In the past few years, location and proximity data have completely transformed the retail environment. The shoppers’ experience can now be highly personalised to both the brand and individual’s needs. Apps use beacon and WiFi technology to pinpoint a user’s location, highlight the relevant discounted offers in stores nearby, and send a push notification providing a truly contextualised offer.
But what is the next step in this scenario? And how can this data be employed further to offer new and fresh marketing insight?
Giving back: what's in it for the consumer?
While many brands are seeing the value of understanding a customer’s whereabouts, there are still very few brands who are using the information for the customer’s benefit. If this is done effectively, brand loyalty and NPS will undoubtedly improve, as you’re offering a slice more than your competing brands, and making people feel truly valued.
For example, in the US, Barneys have digitised their Manhattan store by creating an app that provides all the benefits of proximity marketing, as well as offering recommendations to nearby restaurants and attractions. This cleverly positions the app as less of a marketing tool for Barneys, and more of a local guide for the user. This aspect is very topical considering the changing personal data regulations in 2018. As a result of the current climate, apps that require personal data will need to strike a careful balance between the volume of push promotions, keeping the customer happy, yet doing enough to gain value from implementing beacons.
The next level of contextual marketing
Equally, Swirl and AccuWeather have partnered to provide something extra to subscribers. Swirl is a mobile location-tracking platform used by brands. Their clients will now have access to AccuWeather’s weather data, which they can use to offer personalised in-store experiences based on local weather conditions. Swirl’s platform uses beacons, WiFi and Visible Light Communications to determine a user’s exact position in-store, and use that information to provide weather friendly offers, such as cold-weather clothing discounts during a cold snap. This is another example of brands offering a little extra to those who subscribe to the app, and proving they are thinking more intelligently about pairing their products to consumers' needs.
Attribution and audience measurement
Data collected through proximity and location-based marketing can be used to great effect in terms of understanding consumers, and whether a campaign has truly raised awareness of the brand and brought consumers into stores.
'Placed', a location analytics tool, chose to work closely with a fast food advertising company, to ascertain the effectiveness of a specific mobile marketing campaign. They found that, of those exposed to the ad, 42.6% of the consumer group were more likely to visit the restaurant than the group who were not exposed to the ad:
352,773 visits to restaurant after ad exposure (14 day conversion window)
42.6% lift in restaurant visits compared to non-exposed group
I think most people would agree that such a considerable jump in attribution is an incredibly positive result for proximity marketing.
Lastly, location and proximity data provides a useful snapshot for audience modelling and measurement, not only offering vital information on who is using your app, but also how to target them more intuitively. Through the case study above, the advertiser was able to establish which segments reacted positively to the ad, understanding age, ethnicity and income brackets. In future campaigns, this information, used alongside location and proximity data used to determine foot traffic and shopping patterns, will allow for even more targeted and impactful campaigns, and therefore more foot traffic in-store as a result.