The following is a guest contributed post by Thomas Walle, Co-Founder and CEO of Unacast.
What is Proximity Data?
Proximity data is location-based data from sensors that are typically placed in indoor environments. It’s gathered and transmitted most often using Bluetooth technology but also via WiFi, NFC and QR-codes.
One of the most rapidly growing proximity technologies are beacons, which communicate with user’s smartphones at a very accurate level. There are already over 350 proximity companies worldwide and it is estimated that they will deploy more than 400 million beacons by 2020, according to Proxbook, the web’s leading resource for proximity marketing.
Unlike GPS data, which is just raw numbers (e.g. latitude and longitude), proximity data includes a range of detailed contextual information on the user’s real-time movements and behaviors, for example: what store they have visited, what departments in the store and for how long.
How does it work?
Imagine a customer walks into a retail store and is promoted to open an app that she has previously granted beacon access to. From there, there is a variety of ways to send users targeted content based on their data, most easily via simple ‘push’ notifications.
For example, if they’ve previously used their app to research BBQs, the retailer could push the consumer an offer for a discounted BBQ, and even an indoor walking map to guide them to the correct aisle. The consumer’s reaction to those stimuli and the way she explores, or pursues, the retailer’s calls to action are captured by the various proximity solution providers who have deployed the beacons, creating a valuable source of business intelligence.
The best early opportunity for brands to monetize proximity data from in-store beacons to re-target users online, thereby bridging the divide between ‘online’ and ‘offline’ data.
Proximity data is fragmented
Because beacons are ‘offline’ technology they cannot share data with other, ‘online’ data sources easily. For example, there are a diverse range of proximity platforms and proximity companies on the market, in total more than 400 world wide. They capture, tag, define, format, and store data in different ways.
So, in order to connect proximity data with online data, you first need to harmonize proximity data from different proximity platforms. Fortunately, there are API tools to enable the flow of information between the online and offline realms.
Challenges of using Proximity Data
The common challenges associated with proximity data are a) reaching enough people to get a critical mass of it, and b) then using the data to create relevant, timely engagements with users. One perceived stumbling block on the path to maximum reach goes to the fact that users must have a specific app and must have granted permissions for that app to connect to Bluetooth and location-based services (the data suggests less than half of us leave our Bluetooth ‘always on’).
In Asia, where popular retail apps can achieve 40% penetration, that’s not a problem. But in the western world, it’s generally accepted that gaining that level of acceptance will prove more difficult. To that end, many brands are now teaming up with larger 3rd party apps (Shazam is one example) that have a large, embedded reach and a fresh online dataset that is an excellent complement to proximity data.
To move beyond proximity data’s reliance on the app-based experience, Google recently launched their Proximity Beacon API, an open format that allows developers to build proximity data-based experiences right into the Chrome mobile browser, meaning the issue of permission-based connectivity limiting the potential reach of proximity data is about to go away — a major development.
Proximity data needs a framework to unlock its value
Proximity data – fresh, first and connected though it may be – is still just data. To understand it and unlock its value it must first be accessible by and understandable to the right people. Proximity data also needs to play nicely with advanced analytics solutions and third party marketing technologies.
Ultimately, a ubiquitous standard for proximity data definition, transfer, and storage must be developed. This will create a stable global technical environment for proximity data management, and provide the foundation for commercializing proximity data on some form of exchange, similar to those found in the programmatic ads ecosystem.
In the beginning, proximity technology and our understanding of what we could do with the data was about two things: communicating to the right customer at the right time with the right message, and using that data for in-store analytics (how many people entered my store and where did they go?)
In the end, proximity data will reach across all spheres of the user’s existence, online and offline. The technical and market-driver barriers currently limiting the scope, relevance and business value of proximity data will fall away and we will move to a conversation about the user’s total journey across the digital and physical realms — True omni-channel.