Web Analytics Tools Comparison


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A 5-minute blitz presentation from the February 2011 Columbus Web Analytics Wednesday. This was a comparison of the major web analytics platforms -- Google Analytics, Adobe Omniture Sitecatalyst, Webtrends, and Coremetrics. The comparison was limited to the base tools -- not the various add-ons available.

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  • There are lots of tools out there, but I focused on the major ones in the market. I don’t have enough depth of experience with Coremetrics to cover it on all fronts, so it is selectively included.
  • All of the paid tools have a range of available add-ons. The main one is that they all have a “warehouse”-type tool that allows for deeper ad hoc analysis of data. This presentation is limited to the base packages and what they can do.
  • There are a number of considerations that used to be relevant but really no longer are.
  • Price – this is an easy one, in that Google Analytics is a free service and the other tools are not. As for which of the paid tools is “cheaper?” They all are negotiated contracts, and it’s going to come down to how good your procurement team is at negotiating deals as to what the final cost winds up being.
  • This is the biggest fundamental difference that sets Sitecatalyst apart from other tools. Unfortunately, it’s also difficult to articulate succinctly. This gives Sitecatalyst a lot of its power and flexibility, in that it involves the highest amount of control right at the point where the user action occurs. The downside is that it requires a lot of up-front thought and planning to implement the tool in a way that makes use of that control, and it’s easy for an implementation to degrade quickly if someone who understands the rationale behind the eVar, prop, and events configuration isn’t available to keep an eye on things. In my experience, the staunchest supporters of Sitecatalyst are the first ones to point out that most implementations of the tool aren’t up to their standards, and, thus, aren’t delivering the value that they could.
  • Campaign data is the most common example of “adding meta data.” In the case of Coremetrics and Google Analytics, some level of campaign data is embedded in the tracking parameters themselves, which has both its pros and cons. But, adding cost data, “roll-up” data, and other information can be very handy, and it’s simply not something that is available within Google Analytics (it can be done using the API, but this still means matching up data external to the tool itself).
  • This is most useful if you are looking to feed site behavior for users into a CRM, marketing automation, or targeting engine. It’s forbidden with Google Analytics, and there is an added cost for doing this with any of the other tools – requires an add-on to the base package.
  • Google Analytics absolutely shines at segmentation. A number of segments are available standard – new visitors, returning visitors, paid search visitors, organic search visitors, etc. – and can be applied to almost all of the reports in the tool. Creating advanced segments is fast and easy and can be performed by someone who only has user access to the tool. When a new segment is created, data is available historically – it’s not just data available from that point forward.With Webtrends, new profiles can be set up that only include traffic that meets certain criteria. But, to set these up requires admin access (and that a profile be available – this may or may not be the case depending on the terms of the contract), and the data is only available from that point forward unless historical data gets reprocessed.Sitecatalyst also has this capability using ASI slots, but that requires admin access and that the warehouse functionality is added to the base product (this can also be done using Discover, which sits on top of the warehouse and has an added cost)
  • All tools have “previous/next” page functionality: “Where did visitors come to this page from?” and “Where did visitors go to immediately after this page?” Sitecatalyst and Webtrends have page-level clickstreams, but this really is seldom useful, as the most popular path through any site is typically only a fraction of a percent of all of the paths. Users all behave differently at the individual page level. Google Analytics does not offer this capability at all.Aggregated clickpaths can be very useful, in that they enable a “roll-up” of the content. Sitecatalyst has tremendous power in this area…assuming the s.props on the page are configured in a way that enable the desired aggregation.
  • My time is up!
  • Web Analytics Tools Comparison

    1. 1. Web Analytics Platforms<br />How (some of) the Main Ones Differ<br />
    2. 2. Included<br />Excluded<br />Yeah…I know<br />
    3. 3. Included<br />Excluded<br />Segments (formerly Marketing Warehouse), Optimize, Apps, Social,…<br />Discover, Insight, Test&Target, SearchCenter,…<br />Explore, Monitor, Benchmark,…<br />This is only a 5-minute overview!<br />
    4. 4. Non-Considerations<br />First Party Cookie Support<br />All of ‘em have it<br />Mobile Site Tracking<br />All of ‘em have it<br />API Availability and Excel Integration<br />All of ‘em have it<br />SaaS always an option, and in-house only makes sense in rare situations -- extreme privacy/security policies, long-term data archiving, etc.<br />SaaS vs. In-House vs. Either<br />
    5. 5. Free<br />Paid<br />
    6. 6. Where Majority of Configuration Occurs<br />Mechanism: props, evars, events<br />Pro: configuration at the point of user behavior<br />Con: easy to botch the implementation, and maintenance requires heavy IT support<br />Javascript on Page Builds Image Request<br />Sitecatalyst<br />GA: Custom variables<br />Webtrends: Meta data<br />Web Analytics Server Parses Image Request<br />Mechanism: profiles and filters<br />Pro: data still fairly “raw” and can be routed into multiple reporting areas<br />Con: customization at the point of data capture is limited / constrained<br />Google Analytics<br />Webtrends<br />Sitecatalyst: VISTA rules<br />Data Stored in Web Analytics System<br />Reporting Interface Used to Extract Data<br />
    7. 7. Integration with Third-Party Meta Data<br />Javascript on Page Builds Image Request<br /><br />Translation files<br />Web Analytics Server Parses Image Request<br /><br />SAINT classifications<br />Example: Campaign name and channel<br />Data Stored in Web Analytics System<br />Meta Data Added<br />Category Definition File (CDF)<br />K<br />Reporting Interfaced Use to Extract Data<br /><br />Not an option!<br />
    8. 8. User-Level Data<br />Available with Segments (formerly Marketing Warehouse): Added Cost<br />K<br />K<br />Available with Discover: Added Cost<br />K<br />Available with Explore: Added Cost<br /><br />Not an option and violates Terms of Service to capture in a reportable fashion<br />
    9. 9. Visitor Segmentation<br />Quick and Easy<br />Harder / Limited<br /><br />K<br /><br />(ASI slots…which requires Warehouse)<br />(Filtered profiles…or Segments)<br />Admin access required<br />
    10. 10. Clickstream / Pathing – A Spectrum<br />“Previous” and “Next” Page<br />Aggregated Click Paths<br />Page-Level Clickstream<br /><br />Any s.prop can have pathing enabled<br />Sitecatalyst<br />K<br />Content groups and subgroups<br />Webtrends<br /><br />GoogleAnalytics<br />
    11. 11. Mobile App Tracking<br />* Now in the mobile app developmentbusiness, too, with the acquisition of Transpond<br />
    12. 12. Social Media<br />First seriously to market, and still investing heavily<br />Fast follower, and taking the space seriously<br />Over-reliance on “impression tag*” for social media<br />Reliance on user community to develop hacks / implementation options<br />* Coremetrics differentiator – geared towards display ad “view through” measurement; not a panacea, though<br />