Due to cookie deletion and multiple computer usage, it is difficult to get a true picture of the split between people who have never seen a website before and those who have.  However, recording whether the visitor had a cookie from this website previously does at least give an indication of this new/returning split.

What I like to be able to do is to segment out new visitors for a time period (week or month) and examine their behaviour on the website compared to visitors who had visited previously.  The new visitor segment should include all visits during that time period by these visitors, not just their initial visit.

Frustratingly, this information is usually not available as default in a web analytics tool unless you can segment at visitor level.  However, as long as you have one of the four metrics from New and Returning Visits or Visitors, you can calculate the other three.  And most tools will give at least one number.   As examples:

• Google Analytics gives New Visits and Return Visits
• SiteCatalyst provides Return Visits
• HBX contains Returning Visitors

The key to this is knowing that the first time a site is visited, that is both a new visit and a new visitor.  And as any subsequent visits by these people will be reported as a return visit, the number of new visits equals the number of new visitors.

With that logic in mind, it is simple to calculate all four metrics once you have a single one.  For example, assume that the tool available is SiteCatalyst (without access to visitor level segmentation via Data Warehouse or Discover):

• The number of Return Visits is available but none of the other three metrics
• Total Visits minus Return Visits gives New Visits
• New Visits equals New Visitors
• Total Unique Visitors minus New Visitors gives Return Visitors

And now it is easy to calculate the proportion of Visits that were New or Returning or to calculate the proportion of Visitors that were New or Returning.

The same principle can be applied to Google Analytics:

• New and Returning Visits is available (note that this metric is visits, not visitors as it is titled in the report)
• New Visits equals New Visitors
• Total Unique Visitors minus New Visitors gives Return Visitors

Of course, these numbers don’t mean that much on their own but do become more useful when trended over time or across different segments.

An interesting thing to look at can be the split in New and Returning Visitors for different time periods – day, week and month.  This can indicate the scale of the issue with cookie deletion, but more on that another time.

The obvious starting point is looking at what the most popular search terms are that people are using on your website. This can tell you what the visitors to your website want to get from their visit. It also complement any reports on what the most popular content is on your website. And if people are searching for a topic/product/piece of information on your website which you don’t currently offer, it could be worth adding.

Flipping this around, a report on popular search should be viewed against your prior beliefs on how easy it is to access the key areas on your website. You might believe that it is easy and obvious on how to access a certain page or topic on your website but if people are having to search for it, it can’t be that obvious.

There is more that can be looked at than just the number of times each search term has been used within the website. Other key pieces of information available with on-site search reports include:

• search terms that don’t return any results – if people are searching for content on your site that is there, make sure that your search tool is providing these links.
• relevance of the search terms – are people clicking through on any of the results from their search?
• the proportion of people who are using your search tool – too low and the tool might not be visible enough, too high and people can’t navigate to your content.
• user behaviour for people who use the search tool – are they more likely to perform your key actions on the site?

The set of metrics that I listed in the post last week (visits, visitors and interactions) could be described as the basic traffic metrics. Each are absolute numbers as opposed to a percentage or ratio and each can be used to describe the popularity of the website during the previous period.

The following set of metrics are what I describe as (for want of a better term) as engagement metrics. I do not claim that they describe completely that mystical experience known as a user’s engagement with a website but I believe they give an indication of the level to which people are engaging. All are ratios calculating by combining two other metrics.

Frequency – Visits per Visitor

This is the average number of visits each visitor to the website made during the specified period calculated by dividing the number of visits by the number of unique visitors for that time period. It reflects whether the users of a website are interacting with it on a regular basis or only ever visiting once. The minimum number for this metric is 1.0 – every visitor must have made at least one visit.

Interactions per Visit

This is the average number of interactions made with the website during each visit during the specified time period – calculated by the dividing the total number of interactions by the number of visits for that time period. Again, the usual type of interaction that is used here is page views.

It is an interesting metric in that there is no good or bad result, it all depends on the context. For example, a higher number of interactions per visit may suggest a greater level of engagement but it could also be that the user was having to search through the site in an attempt to find the information they were after.

Duration per visit

Similar to the previous metric, this is the average time a user spends on a site in each visit. It can provide additional information about the average visit regarding the length of time people spend on the website.

A key point to remember though is that web analytics packages can only work off known measurements and there is generally no measurement for when a user leaves a website. Therefore the duration for each visit is typically under reported and cannot be measured at all when only one measurement is received.

Bounce Rate

This is a measure of the number of time a website is visited and the user leaves immediately without engaging with it at all. The simple method of judging whether there was any engagement is to assume that the user has to have more than one interaction. Therefore bounce rate is commonly calculated as the percentage of visits with only one page view.

A website that is used as the user’s home page (portals, google, news sites) would have a high bounce rate for all visits where the user opened their browser but then immediately went to an alternative site. Also, it possible for a user to get all the information they need from a website from a single page – high engagement but only a single interaction. Basically every site has a certain level of bounce rate, it is how it changes over time that is important.

What Next

So these 7 metrics would be your basic set of traffic and engagement metrics, and the basis for any investigation into the performance of a website. From here I am going to go into some methods of how to look at the numbers and how to understand better what they are telling you.

Note: we are dealing with the average in all the engagement metrics and this could produce some misleading results unless you think through what the change actually means. For example, a influx of traffic from a new source may lead to a drop in the overall site frequency as the new visitors have a lower average frequency than the current average average, not that people are less satisfied with the site.

While I will cover this specific concept further in a future post I think the key point I wanted to make is that numbers should not be just taken as black and white, you need to do some thinking in order to understand a change. And you need to understand a change in order to do something about it.

The common theme that runs through any discussion of web analytics is that the industry needs to move beyond a focus on metrics and simply providing reports to instead focusing on the provision of insights and recommendations. I totally agree, in order to add value to a business and justify our salaries, that this is what we need to be doing. But the other point that is often raised is that web analytics is really hard – it is the identification of these insights and recommendations that is the really hard part. I believe that everyone needs a starting point, some simple metrics that may not provide any real insights but give the reader a quick overview of performance. While simple and possibly not insightful in themselves, these metrics do indicate if some aspect of performance has changed and they can also give some hints about the areas that should be examined in more detail in order to do that adding of value.

Traffic Metrics

The starting point for any review of the performance of a website must be the level of traffic that it has. That is the number of visits to the site, the number of people making these visits and the level of interaction they had with the site. These really are simple metrics but they instantly tell you if something has happened to your site performance. An unexpected change to any of these metrics would usually be the first indicator that something has broken or that the new marketing campaign is having an impact.

Visits

Even I find it weird that I am starting with Visits ahead of Visitors but my gut instinct feel that this is an under rated metric is constantly growing stronger. I am starting to think that the visit, that is a sequence of one or more interactions with a website ending with a period of 30 min of inactivity, is actually the foundation metric for web analytics. From a user point of view, it covers all interactions they have with a website during the period they have engaged with it. Understanding user behaviour during this period is a key element of developing websites and/or marketing that meet customer requirements and expectations.

Traditional offline marketing has a big focus on the importance and value from segmenting customers. The online world can take this a step further by segmenting at visit level. For me, the best type of segmentation is based on customer needs/thoughts/actions. Now a person may have many reasons for visiting a website and to assign them to a single bucket reduced the understanding that can be taken from segementation and an investigation into user behaviour. This is improved by segmenting at visit level, placing into different buckets based on method used to get to the site and actions taken once there.

Visitors

Quite simply the number of people who accessed the website during the period specified. I do not agree with the concept of there being two metrics, visitors and unique visitors, where visitors is the number of people accessing the website per day totalled for the period specified while unique visitors is the actual number of people for that period. Adding visitors up over a number of days and calling it a total is not mathematically or logically sound nor does it provide useful information. Instead, for me, it is unique visitors at daily, weekly, monthly or campaign level all the way.

This number is useful in understanding if more or less people are accessing the site and how many people it actually is who are looking at all these pages, placing these orders, clicking out to other sites. There are issues with the accuracy of this metric due to cookie blocking, cookie deletion and multiple computers but the solution is to accept this fact and move on.

Interactions

Traditionally this metric was the number of page views and it indicated how much visitors were navigating through the site. This concept is changing due to the introduction of so many new ways of presenting information on a website, many interactive and not requiring a page to be viewed. Hence my use of the term ‘interactions’, suggesting this could measure the level to which visitors have clicked on or viewed multiple elements of a website, whether this is a page or something else.

For simplicity, I think many sites can still start with using page views as a measure here. In my previous role at Ask.com, we used the number of queries made as our measure of interaction as that was more relevant than the number of pages viewed. Another alternative could be clicks or screen views viewed – the key point is that it should always be an action that every visitor with even minimal engagement with the website performs at least once. More detailed (and insightful) metrics will cover areas that only a proportion of visitors perform, such as placing an order or viewing a certain type of page but the number of interactions gives the brief overview that is a good starting point.

In my next post, I will go on to describe the other simple metrics that I believe are a good starting point for examing the performance of a website.