Determining what Web 2.0 features have the biggest influence on your business is a question of measurement, given that the previous cornerstone of Web metrics -- the page view -- doesn’t capture the full extent of online activity. With the rise of applications based on Flash and AJAX technologies, much of what goes on between a user and a Web page no longer requires the server to generate a new page.
But this doesn’t mean marketers have to guess what’s working online. “The interesting thing about measuring Web 2.0 is that it’s not really that different than measuring Web 1.0. It just has some nuances,” says Judah Phillips, Director Web Analytics, Reed Business Information, who tracks online activity across 130 sites.
The key is using metrics that reflect how users interact with your site in the Web 2.0 world. To that end, Phillips recommends moving away from page views and clickstreams and measuring discreet Web “events” -- user interactions with Web 2.0 features, such as commenting on a blog post, uploading user-generated content or viewing a Flash-based slideshow or video.
By tracking these events, then analyzing their performance and segmenting users by behavior, marketers can get a better sense of which Web 2.0 elements create user engagement and then optimize their sites accordingly.
Here is Phillip’s approach to creating a system to track Web events properly:
-> Step #1. Identify unique online actions that show user engagement
Measuring Web events requires marketers to track datapoints that are similar to page views, but reflect the Web 2.0 interactivity. Start by looking at the Web 2.0 features on your site and then identify the unique events that reflect a user’s behavior once they begin interacting with those features.
Typical Web 2.0 events include:
o Comments on a blog post
o RSS feed subscriptions
o Slideshow or Flash video presentation views
o Updates to a wiki page
o Panning or zooming in on a map or image
o Image, video or audio file uploads of user-generated content
o Creating a mash-up or customized product in a design wizard
o Clicking buttons to subscribe to an offering or access a printable version of a page
Marketers also can classify certain events differently, such as identifying “major” and “minor” events:
- A major event might be a comment on a blog post, uploading a file, viewing a video or other event that signifies significant engagement with that feature.
- A minor event might be an action that requires less commitment on the user’s part, such as interacting with an online map or subscribing to an RSS feed.
“The goal is to start measuring Web 2.0 in a different framework that helps segment the activity of your visitors so you can craft engaging content and generate relevant user experiences,” Phillips says.
-> Step #2. Refine Web analytics system to capture event data
Once you identify the events to measure, make sure your Web analytics tools can capture that data, sort it and generate reports. Unfortunately, most off-the-shelf Web metrics systems don’t provide an easy way to define events in their systems, Phillips says. “You need to really re-assess your Web metrics tool -- can it actually support the identification and reporting and querying across events? If it can’t, how can you get to that point?”
- The first step is to talk to your Web analytics vendor to see if scripting can be modified or added to the system to monitor certain variables or to track meta data on Web pages that can be associated with events.
- If your existing Web analytics system can’t support event tracking, you may need your in-house programming team to develop new code that can track and analyze online activity, such as an AJAX-based routine for passing information to your Web analytics tool.
-> Step #3. Create metrics to score visitor activity
Because users will engage in different Web 2.0 events when visiting a site, marketers need a system to determine which visitors are more valuable. The process requires metrics and formulas that help rank events.
What constitutes a high-value Web 2.0 event and a high-value visitor will vary depending on the type of site and the nature of its audience. For example, an ecommerce retailer might consider viewing a product slideshow as an important Web 2.0 event, while a community-based content site might place higher value in user comments on blog posts.
Here are two sample frameworks to establish visitor value:
- Look for patterns of events that, when taken together, signify a high-value Web visit. If you have already categorized events as major or minor, you can note visitors who engage in a certain number of major or minor events, or specific combinations of events that indicate a highly engaged user. For example, you can search the Web analytics system for users who have added a comment to a blog, uploaded their own media file and subscribed to an RSS feed.
- Develop scores for different events to rank each user by visit. This approach creates a numerical engagement metric by assigning different values to different levels of interaction. For example:
o A user who visits a page with a digital map might be assigned a score of 1
o Zooming or panning on that map might be worth a score of 2
o Contributing data to that map might be scored a 3
o A user who lands on the page, interacts with the map and adds new information would be scored a 6
In addition, you can assign higher scores to repeat visitors or multiple contributions, combining the individual event scores with frequency scores to create a final engagement metric based on that user activity.
Once you’ve established an engagement metric, you can start segmenting users based on their behavior, such as tagging visitors as highly engaged, medium engaged or low engaged. Analyzing Web traffic in this way can reveal important insights, such as whether highly engaged users tend to arrive at your site from searches conducted with specific key words or from certain affiliate sites.
-> Step #4. Track “event streams” along with clickstreams
Currently, Web analytics systems track online behavior in terms of clickstreams -- where users come from and where they go while navigating that site. But tracking the patterns of events users also trigger can illustrate what different visitors do within those clickstreams.
For example, tracking an event stream might show that certain visitors comment on a page and then subscribe to the RSS feed associated with that content, then use an online widget or rich media application.
By analyzing event streams, you can learn a great deal about user behavior and assign different upsell or cross-sell activities based on those patterns. “Having an event path through a Web site provides the ability to better segment your traffic and tailor the user experience to different needs and objectives.”
-> Step #5. Mine event data for optimization and upsell opportunities
Once you have accumulated event data, you can begin mining it to determine which Web 2.0 features are among your site’s best performers. The analysis will rely on developing new key performance indicators that reflect your site and your organization’s goals.
Sample indicators to track include:
o Ratio of events to visitors
o Number of events per page
o Number of events per visit
o Features that generate the most events
With these numbers, you can begin optimizing your site to enhance the user experience:
- If one Web 2.0 feature generates the most events, focus your time and money developing that feature set.
- If certain types of blog posts generate the most comments per visitor, emphasize those kinds of posts.
- If a certain blog or other type of content consistently generates the most contributions (comments, uploads of user content), consider placing them more prominently on the site.
- If you syndicate content, you can make sure you’re syndicating the content that generates the most user interaction.
You also can create rules to correspond with real-time user behavior:
- If you notice high page abandonment around a certain event, take a close look at the typical user path to that Web 2.0 feature or its functionality. You might find a specific problem with that function or notice a pattern in event streams or clickstreams that leads to high abandonment. Then tweak your site’s navigation to limit the confusion.
- Look for ways to optimize upsell or cross-sell offers based on user behavior. For example, you can create customer loyalty offers for users who make frequent contributions (blog comments or uploads of user-generated content). After that, you can establish rules in your content management system that trigger those offers for visitors who match the frequency metric for online contributions. Useful links related to this article
Judah Phillips’ blog, Web Analytics Demystified:
Reed Business Information