The Most Meaningful Insights Will Not Come from Web Analytics Alone

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Judah Phillips wrote a post last week laying out why the answer to the question, “Is web analytics hard or easy?” is a resounding “it depends.” It depends, he wrote, on what tools are being used, on how the site being analyzed is built, on the company’s requirements/expectations for analytics, on the skillset of the team doing the analytics, and, finally, on the robustness of the data management processes in place.

One of the comments on the blog came from John Grono of GAP Research, who, while agreeing with the post, pointed out:

You refer to this as “web analytics”. I also know that this is what the common parlance is, but truth be known it is actually “website analytics”. “web” is a truncation of “world wide web” which is the aggregation of billions of websites. These tools do not analyse the “web”, but merely individual nominated “websites” that collectively make up the “web”. I know this is semantics … but we as an industry should get it right.

It’s a valid point. Traditionally, “web analytics” has referred to the analysis of activity that occurs on a company’s web site, rather than on the web as a whole. Increasingly, though, companies are realizing that this is an unduly narrow view:

  • Search engine marketers (SEO and SEM) have, for years, used various keyword research tools to try to determine what words their target customers are using explicitly off-site in a search engine (although the goal of this research has been to use that information to bring these potential customers onto the company’s site)
  • Integration with a company’s CRM and/or marketing automation system — to combine information about a customer’s on-site activity with information about their offline interactions with the company — has been kicked around as a must-do for several years; the major web analytics vendors have made substantial headway in this area over the past few years
  • Of late, analysts and vendors have started looking into the impact of social media and how actions that customers and prospects take online, but not on the company’s web site, play a role in the buying process and generate analyzable data in the process

The “traditional” web analytics vendors (Omniture, Webtrends, and the like) were, I think, a little late realizing that social media monitoring and measurement was going to turn into a big deal. To their credit, they were just getting to the point where their platforms were opening up enough that CRM and data warehouse integration was practical. I don’t have inside information, but my speculation is that they viewed social media monitoring more as an extension of traditional marketing and media research companies that as an adjacency to their core business that they should consider exploring themselves. In some sense, they were right, as Nielsen, J.D. Power and Associates (through acquisition), Dow Jones, and TNS Media Group all rolled out social media monitoring platforms or services fairly early on. But, the door was also opened for a number of upstarts: Biz360, Radian6, Alterian/Techrigy/SM2, Crimson Hexagon, and others whom I’m sure I’ve left off this quick list. The traditional web analytics vendors have since come to the party through partnerships — leveraging the same integration APIs and capabilities that they developed to integrate with their customers’ internal systems to integrate with these so-called listening platforms.

Somewhat fortuitously, a minor hashtag snafu hit Twitter in late July when #wa, which had settled in as the hashtag of choice for web analytics tweets was overrun by a spate of tweets about Washington state. Eric Peterson started a thread to kick around alternatives, and the community settled on #measure, which Eric documented on his blog. I like the change for two reasons (notwithstanding those five precious characters that were lost in the process):

  1. As Eric pointed out, measurement is the foundation of analysis — I agree!
  2. “Web analytics,” which really means “website analytics,” is too narrow for what analysts need to be doing

I had a brief chat with a co-worker on the subject last week, and he told me that he has increasingly been thinking of his work as “digital analytics” rather than “web analytics,” which I liked as well.

It occurred to me that we’re really now facing two fundamental dimensions when it comes to where our customers (and potential customers) are interacting with our brand:

  • Online or offline — our website, our competitors’ websites, Facebook, blogs, and Twitter are all examples of where relevant digital (online) activities occur, while phone calls, tradeshows, user conferences, and peer discussions are all examples of analog (offline) activities
  • On-site or off-site — this is a bit of a misnomer, but I haven’t figured out the right words yet. But, it really means that customers can interact with the company directly, or, they can have interactions with the company’s brand through non-company channels

Pictorially, it looks something like this:
Online / Offline vs. Onsite / Offsite

I’ve filled in the boxes with broad descriptions of what sort of tools/systems actually collect the data from interactions that happen in each space. My claim is that any analyst who is expecting to deliver meaningful insight for his company needs to understand all four of these quadrants and know how to detect relevant signals that are occuring in them.

What do you think?

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5 Comments


  1. I agree that we need to take a broader perspective. It makes sense given that what we do as “internet” marketers has evolved/matured to the point where multiple digital tactics are brought to bear on a single initiative (in which the website is just one). Our mission is the same, help understand and inform internet marketing strategy & execution and “digital” helps encompass non-web things such as twitter.

  2. I think this makes sense – it’s like the idea of measuring a brand’s “presence” or something. I am also very keen on your use of the word “signals” here. It’s very apt. Sorry that’s not very articulate! Just imagine me nodding vigorously and saying “hmmmm”

  3. I think this is a very informative article, and I agree, Analytics should reall encompass a whole group of variables. I think “digital analytics” is put nicely.

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