2016 is just around the corner and, as a marketer, it’s important to lay out different strategies that will optimize engagement in the coming year. Personalization is becoming a huge priority and trend and I can’t help but agree… to an extent.
Personalization is important in order to engage your audience, however, you have to make sure that the data you’re using to create “customized experiences” for them is actually accurate. No one wants to receive an email or see an ad that we all know is meant for us, but contains messaging or assumed information that is just plain wrong.
Social data can be key to creating personalized content, but when used inappropriately, it can backfire. Have you ever heard of the filter bubble? Eli Pariser, CEO of Upworthy, coined this term to explain how Facebook and Google incorporate both personal and social data to determine what types of items users want to see and know. For instance, I may want to see activity about my hometown sports teams, but now that I’ve moved to Atlanta and interact with Atlanta team pages more often, my hometown teams start to get filtered out of my newsfeed and that’s not cool. I want to see BOTH sets of teams! That’s why I liked both of those pages in the first place.
Christian Sandvig, an Associate Professor in the Communication Studies department at the University of Michigan also uses the term “corrupt personalization” to describe when the internet personalizes a user’s online experience based on behaviors and interactions with others online. The inaccuracy with this comes from Facebook’s “like” recycling. What’s “like” recycling, you ask? Well, according to Sandvig, it’s when Facebook determines that:
- Anyone who clicks on a ‘like’ button is considered to have ‘liked’ all future content from that source.
- Anyone who ‘likes’ a comment on a shared link is considered to ‘like’ wherever that link points to.
What does this mean? Basically, if a user likes an article about puppies one day, a couple years later, their friends’ newsfeeds may say that he or she liked an article from the same source about something completely inappropriate and unrelated to puppies. Also, if the user posts a status with a link to a product they’re mocking and one of their friends like it, later on Facebook may say that the friend liked that product, even though they didn’t. Terrible, right? No one likes being told what they do or do not like. This is an example of taking personalization automation a step too far…to the point of inaccuracy.
So how do we, as marketers, use personalization tactics that aren’t inaccurate and uncool? The answer starts with accurate data and reliable data sources. Social sourced data is valuable, but only if used in the right context and at the right time in conjunction with the right messaging. Where things get tricky is when you get too deep in the data, like leveraging the posts themselves or logic gathered from the social platform, rather than the personal information. The personal information can get very deep on certain platforms, like LinkedIn for example, and can be leveraged just as effectively if not more than using social activity data generated by algorithms. Self-reported data can be trusted much more because the data was input by the person themselves. We know ourselves best, so the information we put online on social profiles is generally the most accurate. That being said, this coming year, don’t try to personalize content the wrong way. Use accurate data you can trust and you will be sure to interact with happy humans who appreciate content that truly reflects what they want to see.