Why Use Google Tag Manager?

Google Tag Manager (GTM) is a free to use system from Google that removes the need to add Google Analytics and other tags, such as AdWords, Facebook tracking etc. directly onto each web page. This has put advance website tracking, digital marketing activity and the opportunity to collect and analyse customised analytics data within the reach of all businesses and not just those with big budgets and advanced technical resources to hand.

The benefits of Google Tag Manager

Increased Agility: Tags can be created, tested and deployed far quicker than if hard coded.

Improved Control: All tags viewed and controlled through a single system, with an audit trail.

Reduced Deployment Costs: Tags can be created and deployed by marketing reducing and in many cases eliminating the need to involve the development team.

Improved Page Speed: Rather than having numerous different tags on each web-page that are loaded as part of the page, these are replaced by a single GTM tag thus page speed is improved.

Some simple examples of how GTM can make tracking easier

PDF Downloads: On sites with PDF downloads available on multiple pages, a single GTM tag can create an event in GA, that records the PDF name and the page it was downloaded from.

Facebook pixel: If you would like to try Facebook advertising, rather than adding the Facebook pixel to each page this can be done using single tag.

Bounce visits: If your site receives a lot of one page visits, it can be important to know if these visitors are leaving immediately or spending time reading the content of that page. Using GTM a timer tag can be added to help find out what is going on.

More advanced tracking includes

  • Recording how far visitor’s scroll down the page.
  • Implementing Google Analytics Enhanced E-commerce.
  • Recording how far through people are watching embedded You-Tube videos.
  • Tracking activity as visitors log in and use on-site applications.

With GTM a wider range of data can be captured far more reliably and easily than ever before.

Beginners guide to campaign tagging

What is Web Analytics?

In a nutshell, web analytics is capturing data about your website’s visitors and using this information to improve your website and online activities in order to generate more business.

For example, knowing how people find your website, which of the website pages turn up most often in search engine results or which pages convert most visitors to customers will help you know where to concentrate effort in order to attract more visitors and increase sales.

Most businesses turn to analytics with three goals in mind:

  1. To convert more website visitors into customers.
  2. To attract more relevant visitors to their website.
  3. To increase the number of visitors who keep returning to the website.

Good Web Analytics is built on Good Data

The starting point is your website data. It provides the foundation upon which conclusions will be drawn and decisions made. So it is essential that it is clean and captures the information you need to be able to assess your websites’ performance.

In order to gain the insights needed to drive up visitor conversions you must identify and measure the steps in the conversion process. This is called your measurement plan, it will contain your Key Performance Indicators: they will be made up of micro-conversions – small steps that lead towards your ultimate goal and macro-conversions – the ultimate goal itself, usually a sales enquiry or a purchase.

Start to gain insights into your website visitors

Once you are collecting data, the next step is to create reports and to start to analyse the information in order to understand more about the website visitors: their characteristics, what they are looking for and their online experience.

This information can then used to:

  • Focus visitor acquisition strategy on acquiring the most relevant visitors
  • Assess the effectiveness of your marketing decisions and advertising
  • Improving the user experience of the website, for example by identifying pain points that discourage conversions or trying out different styles for web pages to see how visitors react.

Improving the measurement of visitor engagement on your website

Audience engagement is a fundamental micro-conversion for any content marketing campaign: it indicates that people are visiting your website for a reason and not just because they have stumbled across it.

With social media how you measure engagement is set by each social medium, such as followers on twitter, likes on Facebook etc. These measures of interaction are black and white: someone has either viewed your post or not, they have shared it or not, liked it or not.

However, with a website you have scope to build a more nuanced picture of how engaged your audience is and the effectiveness of that engagement in generating business.

The purpose of this article is to explain some of the problems with measuring content engagement, and how, using some of the more advanced features of Google Analytics, you can significantly increase the insight available into visitor behaviour.

Measuring website engagement ­for the silent majority

Measuring discrete definable actions in response to website content is fairly straightforward. Event tracking or social interaction tracking can be used to measure public responses to the content such as the number of comments made, comments liked and social media shares initiated from the website.

But these public responses are the tip of the iceberg: for each visitor that responds publically there maybe hundreds or thousands that regularly return to consume the content and never respond in this way.

Assessing the level of engagement of this silent majority requires a different approach.

Because there is no direct measure of how engaged a person is, you need to use measures that act as proxies for engagement such as: time spent viewing the content, the number of website pages viewed and the frequency of visits. These represent the time and effort spent by the visitor on your website.

Time spent and the last page viewed problem

One of the big problems with measuring time spent viewing content, is that the content you want to measure the engagement with is often on the last page the visitor will view on the website for that visit. After all, if you have found what you came for, you won’t always want to look further.

Google Analytics as standard does not record the time spent on exit pages. Since it relies on the next page being opened on the same website in order to tell how long the page was being viewed for.

It may be that this last page is also the first page, in which case the visit is recorded as a bounce and you will have no idea if the visitor spent any significant time at all on the website.

This problem can be overcome by setting up a timeout event. The timeout function works by checking to see if a page is loaded after a specified number of seconds.

So, for example, if you estimate that your blogs take a minute to read, you could set it so that if the page is still loaded after 60 seconds an event is created and a time stamp recorded for the visit.

This would mean that if a page is the last one viewed Google Analytics will record a time of 60 seconds. It will also change the definition of a bounce visit, from a visit where just one page is viewed to a visit that consists of a single page view that lasts less than 60 seconds.

There is a lot of flexibility in how this can be set up: it could be set to recheck every X seconds, it could be set to check all or just some pages, it could use a different length of time on different pages.

The important point is not to record exactly how long a person visited but to establish that they were there long enough to read the content, even if they only viewed one page.

Frequency of visits

For each visit Google Analytics keeps count of how many times that visitor has visited (this is the count of sessions dimension) and how many days it has been since they visited (the days since last session dimension).

This information is very well presented in the Frequency & Recency report found in the Audience / Behaviour section of Google Analytics. It can also be applied to most other reports by using custom segments.

This provides an overview of visitor behaviour i.e. how often regular visitors return, how long they remain loyal for and the content that they look at. They are also useful for investigating the difference in conversion behaviour between frequent and infrequent visitors.

However, if you would like more flexibility and clarity in your analysis you can achieve this by updating a unique identifier for each visitor into a custom dimension. This provides the data needed to make detailed analysis of repeat visits either through custom reports, standard reports or by downloading visitor data into Excel.

The easiest and most readily available means of doing this for most websites is to load the unique identifier from the Google Analytics cookie into a custom dimension in your data.

Making the numbers meaningful

On their own, none of the proxy measures for engagement: time, frequency of visits or number of pageviews, is a reliable indicator of engagement.

For example, if a visitor spends a lot of time on a single page or a visit they might be finding your content fascinating or simply difficult to grasp, similarly if a visit consists of a large number of pageviews the visitor could either be very interested or unable to find what they want.

To form a proper understanding of your web visitors relationship with your website, you need to look at these measures in relation to each other and to take into consideration the nature of the content you are providing.

However, the most important step is to establish the relationship between the engagement metrics and other micro-conversions and, ultimately, the macro-conversions for the business.

Measuring the success of content marketing

Content Marketing is hard work. Coming up with ideas, turning them into content and publishing it takes a lot of time and effort, it is a big commitment.

So you will want to know if it is working and to gain insight into how to improve its performance, and that requires measurement. Without assessing the true effectiveness of your content marketing strategy, the whole exercise becomes a giant leap of faith with no commercial basis.

Why measure content marketing

There are two broad reasons to measure the activity generated by content marketing:

1. To improve the effectiveness of the content. By identifying which content people find most engaging and the channels that are most effective at disseminating it.

2. To assess if your ultimate business goals are being achieved. By measuring the response in terms of macro conversions attributable to your content.

Improving the effectiveness of the content

At an operational level it is important to identify the content that becomes most widely read or viewed and also to understand the effectiveness of each distribution channel for disseminating the content. Tying this information in with your business goals (see below) will provide a basis for improving the effectiveness of your content management strategy.

Which metrics you use to measure engagement and reach will vary according to your situation.

For a website this could involve measuring:

  • Unique visitors, new visitors, number of visits
  • Pages visited, posts viewed, videos watched, pages per visits, time on site, time on page
  • Referral traffic
  • Subscribers that sign up for your email or exchange their email address in return for downloading a brochure.

Social media provide their own metrics such as:

  • Facebook: views, likes, comments and shares
  • Twitter: followers, retweets and mentions in tweets
  • LinkedIn: views, likes, comments and shares
  • You Tube: views, likes, dislikes, comments, shares, channel subscribers
  • Google +: +1’s, shares and comments

These are not business goals they are micro conversions: measures of engagement and distribution that drill down to specific channels and individual content. On their own they are measures of popularity and not business success.

Assessing the effectiveness of your content marketing

These are your business goals or macro conversions; typically they include generating leads and sales.

Establishing the links between your content and your macro conversions is rarely easy.

A video may have gone viral and been seen by hundreds of thousands of people but that is no guarantee that any of them will buy your product and, short of asking each customer, there may be no sure way to tell. Conversely a customer may read a blog article, pick up the phone and place an order without you ever knowing the article was responsible in the first place.

Linking content marketing success to defined business goals

How you tie in your content to your goals will depend on the nature of your business and the content produced: is it b2c or b2b? Does it involve a long decision making process? Is it totally online or do you have shops and show rooms that people visit? And the nature of your content: whether it is YouTube videos, podcasts, tweets, photos or blogs and articles.

The aim is to collect sufficient data to demonstrate the relationship between your content marketing and business goals.

Typically content marketing material includes a link back to a website. So a good starting point for most is to develop a comprehensive campaign-tagging program that uniquely identifies each piece of content and its distribution channel. It will then be clearly recorded when someone visits the website using a link from that content. For content that doesn’t permit this then vanity URLs or dedicated landing pages can be used.

Alongside this make sure you have conversion goals for the capture of prospects, qualified leads and sales.

This will build up a body of data about content marketing generated website activity, that will tie directly to macro conversions.

Total accuracy is unlikely, but with planning you will be able to build a broad picture of content related activity across the website and social media and use this to identify correlations with your business goals.

Putting a £ value on your content marketing

It is important to quantify macro conversions in monetary terms, doing so allows you to assess the value that the content you are producing is generating for the business. Quantifying the cost of producing the content management will then demonstrate if it is worthwhile.

Use the data to inform your judgement

It is important not to look at the data in isolation.

When reviewing the performance of your content marketing always ask the question: “Does what it is telling me fit in with the big picture of what is going on in the business?”

Whether the answer to this is yes or no, you then need to understand why.

That is where the true insights are.

 

Campaign Tagging – An overview

Campaign tagging, also called link tagging and sometimes UTM tagging, is at the heart of Google Analytics’ tracking and reporting of how visitors reach your website.

Google Analytics provides a set of 5 dimensions – think of them as values – that can be updated to record details about the link a visitor clicks to reach your website.

In the normal course of events Google Analytics will automatically update some of these values with information about the nature of the web traffic.

However, if you publish content or adverts on other websites, through social media, or in email to customers campaign tagging can be used to collect more detailed meaningful and accurate information. Thus enabling you to assess the effectiveness of your advertising and the content you are distributing.

What is campaign tagging?

Campaign tagging involves adding parameters and values to links that lead back to your website that are then updated into your analytics data.

There as 5 campaign tagging dimensions: Medium, Source, Campaign, Content and Term available.

Medium should describe the communications channel
Source is the location of the link, such as the website it was on or marketing email it was in.

Campaign, Content and Term should be used to describe the content that drove the traffic to you.

Their use is best described by an example, if you were a percussion manufacturer running a spring promotion on your range of cymbals and you paid to display your “big display advert” on the mikesdrums website, you could capture all that information each time someone clicked on the advert.

The traffic is coming from paid advertising on the mikesdrums website. So you would set medium to paid advertising and source to mikesdrums.

The content driving the traffic is the big display advert from the cymbal promotion. So campaign would be cymbal spring promotion and content big display advert.

In order for this data to be captured you would attached the following link to the advert:

mywebsite.co.uk/?utm_medium=paid+advertising&utm_source=mikesdrums&utm_campaign=spring+15+cymbal+spring+promotion&utm_content=big+display+ad

Note, Google Analytics interprets the “+” signs in the URL as spaces. Using this helps keep your reports easy to read.

By doing this for all your links you will capture the data needed to measure the performance and return of all of your online advertising.

You will also be able to compare the results of your promotions. For examples you might compare: the results from paid advertising against other visitor channels, the performance of different referring websites, how different adverts performed, how different campaigns performed and any permutation you might need.

Five hints for successful campaign tagging

1. Think carefully about the data you want to collect and how the values you choose will display in the reports and fit in with the untagged visits.

2. Use a consistent and structured approach to constructing the values you use.

3. Only use values that will be meaningful to you, even if you look back 6 or 12 months later.

4. Always use lower case for everything. This is important because Google Analytics is case sensitive so, in the above example, “Cymbal Promotion” and “cymbal promotion” would be treated as two different values and show up as two lines on reports.

5. Document your marketing campaign and the campaign tags you use. It is always surprising how quickly the detail gets forgotten.

 

Campaign Tagging: what to watch out for

Tagged Links are not reported as referrals

In the normal course of events Google Anlalytics  would record a visit via a link from another website as a referral. It would do this by updating the value referral into medium and the website’s name into source. This means that visits from tagged links will not appear as referrals, even though they are visits from other websites. This is not generally a problem since the whole point of tagging is to provide more detailed information.

The Acquisition All Traffic Channels Report

Link tagging parameters that you add directly to a link will automatically override the values that Google Analytics would normally use. This affects some of the reports in Google Analytics.

The extract below is from the Acquisition – All Traffic – Channels report and shows what happened when a business started to use link tagging for its content on twitter and LinkedIn. Because they were using their own values for Medium the visits from social media were being categorised as (Other) and not Social.

Channels Report

Provided you have taken a consistent approach to defining your own campaign tags rectifying the above report is fairly straightforward, you need to amend the definitions for Default Channel Groupings. You can either amend the selection criteria for the Social channel to include your tags or you might create a new channel specifically to identify visits that come from the content you distribute that will contain your tagged links.

The settings for this can be found In Admin under Channel Settings. Beware changing these settings permanently changes the data as it comes in.

The Conversions Multi-Channel Funnel Reports

This report is affected in the same way as the All Traffic Channels Report above.

The (other) channel in the report shown is made up of campaigned tagged traffic from social media.

MCF Report

Unlike most other reports in Google Analytics the multi channel funnels can change the analysis of the data retrospectively.

To amend the report so that is displays the visits in the correct category you can click on the Channel Groupings drop down and create a Copy MCF Channel Groupings Template, which you can amend to include your tagging criteria and use for reports. You will need to remember to select the modified copy each time you view the report.

Social Reports

The Acquisition – Social reports are a highly customised section in Google Analytics that rely heavily on behind the scenes logic for determining what is considered a visit from a social media site and hence included in the social reports.

The chances are that the values you choose for your campaign tags do not match Google’s logic and so will be excluded from these reports.

However, it is possible to work out what values of source and medium Google requires for each social site in order to include it. But, unless you have a very good reason for doing so I recommend using the source and medium values to suit your own reporting requirements.

The result will be that the social report will only include visits from social media visits that are not generated by your campaign tags, which you might even consider an advantage.

utm_term or Keyword

The sharp-eyed may have spotted that whilst I list term above as a dimension that can be updated I did not use it in the example.

The reason is that the values from utm_term are updated into a dimension called Keyword. This is used to hold keywords that visitors have used to find your website from Google AdWords paid search and organic searches from search engines such as Bing. Google no longer provides the keywords from searches on Google.

So whilst it is OK to use utm-term to hold more detailed information about your advertising content you will find that it often appears in inappropriate places in the standard reports, along with search terms used.

You must always have values for medium and source

You do not have to use all of the values for each link. However unless you have values for both medium and source all the campaign tags will be ignored and not uploaded to Google Analytics.

Short URLs and QR Codes

Link tagging can be used for any link back to your site and can work with URL shorteners and QR codes. However, not all generators allow you to specify all of your own campaign tags and will substitute in their own values.

Always test before distributing the links, regardless of what is claimed on the generators website.

Never use campaign tags for internal content on your own website

Campaign tags are specifically designed to captures information from referring websites. If you tag internal links then the original information collected about where the visitor has come from whgen they first arrive on your website will be overwritten with your internal information and lost.

 

Tips for using Google Analytics to track your off-line marketing

If you advertise in print, on radio or TV how do you tell which hits were generated by which advert?

E-commerce retailers often include a discount code that enables them to identify which advert to attribute a sale to.

However, not all sites sell direct to the public and this doesn’t identify the visitors who came, saw and decided not to buy. And knowing that people are interested enough to visit but fall short of purchasing is important information that can be used to help increase the conversion rate.

Vanity URL’s

A vanity URL is simply a URL that points to your website.

Businesses often create vanity URLs for each of their products. They don’t go to the effort and expense of building individual websites for each product. Instead they redirect the URL to the companies home page or a webpage dedicated to that product on the companies website.

The important point is to only use these vanity URLs in off-line advertising so that you know the visitor must have seen the off-line advert.

For these visits to be identifiable in Google Analytics the trick is to setup the redirects using campaign tagging. Like this:

www.mycompany.com?&utm_campaign=off+line&utm_source=myproduct.co.uk&utm_medium=url+redirect

The utm_campaign, utm_medium and utm_source values will show up in GA reports such as the AcquisitionAll TrafficSource/Medium report clearing identifying the traffic that came via the vanity URL.

Landing Pages

Another technique is to create dedicated landing pages with easy to remember and type in names on your website such as:

www.mycompany/garden

If there is no other link to this page, you know that all the visitors must have seen or heard the advert and typed in the full URL.

Keeping your Google Analytics data relevant

The value of web analytics derives from understanding the behaviour of your customers and potential customers.

So if your analytics system is recording visits from sources that are clearly irrelevant to your business it will be much harder to understand what is going on.

Irrelevant visits generally fall into two categories:

1. Automated visits: these are generated by web crawling software.

2. Visitors from outside the geographic area you do business in.

How to exclude automated visits and spam referrals

There are systems that crawl the Internet automatically collecting data from websites. One of the main uses is to collect the information used by search engines.

However, there is an increasing trend for these systems to be used to place a referral URL in your web-analytics system, presumably in the hope you might follow it to see what it is. These are known as spam referrals.

There are several ways of preventing these from showing up in your analytics data. But for the non-technical, here are three straightforward steps you can take to exclude them by using Google Analytics.

 a) Turn on Bot Filtering

From within Google Analytics go to Admin, then select View Settings for the reporting view you use. Three quarters of the way down the page you will see a setting titled Bot Filtering check this to “Exclude all hits from known bots and spiders” like so…

bot filtering

Unfortunately it does not exclude hits from all bots and spiders so there are two more steps to take.

b) Filter out unwanted spam referrals

Example of referrals that you might want to exclude are those from: o-o-6-o-o, forum.topic50575248.darodar, humanorightswatch,simple-share-buttons, blackhatworth, buttons-for-websites, iloveitaly and priceg.

It is possible to create a single filter to exclude all of these, but to do this you would need to list all the different sites. However, most spam referrals can be spotted because Google Analytics records the domain name of the website that triggers its tracking code.

For standard implementations the hostname can only have one value and that is the domain name of your website.

To see the hostname for your referral traffic:

Go to Acquisition / All Traffic Referrals Report

Select the secondary dimension button

Type “host” into the search box

Click on “Hostname” in the green box that will appear.

viewing hostname

 

This will display a report similar to the following

Source and hostname

 

As you can see many of these spam visits do not have my website hostname.

So the easiest way to exclude these visits is to set up a filter so that only visits that have your domain name as a hostname are included in your analytics data.

From within Google Analytics go to Admin, then Filters for the view you use for reporting.

Select “+ New Filter

Give the filter a name such as “Restrict visits to my hostname”

Select:

Filter Type: Predefined
Include only
Traffic to the hostname
That contain

In the hostname field enter your website domain name (because we have used “that contain” you do not need to add .com or .co.uk etc.

The filter will look like this…

Restricting to hostname

However, two of the unwanted referrals did use my hostname. To exclude these, set up a second filter that specifically excludes referrals from these websites. The referral web domain will always be recorded as Campaign Source. To create the filter:

Select:

Filter Type: Custom
Exclude
Filter field: Campaign Source
Filter pattern: semalt|buttons-for-website

The filter will look like this…

Anti-spam filter

It is easy to add other sites. The vertical line | represents “or” so just use this to separate the website names.

The system will exclude all visits where the campaign source includes the exact text entered. Be careful not to leave any spaces between the | and the text.

Restrict visits to the country you do business in

The Analytics Doctor website has received visits from over 50 different countries. However, since I only operate within the UK, including these visits gives me a misleading sign of the effectiveness of my website. So I exclude them for reporting purposes.

You can see where your visitors come from by looking at the Audience / Geo / Location report.

To create a filter that will only include visitors from the UK or any other specific country:

From within Google Analytics go to Admin, then Filters for the view you use for reporting.

Select “+ New Filter

Give the filter a name such as “Restrict visits to UK only”

Select:

Filter Type: Custom
Include
Filter type: Country (select from the list)
Filter pattern: United Kingdom

UK only

To match UK visitors only it is important you type in “United Kingdom” exactly as displayed here.

Once set the View will only include visits from the UK.

These changes will reduce your visitor numbers, but because the number of irrelevant visits is reduced any statistic based on the total number of visitors will improve. Bounce rate should reduce and conversion rates for goals increase because there is now a smaller total number of more relevant visitors.

Health warning: Always try changes in a test view before applying them to your reporting data.

 

 

Icons made by SimpleIcon from www.flaticon.com is licensed by CC BY 3.0

Which 50% of your marketing spend is wasted?

It was once said that 50% of the money spent on advertising was wasted; the problem was you didn’t know which 50%.

Online marketing is different.

You can see where your customers come from, what they look at and what they decide to do. Whether that is making an online purchase, signing up for a newsletter or downloading a brochure.

It offers a level of transparency way beyond any other forms of marketing or advertising.

What’s more, this information isn’t limited to your customers. It is likely that over 95% of visitors that come to your website don’t convert. These potential customers, were interested enough to look but didn’t buy.

Wouldn’t it be a great if you could find out why?

How web analysis can improve your online business

Web analysis uses your website visitor data to discover how people find and use your website.

This helps…

Improve your visitor acquisition strategy by focussing on the most successful channels.

Understand what your visitors look at and do and how this correlates with conversions.

Identify where visitors leave the site before converting: Are you attracting the right target audience? Are visitors finding what they came for? Is there something wrong with the checkout process? Are there any particular pain points that need to be addressed?

Get Analysing

There are plenty of analysis systems available such as: comScore, StatCounter, Adobe Analytics and Google Analytics.

Google Analytics is the market leader and installed on over 27 million websites (source www.builtwith.com). The free version, which is suitable for all but the biggest websites, can handle over a million visitors a month.

However, more important than which tool you use is how you use it.

Take time to think about exactly what you are trying to achieve from your website and online marketing. Make sure your analytics system is setup to capture the information you need. Involve everyone connected with the website so they know what is going on. Train people to use the tool, so they can properly interpret the data.

And, most importantly, once you understand what is going on, be prepared to make changes.

A successful online business relies on providing a good customer experience; web analysis will tell you if that is what you are doing and helps you understand what more you can do to meet your customers expectations.

4 Common assumptions not to make when using Google Analytics

On the face of it, the standard reports in Google Analytics (GA) are simple and intuitive.

But, as an old boss of mine was fond of saying: “To assume is to make an ass of yourself.”

So, in a bid to help prevent people inadvertently making asses of themselves by misinterpreting their website data; here are 4 common assumptions to avoid making.

1. That total users represents that number of individual people that visited the site.

Most people look at this figure and assume it means a unique visitor, an individual who has come to look at the website.

The Google Analytics help text even supports this interpretation. It tells you: “The Users metric shows how many users viewed or interacted with your content within a specific date range.”

It would be easy to dedicate an entire blog to explaining the term user and how Google Analytics calculates it in different situations, but the key point to note is that:

A “user” is a unique combination of browser and device, not a person.

So a visitor who first viewed you website on their office computer and then checked it out again using their iPad on the way home from work would be recorded as two users.

2. That Average Session Duration is a true representation of how long people spend on the site.

Average session duration is an important statistic because it measures people’s direct engagement with a website. But use it to identify trends; on its own it is probably the most misleading statistic in Google Analytics.

The problem is that whilst it is easy to determine when a visit starts, because the website has to download that first page. GA does not know when a visit ends.

Knowing that a second page has been downloaded is straightforward and so is a third or fourth. But GA has no way of knowing when the visitor moves onto the next website, and therefore does not know when the visit has ended.

This means that the session duration is actually the length of time between loading the first page and loading the last page. It does not take into account the time spent on the last page. Bear in mind that the last page may well be what the visitor was looking for and spends most of their time on it.

To make matters worse the statistic is horrendously distorted by the bounce visits.

A bounce is when a single page is visited. It is not uncommon for over half the visits to a website to be bounces. A bounce visit has no second page and therefore session duration for these is recorded as 0 seconds.

But because average time on site is calculated as total length of time of all visits divided by the total number of visits (including the bounced ones) the average time becomes significantly understated.

3. That direct visits are always reported as direct visits.

If you look at the All Traffic / Channels report or the All Traffic / Source Medium report in the AChannel Groupingscquisition section of the GA reports it appears to show how visitors arrived at the site for each session.

Looking at this snippet from the Channels report you might think that 427 visitors came direct to the site, whilst 740 used a search engine, 82 were referred from other websites and 57 from links in emails.

However, Google Analytics is a bit more sophisticated than this.

It will categorise the session according to how the particular visit was initiated for all channels except when the visitor comes direct. For direct visitors, it will look back to see if they have visited before using a non-direct method and put the session into the same channel as that. Only if the visitor has not visited before using any other channel will the visit be shown as direct.

Hence a visitor, who first visits using a search engine and subsequently keeps returning by directly typing in the URL, will continually be categorised under the Organic Search channel.

4. That the Funnel Visualisation report shows the actual path followed by all visitors.

This is a great report. It provides a simple visualisation of the path you expect visitors to take through a website as they progress towards a specified goal. This can tell you a lot about how effectively each page is working in attracting visitors and guiding them towards the purchase, sign-up, download or whatever other conversion you are trying to achieve.

But people are prone to taking it at face value and assuming it is showing the exact path followed by those visitors to get Funnel reportto the goal.

It doesn’t.

For a start it does not matter what order the visitor visits the pages in, they are always shown as visited in the order defined in the goal set-up. Furthermore, the report will automatically include as visited any steps that were missed out by the visitor.

If you need to see an accurate picture of how visitors navigate around the website the Goal Flow report is the place to go.

Make sure you understand it, before you report it.

Whether you consider these faults or features, they don’t stop Google Analytics being a powerful tool for helping you understand what is happening on your website. But, like all analytics tools, you need to make sure you properly understand what you are looking at.