From Web Analytics to Business Intelligence to Analytics

Right now, there is a shift happening in how organizations see Web analytics. This shift is part of the maturation of data usage within organizations. Before Web analytics, many organizations had investments in business intelligence (BI) solutions and technologies. Then, the Web came about, and dedicated Web analytics companies (WebTrends, Omniture, CoreMetrics, etc.) sprung up to quickly address these new data and reporting needs.

With the existing capabilities to handle large data sets and provide custom reporting, traditional business intelligence solutions really missed the boat. All they needed to do was figure out how to collect and store the data. But now is their chance to catch back up as organizations begin realizing that the Web is just a single part of the puzzle.

In order for this to happen, business intelligence solutions (Microstrategy, Cognos, Business Objects, etc.) need to develop competing offerings that allow organizations to quickly hit the ground running, with the goals of:

  1. Integrating Web traffic data into their solution from existing Web Analytics players (as mentioned above)
  2. Capturing Web traffic data and storing it in a raw form with a proper database
  3. Selling reporting solutions and visualizations that immediately address the shortcomings of “canned” Web analytic solutions.

In addition to the traditional BI providers mentioned above, there are now reporting-focused solutions such as QlikView and Tableau that enable organizations to quickly drop a visualization and reporting layer/solution on top of a, existing data source. So, once an organization can figure out the data collection and storage side of online performance (no small feat of course), these solutions can surpass the canned reporting limitations of the traditional Web analytics providers.

I’m not trying to say that anyone should leave Web analytics for BI here (in favor of one over the other), but what I am saying is that this is the time for organizations to consider how important it is to integrate Web analytics data with other data sources, what they could do if they owned their own data, had ready access to the raw data, and were not limited by “canned” solutions. The line between Web analytics and BI is starting to blur. If the choice were mine today, this is the approach (simplified of course) that I would take as the owner of analytics (not Web or BI) within an organization as we head into the future :

  1. Acknowledge that the Web is only another source of insight
  2. Collect and store my own data (I’m very intrigued by Pion as a collection tool)
  3. Deploy a reporting solution where I could create any visualization or reporting needed by business stakeholders (QlikView and Tableau could do this once you’ve solved the data storage side of things)
  4. Socialize reporting, analysis, insights and recommendations. Make analytics and knowledge sharing collaborative (again, QlikView and Tableau can facilitate this)

As an analyst, why would you not want access to raw data and the ability to create your own reporting and visualization solutions? And, you are no longer limited by the reporting and data integration capabilities of a “canned” solution that tries to do the collection, storage and reporting within a single environment.

This is all easier said than done of course, and could be more expensive than the “canned” solution. But, there are trade offs to be made in which ever direction you head. Will you sacrifice greater data integration, data ownership, and collaboration, or will you sacrifice the safer, easier to implement, solution? The decision is yours to make, but make sure that you weigh both options.

2 thoughts on “From Web Analytics to Business Intelligence to Analytics

  1. Great post Jason and I agree with you completely that the lines between web analytics and BI are beginning to blur.  Gary Angel called this trend at Semphonic’s XChange in 2011: 
    You rightly highlight the cost and complexity of breaking data out of the web analytics silo into the “BI world”.  There are some productised solutions to this problem though.  My company iJento offers one such solution.  We take advantage of the “raw data” export formats that tools like SiteCatalyst and Webtrends offer, and transform that data into an open-schema SQL Server database – a much easier starting point for integration with BI tools and techniques.  For example, we have several clients using Tableau to work with visitor-level digital behavior data.

  2. @John – That is a very interesting product you have there. I’ve always said that the big Web analtyics providers are fantastic at the collection side of the data. But if you want really free that data up for serious analysis and integration with other data sources, then having the data in an offline data mart such as this would be fantastic.

    As someone that has managed many Analytics strategies and implementations over the last 10 years, I can quickly see the value in a solution such as yours. Having access to the data means that you could change things if a problem is found in your implementation for example, and you could report on data the way you wanted.

    Oh, and bravo to you for handling the raw data feed that Adobe provides. That thing can be a beast. I used to work for a publishing company where a single site received over 14 million page views per day, and the idea of doing anything with that data feed was almost unimaginable. I think it was several gigs of data per day.

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