Google Analytics
This topic comes up a lot because GA and its progenitor Urchin are pretty darn good tools. So why pay for anything else?
On the whole, I like Google Analytics a lot but as an analyst with a lot of experience I see much more value in WebTrends, especially for an e-commerce site where a bit of insight is worth real money. One thing that often prevents WebTrends from being fully utilized is its learning curve, which we get around by starting clients at an above-average level of sophistication in their reports that will hopefully serve them well for a long time, transferring the end-user's "thinking" part of the work to Excel where possible. But directly out of the box, report for report, WebTrends does not have an advantage over GA and certainly not if you factor in the price.
Google Analytics is an excellent tool up to a point. It does a fine job of rendering the basic level of statistics and is superior for campaigns and referrers, and visuals like its geography reports. However, it is a “report card” type of tool that is used for trending high-level statistics or side-by-side comparisons of campaigns or keywords according to a few bottom line performance indicators. And recently, GA added some A/B testing capability which adds another type of decision support. It’s certainly an exceptional value, but for managing a web site, web site marketing, or product management, I don't perceive it to be as valuable as the more flexible tools.
One major drawback of ASP tools like GA is that data cannot be re-analyzed at all. New ideas cannot be investigated by checking historical patterns and errors in setup can’t be fixed except going forward. Without re-analysis, many decisions go unsupported or are delayed until enough data has been collected.
A shortcoming of GA's feature set that is frustrating to many users is its inability to create a report confined to a visit or visitor type. Google Analytics handles segmenting by referrer or campaign but cannot report separately on groups separated by things like geography, time of day, day of week, frequency or recency of visits, visitor lifetime value, or whether a particular page was seen during the current or any past visit.
The lack of visitor history information is especially frustrating. Apparently, a campaign can score a conversion only in the original visit. Campaign latency reports aren't available.
Another has to do with its method of path analysis. Believe it or not, there are several ways of describing the path people take through a site, and Google happens to use the least accurate method. Since a carefully analyzed path analysis can be the basis for developing a typology of visit behaviors, this is a drawback for the idea of basing marketing programs or site personalization on visit behavior types.
Google blobs together all parameters in one report which is a nightmare for sites that use more than one or two parameters in one URL. Not being able to isolate them (or pairs of them) would just about drive me crazy. I suppose the solution is to dump that whole report into Excel and start writing macros. This shortcoming surprised me more than anything else when I started using GA.
Analytics people who want to cull patterns from massive amounts of data like to aggregate rather than split data. In web analytics this means treating several pages as one unit in order to know about visits that saw one or more of a certain set of pages that the analyst thinks belong together. In WebTrends and other software this is done with “content grouping.” [the following was changed 2/2/2009 thanks to a constructive challenge on e-nor's web analytics blog] Google Analytics does Content Grouping as an Advanced Custom Filter, or maybe it's called a Custom Advanced Filter, based on the whole URI. Although it doesn't allow quite as much precision as WebTrends (which treats the URI stem and query string separately when setting up a content group), it does allow regular expressions and, frankly, our categorizing this as a deficiency on GA's part has to be confined to the fact that it's so well hidden in the interface!
There are whole web sites and blogs that deal with Google Analytics and ways to hack around its shortcomings. One “discovery” that was recently widely cited had to do with tricking GA into reporting on the “actual keyword searched on” juxtaposed with the “keyword paid for” for individual visits. This kind of report is trivial to do in WebTrends using the Custom Report feature. Another area of reporting that is somewhat neglected by GA is on-site search. There can be a big payoff in being able to see what is searched for, what keywords produce no results, the page context for searches, and actions after searches. While not helpful for simple high-volume sites like some retailers, it's invaluable for information-intensive sites.
But I think GA’s greatest shortcoming is that it has no API for its results, which means it is limited in being used for more complex analysis and trending, combining with other data sources such as store sales, or using customer databases to create analyses based on CRM data. I've been heavily using the WebTrends API and an interface-building tool (DataLinks by BIData) to quickly create, in Excel, dashboards as well as detailed reports that would have been only a dream six months ago. As I said in our meeting, these spreadsheets can be refreshed quickly with new data ranges, but more importantly the analysis and presentation layers can be custom-modified by end users who know Excel.
Cost can't be ignored, though. Regarding the cost of WebTrends, there are several ways to increase value while controlling costs. Not all pages have to be tagged, and if all are tagged, not all have to be analyzed if good preprocessing or report planning is used. Buying software is a way to save money on WebTrends’ ASP model. Features can be purchased selectively, and discounts can be negotiated. Training and the more sophisticated reporting setup can be spot-farmed out.
On the whole, I like Google Analytics a lot but as an analyst with a lot of experience I see much more value in WebTrends, especially for an e-commerce site where a bit of insight is worth real money. One thing that often prevents WebTrends from being fully utilized is its learning curve, which we get around by starting clients at an above-average level of sophistication in their reports that will hopefully serve them well for a long time, transferring the end-user's "thinking" part of the work to Excel where possible. But directly out of the box, report for report, WebTrends does not have an advantage over GA and certainly not if you factor in the price.
Google Analytics is an excellent tool up to a point. It does a fine job of rendering the basic level of statistics and is superior for campaigns and referrers, and visuals like its geography reports. However, it is a “report card” type of tool that is used for trending high-level statistics or side-by-side comparisons of campaigns or keywords according to a few bottom line performance indicators. And recently, GA added some A/B testing capability which adds another type of decision support. It’s certainly an exceptional value, but for managing a web site, web site marketing, or product management, I don't perceive it to be as valuable as the more flexible tools.
One major drawback of ASP tools like GA is that data cannot be re-analyzed at all. New ideas cannot be investigated by checking historical patterns and errors in setup can’t be fixed except going forward. Without re-analysis, many decisions go unsupported or are delayed until enough data has been collected.
A shortcoming of GA's feature set that is frustrating to many users is its inability to create a report confined to a visit or visitor type. Google Analytics handles segmenting by referrer or campaign but cannot report separately on groups separated by things like geography, time of day, day of week, frequency or recency of visits, visitor lifetime value, or whether a particular page was seen during the current or any past visit.
The lack of visitor history information is especially frustrating. Apparently, a campaign can score a conversion only in the original visit. Campaign latency reports aren't available.
Another has to do with its method of path analysis. Believe it or not, there are several ways of describing the path people take through a site, and Google happens to use the least accurate method. Since a carefully analyzed path analysis can be the basis for developing a typology of visit behaviors, this is a drawback for the idea of basing marketing programs or site personalization on visit behavior types.
Google blobs together all parameters in one report which is a nightmare for sites that use more than one or two parameters in one URL. Not being able to isolate them (or pairs of them) would just about drive me crazy. I suppose the solution is to dump that whole report into Excel and start writing macros. This shortcoming surprised me more than anything else when I started using GA.
Analytics people who want to cull patterns from massive amounts of data like to aggregate rather than split data. In web analytics this means treating several pages as one unit in order to know about visits that saw one or more of a certain set of pages that the analyst thinks belong together. In WebTrends and other software this is done with “content grouping.” [the following was changed 2/2/2009 thanks to a constructive challenge on e-nor's web analytics blog] Google Analytics does Content Grouping as an Advanced Custom Filter, or maybe it's called a Custom Advanced Filter, based on the whole URI. Although it doesn't allow quite as much precision as WebTrends (which treats the URI stem and query string separately when setting up a content group), it does allow regular expressions and, frankly, our categorizing this as a deficiency on GA's part has to be confined to the fact that it's so well hidden in the interface!
There are whole web sites and blogs that deal with Google Analytics and ways to hack around its shortcomings. One “discovery” that was recently widely cited had to do with tricking GA into reporting on the “actual keyword searched on” juxtaposed with the “keyword paid for” for individual visits. This kind of report is trivial to do in WebTrends using the Custom Report feature. Another area of reporting that is somewhat neglected by GA is on-site search. There can be a big payoff in being able to see what is searched for, what keywords produce no results, the page context for searches, and actions after searches. While not helpful for simple high-volume sites like some retailers, it's invaluable for information-intensive sites.
But I think GA’s greatest shortcoming is that it has no API for its results, which means it is limited in being used for more complex analysis and trending, combining with other data sources such as store sales, or using customer databases to create analyses based on CRM data. I've been heavily using the WebTrends API and an interface-building tool (DataLinks by BIData) to quickly create, in Excel, dashboards as well as detailed reports that would have been only a dream six months ago. As I said in our meeting, these spreadsheets can be refreshed quickly with new data ranges, but more importantly the analysis and presentation layers can be custom-modified by end users who know Excel.
Cost can't be ignored, though. Regarding the cost of WebTrends, there are several ways to increase value while controlling costs. Not all pages have to be tagged, and if all are tagged, not all have to be analyzed if good preprocessing or report planning is used. Buying software is a way to save money on WebTrends’ ASP model. Features can be purchased selectively, and discounts can be negotiated. Training and the more sophisticated reporting setup can be spot-farmed out.
posted by cg at
3:08 PM
1 Comments:
Using the webtrends ODBC you could create dashboards using InfoCaptor. It is much more flexible and feature rich.
Post a Comment
Subscribe to Post Comments [Atom]
<< Home