Tuesday, March 2, 2010

Social media analysis moves mainstream

Last week, Webtrends announced that they had extended their customer intelligence capabilities into Facebook. In this new integration, there are two things happening that are worth commenting on. First, there is a continuing move to see a unified view of online behaviour, and online messages across all communication channels, and not a siloed view where each individual communication platform is treated as somehow separate.

In exploring the Webtrends solution, you can see this evolution taking place. When a blog post is written, Tweeted about, then shared on Facebook this is a natural way that information flows in today’s environment. An analytics platform that treats each of the platforms as silos would be forcing marketers to think of communications by “silo” not by “idea”, and that would be a significant mistake. The barriers between social platforms, and between those platforms and our blogs and web properties are rapidly disappearing and already virtually non-existent.

This manifests in both the way that the data is captured (not just within properties under our direct control like main websites, but wherever the audience is, such as on Facebook) and in how it is presented, as an integrated view of activity across communication platforms.

The second interesting trend that became apparent in looking at this integration of Facebook activity into the marketing analysis world was the lack of campaign centricity. Facebook, as with almost all social media efforts, has a “flywheel” dynamic to it. Effort is put in continually, and over time, the success begins to build slowly, but with its own momentum. This is drastically different than typical marketing campaign efforts where each campaign has a fairly defined investment/payback model; a point-in-time investment which is tied to a short-term payback.

Webtrends shows metrics on community success (views, shares, fans, etc), and indicates through “flags” where the driving events (such as blog posts, tweets, and marketing promotions) took place. By doing this, they guide marketers to the view that the driving events are there to build community, engagement, and influencers, which will then over time drive the creation of qualified leads. This view is significantly different than the more direct campaign-to-lead model of typical marketing, but a much more accurate representation of the marketing realities of social media.

As we market to B2B buyers, optimizing how information finds its way to them is crucial. To do this well means that we need to think more in terms of the ideas, and less in terms of the channel by which the information is disseminated. Similarly, as we build our engagement with our buying audiences in social media, we need to think more in terms of how our efforts are building and driving community success, rather than thinking in terms of single campaigns. With their new ability to analyze Facebook, understand the flow of ideas across social media channels, and see community success mapped against the events that drove it, Webtrends helps us make important steps in this direction.

What do you think? Have you tried their new capability in your environment? What insights are you able to gain from it that you weren’t able to get previously?
Many of the topics on this blog are discussed in more detail in my book Digital Body Language
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jascha said...


The web of data we work in so interconnected now the ability to collect data from everywhere and utilize the medium of data visualization to draw insights and make decisions is imperative.

The other interesting element of what we’ve done (and this isn’t necessarily about Webtrends) is that we are extending our ability to let prospects and customers raise their hands no matter where they are. The landing page and the microsite are taking much different forms as they adapt to social and we have to continually stay in front as marketers.

Jascha Kaykas-Wolff
VP Marketing, Webtrends

Great post!

Steven Woods said...

very much agreed, the current explosion of relevant environments from a single, central model to multiple disparate environments is leading to some very interesting challenges!