The business of social media is morphing, which is no surprise. What is interesting to note is the growing importance of what I’d label “filtration and curation” (not just because of the Jesse Jackson ring it brings to the title!).
In the “early days” of social media, we focused on aggregation - picking up the crumbs of commentary wherever it can be found and blending it to amass some scale of commentary. As the world gets more and more conversant, aggregation hatches a new problem, in its quest to solve an old one. Every day, the problem of scale is being solved naturally, via the sheer volume of user participation. Context and interaction form the mantra, replacing more.
a case in point.
One of my regular haunts, Tamayo Restaurant, in Denver. Here is the Google summary page for Tamayo. Aggregation brings me 80 reviews, organized in a manner I cannot decipher - it’s not purely date-based, so Google must be employing some rank logic. Interestingly, Yelp’s reviews are not included. Did I miss some falling out? Well, it’s not like I need another 35 reviews, anyway, right?
The addition of a new tab labeled “User Content”, separate from “Reviews”, further confuses the user and complicates the dining decision. What the heck is the difference between Reviews and User Content, you might ask? It appears to be an attempt to differentiate content that comes via Google Map personalization. How friggin’ engineering driven is THAT piece of user experience wizardry!
to the point.
This kind of aggregation, while it brings together a ton of content in a technically impressive way, plops it on the user experience doorstep effectively saying, “here, you figure it out”.
Is this Google’s demarcation point of it’s job versus the user’s job? Right now, Google is handing the user a crap load of content, with compartmentalized content - big generic buckets that add little value to the user’s decision. Fred Wilson summarized a similar observation regarding Google Blogsearch - “all algorithm and no voice“.
enter curation and filtration.
The term curation is showing up a lot more in the social media blosphere, much to my delight. At Local Matters, we’ve been using it internally for years, but felt it was too “frothy” to use publicly. Alas, the root term curate was a person who is invested with the souls of the parish!
Collating user comments, and republishing them into valuable new methods of navigation is critical to the usability of social media. Consumers increasingly love to browse, but only when you do a good job of facilitating and encouraging them.
In the local cityguide world, Yelp is doing an admirable job in blending purposeful filtration and curation to help the user navigate the voice of its community. If you contrast the general purpose Google page with the Yelp page, you see a MUCH more useful page from which I’d make a dining decision - it collects ratings into a bar chart, and summarizes content, Zagat style.
whose voice?
Specialized social media sites seem to doing the best with filtration and curation. Problem is, however, these sites live in their own worlds. Yelp users have been described as many things, but there is no debating the upwardly mobile young, hip feel and tone of the reviews.
Every community has a distinctive voice, and your alignment with this voice will determine how well the review content will work for you. As communities become larger, the “averaged” reviews become less useful, and the need for richer filtration and curation kick in. More often than not, I find that users leave to align with new communities that better fit their own voice at these points.
Praized Media is executing an interesting model in trying to ignite the blogsphere’s local voice, by integrating tools wherever it can, and then aggregating the tribal streams into some future form of content distribution. Ambitious, but it gets to the heart of the long-term challenge in capturing and filtering the voices around connected social circles.
the best-of list as a filter
One of the obvious, yet underplayed, techniques of increasing importance in dealing with the quantity of reviews is the best-of list. Aggregating user votes is one of the most understood and obvious techniques for summarizing review content, and filtering the choices down. CityVoter is making a pure play of this, and seems to have solid traction.
Of course, best of lists do not solve the issue of alignment between your opinion and the opinion of a specific community, but their popularity point to the consumer’s desire to start with more context.
combining lists with user voices
One of the things we’ve been experimenting with in Guidespot.com is combining these principles. The inherent concept of Guidespot is to be a leading conduit for user-created local lists.
As a local user, I created a guide to LODO restaurants that I frequent, and publish it for other users. As it turns out, Tamayo is found on a half dozen other user lists (which the user sees when they browse the restaurant guide page); it also turns out to be mentioned on CitySearch’s Best of List, which we’ve aggregated into Guidespot.com in partnership with Citysearch.
It’s an early experiment, but the blending of these concepts will help drive the leverage and design of local social media usage in the coming years.
The collection of user voices with community-driven lists with editorial-driven lists is an emerging sweet spot. So far, this feels very disconnected from consumer search.
Hey Perry,
Good description of the problem and some of the solutions being pursued.
What I really want is a personalized recommendation engine approach - as in I like these restaurants in Edmonton, what other restaurants might I be interested in. And for bonus points: when I travel to Denver what restaurants might I want to consider there?
The Netflix Prize has driven a lot of research in to collaborative filtering techniques. I’m surprised that nobody has yet attempted to apply this to the local information. Part of the challenge is in getting enough input from many users to build a profile — but once you get to a critical mass you’d also have a huge network effect.
Cheers,
Eric
Left by Eric Fredine on November 17th, 2008