Retail Analytics for Malls: 5 Key Metrics that can help Increase Customer Engagement
March 17, 2016
It goes without saying that few industries are changing as rapidly as today’s retail sector. Faced with a still-turbulent economy and increasingly demanding consumers, rise of innovative technologies such as proximity marketing have helped malls and retailers to stay relevant and competitive by employing a data-driven approach to measuring the behaviour of their shoppers. So much so that, according to Lightspeed’s Retail Technology Adoption Report, 26% of retailers said that they plan to use data analytics to make better buying decisions by the end of 2016.
The purchasing decision journey of consumers involves multiple points of contact, many of which are now being captured, digitized, and transformed into metrics and data by most in-store analytics solutions available in the market. As this data becomes an implied derivative of essential retail and consumer technologies, the focus is shifting from how to acquire the data to how to extract insights from it— insights that can be turned into competitive advantage for the retailer and a better shopper experience for the consumer. This is where beacon analytics for malls come into the picture.
Not only can beacons help malls gain insights on visitor distribution over various zones within the malls, but also help highlight the paths taken by shoppers, dwell time at various zones, repeat visit patterns, and much more.
In this blog we will discuss in detail about 5 key metrics that can helps malls draw more customers in-store while increasing customer engagement.
But before we dig deep into the metrics that matter, one factor worth noting here is that many of these metrics are used by malls across their entire layout to measure a key performance element that, either on its own or in combination with other metrics, quantifiably improves their ability to manage the business.
1. Traffic/Footfall metrics
Tracking visitor traffic patterns within the premises of the mall provides insights on mall activity trends, peak periods, and some top-level impact assessment of variables such as weather, holidays, and promotional events. For example, malls could use beacon analytics data on visitor traffic to assess the impact that commercial propositions like pop-up exhibitions, product launch events etc., have on drawing more visitors to the mall. Shopping centres could also use this mall level footfall data to gain insights on the best timings to run daily marketing campaigns to drive consumers in-store.
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A good example of the critical role played by traffic metrics is how a retail analytics solution helped the Kamppi Shopping Centre located in the heart of Helsinki, Finland, to better understand their target audience. For a long time, the marketing team at Kamppi was operating under the assumption that post work hours and evening time was the period during which most of the highly engaged and valuable customers (those who spend the most time at the mall) walked in. Leveraging a retail analytics solution to analyze the traffic patterns helped them discover that the longest dwell time was measured around lunch. They learnt that people who came to the city to run their errands or attend business meetings ended up spending their time at the mall rather than heading back to their office.
The marketing team had also assumed that catered to a different visitor population from Monday to Friday compared to weekends. The retail analytics solution helped them discover that the consumers who kept returning to the mall fell under the same demographics, regardless of the day of the week.
Malls can also use analytics data on visitor traffic to compare the popularity and performance of different retail store locations within a shopping centre.
2. Heat maps
One of the factors that plays a critical role in enhancing the layout of malls is having a sound understanding of customer flow. This is where heat maps, another beacon-enabled feature comes into the picture. Such heat maps of entire malls can help track consumer movements within the malls and identify hotspots and bottlenecks in the layout. Malls can then use this data to assess the impact of layout changes, digital signage boards and proximity marketing campaigns on consumer engagement.
Heat maps can also help malls identify zones that are most trafficked. They can then use this data to help revive low-traffic areas within the mall by setting up a food joint or a pop-up store of a popular brand or by simply shifting a high-visit store to those zones. Another way of going about this is to enable pull messaging via the mall’s app by making beacons prominently visible to consumers in such high-traffic zones. This can help visitors discover retail stores in low-traffic areas that they would have otherwise never come across.
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For example, instead of pushing coupons to shoppers based on their location in the mall, Herning Centret, a shopping mall in Herning, Denmark, created ‘Coupon Zones’ (in which beacons were prominently deployed) where shoppers could walk in with their phone to receive coupons from nearby retail outlets. In order to capture the attention of the visitors, these Coupon zones were marked with yellow circles on the floor with a banner above. As a part of this campaign, retail stores in Herning Centret provided their customers with some special, time-limited coupons, which were shown via the app at the Coupon zone.
3. Zone interdependence/ Zone-to-Zone conversion metrics
Analysing cross-store visits will help malls understand and reorganise the positioning of stores to maximize consumer distribution and convenience during their visit. For example say Vero Moda and Sephora are a pair of stores that attract visits by the same customers in the mall. Then the marketing team at the mall can use this beacon analytics data to their advantage by positioning these stores near each other with maybe two low-traffic stores in between. This will not only make it more convenient for customers to move around the mall but also increases the chances of them walking into one of those low-traffic stores.
Shopping centres can also use beacons to measure mall-to-store conversion – the share of mall visitors entering each store. This data will come in helpful when it comes to tracking the real-time impact of in-mall ads and in-store marketing campaigns on consumer engagement. For example, retailers can use mall-to-store metrics to observe visitor patterns just outside the store and gain insights on the impact of window marketing at driving more visitors in-store.
Yet another way in which malls can put beacon analytics to use is to look into repeat visit patterns and understand how loyalty patterns could help enhance those visits. When it comes to active customer engagement, there’s a whole new dimension of personalised in-store engagement that is possible via a loyalty/mall app. Retailers could use this app to their advantage by identifying the location of users who have opted in for location-based services via the beacon-enabled app and using their shopping profiles to deliver targeted promotions. For example, say a visitor’s favourite brand is Levi’s. The brand could use the mall’s app to push an ad asking him/her to come checkout the latest denim arrivals, as he/she walks by a Levi’s store. This way brands at the mall could use the app to drive more visits to their store.
5. Attribution metrics
When it comes to driving revenue for malls, public advertising spaces within the entire layout have always played a critical role. And when it comes such digital signage boards, measuring ad display attribution is key to optimising locations and timings, and picking the right content dynamically. The metrics that play a critical role here are:
(i) Visit pattern data is used to determine areas with most visitors per hour, to zero down on the best locations for ads.
(ii) Path analytics data is used to track the impact of ads. For example, this beacon analytics data will help brands gain insights on whether the store’s ad elsewhere in the mall drove additional visits to the store. Adding on to that, malls can also track shopper’s dwell times near ad displays to measure the effectiveness of ads. This data can further be used to decide on the pricing of the various advertising locations at the mall.
(iii) Anonymous customer profiling data is used to cue the content of digital signage. For example, say a customer who frequents shoe stores walks by a digital signage board. Malls can use beacons to push a shoe ad of that visitor’s favourite brand on the digital signage, as he/she walks by.
This novel approach was demonstrated by SapientNitro at NRF 2015. They introduced passive beacons that could tap into the mobile device in a consumer’s pocket and leverage location information along with the loyalty profile of a consumer approaching the screen to personalize content on a nearby in-store screen.
Focusing on the various metrics mentioned in this article will help malls dig deeper into the data and combine different metrics to get a full view of the overall performance and marketing ROI. Are there other metrics that you think are critical for increasing customer engagement in malls? Let us know in the comments below.
If you are planning a beacon pilot, take a look at Beaconstac, that includes everything you need to get started. Using Beaconstac you can set up your own campaign, without a developer’s help!