Advanced Web Metrics

Finally after 18 months I am excited to announce that the book has been published by John Wiley & Sons, Inc and is now available from Amazon and other outlets. The book started shipping on March 17th (coincidentally my birthday!) and just made the SES New York conference. Lucky for me as it sold out on the first day thanks to Sharon Preiss of Mobile Libris for her promotional work there.

Note, I will be hosting a launch party on Thursday April 24th in London. If you are interest in web analytics, and of course Google Analytics specifically, it would be great to meet my potential audience. If you would like to attend, please email me at: .

Why should I buy the book?

If you have an interest in measuring the success of your web site and you have heard of Google Analytics, then this book is aimed at you. The purpose is to help you drive your business and help you make money from your web site. The content covers the whole spectrum of web analytics using Google Analytics - from initial measurement planning considerations, to GA best practice implementation, advanced configuration, hacks (workarounds), KPIs and real world usage, including analyst tasks such as identifying poor performing pages and funnel optimisation.

Who is the book aimed at?

The book is aimed at a broad audience - essentially anyone with an interest in making their web site successful. That includes website owners, marketers, web designers, developers, content creators, PR departments and all the various intermediaries. It’s about measuring for success (the title of the first section) and applies best practice techniques on how to do so using Google Analytics.

It’s a jumpstart for any business to get up to speed on web measurement but is also for experienced marketers and webmasters to go deep into understanding how to track engagements and how to optimise a website using Google Analytics. There are approximately 178 images to illustrate ideas, analysis and to show example reports from real-world sites. Where possible I have been consistent with example images in order to maintain a coherent story for the reader to follow.

OK, so give me some details on the content…

Spanning over 353 pages across 11 chapters, the content of the book is written entirely for the latest Google Analytics tracking code (ga.js) and is split into four key sections:

• Part I - Measuring Success, is an overview of why understanding your web traffic is important to your business and covers different data collection methodologies (page tags and log analysers), data accuracy considerations and where exactly Google Analytics fits in.
• Part II - Using Google Analytics Reports, explains how to navigate and use the Google Analytics interface and includes 10 Top reports to whet your appetite and begin the analysis of your website.
• Part III - Implementing Google Analytics, is the best practice installation and configuration guide detailing how to track all online marketing channels, Flash events, banners, file downloads and more. There is also an advanced section entitled Google Analytics Hacks featuring implementation techniques not documented elsewhere.
• Part IV - Using Visitor Data to Drive Website Improvement, is the largest section of the book. It describes how to build a culture of measurement in your organisation from objectives and key results, to key performance indicators. This is followed by a chapter dedicated to real-world tasks that covers optimising checkout systems, pay-per-click campaigns (including AdWords), SEO, and e-mail marketing efforts. There is also an introduction to multi variate testing.

Downloads

You can download the Table of Contents, Chapter 1 and the book Index from here or order directly from Wiley (US and Canada only) or Amazon.com. If you use a different Amazon country, simply edit the .com part of the domain from the link accordingly.

Have you read the book?

If you have already had a chance to read the book, please share your own perspective via comments below. I would be deeply appreciative if you could consider writing a review for the book on Amazon. Books like this live and die by their Amazon reviews and I am prepared to take the risk - I hope I don’t regret saying that!

[This article is part of a series entitled: GA Implementation ABCs]

So far what I have discussed in this series has been fairly straight forward - dare I say “easy”! The next step is the difficult part - not from a technical perspective, but purely in terms of communication.

To recap the story so far, the first three best practice implementation principals are:

1. Tag everything - get the most complete picture of your web site visitors as possible
2. Clean your data - apply filters
3. Define Goals - distill the 80+ reports of GA in to performance benchmarks

If you have followed these steps so far, then you have done an excellent job. However, the usual problem is that few other people in your organisation know this or even appreciate your work. You have created a set of nice charts and reports, “so what?” is a common response that is thought, if not stated.

The unfortunate truth is that you will have wasted your time unless you can get the buy-in use the visitor data in driving business decisions and be the focal point for instigating change on your web site. With your initial understanding of your web site visitor data, this is your next step - to map out the objectives and key results for your organisation’s web site. For this you need to bring in your key stakeholders from the other parts of the business. These can be marketing, sales, PR, operations, web development/design agencies, e-commerce managers, content creators - even the CEO.

Setting Objectives and Key Results (OKRs) - 4 Steps

Step 1: Map your stakeholders
Map who your stakeholder departments are from the list above. Then select one person from each as the key contact for initial discussions. They may not be end up being the right person but that can be changed later. The important thing is to get people on board from those departments.

Your key contacts are your point of contact representing the interests of that department within your organisation. They can canvas opinion from the rest of the organisation on your behalf - in other words, they do not have to be the most senior person from that department. Note you should encourage this to be a two way street - you setting the scene with your initial data and thoughts on the current situation, with stakeholders providing their perspective on how it fits with their department. For example, they may provide information from CRM systems, call centre figures, web server performance etc.

» Read the rest of this entry »

[This article is part of a series entitled: GA Implementation ABCs]

In Part I of this series, I discussed the importance of simply getting the data in. Part II concerned keeping the data clean by using filters. In this third install I discuss defining goals - the building blocks for your Key Performance Indicators (KPIs). Remember this is all before tackling the much wider (and also more complex) issues of mapping your stakeholders, building your KPIs or assessing your business needs from your web site.

The importance of Goals in web analytics

After collecting and cleansing your initial visitor data from your GA reports (Parts I and II of this series), you then establish your benchmarks. Assuming there are no horror stories from viewing your initial traffic volume, consider your web site goals. A goal is quite simply the purpose of your web site, which in theory should be easy for you to define. For example, what do you wish a visitor to achieve once on your web site? An eCommerce transaction is an obvious goal, but that is also very black and white. If a visitor does not convert - can you measure how close they came?

Often for non-eCommerce web sites, I find owners and managers struggle to define the purpose of their web site. “We built a site because our competitors have one” is a common response, as well as “because IT wanted one”, “because my nephew wanted to build one”, “because our creative agency gave us one”. However, non-eCommerce sites can and should have compelling goals. If not, then just putting irrelevant content that becomes stale and out of date when your nephew/creative agency/IT department move on, will actually damage your brand.

Whether you are eCommerce enabled or not, any engagement with your visitors i.e. the building of a relationship, can be considered as a goal. Example goals include:

• adding an item to the shopping cart
• subscription sign-up
• a brochure request
• a completed enquiry form
• reading a blog article
• adding/editing/deleting a forum or blog post
• viewing a particular page e.g. Special Offers
• viewing particular page path e.g. pages A-E-F-D
• clicking on an ad/external link
• reading more than X pages
• spending more than Y minutes on your site
• clicking a mailto: link

To learn about configuring goals in Google Analytics, visit the GA Help Center.

With goals in place you can start to benchmark yourself that sets the foundations for discussing KPIs with your stakeholders. Bear in mind that a goal doesn’t always have to increase for it to be a good thing. Sometimes, negative goals indicate an improved visitor experience - for example less support tickets submitted, less complaints logged etc. would be considered an improvement.

A question I would like to get feedback on - how often have you redefined goals? Once setup do they get set in concrete or are they constantly evolving and which sectors are more proactive at this? Please share you feedback by posting a comment.

Recently, the perception of ABCE’s role for the web analytics industry appears to have become blurred. Hence I wanted to post some comments here - these were also posted on the Web Analytics Association’s forum last month.

ABC ELECTRONIC is the trading name of Electronic Media Audits Ltd. To briefly summarise from their web site:

ABC ELECTRONIC is the industry owned, not-for-profit organisation that works with and for media owners, advertisers and media buyers to help them gain confidence in the data they use. The UK company performs many services but essentially conducts independent audits of client’s digital data to ensure it complies with agreed industry standards - as defined by JICWEBS (The Joint Industry Committee for Web Standards in the UK and Ireland).

To clarify, an ABCE web audit is NOT an accuracy report - it is a verification report for web site owners. Simplified that means ABCE auditors verify the pageview and visitor numbers reported in a client’s analytics tool as matching (to within error bars) their manual counts of the data. ABCE’s methodology is to seed the data with ‘known’ visitor activity, count/verify these in the raw logs of the analytics provider, multiply up to obtain the total count, then compare with that reported by the vendor. The final report is private and delivered to the client.

That process is entirely different to ascertaining web analytics accuracy - something that is very difficult to determine by the nature of current data collection methods (cookies). For example, if you mis-configured your web analytics tool - say you forgot to track pdf downloads, your CMS system screwed up and started over-writing tags, or a large proportion of your web site is missing tags, an ABCE audit would not identify this - it simply verifies that what is in the raw logfile matches what is reported in your tool.

So an ABCE audit is important for publishers - web sites that sell advertising space need to verify their numbers to have credibility with their advertisers (trust in their rate card), but beyond that an ABCE audit is less significant to web site owners.

However, would having a setup/configuration audit for web analytics tools be of benefit? For example, such an audit could verify if your particular tool is configured correctly and capturing the complete picture. Please leave your thoughts via a comment - I always respond!

[This article is part of a series entitled: GA Implementation ABCs]

During my first post of this series What is the 1st thing to do when considering a web analytics implementation?, I discussed how important simply getting initial data in was - before tackling the much wider (and also more complex) issues of mapping your stakeholders, building your KPIs or assessing your business needs from your web site. Essentially, my view is: get an initial feel for the project - get the data in and that means tag all your site pages (including the tracking of non-standard pages such as PDFs, EXE, ZIP etc).

With data coming in, the 2nd thing to consider is adding filters. Filters in Google Analytics have many purposes such as segmentation and report augmentation. In this post I focus on their role in data cleansing. Keeping the data ‘clean’ means removing visits that are not wanted or are not valid visits. Essentially considering these as improving the signal-to-noise ratio of your data. Having clear signals means you don’t waste time analysing what could be random events (noise) on your web site.

Example cleansing filters include:

1. Your own access to your web site
   - this can be a significant volume of non-converting traffic if your employees set their browser opening page to be the company web site. Such visits will over inflate your visitor and pageview counts and decrease your conversion rates.
2. Your web developers/designers updating content
   - these can be significant in volume but more importantly, web developers are likely to update conversion pages, triggering goals and over inflating your conversion rate metrics.
3. Data contamination
   - other web sites copying your GATC either deliberately of accidentally which results in meaningless data being mixed with your web site visit data.

All 3 of these should be removed by adding 3 filters to your GA configuration as follows:

Filter 1: removing yourself from the reports

Excluding known visitors is very straight forward. If visitors connect to the Internet via a fixed IP address, you simply select the predefined filter ‘Exclude All Traffic from an IP Address’ from the Filter Manager as shown:

Excluding visits from employees, your search marking agency or any known third party, such as your web developers, is an important step when first creating your profiles. These visitors generate a relatively high number of pageviews in areas that will greatly impact key metrics - such as your conversion rates. For example, employees with their browser home page set to the company web site will show in your reports as retuning visitor every time they open their browser - and most likely a one-page visitor. Remember the GATC deliberately breaks through any caching so it’s important to exclude employees from visits from potential customers.

Similarly web developers heavily test checkout systems for troubleshooting purposes. These will also trigger GATC page requests and most likely these will be for your goal conversion pages. You should therefore remove all such visits from your reports.

Filter 2: removing your designers/developers from the reports

This simply an extension of Filter 1, using the ip address of your agency in place of your own office. But what if ip addresses change each time they log in? I will discuss this scenario in a later post. However, for the vast majority of business broadband lines, fixed ip addresses are used, so you should be ok.

Filter 3: removing any contaminated data
This filter is to ensure that your data, and only your data, is collected into your Google Analytics profile. For example, it is possible for another web site owner to copy your GATC onto their own pages - therefore contaminating your data with their own web site traffic. The simple include filter shown below applied to your Google Analytics profile will ensure only traffic to the mysite.com domain is reported on.

Of course it may be desirable to collect data from multiple web sites into one profile. In that case, add the multiple domains in the Filter Pattern separated with a | character, for example:

Filter Patern: mysite\\.com|yoursite\\.com

Important tip:
It is important to note that when a filter is created within Google Analytics, it’s immediately applied to new data coming into your account. New filters will not affect historical data, and it is not possible to reprocess your old data through the new filter. Therefore, always keep “raw” data intact - that is, keep your original web site profile and apply new filters to a duplicate profile in your account.

How have you approached the signal-to-noise ratio problem? The vast majority of Google Analytics installations I come across have no filters applied, why is this? Please add your thoughts with a comment.