Aaron Gray // Greater Returns


Musings on Web Analytics, product strategy + other stuff.

Tracking Google Universal Search

Next week I’ll be on the panel again for Portland State University’s Quarterly Digital Marketing Breakfast. The event is put on by the University’s Multimedia Professional Program and features panelists from the Digital Marketing Strategies certificate program, in which I am an instructor.

If you want to register, hurry.  Registration closes in two days (2/12).  To find me at other events, subscribe to my Plancast feed.

On the upcoming panel, I’ll be talking about how you can better track search results in Google’s Universal Search results page, allowing you to understand not only what search terms drive traffic to your site and/or or value for your business, but which type of result (blog, image, etc.) is working best for you so you can optimize for the specific words and result types that best benefit your business.

Join me and the other panelists from PSU’s Digital Marketing Strategies certificate program for a lively and informative discussion about Google Universal Search.


If you were at the panel discussion and didn’t get a chance to jot down the blog posts I mentioned here they are…

This post, by Martijn Beijk at SearchCowboys.com explains how to set up Google Analytics to track which type of search result was clicked on the Google search engine results page.

This post, by Mike Belasco at seOverflow explains how to set up Google Analytics to track clicks on local search results on the Google search engine results page.

Filed under: Events, Tools, Web Analytics

Maybe You Need a Web Analytics Turnaround, Not a New Vendor

The Problem

Many companies have invested hundreds of thousands of dollars in web analytics tools and talent, and still find themselves frustrated by a lack of demonstrable value — a lack of real, calculable return on that investment.

It’s not a good situation to be in.  It’s bad personally for the managers and executives who have overseen the investment.  It’s bad for the vendors who take the blame for providing no value.  And it’s bad for the business which, unless corrective action is taken, will continue to throw good money after bad.

What to Do?

Typically, the response to this situation is to blame the vendor and put out an RFP.  It’s a natural response.  But is it the right response?  Most of the time, it isn’t.  Read the rest of this entry »

Filed under: People, Process, Tools, Web Analytics

More OLAP Fun

I’ve taken on a new project in the last few days. I’ll be working to help an enterprise-class company integrate existing customer data into their Visitor Intelligence solution, allowing them to segment existing reports or build new reports, on the fly, with any combination of customer attributes from outside data stores and web analytics data from the page tag.

The power of the reporting and ad-hoc segmentation is as I wrote about here, but this is even more interesting because rather than segmenting and constructing reports only from data collected through page tagging, we’ll be leveraging the power of web services and OLAP style reporting to integrate data about a single visitor from multiple databases and 3rd party systems.

I’ll post more as the project moves forward.

Filed under: Tools, Web Analytics

Adding to Eric T. Peterson’s Commentary on Dainow

So I’ve been keeping quiet on the Dainow post re: Google displacing all other web analytics “products”. Partly because this has been fun to watch, but mostly because I work for one of the other supposedly “dead” competitors. I wanted to see where this landed before I got in the mix.

Eric Peterson’s thoughts
on this are spot on. Here’s Eric:

Dainow demonstrates a near complete lack of understanding of web analytics and the web analytics marketplace. Google Analytics already dominates the market in terms of total domains coded, but dominance isn’t defined by the breadth of your coding, it’s defined by the success your customers have using your application!

I’ll go one further. What Dainow fails to see is the difference between a product and a solution, where a solution is a product and a set of services combined to solve a business problem. While the market well served by Google doesn’t really require a “solution” as much as they simply need a tool to do a job, the customers served by the big players (my employer included) tend to need (and have the money for) services to ensure successful solution design, implementation, deployment, and adoption of the tool set and the business processes required to make good use of the tool set.

The farther you go up the market, out of mid-market and into true enterprise class solutions, the more this is true. In fact, I would argue that in true enterprise-class solution deployments (the area of consulting I specialize in) the services are more important than the tool set. The greatest tool in the world isn’t worth anything if it can’t be successfully deployed across a global enterprise with a standards-based approach. Google, neat tool that it is, is nowhere near displacing the few vendors who can play at this level.

Filed under: Tools, Web Analytics

The Power of OLAP Reporting

With the announcement, today, of WebTrends new OLAP reporting solution (Visitor Intelligence) which adds reporting capability to the evolving suite of tools built on top of WebTrends warehouse architecture, I can finally talk about the power that is coming to the world of web analytics.

If you’re not familiar with OLAP, or multi-dimensional reporting tools, the first page and a half of this article are worth a read. It’s a good introduction to what’s coming.

Essentially, OLAP tools, and WebTrends Visitor Intelligence is no exception, allow you to do deep, ad-hoc drilling and re-arranging of data, on the fly while maintaining the proper relationships and correlations between the dimensional data. While there are pre-configured reports, called Starting Points, in Visitor Intelligence that will meet the needs of “just give me the data” end-users, curious analysts will find themselves in a playground of possibilities.

Don’t like like the order of the dimensions in the report you’re looking at? Rearrange them, and the relationships stay in tact (just like in a pivot table). Don’t like the measures that are in this report? Grab any available measure and drop it in the report. No longer are you confined to defining your report view, and being stuck with that. Nor are you working in a cumbersome environment where the relationships between data are not clearly represented and easily manipulated. The real power is that with OLAP reporting, all you need to know is which dimensions you want to report on, and which measures you want to report. From there, you can construct whatever report you want, on-the-fly, or you can set up starting points that are essentially pre-built reports. Also, the ability to create custom measures on-the-fly is absolutely awesome. No processing time, no analyzing. It’s just there.

Here’s a real-life example from a customer I’ve been working with to develop a robust reporting solution using Visitor Intelligence. This customer has a globally distributed and decentralized online business, which is organized roughly by regions of the world (each country is a division), brands operated by each division, and customer groups serviced on each site. Of particular importance to the customer is understanding how much of each division’s business comes from a country other than where that division operates, and what services those “out-of-country” customers are consuming. This insight will help the business better understand who their customers are, and how to market to them.

In this case, the customer has tagged each of their web sites with a single, universal meta-data model that describes each and every web page in the world, and how it fits into the global organization. The model passes values for the region, country, and division, in addition to descriptive data about product lines and the divisional business units offering the product lines. The result is that we collect a rich set of data easily turned into dimensions in an OLAP environment. The icing on the cake is visit and visitor geo-location data built in to WebTrends that allows us to determine who is “out-of-country” in a particular visit, and who is not.

Upon launch the business will have both default report views tailored to their specific needs, and the flexibility build exactly the right views of the available data. User A, a global business manager who wants to see Unique Visitors by Country, Division, Brand, and Product can easily create that view. User B, a product manager, can build a view that shows Visits and Unique Visitors by Product and Brand. And User C, an analyst, can build a view showing Visitors, Visits, and Visits per Visitor for “out-of-country” visits only broken down by Division, then Country of Visitor, then Product usage broken down to Business Units offering that product.

I’ve never before worked with a web analytics tool that is this powerful, and opens up so many possibilities — and I’ve worked at three different analytics vendors. It still comes down to business results, though, and what a full-featured OLAP solution brings to the table is the ability to easily explore and manipulate the data to discover the insight needed to make business improvements with measurable impact.

Filed under: Tools, Web Analytics