Sketching Around Personal Brand Tracking

October 3, 2008  |  Design

Tracking Personal Brand

This is a guest post by Miguel Jiménez, a user experience and interaction designer based in Madrid.

There's a lot of noise today around Personal Branding and constructing your own self as a global brand on a certain topic. It makes complete sense to increase your professional value reflecting on others and using the Internet to build up this reputation. It's said that you should start by creating an online identity, supposedly to reflect your Real World™ one, with an entry point in the form of a blog or similar. That's a nice introduction and it’s quite easy to implement, but the main problem to the process of constructing a self-brand is monitoring and tracking how your efforts perform and the next steps you should take. So let's have a conceptual look and sketch around the statistical data found nowadays in the Internet.

The Problem

Trying to define the problem as close as possible, let's suppose we are related to the design field. We are expressing our ideas on a personal blog and we use a Twitter account to interact with related people. Smart as we are, we have a Feedburner account tracking our subscribers and we have claimed our blog in Technorati; of course, we haven’t forgotten about Ego Searches on Google and the global rankings of Alexa and Technorati. So there we go, we have around 6 services with a bunch of data to analyze and we must try to determine how good (or bad) we are doing on the self-brand project. If you’ve worked with this data before you can clearly see that it’s missing any context and there’s nothing related to your purposes or the higher branding goal.

Make the Information Useful

So the main point there is to sketch a way of visualizing all those rows of data and convert it into a subset of useful information that can be used to achieve the branding goal. So let’s focus on the blog, probably our biggest content producer. When we publish something in the blog we tend to see how many subscribers we reach on Feedburner, but how can we measure the impact of the published content? A nice relation would be to tie up the content published affecting the subscribers, in order to keep working on those topics. This effect is not only regarded to RSS subscribers, it also affects Twitter followers, so that should be tracked as well; and it doesn’t end here, because it also affects the authority rank in Technorati if someone links the post. It can get even more complex - that link could generate more traffic to the blog and, indeed, also increase also the amount of subscribers. Altogether the content is indexed in search engines and both your tweets, posts and incoming links get searched, found and converted into traffic that can also, at the end, affect your subscriber base.

At the beginning we see ourselves as the centre of the branding goal, and we should reflect the information about the activity we are performing. That is, to measure the consistency of our publishing and the items published we need to track the frequency and amount of elements thrown into the Internet; this can be easily depicted with a bar graph showing the data published in a period of time. This data is not only related to the blog itself, but to all the content we publish, including Twitter and the rest of social networks.

From the moment of publication, our content will start generating some reactions inside our Inner Circle of Influence; in this closer area we can see our actual subscribers, followers or fans and the actions they take are really important to our goal. Tracking the impact on subscribers, blog reactions, incoming links and replies on Twitter give an interesting overview of how the content performs out there. Data in this area is easy to track, it’s already available through the services and tools used, but there’s a global vision around it that cannot be reached without defining relations between them. Those relations are located on the Outer Circle of Influence and reflect all the connections between the different areas of exposition in the inner circle. It doesn’t only show the connections but represents the impact of disparate events across the inner circle and how it affects other parts from the outer perspective. The mix of inner and outer circle reactions is reflected on the global impact our content has on the Internet represented by the Alexa and Technorati global rankings.

Of course this only is a sketch on how we could represent the information, but there are many problems related to the representation shown above. The first one is that we cannot track the progress from a previous state, so it’s just like an instant-shot of the information. The second one is the complexity of the relations, if you are tracked by a lot of people the connections on the outer circle can be a real mess. On the other hand, a really messy outer circle means you are getting lot of reactions. And at the end, it doesn’t provide you with clear steps on what to do, it just shows the impact of your last movements so you can take it into consideration and keep planning reactions to the numbers.

Your Thoughts

It would be really interesting to hear your thoughts and suggestions around this sketch. Are you following any rules to track this information? Is it a complete mess and isn’t worth the time and effort of analyzing so much data? Shall we rely only on the data provided by the external services or should we keep trying to look for intersection points within?

8 Comments

  • It reminds me too much of Simon.

  • interesting mesh, hope to see it live in2 short!!
    As for a suggestion, add a timeline view that it
    is able to be animated and show progress visually…
    of course it would require to save the data and develop
    a layer for this :)

  • I like where you are going with this post, but feel the diagram is too limiting. There are more ways to get your message out than the 4 you listed in your diagram. If you meant that Google included blogs, articles, wiki’s, social networks, then it might make sense. “Google” is so broad that it can cover all 4 if you know what I mean.

    I like the post and your thinking though. This is just a suggestion.

  • I really how you have adapted the idea of a doughnut chart here. You could have the hue of each category reflect growth/change in each area, although that only addresses magnitude. You would have to have color changes indicating whether influence is waxing or waning in a given area. However, you could accomplish both if you allowed that data to be expressed in the size of the wedges.

  • Nathan,

    Your visualization is an interesting way to display social media monitoring. I use Intelligence Feed, a combination of aggregated and filtered RSS stream (think Yahoo!Pipes, MagpieRSS, AideRSS and Dapper), to get a bird’s eye view of both my personal profile and brands I manage. Right now, though, they’re only displayed through Netvibes in a manner much less dynamic than yours (ie. http://netvibes.com/refresh)

    Tracking these data is worth the effort, though, because by aggregating and filtering data, we reduce the time that it takes to manage our online presence. For instance, I can easily see relevant blog posts, and tweet it for my followers to see and talk about. This is because I can see all these data in one environment, without needing to switch between, for instance, a Twitter client and RSS reader.

    I particularly love your notion of ‘inner’ and ‘outer circles,’ and visualizing how our presence makes an impact on the internet.

    However, most of the efforts so far have been centered around gathering and filtering through external, third-party service (Technorati, and services I wrote above.) I’m interested in studying ways in which we can, like you said, “look for intersection points within.”

    Thanks for writing an amazing article!

  • @Bram – i wish i could accept the praise, but this is actually Miguel’s guest post (as said in the first line in italics). I am sure he is reading though and appreciates it :)

    Don’t forget to check out Miguel’s UX blog:

    http://www.migueljimenez.net/

  • I agree with Dan on this one, if by Google you mean all the social networks you can join then yes it works. You cant Ego Search yourself if you dont put yourself out there.

    Blogs are one of the strongest tools on the web for anyone looking to create an online presence. They are easy to create and are only limited by your determination.

  • Hi all,

    Thanks a lot for your comments and to Nathan for publishin the article. The sketch is in a realy early stage, so the sources of data are not clear.

    @Trace and @Danes i think the main points of tracking should be around thinks that already track you like technorati & feedburner, plus your content producers: twitter and rss… i knew there’s a lot of reactions missing here, that’s the reason why google is include: it obviusly will reflect reactions included in the previous systems, but also include a much broader vision of the activity around your content. I don’t know if this should change when adding new trackers (let’s say jaiku, or wikipedia), but for sure google will provide a broader search.

    @Scott the main inner circle is reflecting the 100% of the activity around you… so if most of the content is tracked through technorati, that section will be bigger, representing it actual value. anyway your idea is really nice, focusing on colours to reflect previous states.

    @Bram thanks a lot for your comments, is good to see that this can go up as anything useful to people. the idea was, as you said, to minimize the time of gathering all the information by ourselves, and let the information play new roles on the intersection points between the data collected.

    @Joe definitely it looks like Simon :) maybe with more service tracking inside the inner circle it can look different. I have another version of this sketch in plain stats, without applying polar coordinates transformations around the main graphs.

    Thanks you all for your comments, it’s really nice to see that FlowingData followers are so interested…

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