Part III-E: The Algorithm (continued)
On the previous post we took some time to explain the fuel that runs the Facebook algorithm and created hypothetical scenarios to show how to defeat it. The intent was not to wage war on a digital giant, it was to show you who is really in charge. Digital media has taken such a strangle hold on our lives for needing to know information instantaneously as well as voicing an opinion without knowing all of the facts. Lately, we are allowing platforms such as Facebook to determine which information we are and are not allowed to have access to. This is scary, but I digress...
The purpose of the previous post was to set up the linear lifetime for Max. As described, the more engagement Max receives, the longer Max thrives. As soon as Pat posted Max, it ran through a series of algorithmic checks and ultimately landed on the feeds of Joe, Alan & Jenny. We discussed the priority level of exposure to those users in relation to behaviors, tendencies and predictive engagement actions. But we seemed to leave it at that. Now we want to talk about those user's individual engagement with Max.
Jenny is the first to respond. She logged into Facebook fairly quickly after Pat hit 'post' and was exposed to Max right away. Before even taking the 30sec to watch the kitty and cotton ball video, Jenny immediately liked the post simply because it came from Pat. She added a 'heart eyed' emoji and then watched the video. What definitely brought a smile to her face, and a feeling of 'awwww' immediately led her to click on the comment bar to pop up her text keyboard. "Soooooo adorable! @Pat, where did you find such a cute video?" Jenny's engagement on this post triggered a number of very important response results that Facebook documents:
Jenny 'liked' the post
Jenny 'reacted' to the post
Jenny watched the video in its entirety
Jenny commented on the post
Jenny tagged another user in her comment
It is crazy to think that such a simple act of liking and commenting on a friends post classifies and reclassifies a user into various categories...but I warned you...every action a user takes on Facebook is documented, segmented and sold. The combination of Jenny's input and Facebook's algorithm have created several sellable channels for businesses to target Jenny as a user who:
Engages with posts
Watches video posts
Comments on posts
Clicks on post links
These quantifying measures include Jenny as a user who meets these basic criteria for businesses looking to target users under those parameters.
Let's jump back to Max, who is now elevating its quality status according to Facebook because it trigged some sort of engagement. Jenny's overall engagement not only triggered the data sets for Facebook, it also triggered a series of notification popups to appear on Pat's devices and Facebook wall. This trigger is what keeps the addiction to Facebook flowing and what keeps Max alive. Pat opens his device to see several notifications from Jenny, and immediately clicks to view her actions. Seeing that she likes the post offers a sense of accomplishment to Pat for creating content that sparked the interest of the girl he has a crush on...but reading her comment takes it to a whole new level. Not only did Jenny comment, but she tagged Pat and even asked for a follow up comment. Now the mind games begin...should Pat answer right away or give it some time? Should he like the comment now, wait a while and respond later? Should he not respond at all and use this as a way to engage with Jenny in the REAL world? All of these options are predictable behaviors that Facebook has learned about its users. If Pat chooses to not respond or engage with Jenny's comments, Facebook will predict that Jenny will sign back in frequently to see what is going on with her previous actions to this post. Her signing in over and over again exposes her to other content which she has a high probability to engage with. The minute Pat decides to respond or engage to Jenny's comments, a back-and-forth paradox begins.