Talk Bite: Segmentation’s Greatest Accomplishment

Introducing You to Your Biggest Advocates
It doesn’t usually (or arguably ever) make sense to say everyone is your target, because like we have all heard many times in one form or another: you can’t be everything to everyone, and if you try to be, failure is likely. Instead, you should want to answer this question: Who are my best customers? The answer: Yes, those who spend the most with you and/or are the most frequent purchasers of your brand are some of your best customers, but it goes beyond that. They are also the people who share your brand’s values, those who feel they are getting the experience they want and need from your brand, and those who are most likely to tell others about you. In fact, some of these people may not currently engage with your brand. Segmentation can help you change that.

A well-crafted segmentation will tell you many things about your biggest advocates, including:

1. Who they are demographically.
2. What their interests and beliefs are.
3. When they shop for your brand.
4. Where they shop for your brand or where they cross-shop.
5. Why they purchase your brand and others like it.

And what can come out of knowing all of this?And what do happy customers do? They shop more, they talk more, and they improve business (increased sales, anyone?).

So, I guess what I am trying to say here is, do a consumer segmentation study for your brand and you shall be rewarded. Don’t do it and you might be able to survive, but you can probably be doing better!

All Facebook Fans Aren’t Created Equal: Participation Inequality and the 90-9-1 Rule

Researcher Jakob Nielson suggests that when considering the internet as a network of communities, most large-scale communities consist of users who don’t participate very often. He also explains that most of the content contributed to these communities originate from a small majority of very active users. Nielson refers to this discrepancy as participation inequality and speculates that it typically follows a 90-9-1 rule in which users fall into one of three categories: Lurkers, Intermittent Contributors, and Heavy Contributors.

The 90-9-1 rule aplies to even an inherently social platform such as Facebook. As shown by Adam Mosseri in his presentation presentation during UX Week 2010 about user data’s impact on product design at Facebook, 20% of users generate 85% of content on Facebook. This data comes as no surprise. Many users have those two or three friends within their own communities of Facebook friends who comment on what seems like every status update on their wall and update their own status a hundred times throughout the day. Mosseri makes an important point in citing the Facebook product team’s commitment to accommodating not only to those 20% of power users, but to the lighter users as well.

As brand Pages on Facebook amass millions of fans—becoming large-scale communities—participation inequality challenges brands looking to build a community of advocates on Facebook. The existence of participation inequality within brands’ Facebook communities demonstrates the existence of another hierarchy similar to the one Nielson describes. Brands must recognize the existence of these different types of fans, as they represent varying levels of value for a brand.

• Withdrawn Fans — fans who have hidden a brand’s posts from the News Feed
• Latent Fans — fans who see a brand’s posts in the News Feed but don’t interact with them
• Active Fans — fans who see a brand’s posts in the News Feed and interact occasionally
• Hyperactive Fans — fans who see a brand’s posts in the News Feed and interact often

In fact, Facebook inherently acknowledges this notion, as evidenced by EdgeRank, the algorithm that programmatically decides which stories appear in a user’s News Feed. Firstly, affinity—one of three key components in EdgeRank—draws upon historical interaction data between the viewing user and the originating source of the News Feed story. The premise is that activity from a brand Page that a user interacts on a more frequent basis signifies a more important connection to the user than one with which the user rarely interacts. Therefore, a fan that interacts more frequently with a brand’s Facebook Page holds greater value for that brand. Whereas affinity signifies the frequency of activity, weight, another factor of EdgeRank, demonstrates the different types of activity a fan may take to interact with a brand Page’s content. Simply stated, actions that require more effort from the fan (such as a comment or share) signify greater weight values than lightweight actions (such as a Like). In order to maximize visibility and engagement within the News Feed, then, a brand must incorporate two elements of News Feed Optimization into its Facebook content strategy:

1. Diversity. Content that elicits different types of actions with varying weight values (Shares, Comments, Likes, Clicks).
2. Consistency. A dedication to consistently post engaging content, in order to increase affinity scores among fans.

The existence of these different types and values of Facebook fans further proves that marketing on Facebook—or any other social media network, for that matter—requires a long-term commitment and insightful strategy. Furthermore, the notion of participation inequality supports the claim that when it comes to social media, content indeed reigns supreme.