The Art of SEO : Measuring Search Traffic (part 2)

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7/18/2011 5:36:46 PM

6. Using Analytics Dashboards

In analytics terms, a dashboard is a single-page view that contains your most critical metrics all in one place. Of course, your most critical metrics are different from those of the next publisher, because the needs of different sites vary greatly.

In addition, multiple dashboards may be required in any given organization. For example, the CEO of a large public company probably wants to see different data (and a lot less of it) than a senior business analyst.

Each analytics package provides methods for implementing a custom dashboard. Figure 6 is an example of one from Unica’s Affinium NetInsight.

Figure 6. Custom dashboard

As you can see from Figure 6, a dashboard can be quite visual. What is most important, though, is that it provides the data that is most important to the person for whom the dashboard was designed. As an SEO practitioner, you can implement a dashboard to show progress against the goals you set for your SEO campaign.

Providing this type of visibility has two important benefits:

  • The person viewing the report will appreciate the fact that she does not have to work hard to do a quick health check on the progress of the SEO efforts.

  • You will know what data your managers are looking at. When something goes wrong (or right), or when management wants to discuss some aspect of the business, they will have started from the dashboard you set up for them.

7. A Deeper Look at Action Tracking

Action tracking is one step deeper than basic analytics. Rather than simply observing what pages are visited and how many unique sessions are logged, action tracking allows you to narrow down groups of visitors based on the actions they take on your site.

In most instances, it requires setting up a code in your analytics program and attaching that code to a button, page load, image rollover, or other JavaScript-trackable task (a click or hover). Once you’ve plugged it into your analytics and the website, you can use the action to refine data you’re already collecting. Figure 7 provides a look at how this works.

Figure 7. Action tracking in analytics

You can see from Figure 9-7 that:

  • SEOmoz’s sign-up form has action tracking applied to it.

  • Based on the people who sign up, you can predict which search terms will be better at converting visitors into applicants.

  • The Revenue column is empty, but if you were tracking e-commerce buyers, you could put their totals into the Revenue column and track high-volume buyers.

  • Expanding on this idea, you could also track users by time of day, the search engine they used, their geographic location, and so on.

So, what types of actions should you be tracking on your site? The answer varies depending on your business and site structure. Here are some suggestions as segmented by site type.

E-commerce site:

Add to Cart button

Studies have shown us that users who “add to cart,” even if they do not complete the checkout process, are more likely to return to make a purchase. This is also a good way to calculate shopping cart abandonment and make changes to refine and improve the process.

Complete checkout

An obvious one; this action will show you what percentage of each user group is converting into sales.

Save to wish list

E-commerce sites offering wish lists are still in the minority, but wish lists are a great way to track interest that isn’t quite a purchase.

Send this to a friend

Many sites offer a “share this page” function, and it is a great action to be aware of. If folks are sending out your link, you know you have a hit.

B2B site:

Subscribe to newsletter

A subscription is a tacit endorsement of your brand and a desire to stay in contact. It may not be a conversion, but for B2B, it may be the next best thing.

Contact form submission

A runner-up with subscribing to a newsletter is filling out the contact form. Though some of these forms will report support issues, many may contain questions about your products/services and will indicate a desire to open a sales conversation.

Email link

As with contact forms, direct email links have the possibility of becoming a sales contact. The best thing you can do is clearly label sales emails and track them separately from support or business issues.


Subscribe to RSS feed

An RSS feed subscriber is a blog’s equivalent of a conversion; tracking these is imperative.

Add comment

Anyone who is contributing content to the blog or participating should be paid attention to (as should those channels that send you participatory people).

Social bookmark/share

All those folks who are submitting your content to Digg and Reddit deserve to be recognized (and sought after).

Forum or other site based on user-generated content (UGC):

Sign up for an account

These users are active contributors; you need to know where they come from.

Contribute content

When a user publishes, discovering her path is important (especially if it is not from a bookmark/type-in).

Add comment

As in the preceding list item, comments are a great predictor of engagement.


Even low levels of participation, such as a rating or a vote, are worth tracking when every piece of participation counts.

You can get very creative with many of these and track all sorts of actions. If you offer a tool or calculator, track its usage. If you want to follow who clicks a particular link (rather than just a page), add an action to it. You can even see which users hover on an image.

For many marketers, action tracking is the secret sauce. Once you install and activate this data, it is easy to adjust SEO (or PPC) marketing efforts on particular terms, phrases, or pages that will make a huge difference to the campaign’s efficacy.

For SEO professionals, action tracking is a “cannot-live-without-it” tool. The recommendations made based on this kind of tracking are backed up by real data. High-volume action-tracking studies almost always make a huge impact on a site’s bottom line.

8. Separating the Analytics Wheat from the Chaff

One of the big problems with web analytics is that there is so much data. There is seemingly an endless supply of the stuff—so much that you can get lost in the weeds and waste a lot of time. As Yahoo! Web Analytics’ Dennis Mortensen ( likes to say, do not “report-surf.”

By this he means you shouldn’t get lost in the data, looking at one interesting fact after another, without understanding what business objective you are attempting to accomplish. To avoid this trap, you need to have a plan.

The basis of this plan is the definition of actionable Key Performance Indicators (KPIs). To summarize this concept very briefly, do not view a report unless there is a chance that it will provide enough insight to take action (such as reallocating resources to fix a problem or pursue a new opportunity you discovered).

8.1. Common analytics mistakes

Because of the complexity of web analytics, there are plenty of opportunities to make mistakes. Even if you are laser-focused on actionable KPIs, you can still draw wrong conclusions from the data. Here are a couple of examples:

Making a decision on too small a sample size

A simplistic example would be if you had a keyword that brought you two visitors, and both of them bought something. What does that mean? Your conversion rate will always be 100%? Of course not.

You need to have a test run for a length of time that is statistically significant. According to Jonathan Mendez, long-time evangelist for Offermatica (which is now part of Omniture’s Test & Target product), the “golden rule” for test length is 100 conversions per branch (or tested element). For an A/B test, ideally you would have 200 conversions before you looked at the results. However, if after 50 conversions you have 40 on one branch and 10 on the other, your test is over. If your variance in results is lower, you need more data to make sure the data you are seeing is accurate.

Not recognizing when you have enough data

You can make this mistake in the opposite direction too. When you have enough data, you need to be willing to act on it.

Working with biased data

You can easily collect biased data and make the wrong decision. For example, an e-commerce site basing its SEO plans on December’s traffic numbers is probably being misled. And temporal factors aren’t the only cause—visitor locations, referral sources, and in-house campaigns to existing lists can all skew information.

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