Advanced Web Metrics

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]

I had an interesting conversation while in Seattle recently. On discussing the progress of the book (95% complete now..!) with a friend from the industry, I described how my last chapter is going to be a sum up all the things learnt plus my thoughts on what’s next for web analytics. For the sum up, I was asked, “so what do you think should be the first thing to do when considering a web analytics implementation?”.

“That’s a great question” I replied and gave the following response: “Tag all your pages i.e. Collect the data”.

The conventional wisdom for web analytics, has traditionally said that before you even choose your preferred vendor for an implementation, you should prepare your web analytics business objectives, map who your stakeholders are, canvas throughout your organisation for KPIs, business plans, marketing plans etc. - anything that relates to the success of the web site.

But, you don’t know what you don’t know…
So I disagree with that school of thought, particularly if you are implementing a web analytics tool for the first time. Adding page tags is more important as your first step because they collect your valuable data. Seeing raw, unfiltered, non-segmented data will help you understand how visitors interact with your web site at a fundamental level.

Reflecting on this during my flight home, the first thing to do when considering a web analytics implementation is actually a combination of two elementary things - tag all your pages, then view reports to understand the initial collected data.

Step 1: Tag all your pages
Ensure you tag ALL your web pages with your tracking code (usually a javascript snippet). The emphasis is on ALL as quite often by default tools will not track download files (PDFs, XLS, DOC, EXE) or external links (banners, affiliates, advertisements). Google Analytics for example uses a function call to urchinTracker to create ‘virtual pageviews’ which you need to manually add to your download links. Also, quite often page tags are simply missed out - usually by human or machine error. For sites with many web pages that are constantly updated/evolving, consider a regular auditing service to ensure all page and virtual pageview data is consistently tracked. In fact regular tag audits are an important aspect for the ongoing management of your web analytics solution and many GAACs offer this service for Google Analytics.

Step 2: Understand the initial data
This is the initial pass by of your data before mapping who in your organisation your stakeholders are and what KPIs are useful for benchmarking your web site against. With good data coming in (usually 2-4 weeks worth), simple questions can then be answered, for example:

• How many daily visitors do I receive
• What is my average conversion rate
• What percentage of visitors are from search engines
• What are my Top 5 visited pages
• What is the average visitor time on site
• What is the average visitor page depth
• What is the geographic distribution of visitors
• What is the average visitor bounce rate (single page visits)
• etc.

So my approach is first to understand the make-up (distribution) of your visitors with some base metrics of what these visitors do. That simply requires the tagging of your pages and an initial understanding of what the reports are showing you. Armed with this information, it is then time to start thinking about your stakeholders, KPIs , and how to benchmark yourself in order to make improvements.

How have you approached the implementation of web analytics? What came first, the data or the stakeholder maps, business plan or KPIs? Please add your thoughts with a comment.

The Google Analytics business model is unique for the web analytics industry - a deep dive reporting tool suitable for companies of all sizes (past article - Who uses Google Analytics?) given away free of charge. But is there a catch to this uniqueness? Well in my view there is none. Of course I am slightly bias in my opinion, but the idea behind providing Google Analytics for free makes perfect sense to me:

• Provide accountability and transparency to existing Google advertisers
• Provide confidence and prove the value of online advertising to potential new advertisers

Lets face it, happy customers are good for any business. For Google, may be as a result of using Google Analytics, customers will remain advertisers for a longer period, become less likely to lapse their accounts (take breaks from advertising), even raise their AdWords budgets to capture a greater share of the search market. For those users that are not advertisers, perhaps Google Analytics will give them the confidence to try it - that is Google Analytics helps Google acquire more advertisers. So to me, giving away Google Analytics for free is a valid business model as it can help generate revenue for the business.

Compared to this return, the cost of providing analytics is not so great. Following Moore’s Law, data collection (bandwidth), data storage (hard disk space) and data processing (CPUs) are inexpensive to provide and becoming more so.

Is this such a unique business model?
Giving away your technology up front in the hope of making your money back later in other ways is used in other industries. For example, the mobile phone industry has been giving away cell phones to customers with annual contracts for many a year now. Satellite TV companies offer free receivers, dishes and installation with their contracts and Internet Service Providers ship their routers for free to new customers. Of course these are not directly analogous to Google Analytics, as they all require a customer commitment to spend a minimum fee usually over a 12 month period. With Google Analytics however, there is no commitment. In fact anyone can use it without charge (and cancel at any time) even if you are not a Google Advertiser.

However being free can also be a hindrance. Some people dumb down the product, claiming that decent features must come at a cost. Others speculate that sharing your data with Google is a bad thing - “they will hike up your bids”. But that is fraud and no business can survive that, as Enron proved. Perhaps by sharing your data, Google could provide a better service such as more qualified leads, better click fraud protection etc. - but that is pure speculation at this stage.

So until Microsoft release their alternative (Gatineau, which is most likely going to be free), Google Analytics remains a unique tool in the web analytics market.

Is having a free tool good or bad for the industry? Does it stifle competition or create new opportunities? Share your thoughts by adding a comment.

Its actually quite easy to detect which web analytics tool a web site is using - you can simply view the source code and look for the page tags yourself. Of course pure logfile analysers cannot be detected in this way, but those are now much less common due to their inherent limitations.

To save you the laborious task of manually checking html source code, there are now various tools available that can detect the javascript page tags for you. One excellent one I use myself is WASP - a Firefox plugin (by Stephane Hamel, Immeria blog) that shows you the web analytics vendor as you browse around the web. It can currently detect 32 different vendors including GA, Urchin, Omniture, Visual Sciences (Web Side Story), Webtrends, Unica, Clicktracks, Indextools plus many others.

Last week, I spent 30 minutes browsing around and found a number of household names now using Google Analytics and/or Urchin. These include:

Alliance & Leicester Bank, ABN Amro, Blockbuster, BOC Group, Dixons, FT.com, Halfords, Interflora, GE Money, Lycos, Harrods, Citibank, National Australia Bank Group, MySpace, Nestle, P&G, Roche, Royal Albert Hall, Stena Line, TUI, Unicef

What is interesting is the number of web sites that use multiple tools and there appears to be a pattern - US companies tend to be the ones with multiple vendor tags on their pages, while European organisations tend to only have one.

Any ideas on why this would be? Is it simply a sign of a more mature market that samples the benefits of multiple web analytics vendors? Please share your thoughts via comments.

Some background information…

Often web analytics data can be extremely revealing - I have seen conversion rates increase ten fold as a result of web site changes brought about by such data. However as the analyst, you will know that interpreting the data is only half the story. You also need to communicate this story effectively across your organisation in order to get the buy-in required for the wholesale changes you may be proposing. You do this by creating internal “stakeholder” reports. The report is a very abridged version of your web analytics reports, usually summarised in Powerpoint and/or Excel and known as a Key Performance Indicator report (KPI Report).

There are literally dozens (if not tens of dozens) of possible KPI values to include in such reports and Eric T. Peterson’s The Big Book of KPIs lists just about all of them. The trick is to only select a handful relevant to each of your particular stakeholders i .e. don’t show all stakholders, all the KPIs - its too much information that will result in a loss of impact.

An example KPI report may include:
• Average conversion rate
• Average order value
• Average per visit value
• Average ROI
• Percentage revenue from new visitors

Note there are only 5 KPIs in this report, which is entirely acceptable and even desirable.

New Customer on First Visit Index KPI

Definition: What is the likelihood of a new visitor becoming a new customer on their first visit?

This is a key question many Marketers and E-commerce Managers (usually the same person!) are asking themselves. For example, should they be investing their time and effort in attempting to get their new visitors to convert first time i.e. emphasizing calls to action in their marketing efforts and page content? Or should more engagement and relationship building methods be employed?

Figure 1 - revenue by visitor type

Figure 1 is an example web site that shows a high proportion of its revenue is generated by first time visitors. But how does that relate to the number of first time visitors to the web site? The New Customer on First Visit Index KPI can tell us this:

Figure 2 - %transactions from new visitors (click for new window)		Figure 3 - %visits from new visitors (click for new window)

For this web site, the numerator is taken from Figure 2 and denominator from Figure 3, the value is calculated as:

New Customer on First Visit Index = 62.50 / 77.20
New Customer on First Visit Index = 0.81

Interpretation for the New Customer Index KPI

• A value of 1.0 tells us that a new visitor is equally likely to become a customer as a returning visitor.
• A value of less than 1.0 indicates a new visitor is less likely to become a customer than a returning visitor.
• A value of greater than 1.0 indicates a new visitor is more likely to become a customer than a returning visitor.

For the example web site (New Customer on First Visit Index = 0.81), a new visitor is less likely to purchase than a returning visitor. This is not surprising as the average order value KPI is high (£1,315.99). Considering this, it is therefore surprising is that the New Customer on First Visit Index is so high. This indicates that the value proposition and other on-site factors such as trust, page content quality etc. is very high for this web site.

Conclusions

Q: What is the likelihood of a new visitor becoming a new customer on their first visit?
A: For this example web site, a visitor is slightly less likely to purchase on their first visit.

However, the emphasis is on slightly. Conventional thought would be that such a high value item would require multiple visits for the potential customer to be convinced to purchase. In this example, it appears the visitor has already made up their mind they are ready to purchase (perhaps there is a strong brand influence) - they just need a quick, easy and trustful source to purchase from.

So the Marketers and E-commerce Managers should indeed invest their time and efforts in emphasizing calls to action in their marketing efforts and page content.

What do you think? Do you have a KPI for your organisation that has not been documented elsewhere? Please share your thoughts via comments.