Marketers are increasingly gaining visibility of consumer behaviour, not only online but also in the offline world.
Location profiling data is the key to this new level of visibility of consumer behaviour, and it’s offering useful insights into how online marketing may be impacting on offline behaviour.
The reason location profiling is likely to be so impactful in the future is that it offers marketers the same kind of insights into offline activity that we might usually only expect to find by looking at web or mobile app analytics.
Location-based audience profiling offers marketers visibility of what consumers are doing in the real world, often helping them to unite it with their online marketing efforts. This allows brands and retailers to seamlessly integrate their digital marketing and offline activities by connecting in-store footfall with online browsing and purchasing. Location profiling can potentially overcome the ‘blind spot’ in attribution modelling: the offline behaviours that have previously been almost invisible to marketers.
The reason location profile data has so much potential is that it may enable marketers to gain understanding of audience behaviour across the entire purchasing cycle.
With an estimated 87% of transactions in the UK and 86% of retail sales in the USA still occurring offline, that’s a huge amount of audience data to shed light on. It’s thanks to the growth in mobile devices that all this data is now available and a number of providers are finding new ways to yield consumer insights from geo-location technology to drive sales both on- and offline.
Location profiling for better decision-making
Location profiling is a tool for making better decisions about online advertising and other messaging in terms of how these impact offline sales.
Location data is time-specific, allowing customers to be reached with very time-dependent messages that are relevant to them at a particular location.
The level of targeting this unlocks could offer savvy marketers cost-effective ways to reach people when and where they’re ready to buy.
Many marketers will find they have better visibility of how online ad exposure relates to offline sales – at present many brands have only the vaguest idea how the two may be connected. This is despite efforts by some of the large tech companies and social media networks to bridge the gap. Google’s Store Visits, Facebook’s Conversion Lift Measurement and a partnership between Twitter and DataLogix also seek to connect the dots between online and offline sales.
Location profiling in this way offers the potential to improve ROI by gaining better visibility of how ad exposure relates to sales. This is likely to include offline advertising, which can also be identified by location.
Location profiling also offers insights into consumer demographics and behaviours, such as how long a consumer’s commute might be and what their working patterns are, whether they visit major supermarkets daily, or less frequently.
All this data is immensely useful to brands trying to reach out to their customers. And of course it’s of particular interest to offline advertisers who now have a better understanding of who might be passing a billboard and when and how these ads impact on their purchasing behaviour.
The Big Data challenge
Location profiling data offers information from multiple perspectives. It’s possible to segment audiences by behaviours such as how often they visit a location in a particular time frame. This might include how often they visit a coffee shop each month, and how long they spend there.
Another way of looking at data is to identify locations by particular characteristics, such as how many parents of school-age children pass an advertising spot each month. All this data yields beneficial information for marketers – with the additional challenge of finding ways to handle Big Data like this and yield meaningful insights from it.
Location profiling tools currently available allow brands to segment users based on their current location and where they have previously visited.
It’s also possible to use location data to push messages at key points and locations, such as offering a drinks voucher to a person who regularly passes the same coffee shop on their commute.
It’s likely the available features will be expanded in future and further possibilities will emerge for both segmenting and profiling customers. Location profiling is another example of the kind of digital innovation that will require new skills and abilities from both marketing strategists and data scientists as they struggle to mine useful information out of the huge datasets available.
Location profiling technology has also been combined with live video and image recognition software. Used in this way, the layered location data can be used to enhance other kinds of understanding, such as where new stores should be located for optimum footfall. This offers potential for more efficiency in business decision-making outside the immediate marketing team. There are also implications for store locations and layouts of the stores themselves.
The challenges of location profiling
Like any kind of data, location profiling is only useful when used intelligently to yield accurate and useful insights.
Time is certainly a critical factor in understanding the data. A hotel marketing manager using locational profiling data to identify who visits his hotel most often has to be careful to weed out the taxi drivers who are dropping off guests from the guests themselves. The data is only useful if it is used intelligently and the insights it offers are fully understood.
Marketing continues to struggle to unite all of its disciplines and location profiling data is no exception. Smart companies will maximise their use of this location profile data, whilst others will struggle to integrate it with other data streams and merge with other technologies such as eCRM. There’s also a considerable cost to all this new technology, with big players likely to be the first to be able to find the funding to embrace the new data possibilities.
There’s also likely to be some debate over the intrusiveness of this kind of technology. Providers such as Placed currently rely on data from opted-in mobile users and the data depends on the co-operation of consumers.
As marketers increasingly make use of location data, consumers are likely to become increasingly aware of the practice and resistance may develop.
There are obvious parallels between location profiling practices and the use of retargeting. Consumers are often highly aware of when they are being retargeted, with some finding it creepy. It’s unclear what kind of legislative response there may be to locational profiling practices.