Leveraging Web-Traffic Data for Competitive AdvantageThe Internet is one of the most exciting technologies to evolve in the 20th Century. But can companies exploit the technology for the benefit of both the consumer and the business? Can they identify their good customers and leverage Web-traffic data for a competitive advantage? The answer is a resounding yes.
There is a maturity cycle through which all Web-site owners progress. As a Web site becomes an integral part of a company's business plan, Web-site owners want more information.
They realize that reporting on only hits, or even page views, doesn't offer the information necessary to improve a site's effectiveness, particularly when the numbers can be manipulated by Web-site design. However, investigating and interpreting visit patterns can help determine the most effective placement of information. Also, understanding the quantity and quality of visitors can make a dramatic difference in a Web site's success. The result is improved customer satisfaction and, ultimately, increased sales.
The three elements of Web-site analysis that prove to be most important are path analysis, referral analysis and advanced data mining. Any such analysis, to be effective, requires a well-designed database with a fail-safe method of populating it with clean data. This data must be stored so that the sequence of pages can be determined.
Path analysis is a way to investigate what pages are seen before and after a specific page. This includes determining time spent on each page as well as entry and exit points from the Web site. It is an effective technique for measuring content affinities as well as the effectiveness of site design. It also can be used to measure the impact of creatives.
The Internet is a wonderful medium for experimentation with marketing and design strategies because it allows site owners to change content, immediately measure the results and take appropriate action based upon those results.
Referral analysis determines where Web-site visitors came from. It can be very effective in measuring the clicks on ads placed on other Web sites and the subsequent Web pages these clickers investigated. Such analysis also can reveal how long they spent on each page and the duration of the visit. This information can help assess the value of affiliations with other Web sites or search engine traffic, including search terms used that resulted in those valuable visits to the site. The Web-site owner can thus make appropriate modifications and strike business agreements based upon fact rather than intuition.
Web-site owners often use the term data mining when they have implemented only a query interface for analyzing data. This application is referred to as verification-driven data mining, where the user validates a hypothesis such as, "traffic from a specific location is increasing by x%."
A more sophisticated form is known as discovery-driven data mining and uses techniques such as clustering, associations and neural induction. This application requires advanced software and yields results created by the data relationships and not by a hypotheses. This advanced data mining technology can be very valuable in determining content affinities and site-visitor behaviors, which can increase content effectiveness.
Path analysis, referral analysis and data mining can be effectively implemented without the use of technology that is often perceived as invading consumer privacy like registration or "cookies," although the technologies offer increased analysis potential.
For the Web-site owner who truly believes in the power of the Internet to effectively deliver solutions, the time and resource spent in analyzing Web traffic can yield significant competitive advantages. It does require an investment of time and talent to determine what will deliver a competitive advantage in this new worldwide medium, but it is an investment with a great return.
<I>John Payne is solutions executive at IBM SurfAid Analytics, Dallas.<I>