Technological advances have enabled us to target consumers with marketing materials relevant to them in every respect. Not only do we know what they are interested in and the platforms they are most likely to visit, we can also hit them where they physically are at a given moment. This is something consumers want. According to research carried out by Google, four in five want ads pertinent to where they are, and marketers are sensing a real opportunity. In a Posterscope survey of 100 marketers, respondents said location data could improve ROI by an average of 60%. Forrester, meanwhile, estimates that the adoption of location analytics will increase to more than two-thirds of data and analytics decision-makers by the end of 2017, up from less than 50% currently.
However, many are still not equipped to use the location data they collect to its full potential. In another recent Forrester survey, 94% of advertisers said they experienced difficulty working with it, listing an average of four challenges holding them back. Of those surveyed, 30% said they lack clarity around what location-data offerings exist, 33% that they don't fully understand how to leverage location data to deliver relevant messages, and 34% that it's unlikely their location data is even accurate in the first place.
This should not be the case. Key to our ability to target by location is the collection and analysis of data in real time. The rise of smartphones and connected devices means it is now easier than ever to identify where customers are and where they are likely to be in the future. According to eMarketer’s latest forecast, almost 2.4 billion people will use a smartphone this year, an increase of 10.8% on 2016, while Gartner estimates that there will 20.4 billion connected devices by 2020. These provide companies with a scary level of knowledge, from sensors identifying how many people are in a store, through to apps such as Google Maps and Facebook pinpointing our location and blending this with other information they hold, such as likes and purchasing habits, to engage users in real time.
Indeed, in just one visit to a store, a customer will generate more than 10,000 from various sensors placed throughout a store, indicating where they will go and at what point they make the decision to pick up an item, essentially re-creating the online shopping experience for the brick-and-mortar environment. US fashion retailer Nordstrom, for example, has spent millions introducing technologies like sensors and WiFi signals into its stores that enable them to track such information.
There is also a growing raft of tools to analyze this data. The global indoor location market size is expected to swell from $7.11 billion in 2017 to $40.99 Billion by 2022, according to MarketsandMarkets. This is a Compound Annual Growth Rate (CAGR) of 42.0%, and location analytics software is expected to make up the bulk of this. Location analytics firm RetailNext, for example, is tracking over 500 million shoppers per year by collecting data from more than 65,000 sensors installed in thousands of retail stores, using this to provide shops with actionable insights that they can translate into better product placement and marketing solutions.
Impending EU data protection rules, General Data Protection Regulation (GDPR), is also making location data increasingly important. Under the rules, which come into force in May 2018, consumers have the right to modify, delete, and receive data any organization holds on them. Businesses will also have to receive explicit consent from people in order to use their data for marketing purposes - including whether they can send them marketing messages - which can be revoked at any time. This presents challenges around compliance for location analytics, but it also presents opportunities. Marketing messages will have to be even more relevant and useful to consumers if they are going to choose to continue receiving them. As the Google survey mentioned earlier shows, consumers want marketing relevant to where they are, so it stands to reason that the more location-focused, the better.
Furthermore, while there are compliance issues, they are not as serious as with other data. The previous privacy regime defined personal data as name, picture, email address, phone number, physical address or personal ID numbers, for example, bank account numbers. GDPR widens the goalposts to include 'identified' and 'identifiable' data. Essentially, personal data now includes any information that could identify a person, which could include location data. For some, the explicit inclusion of location data within the definition of 'personal data' may result in additional compliance obligations. However, on the whole, knowing one’s identity is not necessary for most location analytics initiatives. It is more about analyzing and reacting to behavior in real time, hitting people with deals when they enter a store and positioning physical materials where it drives purchase for example, so it should push users without requiring personal information.
Ultimately, real-time consumer behavior is primarily about location and its context. The data to understand this is out there, as are the tools to leverage insights from it. As with all marketing efforts, what is required is a greater emphasis on hiring and training data talent, investment in the necessary tools to use it, and a strategy that enables the business to act on the insights provided. Given its importance, marketers in organizations which have a physical operation must build out their approach to data with real-time location intelligence as the foundation from which the rest can be built out. Only then will they truly be able to truly target customers in real time and use their data to its full potential.