Hits, Page Views, Visitors and Visits Demystified

This article is an introductory level and the intention of this article is to clarify few terms that you constantly hear in Web Analytics. Why am I writing this article? I hear some confusion about these terms from people new to field, so I thought I will write this blog post to clarify some of the common terms.

I am going to explain, Hits, Page Views, Visitors and Visits in this blog post.

Hits

Back in the early Internet days, Hits was a term commonly used to measure websites traffic. This term was mainly used by IT folks, early users of web analytics tools, to get an idea of the load on the server. As Web Analytics has moved into marketing and we have move to JavaScript based solutions, this term does not hold much meaning today as terms such as Page Views, Visits and Visitors have taken over.

So what is a Hit anyway? Let’s take an example of a simple web page shown below

This page is an html file with one image embedded in it.

When a person browses to this page (in her internet browser), she is requesting this page from the server to be downloaded to her internet browser. She views this page as one entity. In return browser is actually requesting 2 items from the server

  1. The actual HTML page
  2. The image embedded in it

When server returns these items, the browser assembles them and makes them look like one page to the person browsing this page.

This is what the log file of the server might look like (I have removed several items to make it simple)

291.111.276.23 – – [16/Jun/2007:11:17:55 -0400] “GET /samplepage.html HTTP/1.1” 200 3225 “http://www.anilbatra.com/” “Mozilla/5.0 (Windows; U; Windows NT XP; en-US; rv:1.8.1.7) Gecko/20070914 Firefox/3.0.0.7”

291.111.276.23- – [16/Jun/2007:11:17:55 -0400] “GET /batman.jpg HTTP/1.1” 200 3225 “http://www.anilbatra.com/” “Mozilla/5.0 (Windows; U; Windows XP; en-US; rv:1.8.1.7) Gecko/20070914 Firefox/3.0.0.7”

That means there were 2 hits on the server, one for the html page and one for the image. So with one page request there are 2 HITS (in this example)

All the above items will show up in your analytics reports if

  1. You use log file based solution
  2. You do not filter them out when setting up your reports

If you use a JavaScript solution then the only thing which is tagged (contains the JavaScript code) is the HTML page and that’s the only thing which will show up in the Web Analytics report.

Now let’s take a look at this sample again but this time we will look at the source to make sure there are no items hidden behind the HTML code. Sometimes (read most of the time) there are files that are not visible to the individual but still need to be downloaded from server and count towards the hits.

Here is what the source code looks like:

You will see there are two more files that are embedded in the page. One is a style sheet (stylesheet.css) and the other is a JavaScript (myjavascript.js) file.

So when a user requests this page, a total of 4 files are being requested from the server

  • The actual html page
  • The image embedded in it.
  • The .css file (stylesheet)
  • The .js (JavaScript File)

This is how the log file will look like

291.111.276.23 – – [16/Jun/2007:11:17:55 -0400] “GET /samplepage.html HTTP/1.1” 200 3225 “http://www.anilbatra.com/” “Mozilla/5.0 (Windows; U; Windows NT XP; en-US; rv:1.8.1.7) Gecko/20070914 Firefox/3.0.0.7”

291.111.276.23- – [16/Jun/2007:11:17:55 -0400] “GET /batman.jpg HTTP/1.1” 200 3225 “http://www.anilbatra.com/” “Mozilla/5.0 (Windows; U; Windows XP; en-US; rv:1.8.1.7) Gecko/20070914 Firefox/3.0.0.7”

291.111.276.23- – [16/Jun/2007:11:17:55 -0400] “GET /stylesheet.css HTTP/1.1” 200 3225 “http://www.anilbatra.com/” “Mozilla/5.0 (Windows; U; Windows XP; en-US; rv:1.8.1.7) Gecko/20070914 Firefox/3.0.0.7”

291.111.276.23- – [16/Jun/2007:11:17:55 -0400] “GET /myjavascript.js HTTP/1.1” 200 3225 “http://www.anilbatra.com/” “Mozilla/5.0 (Windows; U; Windows XP; en-US; rv:1.8.1.7) Gecko/20070914 Firefox/3.0.0.7”

If you are counting the Hits then there are 4 Hits on the server. It is evident it does not make a lot of sense to count Hits. Let’s look at what make sense (at least for now).

Page Views

According to Web Analytics Association Standards, “Page is an analyst definable unit of content”. Page Views is the number of times a page (an analyst-definable unit of content) was viewed.

So what does it mean? It means you can define type of file, Module, Flash interaction, PDF etc as a page and when a user views them they can be counted as Page Views.

Let’s use the above example and define a valid page as the files with .html extension only. When using a log file solution we configure the tool to filter out the other types of requests and only count pages with .html extension as valid pages. In a JavaScript based solution, all other types of files mentioned above (except .html in this case, if it has the JavaScript tag) will be automatically excluded from the Page View count.

So how many pages will the analytics report show? One, as there is only one html page. (You can configure your JavaScript based web analytics tool to track other forms of files as page views too but that requires customization).
The one page that is showed in the reports is a page view.

Visitors or Unique Visitors

Visitors or Unique Visitors, sometimes also referred as Unique Users is the number of unique individuals visiting a site. The most common way to identify an individual is via an anonymous cookie. Keep in mind that this is a close estimate of unique visitors and not an exact measure. Here are four examples on how unique visitor count can be wrong

  1. If two people use the same computer and same browser to visit a site, that identifies users by an anonymous cookie, both of them will be counted as one unique visitor since their cookie will be the same.
  2. On the flip side, if one individual uses two different computers to access the same site, the individual will be counted as two unique visitors because the new anonymous cookie will be issued on both the computers and show up as two different cookies in the analytics tool and hence will count them as two different visitors.
  3. If an individual uses the same computer but two different browsers (say IE and Firefox) then the person will be counted as two unique visitors because each browser will have its own cookie.
  4. If the individual visits the site, she will be counted as one visitor. Then if she clears her cookie and then visits the site again, she will be counted as two visitors.

Note: Visitors are calculated over a period of time e.g. day, week, month, year etc. and a visitor count from two periods can not be added together to get a total visitor count. Let’s take the data for following 2 days
Day 1 – 30 visitors
Day 2 – 45 visitors

The total visitors count for day 1 and day 2 is NOT the sum of the visitors count for the two days i.e. it is not 75 (30+ 45). Why?

For simplicity let’s assume that all the visitors who came to the site on day 1 also returned to site on day 2. In that case we will have 30 visitors from day 1 and 15 (45-30) on day 2 as unique between those two days, making the total unique to be 45 for the two day period and NOT 75.

The calculation I showed above has been simplified for this example. My advice is to let the analytics tool do the calculation for you and not sum the visitor count from separate period to come up with the total count of unique visitors.

Visits

Visit is also known as session. Visit starts when a visitor interacts with this site. In most case the interaction is the first page view by the visitor. The visit ends when user does not interact with a site for specified period of time. Most of the web analytics tools set 30 mins of inactivity as the end of the visit, however in most tools it is configurable and you can set it to whatever makes sense for your business.

Unlike, unique visitors, total visits to the site can be summed across time periods to get the total visit count for the period.

Hope this clarifies some of the confusion surrounding these terms.

Questions? Comments?

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Online KPIs – Back to Basics

Those who have been doing web analytics for a while know how important it is to define proper online Key Performance Indicators (KPIs). But believe me, there are a lot of marketers who are confused about online KPIs, difference between KPIs and metrics and how to define them. So I am going back to basics with this post.

What are KPIs

Web analytics tools collect a lot of data and provide a lot of metrics and reports. In fact most of the web analytics tool vendors proudly talk about number of reports that can be created in their tool. These reports, metrics and data might look interesting but we all know interesting is not necessarily important. KPIs, on the other hand, are the important metrics; the metrics that provide a view into the health of the business and are tied to the business goals. They allow business owners to focus on the things that are important to drive their business. Key Performance Indicators tell a business owner whether he or she is meeting their business goals or not. Good KPIs provide context and hence are usually represented as ratio, percentage, indexes etc and not as raw numbers. KPIs drive actions within an organization.

KPIs are specific to a business role. So, not all people in the organization have the same KPIs though all the KPIs should ultimately be tied to overall business goals. The CEO has a set of KPIs, a merchandising manager has a set of KPIs and a marketing manager has yet another set of KPIs. However, all of the respective executives (departments) need to be defined keeping overall business goals and CEO’s KPIs in mind.

Another way to understand KPIs is that they are the metrics that make people freak out when they go in the reverse direction from the expected and call for immediate actions.

Since so much is riding on the KPIs, it is very critical that you pay due attention in defining your KPIs. Understand what business goals are and then think about what activities and/or user behaviors relate to your business goals. Put together a list of all the metrics that will measure those activities and/or user behaviors. Weed out the unimportant metrics, figure out what are important metrics and what are critical few (and hence KPIs) that have an impact on the business goals. Note: For your analysis you will need to look at more than your KPIs to provide you a bigger picture. Remember, all KPIs are metrics but not all metrics are KPIs

Characteristics of KPIs

Dennis Dennis R. Mortensen lists following 7 KPI characteristics on his blog “Visual Revenue”

  1. a KPI echoes organizational goals
  2. a KPI is decided by management
  3. a KPI provides context
  4. KPI creates meaning on all organizational levels
  5. a KPI is based on legitimate data6. a KPI is easy to understand
  6. a KPI leads to action!

Those are all great characteristics of KPIs. I however differ a little on point number 2. In my opinion great KPIs are those that are agreed upon by those it directly impact and will be taking actions so they are not just handed down by the upper management. And as I said above they should all be tied to overall business goals.

How many KPIs should you have?

I don’t think there is any rule but in my experience you should limit it to no more than 6.

Reporting on KPIs

KPIs should be presented in an easy to consume dashboard. Web Analytics tools have built in dashboards but most of them are limited in terms of the functionality and flexibility. My recommendation is to present KPIs in a separate dashboard that not only shows KPIs but also trending and brief analysis. Without trending and analysis the KPIs might not provide a complete picture. Excel, PowerPoint or third party dashboard tools work the best for reporting the KPIs. Since they are outside the web analytics tool they also allow you to integrate other data sources, as needed.

Books on Web KPIs

Eric Peterson has a great book on the subject, called The Big Book of KPIs

Bounce Rate Demystified

Time and again my clients ask me about Bounce Rate. This made me think that there is still confusion about what is bounce rate and exit ratio. The three main questions that have come up are

  1. What is bounce rate?
  2. What is the industry standard for bounce rate?
  3. What causes high or low bounce rates?

I am going to answer these questions in this post.

What is bounce rate?

Bounce rate is the percentage of visitors who enter a site (or a page) and then leave immediately. Think of a ball (visitor) that is thrown (visits) towards a table (site). It hits the table and bounces back without rolling (visiting any other pages).
Generally, “leave immediately” in the above definition means without going to any other page. However it could also be expressed in terms of time spent on site, say users who spend 5 seconds or less on the site irrespective of the number of pages they view.

Bounce rates are calculated both at the individual page level and at the site level. For an individual page, bounce rate is the ratio of visitors who enter the site from that page and leave without going any deeper, to the total number of visitors who enter the site through that page. In other words it is single page visits/ total entries to the site through that page.
At the site level, bounce rate is simply single page visits/total site visits.

Note: If a visitor enters though a page, refreshes it (manually or via auto refresh such as ESPN score page or MSN money page) but never goes beyond the first page the visit is not counted in the bounce rate.

  • Bounce rate is often confused with Exit Ratio. Exit ratio is usually expressed as the percentage of exits from a page to the total number of visits to that page. As a side note: A lot of times exit ratio expressed as % of visits can be misleading. In most cases, page views are actually more appropriate than visits for this ratio. Why page views and not visits? If I view the same page twice during the same visit, and after one of those page views I exit, shouldn’t my exit ratio be 50% rather than 100%? The first view of this page was compelling enough for me to further engage. A 100% exit ratio would indicate a problem that may not be there.
  • Bounce rate is confused with Single Page Visit Ratio: Single page visit ratio is calculated as a percentage of single page visits over total visits to a page.
    1. Here are two examples that will help you clarify

      1. A visitor who enters site at home page and then goes to contact us page and leaves from contact us will be counted in the exit ratio from the contact us page but won’t be counted in the bounce rate of contact us page.
      2. A visitor who enter the site from contact us page and then leaves without going any further counts in all three, exit ratio, single page visit ratio and bounce rate.

      So to Recap:

      Single Page Visit Ratio= Single Page Visits to the page/ Total Visits to the page
      Exit Ratio= Total Exists from the page/Total Visits on the page or Total Exits from the page/Total Page Views of the page (see explanation above)
      Bounce Rate= Single Page Visits to the page/Total Entries to the site through that page.
      Note: All of the above three are generally expressed as percentages.

      What is the industry standard for bounce rate?

      The simple and short answer is that there is no industry standard. I know you don’t want to hear that, but it is true. There is no industry standard. There are some ranges that I will share shortly but we can’t call them industry standards. There are a lot of factors that influence the bounce rate, so you really can’t compare bounce rates of one site (or page) to another. I have listed those in the next section.

      The goal of the site should generally be to reduce the bounce rate to as low as possible. The lower the bounce rate the better job the site is doing to keep users engaged. One exception may be a site that is intended to accomplish all relevant user engagement on it’s landing page. This is more common on say, a campaign landing page intended to sign up users for direct marketing emails.

      Bounce rate is very unique to your site and page. The best way to know if you are doing better or worse is to set your own baseline and compare your performance over time.

      I have seen most bounce rates fall between 18 – 30% on home page and the site overall. Any page with a bounce rate higher than 30% should be looked at closely. I am not saying that you should not analyze the pages below 30% bounce rate. Remember there is always room for incremental improvement.

      There are several factors that determine the actual bounce rate of any page.
      Here are some of the numbers that were listed by Steve Jackson based on his experience with various sites.

      Source: http://tech.groups.yahoo.com/group/webanalytics/message/6116

      Retail sites driving well targeted traffic 20-40% bounce.

      Simple landing pages (with one call to action such as add to cart) I’ve seen
      bounce at a much higher rate, anywhere from 70-90%.

      Content websites with high search visibility (often for irrelevant terms)
      can bounce at 40-60%.

      Portals (MSN, Yahoo groups etc) have much lower bounce rates in our
      experience 10-30%.

      Service sites (self service or FAQ sites) again usually lower 10-30%.

      Lead generation (services for sale) 30-50%.

      Per Steve,
      “I must stress that all the above figures are based purely on our own
      experience after working with clients. I wouldn’t advise you base an
      optimization model around these numbers. We advise that when forming a
      benchmark, that you do it internally. Take the average bounce rate over a
      given period on your current site. You need to have at least 1000 entries
      coming from normal sources to get reasonably actionable data.
      Measure what the average bounce rate is and then work to get that down.”

      What are the factors that affect the bounce rate?

      Below are some of the factors that determine the bounce rates. You can use this as a checklist to diagnose a high bounce rate issue.

      1. Source of your traffic – Each source results in a different bounce rate. When setting your baseline create overall baseline and baselines for each traffic source e.g. display advertising, organic traffic. With one client I found out that the traffic driven by searches (paid and organic) and sources other than campaigns had a much lower bounce rate than traffic that was driven via display ads. Their display ad had 90% bounce rate while other traffic only had 35% bounce rate. Their overall bounce rate was around 55%, way lower than 90% and giving them a misleading picture.
      2. Search engine ranking of the page – A page which ranks higher on irrelevant keyword will get a higher bounce rate. I have seen this to be an issue a lot of times. I wrote an article on how to follow the search and reduce your bounce rate.
      3. Type of Audience – If you are advertising and reaching the wrong audience you will see higher bounce rate. Bounce rate will tell you if you need to better target your ads.
      4. Landing Page Design – Landing page design affects the bounce rate. I suggest A/B testing to improve after you have set your baseline. No matter how low you go there is always an opportunity for improvement unless you somehow achieved 0% bounce rate.
      5. Ad and Landing Page Messages – If the messages on your banner or search ads are not aligned with the messages on the landing page then the chances are you will have one of those 50% + bounce rates. Make sure messages are aligned and give visitors a clear call to action. Many a times I have seen marketers sending users to a generic page instead of an appropriate landing page. This can (and will) result in higher bounce rates. Again A/B or multivariate testing should be used to reduce the bounce rate.
      6. Emails and Newsletters – Subject lines, to and from, links, banners, the layout of email and the landing pages all work in tandem. They can either result in a great user experience and hence lower bounce rate or can result in a disaster. Do testing (More on this later in another post) to reduce bounce rate.
      7. Load time of your page(s) – A longer load time can result in visitor bailing out of the site causing higher bounce rates. Conversely, users can hit the refresh button, thinking there was a problem with the page load. This will incorrectly reduce bounce rate.
      8. Links to external sites – A page that has links to external sites (or sub domains/ pages that are not tracked in the same data warehouse) will show higher bounce rates.
      9. Purpose of the page – Some pages’ purpose is to drive users inside the site while other pages provide the information that user is looking for. A page that provides the end result can show higher bounce rate. One example is the support page on my bank’s web site, I have this page bookmarked. Whenever I need my bank’s phone number, I go to my favorites, pull this page, get the number and leave.
      10. Other factors – Pop-up ads, pop-up survey requests, music, streaming video, all can have an adverse effect on bounce rates if users become annoyed.

      Hope this clarifies the confusion around Bounce Rate. I would like to thanks Brad Gagne, who challenged my thinking on this subject, provided his valuable insight and proof read this article.

      As I was writing this post I came across another article on the same subject by Avinash Kaushik, you can read his article at http://www.mpdailyfix.com/2007/06/bounce_rate_sexiest_web_metric.html.

      Here are the other articles in the Demystified Series

      Question? Comments?

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      Referring Domains Demystified

      A while ago a user of the yahoo webanalytics group asked why their own domain was showing up as the number one referring domain. Interestingly enough another person asked me the same question the same day. I have also seen this question pop up several times in past so I thought why not clarify for everybody.

      Note: I know the images on this post are very small. I am trying to figure out how I can make them bigger but had no luck so far. As soon as I figure out hot to fix it, I will update this post with better pictures

      This will be a two part series. In this part I will explain how Web Analytics tools report the referring domains and pages. I think this is a very critical aspect before we dig into why your domain shows up the referrer in referring domain report. Part II will explain why your own referrer shows up in the referring domain.

      So let’ begin with understanding what a log file contains:.

      What is contained in a log file:: (Note: Even tag based solutions generate a log file, although they don’t call it a log file. This log file is in the vendor’s proprietary format but for this example you can assume it looks the same as the example below).

      Every log file contains a line for each of the server ip, request file (URI stem of the file), with time stamp, a cookie (if one exists), and the referrer (URL of the page that referred user to the current file/page). There are other fields as well but they are not required for this example. The assumption here is that if you are using your server logs and they are in W3C Extended Log File format or you are using the JavaScript solution of your web analytics vendor.

      Here is a list of all the fields in W3C Extended Log File Format:

      Here is an example of the log file

      You can read more about is at: http://www.microsoft.com/technet/prodtechnol/WindowsServer2003/Library/IIS/ffdd7079-47be-4277-921f-7a3a6e610dcb.mspx?mfr=true

      Below is a an example of the log file from http://www.seattleindian.com

      #Fields: date time c-ip cs-method cs-uri-stem sc-status sc-bytes cs-version cs(User-Agent) cs(Referer) cs(Cookie)
      2007-02-21 07:07:30 66.171.173.27 GET /Seattle/moviepictures/bollywood.asp 200 33453 HTTP/1.1 Mozilla/4.0+(compatible;+MSIE+7.0;+Windows+NT+5.1;+.NET+CLR+1.1.4322;+.NET+CLR+2.0.50727) http://www.seattleindian.com/seattle/ USERID=1234;+RID=3423

      In this log file /Seattle/moviepictures/bollywood.asp was the current page that the visitor viewed and it was referred by http://www.seattleindian.com/seattle/. Every log line has the referring page that contains the URL of the page that referred the user to the current page.

      Let’s take an example of visits for one visitor. For this example I am only showing 5 fields (s-ip, data, time, URI stem, cs(referrer)

      Below is the data for a visitor:

      The visit started with a referral from http://www.google.com/?q=seattleindian. The referring domain in your web analytics tool will be Google.com

      Let’s assume, this visitor goes on a lunch break leaving the site open in her browser. Come back after an hour (note the time change) and clicks on the home page links, here is how the log file will look like

      This constitutes a second visit (assuming a 30 min session time out). The referring page will be http://www.seattleindian.com/seattle/advetise.asp and the referring domain will be SeattleIndian.com for this second visit.

      This is one of the reasons why you will see lots of visitors referred by your own site. We will cover other reasons in Part II.

      Let’s assume that this user clicks on a link on SeattleIndian.com that takes her to a new domain, SFIndian.com. This domain is identified by a different server ip (9.8.7.6) in the log file. Here is the log file for this other domain

      Referring page for this visit will be http://www.seattleindian.com/seattle/advetise.asp the referring domain will be Seattleindian.com.

      SeattleIndian.com and SFIndian.com are both owned by the same owner who wants to see the combined traffic. Let’s assume you were to combine both the domains in one profile (or reporting suite) and assume they were using the same third party cookie. This is how the combined log file will look like

      When your web analytics tool parses these log lines, it will report 2 visits

      One visit started at 10:59:50:00 and ended at 10:59:50:04 and the referring domain was Google.com

      The second visit started at 11:59:50:05 and ended at 11:59:50:13 on SFIndian.com, the referring domain was SeattleIndian.com

      Now let’s take an example where user goes out to another site and then comes back to the site

      In this example: The visit started by referring domain being google.com, the user leaves the site from bollywood.asp page and comes back via yahoo search to aboutus.asp page. In this scenario the visit started via google so yahoo will never show up in the referring domains (that is the case with most of the web analytics tool).

      Note: If you run a campaign on Google and Yahoo and tag them so that your web analytics tool can track them, then you can configure the tool to show either the last or the first campaign. However; the out-of-the-box referring domain report will only show the first referrer of the visit.

      Hope this clarifies some of the confusion around referring domains and pages.

      I would like to thank Brad Gagne for helping me the flow of this article. Brad is also responsible for making me split this article in two parts.

      As I mentioned earlier, I will be out of the country for next 10 day so you will see Part II when I come back.