Will Geolocation Really Fuel the Future?

Personalisation is on the tip of every marketer’s tongue – cited by almost half (42%) as a top priority – and they’re increasingly looking to geolocation data for the insight needed to achieve it, writes Paul Maraviglia, general manager, Europe, MaxPoint, exclusively for ExchangeWire.

This isn’t surprising: the ability to pinpoint and trace an individual’s location can provide a valuable window into consumer activities, preferences and, crucially, their shopping habits.

But, while the utility of geolocation data as a basis for personalisation is unquestionable, whether it is being applied effectively to meet targeting goals is debatable ­– and here’s why: 

Fenced in: location isn’t just about proximity

For many marketers, especially those in retail, the most effective use of geolocation data is geofencing. And it can’t be denied that this process (where a virtual perimeter is set up around a location to monitor for, detect, and engage nearby mobile users) does represent an obvious way to leverage digital appeal as a means to drive consumers into physical stores.

Yet there are many drawbacks to relying solely on geofencing. Firstly, it restricts the scale of targeting: messages will only reach consumers who are close to the store and happen to be using their device. As a result, both the pool of those likely to be engaged, and the chances of retailers meeting their targets for in-store sales, are limited.

Secondly, it doesn’t follow that every consumer who enters the perimeter of a certain store is inclined to shop there. For example, just because a commuter passes a Starbucks branch on their way to work each morning, doesn’t mean they automatically want to buy a coffee.

Finally, geofencing accuracy is variable. Although some technologies can determine the location of a smartphone to within 15 feet (close enough to be directly outside a store) others can only do so to within 300 feet in built-up areas. What’s more, geofencing precision is even more reduced in rural areas, as wi-fi and cellular network signals are often weaker.

So, taking such a one-dimensional view also narrows the scope and efficacy of marketing efforts. If marketers want to inspire individuals and hit their objectives, they must expand their horizons.

Taking a 360º perspective

To increase in-store traffic, sales, and customer engagement, marketers need to know more than simply how close consumers are to a store or how often they walk past it – they need to know who individuals are.

While its use for this purpose may not immediately be apparent, geolocation data can offer crucial insight into consumer identity by defining where individuals come from. Pinpointing where a consumer lives can reveal a lot about them, including their household makeup, income and, local purchasing opportunities. This understanding alone can help to serve the right messages for specific individuals; but it is much more powerful when merged with further data layers – such as demographic, offline spending, browsing habits, and online indicators of purchase intent.

In this way, marketers can create 360º profiles that detail unique attributes, and connect online and offline activity, without making individuals personally identifiable. So, instead of waiting for individuals to pass by, retailers can send personalised messages to consumers that pique their interest and encourage them to visit stores.

Additionally, using advanced data management tools, marketers can also build precise audience segments: grouping consumers by neighbourhood characteristics such as age, income, and ethnicity to enable in-depth, yet large-scale, targeting that always strikes the right chord.

Geolocation data has a core part to play in facilitating more effective personalisation; but its success depends greatly on how it is implemented. Marketers need to take a multifaceted view of geolocation data, leveraging both obvious applications (like geofencing) and its lesser-known uses, such as enhancing consumer knowledge. This will not only enable marketers to build a complete view of consumers that incorporates their tastes, wants, and habits, but also creates personalised messages at scale, enticing consumers into stores time and again.

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