If properly implemented and used, web analytics provides an array of the following powerful functions:
Provides marketers with information about number of page views, number of first-time visitors, unique users, return users, search keywords, user domain, geographic location, pages viewed, entry pages, exit pages, referring web site, frequency of user visits, frequency of downloads and repeated views.
- Path Reporting.
Enables marketers to visually grasp the visitor leads, compare and contrast multiple reports with a help of information such as last page and next page flow, most visited pages, entrance and exit pages, and fallout reports. This function provides the possibility to research how, when, from where users are navigating through the website.
- Conversion Reporting.
Provides marketers with detailed information about purchasing metrics, customer loyalty, campaigns, visitor profiles.
- A/B Comparison.
This method simplifies design changes by comparing site performance across different segments, versions of websites or time frames. With this tool, marketers can compare various versions of the website and improve the website in the most efficient way possible.
- Campaign Analysis.
The marketers can analyze marketing campaigns and track the users’ footsteps in terms of which particular advertisements the users were exposed to before reaching the website.
- Report Methods.
This function enables an analyst to bring various reports to a customized dashboard for analyzing and comparing them.
Having an opportunity to obtain, track and measure the outcomes of the online activities creates a decision-making environment which is not based on opinions, assumptions and guesses, but relies on real data rational solutions. There are certain practices that need to be kept in mind such as:
- 1. Avoiding preconceptions. Analyzing metrics such as bounce rate is a very tricky process. A high bounce rate should not always be perceived as a negative sign – What if the visitor made a purchase and left? The bounce and conversion rates would be high for that page. The marketer should analyze a number of metrics in order to make conclusions.
- 2. Regularly test the performance of a website, web page or an ad trying out different designs. For instance, A/B testing is one of the most popular tests that allows to serve different designs and make conclusions which are working the best.
- 3. Investigate historical data and compare it to the current trends.
- 4. Communicate. “Analytics is a valuable tool for evaluating online performance, but it’s strictly quantitative. All sites should also be looking for qualitative input, and the best source of this data is your visitors. Use real-time survey tools or e-mails to registered users to get feedback from actual visitors” (Rapoza, 2012).
Sometimes the businesses are so busy developing and managing the websites and ad campaigns so that they forget to tie that back to the actual outcomes. “The challenge is to make the connection between effort and eventual outcomes, between the initial investment and eventual return on that investment” (Guenther, 2003). Are the efforts effective? Do they bring any results? The marketers should know what metrics to track, what data to capture and how to turn results into actionable insights that will support decision-making. The goal is to establish meaningful metrics prior to launching any online activity so that it could be tracked, analyzed and, in other words, controlled.
“The goal of web analytics is to attract the right visitors for the lowest cost, turn visitors into consumers or customers (conversion) and build brand loyalty so that these customers repeatedly come back. With conversion applied directly to a formal campaign or promotional effort, an organization can determine specific return on investment for each new customer. Done successfully, the return of gaining a new customer, and especially a repeat customer, should outweigh the cost of attracting and keeping the customer”. (Guenther, 2003).
Guenther, K. (2003, December). Nothing Measured, Nothing Gained. Online, pp. 53-55.
Rapoza, J. (2012, June 12). Best Practices for Web Analytics. Information Week, p. 40.