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!

I have heard the notion of Google being analogous to a bank for a number of years. Recently, Jim Sterne also referred to this bank analogy while we were discussing online privacy at the Orion Analytics panel of SES London. So I wanted share and expand upon this discussion.

Please take a moment to read my disclaimer before continuing - that is, the views express on this site are entirely my own and do not represent those of my employer.

Is Google entering into online banking?

In this respect no (I am not considering Checkout here). What I mean by being analogous to a bank, is in the way that data itself has become “currency”. Information has always been valuable - no one likes to be the last to know, and being the first to know gives you a competitive advantage. So whether online or not, the storage and access of data, its security and privacy, is of paramount importance to anyone who hands over information to be stored by a third party.

That is pretty much everybody with Internet access and includes individuals, small businesses and corporations alike. Google occupying such a strong online position - the conduit for many people to find information, products, businesses etc. obviously has an important role to play when it come to data privacy and security.

It’s important that privacy and security have no intrinsic value

A key factor that makes a good, secure and private data storage system, is the strict application of a one size fits all privacy and security policy. That is, regardless of whether you are one of the worlds largest brands spending millions of dollars on operations, manufacturing or marketing, or a small company selling your handicrafts locally - your data should be treated with equal importance.

As an example, imagine if a search engine or bank provided a greater level of security and privacy to large advertisers rather than smaller advertisers (or to those that saved more than others). Even the perception of such a practice would be disastrous for the organisation in charge of protecting your data “currency”. You of course want bullet proof controls whether you save $1 or $100 million dollars. That is how the banking system works and is also how Google operates with respect to handling all visitor and customer data.

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This started off as a reply to a comment from Sara Andersson (of search-input.com) concerning my post about the accuracy limitations of web analytics and the difficulty of aligning data from disparate sources: 2008/02/16/accuracy-whitepaper/#comment-2153

However, the subject is broad enough to warrant a separate post, and probably subsequent ones too! To start off, I paraphrase Sara:

“Most sites are not conducting e-commerce and we [marketers] need to spend our resources analysing the lead generations through a combination of the online traffic to the other trend tools available. In your opinion, how would you best go about to study a trend when you have to aggregate additional resources of information from various tools - all with their accuracy problems?“

As I said in my initial reply, this is a very good and difficult question and it got me thinking…

Huge sums of money have been invested by many a corporation in trying to achieve this, but the fact is, its difficult. For example, how can you compare a TV audience that is passively digesting your ad which mentions your web site (with an unquantifiable number of viewers reading a newspaper, checking emails, making a cup of coffee, taking a bathroom break, putting the children to bed or any other activity that takes place during an advertisement break), with a pro-active person that has connected to the web, conducted a search engine query with specific keywords, and landed on your web site?

Assuming some TV viewers remember your brand or web URL and later visit your web site, are these two types of visitors comparable? The simple answer is NO.

Marketers still need to analyse and compare data from disparate sources

So what can be accomplished? First, lets set up some examples:

Example 1: You are a non-eCommerce web site and you are using and ad serving platform (e.g. DART from DoubleClick) to display banners on a selection of related portal sites in order to drive enquiries to your web site. Your web site’s call to action is to generate a telephone call to your call centre to complete the transaction. You use an internal tool to track how many calls are being made as a result of this.

Example 2: In addition you are running a print campaign (magazine) driving brand recognition by directing visitors to your web site and you wish to measure its impact. All you have from the magazine publishers, is a monthly distribution figure of 50,000 readers.

How to integrate data

The key to be able to make comparisons is to ensure you have an integrated approach to your marketing That is, don’t treat different channels as silos. Keeping web analytics at the heart of your strategy gives you the best possible chance of success - consider Figure 1. Put simply, the web is the most accurate form of marketing measurement. Therefore use it to your advantage.

Using Example 1, integration could be achieved by the use of a unique telephone number on your web site landing pages. Ensuring your specific DART landing pages are not accessible by non-DART referred campaigns (not linked to within your web site or visible to the search engines), your call centre could then identify these calls as originating from a particular banner advertisement.

In fact, a clever CRM system can dynamically assign the page’s unique telephone number on-the-fly depending on the referring source. For example, if from a DART banner use: 1234-5678, if not use: 4321-09876. By this method, you are able to directly measure, and differentiate, how many visitors and how many telephone enquires are received from your DART campaign.

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Its been a long time since my last post (October!) but I have still been busy writing - essentially finishing the edits to the book and that has given me plenty of ideas for future posts… Anyhow, happy new year!

This post is an extrapolation of a section in Chapter 2 of the book which has led to a separate PDF accuracy whitepaper. Why is this necessary? Well, the question of accuracy crops up all the time on numerous forums and at conferences. Essentially many practitioners of web analytics worry about accuracy. Some vendors even claim greater accuracy than others (though as I explain in the whitepaper this cannot be true), and there is the inter-industry debate about whether off-site analytics (for example, Hitwise, comScore, Neilsen//Netratings etc.), are better at predicting traffic levels than on-site analytics tools (such as Webtrends, Omniture, IndexTools, Google Analytics etc.). I won’t go into that debate here, except to schematically illustrate the two different web analytics approaches in Figure 1.

Figure 1: On-site v off-site web analytics

The truth is, for either approach, web analytics is not 100% accurate, and even the error bars are difficult to measure. But just how important is this?

The initial reaction to this question is usually “very important”. Marketers need to manage visitor acquisition budgets, content creators need to be know if their work is engaging (building relationships or not), e-commerce managers need to know their conversion rates, and webmasters/developers require data on which to base decisions for technology investment (internal site search, rich media applications, checkout systems). But is this a question of accuracy or is precision the more important factor?

Wikipedia has an excellent article on the difference between accuracy vs precision and I am reliably informed that Jim Novo spoke eloquently about this at the 2007 eMetrics Summit in Washington (though I wasn’t present!). From the Wikipedia article, the two targets shown in Figure 2, schematically illustrate the difference beautifully.

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When viewing Google Analytics reports, I constantly need to remind myself of the difference between goals and conversions (may be its just me that gets confused..!). Whatever, I thought I would share my clarification.

One obvious difference is that a transaction is associated with an e-commerce completion (a purchase) while a goal conversion is considered a non-ecommerce conversion, such as a PDF download, a form completion or visit to a special offers page. Of course they are all conversions, which is where I think confusion lies.

Explanation: The most important difference as far as Google Analytics is concerned, is that a conversion can only happen once during a visitor session - that is, a visitor can only become a customer (convert) once and that makes sense. However, if one of your goals is set to *.pdf for example (any PDF file download), then should a visitor download 5 PDF files during their session, it will only show as one conversion in your Goal Conversion reports. Assuming you are tracking pdf downloads, the 5 PDF files will of course show in your Content > Top Content report.

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