In a recent post I discussed why and how beacons play an important role for upcoming years in the advertising industry.
Simply put, beacons provide accurate location intelligence. And by connecting beacon data with programmatic advertising, it is a substantial leap towards truly relevant ads. But in order to use beacons or any other proximity technology for personalized messages or for advertising in a scalable and successful manner, the data needs to be properly tagged.
What is data tagging?
Essentially tags are just like the ones you often see in different blogs to filter certain topics. In online advertising the interactions one has around the web, are translated into tags/categories which are aggregated into a customer profile. For example, if you spend a lot of time on baseball websites, categories like “Sports” -> “Baseball”, will be part of your customer profile. These categories/tags are very important for companies to identify and advertise to their target audience. All these tags/categories are structured and translated together into a taxonomy. The richer and broader the taxonomy, with synonyms and other terms, the better and more precise is the potential outcome and targeting.
Tagging the beacon data
Whether it comes to online retargeting, welcoming back messages or any other push notification, it is vital to know the customer; their preferences, previous interactions and routines. There is simply no other way for a personalized experience. Some beacon companies don’t leverage data at all, resulting in generic and spammy notifications.
Beacon companies who do leverage data from previous interactions, usually use their own taxonomy. In other words Proximity Solution Providers around the world have different categories and tags, which they use when translating the beacon interactions into context.
What if all the Proximity Solution Providers could use the same taxonomy?
Currently online advertising giants like Google, Facebook and BlueKai for example all use their own taxonomy. Here is an example of BlueKais taxonomy logic. But as we know, the proximity industry is in a very young phase. Meaning that there are not yet billions of interactions with beacons, like there are online. But if Proximity Solution Providers around the world would use the same beacon taxonomy, they could build hyper accurate customer segments, using each other’s data. From hundreds of proximity companies isolated data silos there would be hundreds of millions of data points translated into one language - into a universal proximity taxonomy.
Let me give you an example.
A beacon campaign serves 2 000 interactions in a two day conference where there are 1000 visitors. Is it a good result? Can I identify the target audience for the future? What are the most popular areas in my venue? Answers to these questions are very valuable, and several beacon companies are able to answer with the help of their beacon and CMS platforms. But is 2000 interactions enough data to make these conclusions? Probably not.
Imagine if you could compare these results to hundreds or even thousands of similar beacon campaigns, that are using the same taxonomy.
Then you would have enough data to truly analyze the patterns, trends and results.
Trust & Quality Control
In digital advertising, “Interactive Advertising Bureau” (IAB), has developed industry standards. They have partnered with over 650 leading media and technology companies that are responsible for selling, delivering, and optimizing digital advertising or marketing campaigns. IAB has developed quality assurance guidelines and their own categories, which even Google is certified for. The reason is simple; when a company is IAB certified or using their taxonomy, they can be trusted and they are able to deliver contextual data.
If the proximity industry would follow a unified taxonomy, it would be an indication of quality and trust for companies that are part of it.
Therefore helping to keep the reputation of the proximity industry.
Global brands are digging into beacons
Currently there hasn’t been news about a truly global beacon campaign (yet). But it is a matter of time. Currently giants like Coca-Cola, Target, Macy’s and so forth are slowly maturing their beacon projects. When these campaigns expand, retailers will be looking to leverage their existing data.
Not only would a universal taxonomy help you to offer richer analytics, but also give you a competitive advantage.
Because when a retailer has a choice to partner with a Proximity Solution Provider that is using the same categories/tags versus a PSP who is using their own taxonomy, who do you think they will pick?
A unified proximity taxonomy would lead us towards richer analytics and relevancy. It would be a big leap towards on actually delivering the right message at the right time to the right person. The industry has proven by now with use cases that there is value in proximity data. But if used in fragmented silos, like it is now, that value is realized in a very limited manner. By having a unified taxonomy, we as an industry could defend the reputation of proximity and be ready to participate in global campaigns.