[Posted by Mickael Bentz, Product Marketing Manager, Neolane]
In addition to serving as a channel to develop brand awareness and improve engagement with customers, Facebook is a personal information goldmine. This information can be captured through what we call the “social opt-in.” The social opt-in occurs when Facebook users accept applications requesting personal information on facebook.com or use Facebook to log in to third-party websites. A lot of information can be requested, including email, pages liked and declared interests.
In two Neolane studies of websites with Facebook Login and Facebook applications, we realized that the ‘like’ capture is not very popular among marketers for the moment. About 25% of Facebook applications analyzed require users’ likes, while only 17% of websites using Facebook Login collect the likes.
Why this percentage is so small?
When we ask our customers why this percentage is so low, we get the following answer: we didn’t know that we could capture pages likes. It’s true, only advanced social media marketing solutions like Neolane Social Marketing can do that and therefore many marketers don’t know how to leverage them.
However, likes are really simple to use. For example, it is easily possible to interpret if “opt-in individuals” are:
- Fans of competitors, which could lead to specific actions. Example: which Adidas fans also like Nike?
- Fans of brands of the same environment to build partnerships, co-brandings, joint events, etc. Example: Among fans of Quicksilver, what percentage also likes Red Bull or Monster?
- Fans of partners to target them with specific content. Example: fans of Emirates and PSG football club.
- Fans of specific locations. Example: London Zoo, Stade de France, Scuba Diving Club of Phuket, Starbucks of the 5th Avenue NYC, etc.
- Fans of specific celebrities to better target marketing actions and partnerships. Among Chevrolet fans, what percentage likes Justin Bieber or Johnny Cash?
- Fans of specific activities. Example: fan pages of a cinema, of a running association, of a local fair trade shop, etc.
- Fans and app users of my page apps. Example: This contact used two apps of my page within the last two months, downloaded two coupons on my couponing app, shared one coupon with a friend, etc.
- Fans of my brand to provide them exclusive content.
- Heavy page likers, heavy basketball team likers, heavy supermarket likers, etc. to offer them targeted contents.
All of this information can be leveraged immediately or interpreted with simple aggregate and analytics tools and solutions such as those provided by Neolane.
For companies willing to go beyond this easy-to-acquire information, it is also possible to predict certain behavior of users, such as their personality traits according to a study called “Private traits and attributes are predictable from digital records of human behavior” by the Proceedings of the National Academy of Sciences.