I’ve been intrigued by the idea of using Google Wave as an analysis collaboration tool since I became aware of the project.
Web analytics, simply put, is the process of measuring online behavior and communicating the results to some audience, with the intent of driving positive business outcomes. The operative phrase being “communicating the results”--that’s the hardest part of web analytics, believe it or not. Do you remember those math teachers you had in school who were really good at solving math problems, but confused the whole class when they try to teach how to solve it? Analysts, struggle with the same problem. Most have a firm grasp of what’s important to measure, how they should go about measuring online, and what the data is. Few have the ability to articulate what that means, and fewer can articulate it to an executive audience. Communication is the ‘last mile’ of the analytics value chain.
The difficulty during the ‘communication’ phase is, IMHO, two-fold. First, there’s a clear challenge communicating results to the audience in an accessible way--meaning that the narrative should create a compelling, step-by-step ‘story’ that a stakeholder can follow. Think of it this way; even though the ‘punchline’ of the analysis is the first few paragraphs, the story leading up to the conclusion should be logical and sequential upon closer inspection. Indeed, the more compelling the call-to-action, the more clear the supporting analytical ‘story’ needs to be.
Second, the audience typically needs additional context to any analytical content. This has more to do with the detail found within the analytic ‘story‘ rather than the structure and layout. I’m talking about more than just definitions to terms--stakeholders need to understand that the dip in graph 2 is seasonal and expected. Or they need to understand that the increased conversion rate is actually artificial due to a decrease in corresponding site traffic. These are the kinds of discussion points that are difficult to capture effectively in e-mail or within a traditional document. A Wave could more easily include these contextual elements and be updated in real-time by both stakeholders & analysts.
At least, that’s the theory.
I get that wave isn’t a panacea for every ill associated with communicating complex analytical ideas. I’m still not sure if there needs to be a custom plugin that can provide some of these features or if it can work out-of-the-box. Further, I’m still not sure that a wiki, well implemented, would do the same job (albeit without the real-time chatty feature). But I intend to play around with Wave enough until I’m convinced it’s the wrong tool for the job.
Great post Matt! Your comment,”…the increased conversion rate is actually artificial due to a decrease in corresponding site traffic” speaks volumes to the complexities of analytics and how easy it is to misinterpret statistics as a whole. I’m so glad I took some of the more advanced stat classes in college because even though I don’t remember a lot of the specifics I do remember how easy it is to confuse or misdirect using statistics… for example, it is amazing how often people (even those who we label as experts) confuse correlation with causation.
Regarding Wave: I really hope it takes off, if only to really start pushing the envelope of what it means to communicate online. In email and on my forums there is entirely too much room for miscommunication and misinterpretation. I’ve read that up to 30% of a conversation is lost when body language is unavailable (mannerisms, facial expressions, etc.) and possibly another 40% can be lost when you loose verbal queues like tonality, etc. Hopefully Google Wave can help resolve some of these issues.
Keep us posted with your experiences using the platform!