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Web Analytics 101, Part 2

jones-ron
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Before we look at specific tools, I want to cover a couple more principles I didn't get to in "Web Analytics 101, Part 1." When using Web analytics, it's easy to get caught up in all the numbers and statistics and lose sight of the overall goal -- getting the intelligence you need to make effective adjustments to your Web site and online marketing strategies to increase the ROI your site delivers. It doesn't do any good to use Web analytics to produce cool charts and reports but then fail to make adjustments to improve your site's performance!

To illustrate how Web analytics can be used to make decisions to improve the effectiveness of an online marketing strategy and the performance of a Web site, consider the following examples:

  • Analysis: Site visitors are abandoning a sale during a particular step in your site's checkout process. Strategy: Look for ways to improve or eliminate that step in the checkout process.
  • Analysis: A particular e-mail campaign produces a lot of traffic to the landing page but very few sales/conversions. Strategy: Look for ways to improve the campaign landing page and/or e-mail content to encourage more conversions.
  • Analysis: Several different PPC campaigns are producing mixed results. Strategy: Eliminate or focus on improving less effective campaigns and continue with effective campaigns.

Measuring Your Site's ROI

Entire books have been written about this topic, so don't expect to understand this in detail at first. The basic idea is fairly simple and I've summarized it below:

  1. Set trackable goals/conversions for your site (emphasis on the word trackable).
  2. Assign a value to each goal/conversion.
  3. Use analytics to track the number of conversions and the associated source (e.g. sales revenue from natural SEO, paid search, e-mail campaigns, etc.).
  4. Compare the cost of each traffic source against the total conversions/benefit generated by that source.
  5. Use ROI data to make adjustments to your site and online marketing strategy.

Two Flavors of Web Analytics: Log Analyzers vs. Tag-Based Analytics

Web analytics tools come in two basic flavors: log file analyzers and tag-based tools. Log analyzers don't require any changes to Web site code -- they use the log files that your site generates automatically and analyze this data to produce reports and charts.

On the other hand, tag-based tools require the addition of some (small) code to each page of your site you want to track. These tags send information to a database/server, which then uses the data for generating analytics reports. In general, log analyzers tend to be software that is purchased and installed, while tag-based analytics programs tend to be hosted on another site and accessed via a Web browser.

Neither of these flavors is fundamentally better than the other. Tag-based tools, like Google Analytics, seem more popular recently. If you don't have much control over your site code, however, a log analyzer might work better.

It's important to understand the difference and what needs to be done to implement each type. In the end, this shouldn't be a huge determining factor in picking a Web analytics tool.

Let's look as some basic and advanced tools.

Basic Tools

Basic Web analytics tools are ideal for personal or small sites. I'll quickly review three of the most popular ones: Webalizer, StatCounter, and Mint.

  • Webalizer: A good free solution for anyone who wants to control the data and keep it on their end. However, Webalizer is rather data intensive. It displays some graphs but is mainly tables of data. Basic stats include number of visitors, referral, search term, entry and exit pages, hourly traffic, and basic geographic information.
  • StatCounter: This tool has similar stats, but provides more detailed information, including visitor paths, returning visitors, browser data, operating system, and IP. StatCounter is a hosted solution, which means you have to paste a line of code into every Web page you wish to track. StatCounter has more graphs than Webalizer and allows you to export your data into an Excel file.
  • Mint: Like Webalizer, Mint must be installed locally and only works with Linux servers. It's a little more robust and easier to use than Webalizer. A unique feature of Mint is "peppers," which allow you to plug-in features that other developers have created, like conversion funnels. It also allows you to view your stats through RSS instead of logging into Mint each time. The downside: a $30 one-time fee to use. Overall, Mint is great balance of general, yet detailed statistics.

Advanced

Many advanced analytics solutions allow you to track conversions, goals, revenue, expenses, etc. These solutions aren't for the faint of heart; they're designed to provide detailed metrics to make decisions on the best way to make improvements. For space reasons I'll cover only two: Google Analytics (formally Urchin) and Omniture.

  • Google Analytics: This is the most robust solution for its price, which is free. It can track campaign conversions, goals, visitor performance, basic ad A/B testing, and content performance. It's a tag-based solution that boasts all the features that basic providers have, as well as a site overlay and flexible dashboards.
  • Omniture Sitecatalyst: If you spend a lot of money on online advertisements and are in a competitive industry, SiteCatalyst may be your solution. SiteCatalyst is great if you're looking for more flexibility and need go beyond what Google Analytics can provide, but with a price. SiteCatalyst starts around $1,500 to $2,000, but the data it provides can be easily justified. One great feature is comparison, which allows you to compare different campaigns and groups to see how they're doing against each other, so that campaigns can be optimized.

There are many other options, which also vary in price. Consider HBX, WebTrends, and Lyris (formerly ClickTracks).

Take a close look at what your needs are and find a tool that's good match. Let me reemphasize the importance of first establishing goals and then using these tools to help measure against those goals. A good analytics strategy is very well worth it.

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