transportation.
QSR & Coffee Shops: LBA can help the QSR segment and analyze their traffic flow by three important times of the day: breakfast, lunch, and dinner. By analyzing traffic flow and segmenting it by peak hours, QSRs are able to change their operations to cut costs and increase revenues. Examples include opening at a later hour, reducing staff at certain times of the day, and running promotions to boost sales.
Transportation: For bus stations, train stations, and airports, understanding traffic flow is very important to improving utilization and customer service. For customers, Wi-Fi inside an airport terminal is an expectation as many travelers come from international destinations and will look for alternatives to high roaming fees. In this aspect, many airports charge for Wi-Fi access because they know that customers have no other choices, giving airports a direct stream of revenue. LBA can maximize this opportunity by creating in-direct streams of revenue. With LBA, transportation hubs can provide targeted marketing for stores within the terminal and charge for each push notification to a consumers’ smartphone. Airport terminals can even charge airlines to push notifications to their passengers on flight status and boarding times. With the ability to track passengers inside a terminal, airlines can stop paging late customers and directly send them directions to the boarding gate.
LBA can also assist with costs. By enabling LBA, airports and transportation hubs can use their access points to control traffic within their venues. For example, LBA can help improve wait times at airports security. LBA can measure the number of people standing in line and as the line builds up, LBA can notify security to open up a new security checkpoint.
Hospitality: LBA can be instrumental in helping hotels and resorts provide the best customer experience possible. Just like with transportation, many clients will seek Wi-Fi access to reduce data charges. There is an opportunity for hotels and resorts to charge for that connectivity, which they often do. With access points already in many hotels, it becomes easier for the hospitality industry to make the leap to LBA. Data from LBA can influence staffing (staff more employees in dense traffic areas), provide push notifications on relevant value-added services, and identify a loyal customer before they even reach the check-in desk. Evidently, hotels can create a more personalized experience for each of their customers.
Enabling a City of Analytics
LBA will prove useful to many businesses. In isolation, it allows a business to optimize their operations and marketing on a micro scale. This can be incredibly powerful for large chains who have hundreds of nation-wide stores. LBA allows head office to give the power of micro analytics to each store manager to drive new value.
Now what if businesses could take this a step further? If shops, restaurants, airports, and hotels are all moving towards LBA, then what benefits can we get out of connecting all these venues together? The company supplying the analytics platform can tie data together across all venues that are nearby, meaning that a store will know where their customers go over the course of the day. Businesses will know where their customers are coming from and where their customers are going. If a cinema knows which restaurants customers are likely to come from, then that cinema can work in partnership with the restaurant to create a dinner and movie promotion that is highly relevant to customers of both businesses. Another example would be measuring the traffic flow of commuters every morning. If LBA can detect a surge in the number of commuters coming into the city, then the platform can notify shops in the area to expect a surge in traffic outside their stores during the day. By providing this network of analytics, businesses can now harness the power of predictive analytics making them proactive businesses.
Coming Back to Retail: Current Situation and Competition
Currently the low-hanging fruit rests with enabling retailers. In a fiercely competitive industry, using new insights to deliver higher margins is key for survival. As a result, retailers have been open to driving the adoption of LBA. As LBA progresses we are likely to see use cases in transportation hubs and hospitality where access points exist, and buy-in is easier as businesses are already seeing direct revenue from wireless technology. Finally, dense public spaces like malls and city centers are likely to adopt the service to drive better utilization of their public spaces for their community.
The market for LBA looks just as competitive as the retail industry that it seeks to help. Many of these startups, having only existed for the last 3-4 years, have a tough battle ahead of them:
|Company||Founded||Country||Financing to Date ($M)|
|Fancy That (Acquired by Palantir)||2013||United States||N/A|
|Purple Wi-Fi||2009||United Kingdom||N/A|
|Swarm Mobile (Acquired by Groupon)||2012||United States||4.5|
This is only a brief extraction of the number of startups playing within the field. For every 10-15 minutes I spend on the subject, I seem to come across a new startup that aims to provide smartphone tracking analytics to retailers. The products that each start-up offers are relatively similar to one another. Each platform will use either a Wi-Fi access point or beacon technology to track smartphones, and then provide retailers with a cloud-enabled dashboard with metrics and insights on how to improve their business. With so many start-ups creating similar services, I predict that the underlying data is likely to become a commodity for retailers. If that’s the case, then what could be the fate for many of these start-ups?
In the short-term we are likely to see little competition between startups as the market (~715,000 retail firms in the US alone) leaves lots of room for these companies to grow. Startups can choose between targeting clients based on location and business size (number of establishments) giving them lots of options on how to go to market. However, likely over the next 2+ years we will begin to see companies butt heads. When analytics becomes a commodity, startups will win business by either providing more value-added services or competing on price. Value-add serviecs in this case will help businesses turn these metrics into actionable insights. This could include some businesses deploying their own consulting/implementation teams that work with large enterprises to optimize their stores. These value-add services will require significant costs (hiring highly sought after data scientists and retail consultants) which will likely only be offered by the larger companies with the capital available.
The good news for the smaller start-ups is that their existing customers will likely remain with them as switching-costs will be somewhat high. Having to install an access point and the analytics platform over-top may be time-consuming for many store managers. With commodity like services, a price drop will occur across all startups, giving businesses no reason to leave their current supplier unless they seek higher-value. With this in mind, it becomes very important for start-ups big and small to grab as much land as possible over the next 2-3 years. During this time frame, these start-ups are unlikely to interfere with one another, making the cost to acquire a customer lower and the profits much higher. After this time frame, prospective customers will likely be in discussion with multiple service providers. With this, consolidation in the market will take place as larger companies begin to acquire the smaller ones to gain new clients and acquire new talent. A recent example of this was when Brickstream acquired Nomi, a competing in-store analytics service in October 2014.
Brickstream, Euclid, Purple Wi-Fi and RetailNext are currently the largest players in the space who will likely drive acquisitions into 2015 and beyond. Acquisitions will not only drive growth, but will be necessary to stop larger IT players from entering the space. In November 2014, Groupon acquired Swarm Mobile, signaling its intention to compete in the LBA market. Keeping other large players from this space is a game of speed. Who can acquire clients the fastest, grow organically in their current strongholds, and then use remaining cash on hand to acquire the others? Will the four leaders eat the rest? Will a large company like Google make a move before they can consolidate? Or will one of the big four collapse, leaving an opportunity for another younger startup to take its place? Definitely an exciting industry to watch, but even more stressful to be active within.