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How robust are communities? November 3, 2008

Posted by jeremyliew in communities, product management, usability, user generated content.
4 comments

Wired has an article in its November issue about Urban Baby and You Be Mom. Urban Baby is an anonymous forum for Moms. Like 4chan, its anonymity makes for a mix of candid discussions, raw honesty and trolling, but with a mommy bent (think cheating, divorce and public schools). Says Wired:

Then in May, UrbanBaby, which was purchased by CNET in 2006, launched a redesign. All hell broke loose.

The changes weren’t huge, but each of them subtly altered the flow of conversation. CNET added a wide sidebar on the site to create space for ads. This reduced the reading area, a big problem on a board with hundreds of comments per hour. Discussions had been organized chronologically, but immediately after the relaunch, the default setting had “most popular” threads at the top, even if they had been started days earlier. Worse, you had to refresh your browser to see new posts. UrbanBaby users went nuts, demanding a return to the old design.

They soon got it. But not from UrbanBaby. A week after CNET rolled out the hated redesign, a couple of work-at-home computer programmers—longtime UrbanBaby users themselves—launched a rival site called YouBeMom.

They perfectly re-created the look and feel of the old boards. Better yet, they made improvements, including a souped-up search engine and privacy controls that make sure your spouse can’t use your computer to find out what you’ve been posting. They also set up a blog to capture users’ requests for site improvements and to outline what YouBeMom plans to do about them.

Within days, there was a mass exodus of users from UrbanBaby to the new site. CNET won’t give out traffic figures, and neither will the owners of YouBeMom. But I logged on to both sites recently and compared how often people posted. I’d estimate that YouBeMom has three times the traffic of UrbanBaby. That’s just how fragile a social application can be.

I found much higher comment volume and more vibrant conversations at YouBeMom as well when I looked at conversations on similar themes on both sites. The moral of the story according to Wired:

People have a very sophisticated sense for their online hangout—if you mess up the feel of it, or impede the ways they want to schmooze online, they’re gone.

What a terrific parable about the importance of community. What is strange though is that the traffic stats don’t appear to bear it out:

According to Compete, not only is Urban Baby far bigger that You Be Mom, but the redesign actually seems to have dramatically grown usage.

Sometimes communities are more robust than you think. Redesigns almost always create a lot of negative feedback when they first occur because all users hate change. You have to leave a little time to pass for users to get used to the changes before you can truly judge if the redesign has been a success or a failure.

There are three classes of user within social media, creators, curators and consumers. It may well be that many of the Urban Baby creators moved to YouBeMom, but the 90% of social media consumers, who read but don’t write, stayed at Urban Baby.

Do any readers have experiences of the impact of redesigns on a community?

Viral marketing, randomness and the difficulty of controlling growth in social media September 13, 2007

Posted by jeremyliew in communities, Consumer internet, social media, social networks, viral, viral marketing.
16 comments

I recently met the CEO of a company who claim to be one of the most popular social networks in Turkey with several million monthly visitors from Turkey. This happened by accident – the founders are Americans who have no prior connection to Turkey.

This is just one of many examples of how difficult it can be to predict or control the growth of viral social media. Google’s Orkut, is a better known example – a social network started by a Turkish engineer working in the US that now dominates in Brazil and India. Friendster and hi5 fall into this bucket as well. As I’ve noted before, the online advertising market in the US is bigger than that in the rest of the world combined. The senior management of these companies know this, and all would love to see more US traffic, but it is now beyond their control.

The reason is the mathematics of viral growth. If the viral coefficient (the number of additional members a new member brings) in a population is less than one, it grows but eventually hits a ceiling. But if the viral coefficient is greater than one, it grows unbounded. Although your social media property may start in many different populations, it will come to be dominated by those with the highest viral coefficients.

This is best demonstrated by example. Consider a new social media property with 30 members, 10 each from three distinct populations; call them Pinks, Purples and Greens. Suppose that by luck and because of the initial users, the viral growth coefficient for the Pinks is 0.6, for the Purples is 0.9 and for the Greens is 1.2. Watch what happens to the populations over time:

viral-coefficient-impact.png

All three groups are initially equally represented, But already by time period 4 the population is more than 50% Green. By time period 10 it is more than 75% Green and probably considered a “Green social network”. By time period 16 less than one member in 10 is not Green. For Green now substitute whatever national, language based, religious, racial or other demographic grouping that you choose.

These evolutions can happen very fast since a time period is the time it takes for a new member to invite more members. 2-8 weeks might be a reasonable assumption.

This example is vastly simplified, of course. Viral coefficients vary over time within and between groups. Viral coefficients also don’t vary quite as much between groups; the same underlying feature set is being exposed to all groups. But it illustrates the point that randomness can play a significant role in the eventual makeup of a social media property’s user base.

I posted about a similar finding in May, how you don’t necessarily get the wisdom of crowds, but sometimes just the crowdiness of crowds. It was based on a NY Time’s article that showed how randomness can have a big impact on the most popular songs for a crowd when popularity information is public.