Set Up Google Analytics for Success

by admin on August 18, 2011

Set Up Google Analytics for Success

Google Analytics is the leading online tool for analyzing traffic to your website. The purpose of web analytics for most people is to evaluate data on visitors to and from your website (for online marketers, these are shoppers and potential customers), in order to improve the experience that these visitors have, with the goal of advancing your desired results (sales).

Google Analytics is a powerful tool that can provide a wealth of useful data once you become proficient at it. To get the most out of it, however, you have to perform proper setup. This includes not only technical configuration of the tool but also determining how you want to use it and what you want to get out of it.

First, start by deciding why your website exists and what you want visitors to do. This will help you decide what to measure and try to improve regarding your site. Just measuring the number of visitors to your site or each page is not sufficient. You need quantifiable metrics that directly relate to your goals for the site. If the site’s purpose is to generate ad revenue, then your measures should relate to how many pages and ads the visitors saw. If the purpose is to generate sales leads then measure how many leads were generated. If it’s to sell products then you measure sales revenue.

In addition to metrics, you should have goals in order to evaluate how well you’re doing. Your business plan includes goals for leads, ad views, sales, or what your purpose is. The analytical tool can help you gather data to measure performance.

Google Analytics does include the helpful feature of setting goals for your website. By using the Goals feature, Google Analytics can track your performance and measure metrics against your goals.

You should select just a few metrics that represent how you define success for your website. Google Analytics can provide an abundance of data, but you almost certainly don’t need all of it. Focus on fewer than 10 measurements as crucial, and possibly include a few others as supplementary data.

Be careful when changing configuration settings or filters in Google Analytics. The tool starts recording data immediately after you implement it, and you can’t go back to change previous data. So for continuity, it’s best to make sure you set up and configure the tool correctly the first time.

Segmentation is useful for assessing how each of your activities are doing. Divide your metrics among each of your online business areas, such as PPC, email, and banner ads. Devise metrics to understand which areas are profitable and which are not.

When analyzing web data, consider trends, not specific data points. No web analytics tool is 100% accurate. So look at trends over time, rather than individual numbers, in order to prevent misinterpretation of the data.

Finally, remember that web analytics is a perpetual, ongoing process, just like overall business improvement. When you notice something is working, you find out why and see how you can keep doing that and expand on it. When something isn’t, you find out why and implement steps to improve. Then you measure and analyze again.

Google Analytics is the leading online web analytics tool and it’s free. For in-depth training on web analytics using Google Analytics and other aspects of internet marketing, visit


data analytics

The idea behind this video is to show how innocent operations of a business user within his or her desktop analytics tool (SiSense Prism) turn into complex database operations that would choke any relational database, such as SQL Server or MySQL. This is the main reason why business users couldn’t use tools like this prior to columnar technology. Moreover, to emphasize the dramatic effects of columnar databases, the ElastiCube (a columnar database designed for ad-hoc analytics) was installed on a machine that did not have enough RAM to hold the entire database. This assured that I/O operations (disk reads) must be involved in order to be able to query the entire database (ie using an in-memory database would not be possible). Here’s some technical data: 1. The database was 30GB in size representing granular retail data. 2. The database contained 13 tables. The two largest tables contained 100M and 40M rows each. 3. The database (ElastiCube) was installed on a 64-bit desktop PC (Windows XP) with 6 GB of RAM.
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