First, lets start by defining home pages and their goals. The home page is typically the main gateway page for your site. It’s the first impression that your visitors will have of your site. Its role is to showcase your offerings, your value proposition and provide quick access to the most popular or important sections of your site. For this reason, web analytics should help you answer some of the following questions:

• How effective is the home page at directing visitors to product pages?
• Which part of the home page is the most effective?
• Is the home page effective at enticing visitors to learn more?

Based on these, below are some popular web analytics reports for home page analysis along with the explanation:

• Bounce Rate
• Micro Step Conversion Rate
• Conversion Rate
• Acquisition Sources
• Home Page Real Estate

Bounce Rate

The bounce rate is defined as the number of bounces (single page visits) divided by entries. It shows you what percentage of the traffic landing on the page bounces and does not view any other page on the site. It is a reflection of the home page’s ability to retain visitors. Clearly the goal is to make changes to the home page and lower the bounce rate. It’s probably one of the best reports to look for when analyzing home pages. This report is widely available in most web analytics tools such as Google Analytics, Yahoo! Web Analytics and Unica NetInsight.

Micro Step Conversion Rate

Although the ultimate goal of your site is to drive conversions, we recommend micro step conversions as a better way to assess home pages. The goal of your home page is to drive people to your product description pages. It’s at that level that you do the selling. For this reason, when assessing the success of your home page, it should be around its ability to get visitors to those ensuing pages. You can get this in a number of way. Inside tools such as Yahoo! Web Analytics and SiteCatalyst, you can tag your product description pages as events and look at the success of your home page around this event. In Google Analytics, you can create a goal for your product pages, as long as the pages have a consistent nomenclature. If not, you can create an advanced segment for your product pages and look at the home page traffic for the segment. Such metrics can pretty easily be created inside Unica NetInsight and Webtrends.

Conversion Rate

Yes, this should not be your primary report for home page analysis, but you can still use this report as a tie-breaker. For example, if two versions of home have similar bounce and micro step conversion rates, then you can use the overall conversion rate to see if one version does in fact do a better job. Unfortunately, we often see that many people use conversion rate as the primary report for assessing home page effectiveness.

Acquisition Sources

Want to lower your bounce rate? One place to start is by looking at the acquisition sources. You can start with the sources of traffic to your home page and look at their respective bounce rates. Start with referring sources with high bounce rates. Often, you’ll find a messaging gap between the referring sites and your home page. The referring site may be saying something while your home page could be promoting something else. While you cannot optimize your home page for all referring sites, you can start with those with high traffic and high bounce rates and provide messaging on your home page that helps retain this incoming traffic. You’ll typically find that a handful of sites may account for a high percentage of your bouncing traffic.

Home Page Real Estate

To understand the real estate effectiveness, you’ll have to look at the click activity on the page. Rather than looking at all page links, we recommend classifying the link into sections or categories (such as as header, footer, navigation, left box, right box, etc.), and analyzing the activity by such sections. This is different than the default site overlay that you typically get from web analytics tools and requires some additional configuration to get proper reporting. For example, if you’re using Google Analytics we recommend using Event Tracking to track the activity on various sections and links within sections. You can then see how effectively each section and each link gets visitors to product pages and to final conversion.

You can also investigate some of the in-page analytics tools such as CrazyEgg and ClickTale, which do a more thorough job of providing such reports than web analytics tools.

Of course, depending on your business, your reporting needs may vary, but we believe this list should provide a good starting page for optimizing one of your most important pages.

Page views

This is probably the best out-of-the-box metric for measuring the success of a content. The more the number of page views, the more popular the content. However, relying on this number alone has two potential shortcomings. First, it fails to differentiate between segment traffics. For example, a loyal visitor is more valuable to a content site than someone who visited the site for the first time and will likely never come back. Also, page views alone fail to report the level of engagement on the page. For example, visitors could be clicking an article and spending only a few seconds on it. The quality of traffic should therefore be accounted for.

Time spent on page

This metric clearly adds a new dimension around engagement. The more time visitors spend on the content page the more engaged they are. However, you cannot rely on this metric alone. One key reason is the fact that this metric is not always available to all visitors. For example, if the content page was the only or the last page viewed during the session, then this metric is simply not calculated within popular web analytics solutions (we’ll discuss this in a separate post).

Another shortcoming of this metrics is that like page views, it fails to segment the reports by the quality of visitor (first-time vs. loyal).

And finally, the Time Spent metric alone does not take into account the popularity of the content. For example, an article could be very engaging but only be viewed by a handful of people.

Visitor Loyalty

Web analytics solutions often provide this in context of the overall site traffic and you may have to do some tweaks to your reports to get this, but it’s important to note what percentage of your content is consumed by first-time visitors and what percentage by loyal visitors – visitors that come back to the site. The reason this is important is because in the long run, you may want to create a loyal following and create content that’s tailored to them.

Bounce Rate

This is also one of the most popular metrics within analytics solutions, but media sites should be careful not to over-analyze their bounce rates. As an example, consider a media site with an RSS feed. Through the RSS feed, visitors can see the headlines of new content using their favorite RSS aggregator. If an article looks appealing, they click the link, enter the site, read the content and then leave. That’s a bouncing visit but still a highly qualified traffic, because the visitor has subscribed to the RSS. The visitor loyalty metric indirectly takes care of this shortcoming.

Content Engagement Score

In this post, we’d like to introduce you to a content scoring KPI that we’ve used to help some of our media clients put a monetary value next to their content.

The formula is as follows:

Engagement Score = (Page Views × Avg. Time Spent  × Avg. Loyalty)

Where:

• “Page Views” is the number of times the page was viewed during the reporting time period.
• “Avg. Time Spent” in the average number of seconds or minutes spent on the page by visitors.
• “Avg. Loyalty” is the average number of visits to the site by your visitors (1 for first time visitors, 2 for those who’ve been to the site twice, and so on).

Of the three metrics needed to create this KPI, “Avg. Loyalty” is the most difficult to get, but this can be obtained done using estimates in popular tools. For example, with Google Analytics, you can use the %New Visits metric to estimate the average loyalty. You can use the following formula for this purpose:

Avg. Loyalty = (%New Visits) + 2 * (1 - %New Visits)

What this formula does is that it assigns a score of 1 for each new visitor and a score of 2 for all others, providing a reasonable approximation. You can create a similar model with Yahoo! Web Analytics – see below figure for an example of such report in Google Analytics.

Using this model, pages with the highest traffic, time spent and the most loyal visitors will get the highest scores, which is the desired outcome. You can of course use any analysis tool to create your score. One popular tool is Microsoft Excel, where the score can easily be created and analyzed. See figure below for an Excel example. It shows that our posting for tracking internal campaigns is the most engaging even though it’s an old blog post.

Overall, this model provides a simple KPI for measuring site content, while taking into account the popularity, engagement and the quality of the visitor. It does however have its shortcomings. The primary shortcoming is that it is dependent on cookies. For loyalty to be counted, visitors have to accept cookies. Furthermore as visitors delete cookies, it will impact this KPI. However, it’s fair to assume that visitor cookie deletion is not dependent on their content preference, so you should expect the same rate of deletion across the board.

The metric also depends on time spent reporting, which is not available to all visitors. Having said that, it’s also fair to assume that the time spent by those who view a certain content as their last page should be inline with those who view the content in the middle of the session. After all, the purpose of this model is to provide an approximate score for content engagement and popularity.

You may also be in a mode where loyal visitors are no more valuable than first-time visitors. For example, newer web sites fall into this category. In that case, you can simply omit the “Avg. Loyalty” metric from the formula (or replace it with the value 1).

So there you have it. We welcome your feedback on the model and hope you find it of use.

Happy Analyzing!

One of the best presentations that we’ve seen using this technology doesn’t even involve web analytics. Instead, it’s a presentation by Hans Rosling, the statistics guru about trends in developing countries.

This is not a new presentation, but the concepts presented and lessons about the use of data are still very relevant even in our industry.

What’s so special about Top Sites? Besides the fact that it provides a nice graphical view of your favorite sites, it lets you know if they’ve also been updated since your last visit. That’s right. Safari automatically fetches for new site content in the background and lets you know (using the blue stars in the right corner) that your top sites have been updated.

While this is very convenient for the user, it introduces new challenges for web analytics practitioners. Primarily, the inclusion of your site in your visitors’ top sites means an increasing amount of artificial traffic. Primarily, if you’re in a situation where users of Safari place your site in one of their top sites and don’t end up visiting your site, the traffic will likely show as bouncing traffic. This results in an increase in your bounce rate even though the visitor never entered your site.

We have tested the inclusion of a number of sites in Top Sites and have seen the traffic registered in web analytics even though we never visited the sites.

Safari 4 is currently in beta, so only a small percentage of your audience is exposed to “Top Sites”. Once generally available, this is sure to cause an increase in bounce rates for some popular sites. More importantly, the Safari market share has been on the rise, according to the figure below by Market Share. The latest figures show the market share at 8%. This means that as Safari continues to gain traction, this problem is bound to get bigger.

So as you’re analyzing your data, keep this trend into consideration as it could impact your overall bounce rates.

The pre-defined segments should greatly increase user adoption of this functionality. At the same time, users will be able to further extend the value they get from the tool. We’re going to outline some additional segments that can further add value. For this post, we’re going to concentrate on lead generation site types, whose goal is to generate leads for the sales team that are eventually closed off-line.

Note: These segments are also applicable in other web analytics solutions, even though the examples are provided for Google Analytics.

Some quick win segments that you can get started with are:

1. Form Page Visits
2. Form Abandonment Visits
3. Engaged Visits
4. Highest Value Conversions

Form Page Visits: One of the pre-defined segments in Google Analytics is “Visits with Conversion”. As long as you’ve defined your site goals in Google Analytics, this segment will filter out visits where a goal event has occurred. The segment will let you identify your most effective acquisition sources for example. However, you can take Google Analytics to the next level and define a segment based on visits where your site visitors hit the form pages (just before the conversion). Why? People who make it to the form pages are also considered as qualified visitors, even though they don’t fill out the forms. This segment will also let you identify your best acquisition sources, whether a conversion occurs or not. This segment can be created by selecting the dimension “Page” from the “Content” list and typing in the name of your form pages. If you have multiple form pages, you can add them by adding an “or” statement.

Form Abandonment Visits: This segment will filter out visitors that make it to the form pages but do not complete the process. This segment is valuable because it lets you identify where you’re leaving money on the table. This segment will consist of two filters. The first one is similar to that used for the “Form Page Visits” segment. The second filter is using the metric “Total Goal Completions” and setting the value to equal zero. The relationship between the two filters should be an “and” statement.

Engaged Visits: Regardless of whether your visitors convert or hit the form pages or not, you’re still interested in how they consume your content. The “Engaged Visits” segment lets you filter out the site visitor that are engaged in your content. An easy way to do this is to start by your average number of pages views per visit and time on site. You can then build a segment with two filters. The first filter is by selecting the “Pageviews” metric and making sure that it is set to a value greater than your average. The second filter (“and” statement) uses the “Time on Site” metric, as shown in the figure below. You can take also this segment to the next level by adding recency into the equation. Eric Peterson has recently posted about this very topic, and we recommend his approach for media sites. For lead generation sites a simplified engagement approach should suffice.

Highest Value Conversions: Not all web leads are created equal. For companies that offer only one product or service, this may not be an issue. But for many lead generation sites and companies that offer multiple products, this will be of importance. For example, you may have a free and a paid version of your product. In that case, you would be more interested in visits that result in a lead for your higher-end products.

In some cases, this may be an easy segment to build if your conversion pages for your various products are different. Often times, you’re using the same form page to capture leads for all your products. In such cases, we recommend that you allow visitors to choose which products they’re interested in form within the forms and capture the user selection in Google’s User Defined variable. By doing so, you can then build a segment based on the “User Defined Value” dimension under the “Visitors” group. The new segment will then allow you to determine where to target in order to capture leads for your highest value products.

Apparently, this is not just isolated to web analytics. An analysis of the VP debate by a language monitoring service shows that the phenomenon also applies to the world of politics. Here’s a link to the story.

Highlight KPIs from the VP debate:

Sentences per paragraph: 2.7 for Biden and 2.6 for Palin.

Letters per word: tied at 4.4.

Ease of reading: Biden, 66.7 (with 100 being the easiest to read or hear), versus 62.4 for Palin.

Number of words spoken: 5,492 for Biden and5,235 for Palin.

There is definitely entertainment value in the data, but not much value beyond that.

Why do we bring this up? Because we’ve seen many web analytics practitioners fall into the same trap. Yes, you can measure just about everything online: detailed user interactions, mouse movements, etc. But just because you can measure it doesn’t mean you should. Rather, you should always start with the question “what would I do with the data”.

1. Search Usage
2. Searches per Search Visit
3. Top Search Terms
4. Top Failed Terms
5. Visitor Segmentation
6. Top Pages Driving Search
7. Search Groupings
8. Success Rate
9. Micro Step Success Rate

In this post, we?re going to cover the last three items.

7. Search Groupings

This practice refers to grouping of search terms into categories that make business sense. These groupings ought to be done by business people and not necessarily managed by the capabilities of your site search tool or content management solution.

For example, an electronics reseller may want to categorize the terms ?ipod? and ?zune? as the category ?MP3 players? and treat ?ipod case?, ?ipod speaker? and ?ipod armband? as the category ?MP3 Accessories?. We find this practice to be manageable when done in a spreadsheet such as Microsoft Excel and using the vlookup function.

Why go through this exercise? The answer is because it reveals information about which categories or groupings are most popular among searchers. The information can be used to build a better navigation menu ? one that supports your visitors? interests. So for example, if you find the category ?MP3 Accessories? to represent a large enough portion of your site search traffic, then you can add the category into your navigation menu.

8. Success Rate

Let?s face it. The whole point of implementing a site search is to enhance the user experience towards your business objectives. So if your business objectives is online sales, then site search performance should be assessed using this objective. And if your site goal is to generate leads, then your site search results should be assessed using that objective. Most web analytics tools today will account for this type of reporting. The goal is simply to understand what search terms are converting best so that you can improve your site-wide promotional offerings. Consider the table shown below.

Simply looking at the search conversion report reveals what products have the better success rate and therefore will provide a higher return when being promoted on your site. So if you?re considering promoting a gaming device on your home page, you can see from the above data that Playstation 3 provides the biggest bang for the buck. Even though its conversion rate is less than Xbox 360, because of its higher price it provides more revenue per search than other products.

The search conversion report will provide you information on what works best ? in terms of conversions and dollar values. However when it comes to providing more insight about the reasons, it can come short. This is why we use micro-conversions so that we gain a deeper understanding into the sales funnel. This is covered in the next point.

9. Micro Step Success Rate

Lets face it. Your visitors don?t buy or fill out a form straight from your search pages. The goal of your site search is not to sell an item, but to help you find it. There is a sales cycle that visitors have to go through. First they have to find the product (this is what your site search is designed to do). Then, they have to add the product to cart, and they?ll have to go through the checkout steps on your site. At each stage, various things have to be accomplished to get the visitor to the next stage.

Let?s go back to the conversion table from the previous example, where the conversion rate for each search term is shown. We can see from the table that the terms ?wii? and ?wii sports bundle? are really underperforming compared to others in their category. Does this means that your visitors are not interested in Wii products? Not necessarily. The best way to find out is to look at the micro conversions for these same search terms. This is shown in the table below.

The micro conversions reveal a very different picture. It shows that in fact the click-throughs from search to product pages for the terms ?wii? and ?wii sports bundle? are higher than those of ?playstation 3? and ?xbox 360?. It is however at the product pages that the Wii products underperform. We therefore need to revisit these product pages, at which point we come across the following scenario, shown below.

These products enjoy a high click-through, but once visitors get to the product page, they?re presented with an ?out of stock? message that stops their progress.

Micro conversions let you see the progress at each step and therefore let you diagnose your site at each step of the way. They make it easier to understand where in your site you should concentrate in order to streamline the site conversion.

Conclusion

Of course, based on your site objectives and site search deployment, you will find some reports more valuable than others, but you should be able to select from the list provided in this series to better optimize your site search. Also, if you need help getting the right reporting dashboard in place, we’re here to help.

1. Search Usage
2. Searches per Search Visit
3. Top Search Terms
4. Top Failed Terms
5. Visitor Segmentation
6. Top Pages Driving Search
7. Search Groupings
8. Success Rate
9. Micro Step Success Rate

In this post, we?re going to cover the remaining items.

4. Top Failed Terms

Failed terms are defined as search terms that provide no results to the user. Why is this important? Because it reveals gaps in your site search deployment. You can use this information in a number of ways:

• If a product that you carry is showing up as a failed search, then you clearly need to reindex your site to make sure that those products are displayed in your search results.
• Products you should carry? You may find a series of products that you currently don?t carry but should be in your inventory. The failed terms report will let you know how much money you?re leaving on the table by not carrying these items.
• Misspellings ? Let?s face it. Visitors don?t always correctly spell every word. You should use this report to detect such misspellings and optimize your site search tool for such occasions. For an example of good implementation, go to Overstock.com and do a search for ?bedding? and ?beding? (screen shot below). You?ll see the same results in both cases.

5. Visitor Segmentation

Not all visitors are created equal. Visitors of different segments will behave differently and therefore will search differently. Two segments of interest are “new visitors” and “returning visitors”. By understanding the difference in search behavior between these two segments, you?ll be able to see your site navigation?s effectiveness between these two groups. Typically, you want to look for abnormalities in ratios between new and returning visitors.

Consider the example in the above screen shot. What you see is the top search terms and the breakdown of search between first time and returning visitors. Overall on the site, returning visitors constitute 19.80% of site visitors and we can see that this ratio also holds for most of the search terms. However, you can see that the terms ?vaio battery? and ?macbook battery? both get a greater share of search from returning visitors. Why is it that a larger share of returning visitors are searching for battery products compared to other products? Perhaps it?s because your battery inventory is not well promoted on the site and as a result a smaller share of first time visitors is aware of their existence on your site. Whatever the reason, this high discrepancy in ratios should alert you about an investigation that ought to be made between your navigation and the battery products.

6. Top Pages Driving Search

This report provides a listing of pages that the visitors were on prior to conducting a search. In most web analytics applications, you can simply look at the navigation reports or previous pages to get this data. It reveals what pages did your visitors get stuck before resorting to search. For many people, this may simply be the home page or the landing page, which is not a cause for concern since some people simply resort to site search as their first option. However, if the search originated on a product page, then it could be cause for concern since the product that the visitor was browsing may not have been what they were searching for. In this case, you?re looking for those oddities that could give you insight onto the navigation flow and visitor interest.

In our next and final post, we?ll cover the remaining reports that you should be looking at for site search analysis.

Why? Because most of what web analytics gives you is quantitative data – what your visitors do on your site – and it leaves it to you to figure out from the volumes of data what your visitors are looking for. Site search on the other hand is user-entered data;  your visitors are actually telling you what they’re after.

In this three-part series, we’re going to provide information on the top reports or data points to look for when analyzing site search. The top reports are:

1. Search Usage
2. Searches per Search Visit
3. Top Search Terms
4. Top Failed Terms
5. Visitor Segmentation
6. Top Pages Driving Search
7. Search Groupings
8. Success Rate
9. Micro Step Success Rate

1. Search Usage

This metric is measured as the ratio of visits (or sessions) conducting site search to overall site visits. For example, if your site had 1,000 sessions and 65 of them conducted a site search (hit the search results page), then your search usage (as a visitor ratio) is 6.5%.

Why is this important? Because the search usage could be an indicator of navigation shortcomings. Site search is a navigation feature and is meant to complement your site navigation design. In cases where your navigation fails, then your visitors resort to site search. This isn’t always the case, as we?ll discuss in ensuing points, but if you have a high search usage, then it is an indicator that your visitors are bypassing your navigation and therefore you should be revisiting your navigation design.

Like all KPIs, search usage should be trended so that you can see the impact of site changes to the ratio. In our studies of top e-commerce sites, the site search usage is between 5% to 10%.

2. Searches per Search Visit

This KPI is measured as the ratio of the total number of searches conducted divided by the number search visits (or sessions). Going back to the previous example, say the 65 sessions or users of site search conducted a total of 260 searches. This means that the average search user conducts 4 searches.

Obviously you want your site search results to be accurate and to the point. This means that the higher this number, the more cause for concern you have that your site search is not providing the necessary information to users, forcing them to refine their searches. Realistically, you want the average user to search for no more than two searches per session. Obviously, based on the complexity of the product or service, this number may vary.

3. Top Search Terms

This is the core of site search reporting. What are your visitors searching for? What are they telling you? For example, if your top search terms are ?Wii?, ?Xbox? and ?PlayStation?, then it will be a good idea to have a gaming related promotion or banner on your home page and other main landing pages, since a large number of your visitors are interested in this category. Additionally, because site search complements your navigation, you can use the information to conduct gap analysis on your navigation menus. This means that you can look at your navigation menu and if the category “Gaming” is not being presented in there, then you should consider adding it to the menu. The end goal is to create a navigation menu that reflects your visitors’ intent.

In our next posts, we?ll cover the other reports and KPIs that you should be looking at for site search analysis.