Learning how our web site works is an important task. We’ve seen some simple examples in previous steps (visits, page views, and unique visitors) as well as determining how long someone visited your site, and which was the last page they viewed. We’ve shown how some pages are viewed more than others, and where people exit your web site. We’ve even shown what pages people come to your web site.

What we will look at now is how did they get to your web site. Before they were on your web site, odds are they were somewhere else. Knowing this tidbit of information changes everything, and starts to allow us bring things together.

In the past articles I’ve had a decidedly split view, why this matters, why this doesn’t matter. This is going to be one sided – this matters. And the follow up where your (quality) visitors come from, will matter even more as we show you how the metrics from the previous articles start to fold in with where your visitors come from.

You will get visitors from all over the Internet. Web sites you don’t know about link to you, and such. However, all of these methods/places can be grouped into the following categories.

• Search Engine (organic) – this is where someone types in a question, and you site was on the list of answers. Depending upon the phrase entered, you may have little (rarely) or lots of competition.
• Search Engine (paid inclusion/pay-per-click) – You have purchased key words/phrases, and when someone enters a phrase, your ad comes up. That person clicks on the ad, instead of an organic result, you get charged a fee, and they go to your site.
• Online Ad Network – other networks beside those run from search engines exist, and you have purchased ads to be placed on websites based upon some criteria, and users came to your site from these ads.
• Another Website – another website, be it a standard site, a blog, a forum, etc. has your.
• Direct Access/Bookmark – someone typed in your web address or had previously bookmarked your site. This number is often a higher than it should be as sometimes the information used to pass where the visitor came from, isn’t passed. In that case, the Direct Access gets artificially inflated.

The question of course is, why is it this that matters? Here are how we look using the previous metrics to start to determine relevancy, and in how this metric matters.

Lets say you have a small business. And you have a few friends who like to refer their friends to your business. We all know that all referrals are not equal, and someone is going to send you better referrals than others. But how do you know which is which.

Obviously, the one that leads to the most sales is sending you the best referrals. But can you find out why that friend gives you the best referrals? Or better yet why?

You see, search engines, other sites that link to you, and your banner ads are your “friends”. They all want to send you visitors, just some are better at it than others. And just because someone refers a lot of people, doesn’t mean they are sending you the right visitors.

Lets say we look at some on-line ads you are using. You know that you are getting leads from them, sometimes 1000 a day. However, the users leave quickly after viewing the page. If you can segment your viewers and determine that 80% of the visitors that come to your site from this source “bounce” then you know you have a problem you have to address. You don’t know exactly why, maybe the leads/visitors aren’t qualified, or maybe the landing page (the page the visitor sees when clicking on the ad) is ineffective, but now you have something to start looking at to determine what to fix.

On the other hand, you have 1000 people coming from another web site, maybe Google Ad-Words and Yahoo’s pay-per-click. You can see from there that you have a bounce rate of 40%, and they tend to stay for 3 or 4 pages, by then 60-80% of people have left your site. Now we can look at a different set of problems. Could they not find how to buy? Did they get “fatigue” where they got tried of going through the pages? Now we can look at the exit pages, do they move from page to page as expected, or do they bounce around unexpectedly?

As you step through these numbers, I’m sure you will see that not all sources are equal. Some might result in lots of page views, but few conversions (sales, or requests for more information). This is why visitors, page views, and time on site are not necessarily good metrics. You have to learn what type of lead from a source is your best type.

Additionally you can start to segment your search engine data, be it from normal, organic, searches, or from paid search results. Now you can start to see what words and phrases people are using to find you, and how effective you are at converting those people into buyers. This is where your metric data starts to become real important.

Knowing what keywords and key phrases people are using to find your site when dealing with search engines. You might find that the phrases you would use, and you have optimized your site for, are not being used. Is this because there is too much competition, or because consumers use different words than expert/owners. It can also reveal when a phrase is ineffective, because it yields too low a conversion rate.

Knowing how many people repeat visit your site, and/or bookmark you site and directly access it indicates how valuable other’s feel your web site is. Likewise, if you find that most people visit from a given source once, but never return, you can start to see that they don’t place a high value on your site.

You may not be able to determine why people are leaving your site, but you can start to develop some good theories. Just start looking at it from a users point of view, and see what if anything you have to do to enhance your site to increase those conversions.

Popularity: 25% [?]

Learning how our web site works is an important task. We’ve seen some simple examples in previous steps (visits, page views, and unique visitors) as well as determining how long someone visited your site, and which was the last page they viewed.Most of these metrics were simple to user, and that is fine. However, now we want to look at the flip-side of which pages people leave on, that is what pages they are viewing, and which ones do they view first. This is which pages people go to first, and how many times was a page shown to someone. Let’s look at the larger picture: which pages were viewed, then look to see what order they saw the pages.

Pages Viewed may go by different names, such as Top Content, or Most Viewed Pages, tells you which pages are viewed most often. Depending upon your Analytics package, you may get this by file name, by web page title, or both. Depending upon your needs that you will look at. When they use the file name, anything after the file, which might change, will be displayed as a separate entry, despite the physical file being the same. This is because the part after the file name might change what the file displays. Consider these two examples:

• Product.php?id=21 – this might display product information for Widgets
• Product.php?id=32 – might display product information for Gizmos.

Because the content can change, each entry is listed separately. Pages based on internal search forms fall into this category quite often, and can cause quite a bit of confusion. Even if the parameters are reversed, it will often view the two entries as two separate pages. This is intentional in case someone wants to track the path on how they got to the file, or other similar things.

Why this is important: from here were can start to see what files are viewed the most often. Clients are often surprised to find out that it is not necessarily the home page (more on that in a bit). They are also (sometimes) surprised that some pages are viewed a lot more than others. Consider the following graphic. At the top, you will notice over 1,700 URLs (web page addresses), in the bottom graph, you will notice there are only about 30 page titles. This is for the same site, same time frame, the difference is the first graphic is for the page file name, and the second is the page titles. Because the file names are similar, but a lot of extra stuff is appended because of the search pages, the 1700 files are exaggerated. You have to find the report that works for you.

These reports came from Google Analytics, and they provide some additional information. We’ll look at that in the next article or two.

Why this doesn’t matter: outside of wanting to know what page is being displayed, this isn’t important. That is an important thing to understand. This report can’t show you why they went the page they viewed, if they found the information they were looking for, or, when viewed by itself, what did they do after viewing the page.

A count of individual page views is also unimportant because it doesn’t specify why the person has come to that page, possibly repeatedly. Are they lost? Do they have to go through a series of “hoops” to get where they want to go? Page views are a lazy man’s metric because it can look impressive, but not provide any key insight.

Top Landing Page, sometimes called an Entrance Page, is the page that the user enters the web site on. Many people naturally assume that someone will go to the home page first. They will spend lots of money making a cool splash screen, and not spend those resources on making the other pages better. There are many times another page is the used to enter the site. For example:

• Search Engines take people to the most relevant page, not the home page.
• Other people might link from their web page to a favorite article, product, or review.
• People bookmark the page in a site that helps them, not the homepage necessarily. (I commonly bookmark login pages – especially if I have to pay a bill on a web site.)
• Someone might send/receive an e-mail with a link to your site, that isn’t to the home page.

All of these and more cause other pages to be the “landing page”.

Why this is important: Knowing what pages people enter your site from, helps you know what pages to focus on. You should also watch to see if a change in your site/page increases or decreases the people entering your site through that page. While this wouldn’t necessarily define the cause and effect, it allows you to see some of what is happening and start to make an educated guess. It is also important to know if you will be moving a page, as it lets you know that other’s will be effected. Often if someone reaches your site, and it gives them an error page (404 is the Not Found Error) – they will leave your site and find the answer somewhere else. Knowing this can provide you with the information to take to your technical people to ensure that they use the proper redirects to make sure people don’t get lost on your site. (Hint: You should always redirect your pages…)

Why this doesn’t matter: When we put together this metric with some others, you will see how this can be a powerful metric. However, by itself, as with most other metrics, you will not be able to gather much information from it.

Popularity: 45% [?]

Learning how our web site works is an important task. We’ve seen some simple examples in previous steps (visits, page views, and unique visitors) and we’ve seen some data that gets calculated (average page views and time on site).

While these were simple, and often given on the front page of your reports, I want to look at two related pieces of information that are not always so prevalent: exit pages and bounce rate.

The Exit Page is an easy metric to understand. This is generally a list of pages that was last page that a user visits. So if a user X visits p1, p2, then p3; p3 is the last page they visited, and this is counted as the exit page. If user Y visits p2, p3, then p1; p1 is their last page, and counted accordingly as the exit page.

Why this matters: This information is important because it allows us to see where people are leaving the site. In some cases this may not be a bad thing. Look at figure 2 to see how people are often leaving on the Sign Out page, which means that they have concluded their business. Additionally, people might exit after viewing a FAQ, because their question was answered. However, if people start to exit on an Account Sign Up page or on a Check Out page, this might start to indicate an issue. While this does not directly define the issue, it does allow us to know where to start to look.

Why this information can be misleading: Every user will eventually leave your site. So worrying about users leaving your site does you no good. Worrying about users leaving your site for no reason, or for the wrong reasons should worry you. Unfortunately, this metric doesn’t tell you why they left. And when you consider the number of “tire kickers” there are on the Internet, many will leave after checking your price to go and shop around to see if they can find a better deal. (Web conversion rates are notoriously low, with 2-4% being considered good depending upon type of product, price, etc.)

We will also notice that there are files which it is perfectly acceptable to be the exit page. This would be things like the last page in checking out with their order, a sign-out page, etc. It can also be noted that many people will go to the homepage when leaving. Don’t ask why people do this, but the more I see different sites, the more I see this happen.

Bounce Rate is a modification of the Exit Pages metric. What can make it difficult to determine is that there are different ways of calculating this metric. There are two main ways of calculating a bounce. In the first example, a person visits a site, and then leaves the site without visiting any other pages; then they are counted as a bounce. The second method used, is to determine if the user was on the site less than a given amount of time, 10 seconds for example. If this is the case, then they are counted as a bounce. (Remember, we don’t know how long someone is on the last page, if they were on the first page for 7 seconds, and the second page for 30 seconds, we don’t know about the 30 seconds, and a bounce could be calculated.)

The bounce rate is a huge contention between different analytics people, and some analytics packages don’t even offer this as a metric. Let’s take a look at how it can be used, and why it may or may not matter.

Why this matters: If someone is on your site for less than 10 seconds or 1 page, then odds are, they are not engaged in your site. This means that your end goal cannot be met. Finding out what the bounce rate is, and more importantly why, will help you determine how to improve your site, to be more effective in meeting your end goal(s).

Why this may be misleading: As mentioned above, if this metric is being based on length of time of the visit, we don’t know how long the last page is viewed, we can get less than accurate information. Secondly, the bounce isn’t necessarily a bad thing. Let’s take an example of a person who is searching for a piece of information. They come to your site from their favorite search engine. When they get to your site, they find what they are looking for, and leave once they have properly consumed your information. If your site’s end goal is to provide information, it has succeeded, while still having a bounce. And finally, it isn’t uncommon to have an acceptable bounce rate on the web. Depending upon the type of site, you may have a higher or lower rate of bounce. For example, niche sites, will have lower bounce rates, and blogs tend to have higher bounce rates, landing pages might have higher bounce rates, while a portal or intranet tend to have the lowest.

See: http://blackbeak.conversionchronicles.com/2006/04/12/bounce-rate-or-single-page-access-industry-averages/

Given all of this, you might ask, why is this one of my favorite metrics. As with everything analytics, this is a starting point. With it we can measure and track trends, and start to look for reasons why. Looking at the bounce rate as a web site wide number doesn’t really help, however when we start to drill down into the numbers, we can start to see more details that can help us.

Popularity: 23% [?]

Learning how our web site works is an important task. Learning how to properly measure it is even more so. We have to look at not only the data, but we also need to know what questions to ask when looking at the data to put it into the correct perspective.There are a couple of “obvious” measurements mentioned in the last article (visits, page views, and unique visitors). While that information is often raw data, and easy to display, we will now look at some data which most systems will calculate for you. Once people move out of the “visitors” and “page views” mentality, they feel they take a large step forward with the secondary measurements.

The two metrics we’ll look at can easily mislead, or provide “no real information” to the user. I’ve included these early on because people often want to look at them, as they are “easy to understand”, but harder to get information from. We’ll look at them, and look at why they are not as important as one might think.

The secondary obvious measurements

• Pages per Visit, and
• Time on Site.

The Pages per Visit is an easy enough metric. Generally, it is displayed as an average by taking the total number of pages from a site and dividing it by the visits to the site. So if you had 1,000 pages in one day, and 100 visits (remember unique visitors are different than visits) you would have an average of 10 page visits per visitor.

Why this matters: By watching how many pages people are visiting, we can begin to see a couple of things. First, under most circumstances, people will not reach their end goal in a single page, or even two. Therefore, as we see people tracking numerous pages, we know that they are looking for information, and believe that they can find it on our site. Second, if we see the number growing, we might see we have a problem. For example, let’s say it take a minimum of 3 pages to reach an end goal, and that people on average visit 10 pages to compare information on different offerings, may be they look in the wrong area, et cetera. However, if we see that number go up, 15, 20, and 30 pages, we now can start to look to see if the site has an issue where it isn’t clear. With this information, we can start to look at areas more specifically, to know if we need to simplify the pages.

Why this can be misleading: This site is an average, and if the site only has few people one day (holidays, weekends, etc), then we might see artificially high or low numbers in this area. Second, we don’t know how much “comparison shopping” a person may or may not want to do. The user may not be lost, just curious. These are things that just looking at the numbers cannot answer for us.

Time on Site is a metric that can also easily mislead. It is usually displayed as an average of users by adding the total time each user spends on a site from the time they start, to the time they leave. From there, they divide that by number of users, and you have your average…sort of. I’ll explain why the number can mislead in a little bit. First, let’s talk about why it matters.

Why this matters: The theory goes, the longer that someone is on the site, the more likely they will convert into making good on the end-goal. The theory is that you are building a trust with the user. The truth might be your site is slow, and/or confusing – and we should know which one it is. Each site should determine a base line for this metric and see if it rises or falls and know how that equates to the success of the site. For example, a site that has 2 to5 minute long video clips would expect longer time on site, than a site that allows you to download product information sheets as a PDF.

Why this can be misleading: First of, the numbers we have to work with are not accurate, and this is beyond the normal accuracy of the numbers. We only know how long a person is on a page given the time they view from one page to the next. However, if there is no follow up page, we don’t know how long the person was on the last page. It might be very long, or very short, but we always see that as a zero time length, so nothing is added, even if they view a 5-minute video as their last action.

Second, people who only view one or two pages can scale this average in ways not expected. Let’s consider 100 people visiting your site for an average of 1 minute. This means the total amount of time tracked was 100 minutes. However, lets assume that 30 of those people visited only 1 page on your site. This means the 100 minutes should be divided by 70 people, not 100. This gives you a new average time on site of: 1 minute 25 seconds.

Third, if your site is a little slower on any given day, even by only a few percentage points, it will slow down the user viewing the site, and they may either leave early (good to find out why) or spend longer on your site waiting to check out.

And finally, people may be on your site long, if they can’t find what they are looking for, but know that this is where they need to get it. (This directly correlates with too many page views.)

Because of this, I like to look at time on site from a trending point of view, and figure out the cause of the effect. Consider a site where the person is looking for information in the FAQ. The person is directly linked from a search engine, or finds it in just a couple of clicks, and finds the information.

Next we’ll look at information that can start to tell us something.

Popularity: 29% [?]