Activity streams (whether Facebook’s news feed, Twitter’s tweet stream, Yahoo!’s Updates, LinkedIn’s network activity, MySpace’s Stream or those using the activitystrea.ms format) are all the rage around the Web now. In each instance, users publish directly (via entering your comment into a Sharing dialog box) or indirectly (by the system generating content based on an action they take, such as posting a rating you give to a music video) in ways similar to how they’ve blogged or engaged with the Web in the past.
But, unlike blogging or even some advanced message boards, these activity streams hide the results of such posts from the very people who publish them. How many other people click on a link that you share? How many people even saw your activity stream post? If you look at the interfaces for these streams, you’d assume people didn’t care about whether other people care about their posts. The absence of visible analytics per post, however, belie the desire of people to know the impact of their effort.
Google Analytics’ self-service, free solution (among many others) for any Web page quickly demonstrated how import content publishers considered the performance of their publishing. And, already, the rise of URL shortening-and-tracking services such bit.ly and awe.sm demonstrate that those who actively publish content through these streams want to know how their content performs with services like Twitter and Facebook.
Think such analytics aren’t popular with the mainstream and only useful for power users? Remember Web counters? There remain hundreds (possibly thousands, if you have the time to tally up all the true solutions from the 1.2 billion results for “web counters”) of easy-to-integrate tools for users to both track visitors and show others how meaningful are their contributions to the Web. One needn’t look at nerd technology for this validation, either. Before you tell a joke, do you think about the number of laughs you got from your last re-telling of the entertaining tale? We are a social people, and the striving for validation that comes from our peers’ responses to our actions have long governed most folks’ actions at nearly every level of our development.
But, back to nerd technology… Facebook has long had a “Like” button underneath each item in their news feed, and Twitter has also long-served a “favorite this tweet” button (i.e. the star icon) next to each of its tweets. (Additionally, Twitter offers the “Retweet” functionality, which exposes a visible counter of others’ retweets.) These indicators are great means of determining our peers’ positive responses to each micro-publication, but they do not capture the true value behind each of these micro-publication: the number of clicks a link generates divided by the number of times it has been displayed to other people. And, not only is the publisher of the link robbed of this information, so to is her audience.
So, why would exposing these numbers and ratios be valuable to people and publishers?
On a page with 10 links from 10 different people, which should I click on? Obviously, the subject matter matters as does the publisher (if they’re somehow connected to me). But if I don’t know the publisher, and the subject matter is all the same, which link should I check out? Some people, of course, will want to follow the road least travelled; most, however, would trust the one with the most traffic (as the preceding people voted for the best link with their clicks).
From a publisher’s standpoint, knowing what types of content my readers click on (and what content they see but don’t bother clicking through to) helps me tune what I deliver to my audience. Even as a publisher of just my life’s activities (i.e. what I generally post on Facebook), if I know no one clicks on my activities posted from games, I might think twice before connecting Facebook and the next game I install; connecting such a game would just produce more chaff, which will dilute the value of all my posts in my readers’ eyes.
So, assuming such analytics should be exposed, what would these activity streams look like if they began surfacing such statistics? Twitter’s Retweet exposure (and contact card overlay) offers a glimpse:
In this vein, links could have a hover state (akin to the Twitter user hover card) where link click-throughs can be displayed (as well as the target of an URL, if the URL displayed is that of an URL shortener).
Publishers, of course, might also receive more details than those displayed for all people. Facebook Pages similarly provides a sneak peek at this direction (where the highlighted details in the screenshot below are displayed only to the Page’s publisher):
By exposing statistics to both all people and the publishers themselves, the hosts of these activity streams can provide a more meaningful, measurable and desirable experience to all users. And, in doing so, help us find the validation we look for in nearly all our daily activities.