19 Dec 08 Better Twitter-WordPress integration here now
I have switched from hashtags.org to Twemes for the Twitter tag feed for web analytics (#wa) that appears in the sidebar. Sorry, hashtags, but you just weren’t reliable.
I have also added a Flash widget for Twitter, showing my tweets, to the top of the sidebar. It’s kind of flashy, so I might switch to the text version.
Finally, I have added TwitThis (shouldn’t that be “TweetThis”?) at the bottom of each post, allowing you, my fine readers, to Tweet, with ease, I hope, any post you choose.
Ah, the joy of actually using social media!
Tags: admin
19 Dec 08 Privacy and third-party analytics
I’ve been scratching my head reading a WAA discussion that raised privacy concerns. The original post said this:
One of my clients is a professional membership association. They
would like to track which pages members go to after they have logged
in to the Website Members Only section, on an individual (i.e. by name) basis.
Perfectly reasonable, I thought. Apparently others disagreed, perhaps because of that parenthetical “by name” part, which perhaps deserves to set off a minor privacy concern.
I would be very disappointed if privacy issues made it impossible for use to differentiate between registered users and other visitors. I don’t think there is any reason for that, even when using third party analytics solutions and their privacy restrictions. Assuming that membership is required for full participation, people who go to the trouble of becoming members implicitly are the most active and involved people in the social network.
For example, rewarding “super-users” is generally regarded as a key to community management, but it is only possible if analytics tells us who they are. Privacy policies were never intended to prevent such analysis; their purpose is to restrict who has access to which data when third parties are involved.
Here is the relevant section of the Google Analytics Terms of Service:
7. PRIVACY . You will not (and will not allow any third party to) use the Service to track or collect personally identifiable information of Internet users, nor will You (or will You allow any third party to) associate any data gathered from Your website(s) (or such third parties’ website(s)) with any personally identifying information from any source as part of Your use (or such third parties’ use) of the Service. You will have and abide by an appropriate privacy policy and will comply with all applicable laws relating to the collection of information from visitors to Your websites. You must post a privacy policy and that policy must provide notice of your use of a cookie that collects anonymous traffic data.
Now we need a definition of “personally identifiable information,” so here is what Wikipedia has to say about that:
In information security , PII is any piece of information which can potentially be used to uniquely identify, contact, or locate a single person or can be used with other sources to uniquely identify a single individual.
So, as long as I, the site operator, am the only one who can connect the user IDs in the analytics system back to an individual’s real identity, I don’t believe there is a privacy violation. In other words, if I’m using a third-party analytics solution, I cannot include any sort of ID that would allow anyone other than me to connect the data back to a real person . No social security number, phone number, email address or anything like that, which I hope is common sense these days.
Our litigator-infested world has raised the privacy stakes considerably as digital media has grown. I have no objection to giving it a lot of thought and attention. However, as my friend David Brin has written, the trade-off between privacy and freedom is not as real as many people think.
Note: I host a mailing list that (purportedly) focuses on Brin’s ideas, along with other “Killer B” science fiction writers – Gregory Benford, Greg Bear, Stephen Baxter and Vernor Vinge (who is an honorary “B”).
15 Dec 08 Self-organizing media: It’s the patterns
A friend who is a community manager challenged me recently with the idea that people are doing nothing really new with social media. All that has happened, he argued, is that conversations have moved from one place to another, but people are still people and none of all the new technology has really changed how they behave. This came up in response to my posting about social media answering strong demand for people to connect with one another.
There is something fundamentally new about social media, which is slowly reshaping our view of the world – the fact that it is full of self-organizing phenomena. The Internet itself is self-organizing; nobody is in charge. The most successful social media venues are self-organizing, if only because they grow and operate on scales where that’s the only way they can exist. There is a historical context to this change.
The medieval world-view was primarily hierarchical. The source of order in the world was hierarchical authority, which led to ideas that seem bizarre today, such as the custom that the length of your sword (or even the right to carry one) depended on your position in the social hierarchy. The Enlightenment brought forth any number of models based on self-regulation – democracy, capitalism and evolution, to name three ideas that transformed the world. Those ideas arose partly from the challenge posed by self-regulating machinery – clockworks were the first widely encountered ones – which were somewhat inexplicable in a hierarchical world-view. Another invention based on self-regulation through mechanical feedback, Watt’s steam engine (his innovation was the regulator), also transformed the world.
In a world where we are still trying to figure out appropriate balances between the freedoms of self-regulation and hierarchical control (consider mortgage-backed securities, for example) we are faced with an innovation, the Internet itself, where order emerges from a set of simple rules (protocols) interacting on a vast scale, raising the possibility and need for models that transcend hierarchies and feedback loops. Welcome to the confusing world of self-organization.
What this means for those of us who create and manage social media technologies is that it is often a mistake to depend on authority based on hierarchy or feedback. In other words, heavy-handed management will usually backfire because people will depart for places it doesn’t exist. Voting may be entertaining, even informative, but a social network that are regulated primarily by feedback are also likely to be abandoned in favor of those where the primary authority model is the network’s self-organization. This also means that keeping protocols simple and open is essential to success unless you really think your social network can survive as an island.
In terms of measurement, the self-organizing nature of today’s social media calls for metrics that reveal the patterns that emerge from the participants’ large-scale interaction. These are the qualities that get attention – witness the idea of the “long tail” – not a measurement, but a pattern. The “90/9/1 rule” is a pattern. Same for “Groundswell.”
I think that some of the coolest work being done today, if not the most profitable in the long run, calls for having the intuition to see patterns and the insight to figure out what they mean.
Tags: self-organization, self-regulation
12 Dec 08 Admin notes
You no longer have to register to comment here… I didn’t realize that was set until a friend told me last night at the social media Tweetup. Your first comment will be automatically held for moderation.
The Twitter feeds on the right side of the page don’t seem to be working well. Tweets are missing from my feed; the web analytics (#wa) tag tracker feed from hashtags.org seems to be unreliable.
Tags: admin
11 Dec 08 The 90/9/1 rule is just one kind of behavioral segmentation
To anybody who has been measuring social networks for long, the “90/10/1 rule,” subject of recent buzz, is nothing new. I don’t just mean online social networks, I mean social networks in the real world, long before computers became a social networking medium. Mark Williams, a community manager, asked the right question in his blog, what is it good for? It is a guideline, Mark says – a way to set reasonable expectations with clients who might imagine that a far larger percentage of visitors will become deeply involved in the community.
Mark is right – that is certainly the primary purpose of the rule, but it is just a start. When you think of it as a way to segment community by a particular kind of behavior, you’ll quickly recognize that there are other behaviors that are worth examining similarly. Call it a “contribution” behavioral segment, since it is is based on how much each visitor contributes to site’s content. There are many other interesting behavioral segmentations:
- Responsiveness – which of the community’s interactive features do visitors use and how often do they use them?
- Retention – how often do visitors come back?
- Churn – what is the turnover rate for visitors?
- Topics – do people participate equally in the community discussions?
One of these days, perhaps we’ll all know what is normal segmentation for various types of communities (e.g., a support community will be quite different from an affinity community).
For deeper insights, compare the different segmentations and look for disconnects. I would be especially concerned to find disconnects between contribution and the first two examples, responsiveness and retention (my “R&R” of engagement). If the major contributions aren’t using interactive features as frequently as they contribute, that might reveal a design or even more fundamental problem with the features. If they aren’t returning to the site at a normal rate, that suggests trouble ahead.
Side note: I suspect that behavioral segmentation is a good way to find communities within communities. One of the challenges of community management is to figure out when a group needs to be split into two or more. Discovering cliques that are naturally following the normal patterns might be candidates to spin out. In other words, I’ll bet behavioral segments are somewhat of a fractal phenomenon. And if nothing else, they give us more ways to generate pretty visualizations, eye candy for that next conference or sales presentation.
Tags: community, Engagement, R&R, Segmentation
10 Dec 08 A couple of notes about this blog
With gratitude toward those who have given me feedback about this blog… I just changed the RSS feed to supply the full text of posts, rather than truncated versions.
I was asked off-line about the Google ads that appear here. They’re not here to make money (not that I have any real objections), they’re here so that I can see what happens, since I’m always interested in the relationship between social media and advertising.
Tags: admin
09 Dec 08 What business problem are we solving?
“Technology in search of a problem,” is a longstanding Silicon Valley standard criticism of companies with smart people who build cool stuff but fail to generate revenue. Sometimes it seems like the entire world of web analytics could be described that way. The squishier the metrics definitions are (prime example: “engagement”), the more accurate the description is.
The most important word in that description is “a.” In other words, find just one problem to solve at a time, rather than a dozen. This is a normal problem in a developing environment, where inventors are driving. The problem is that people who are good at inventing products and services are also good at seeing problems they can solve, so they do a lot of things moderately well and excel at none. In the day-to-day work of web analytics, this often appears as “data smog,” a term I first encountered in Actionable Web Analytics, which credits it to David Schenk.
Somebody involved in every analytics effort absolutely needs to be talking to the ultimate customer, the one who is actually generating revenue, to understand their business. At the very least, analytics should address the specific business problem a customer knows it has. Ideally, it goes further and sees solutions or opportunities that the customer didn’t realize that data could address.
In other words, I think it is a mistake to just ask or settle for being told what numbers to deliver. Ask why the numbers are needed. Ask for the goals and their priorities so that you can set analysis priorities. For example, the goal is support, the speed of responses in the social network matters a lot more than when the goal is loyalty.
If there is no way around the need for a lot of measurements, fight data smog by knowing your priorities and packaging the data with some sort of drill-down that puts the most important numbers on top. This is where the dashboard idea becomes critical – hide the complexity behind a one-page (or less) summary. The fact is that even when people think they want complexity, they almost never do. I created a set of Excel-based dashboards with deep drill-down… and I’ll bet that hardly anyone used more than a small percentage of what was there. But it was there if they wanted it and that keeps people happy.
All of this adds up to one word: focus. A venture capitalist friend gave me a mantra that stuck: the five most important things (for startups, but it applies to innovation in general) are focus, focus, focus, distribution and focus.
