So what happens if a man were released from the cave and shown the real world? His first instinct upon “seeing the light” would be to want to return to the cave, to that which is real to him. But as time wore on, he would adapt to the new reality. He would realize that it was the real world and its reflections on the cave walls that caused the reality he once believed in.

Finally what happens to the man when he is brought back to the cave? How would he remember his first home, what was considered knowledge there, and his fellow prisoners? Would he not feel pity for their ignorance and ashamed of who, and what, he once considered wise? For the wisest man from the cave, is the most ignorant man in the real world. His wisdom is based on guesses and inference instead of analysis and facts. But in “seeing the light” the veil has now been lifted and all of the cave’s values and beliefs are not only going to be questioned, but answered.

This is the analytics crossroads we now find ourselves at with the addition of advanced segmentation and custom reporting in Google Analytics. The goal of any analytics tools should be to allow the user to view data from as many angles, and in as many ways, as possible. Much like gems, there are facets of data that can only been seen if you are allowed to look at the data from a particular angle. With the ability to create custom segments, Google Analytics has exponentially increased the number of ways an analyst can look at the same data that has always been there.

In the cave, analytics professionals were the wise men who were the best at interpreting the shadows. Google Analytics was the fire reflecting the reality of the website, and analytics professionals were forced to make conclusions based on these echoes and shadows of reality. That is not to say there was no truth in the data before advanced segmentation, certainly there was, but without segmentation a good deal of the wise man’s conclusions needed to be based on inference or educated guesses. Advanced segmentation is going to change the analytics society by dragging all of us out of the cave and finally allowing us to see what was behind the shadows we saw before.

As an example, here is a custom segment I made within 10 minutes of having the feature activated in Google Analytics. Since it didn’t exist as a metric before I created it, I am going to call it 3/3 visitor {If only analytics were astronomy, I could get naming rights and henceforth these people would be known as Devlin Visitors…}. This would be someone who has visited the site at least 3 times and has made at least 3 purchases. To me that would be an indication that this type of visitor is site loyal and potentially very valuable. Mining this data out of GA before would have been nearly impossible. The results that came back were startling. So mind numbingly shocking that I took a screen shot and I am going to post it here.

So in about 10 minutes advanced segmentation has identified a segment of visitor who:

Now think about thousands of analytics professionals spending thousands of hours with advanced segmentation and you can easily predict the amount of discovery and knowledge this advanced segmentation will lead to. Identifying, capturing, and catering to unique visitor segments is the next evolution in analytics and website usability. Advanced segmentation will allow for marketing budgets to be more focused and have higher ROI, and help direct multivariate testing on site to optimize the revenue return on segments that have been identified as highly profitable. The most valuable segments will find shopping easier as the website adapts its acquisition and retention models to cater to these high value visitor’s shopping and buying habits.

My guess is that advanced segmentation will lead to monumental discoveries about metrics, KPIs and how different types of visitors behave on a website. Much of what we once knew and took as fact are going to end up being shadows that tricked our eyes and echoes that seduced our ears. Some men who were considered wise are going to be exposed, while some who were considered insignificant are going to make great discoveries. But if knowledge, and not fame or fortune, was the ultimate goal, then these will be the best days of our lives.

It’s time to step out of the cave and into the light. Plato would be proud.

This off-site, multi-channel discussion, the bed-rock of social media optimization, is just what Nielsen overlooks, and what Mashable over-emphasizes.

I know I like lolcats, but I seriously doubt that I would put “can I has a cheezburger” into a search engine no matter the amount of alcohol involved, well, maybe…But that’s beside the point. Without StumbleUpon, I would have never discovered the wonder that is a lolcat or, God forbid, known what white people like. I wouldn’t search for these topics, but based on my browsing history, vague interest categories and total lack of anything better to do; I discovered, found I liked and told others about all of these things and tons more. I even purchased this grill after stumbling upon it at A+R.

My example, whilst conjuring a bit of a rosy view of Stumble and its ilk (I bounce off of pages just as much as the next attention deficit disorder victim,) shows the beauty of social media. I was in the market for a grill, but not actively looking for one when this little guy popped up. I liked it, Googled it, read about it on a few design and cooking blogs, and eventually bought it. I am probably in the minority of users who’ve actually converted, but it goes to show that nobody should discount the collective mind of social traffic sources. Whether it is summer, the beginning of Spring semester or the holidays, Stumblers, Diggers and Reddit-ers(?) have the same thing on their minds as every other consumer out there, you just have to be in the mix to capitalize.

Now, I said that Mashable over-emphasizes the impact of social media, and I meant it; it’s just a little saccharine. If your name is mentioned in blogs or on the Digg boards, without you in the discussion, you run the risk of Google, the best and most-likely-to-convert-users traffic source, turning against you. We only need to look so far as Sen. Rick Santorum to see what the fickle nature of Google can do.

The reason to get in on what users are saying about you is to protect your Google-able ass (no pun intended, Senator) and make sure your SRP’s aren’t overrun with content from boards and blogs. Converting social network traffic is unlikely. You can, with most analytics programs, lengthen the time-to-die on your cookies to measure the effect of social network referrals, but for the most part, you’ll be lucky if you ever see them again. Then again, luck might be more fickle than the Digg crowd…but probably not.

Readers of this blog know that we recommend Google Analytics for all our clients. This is not to say that Google Analytics is the right solution for every client. Larger clients running complex campaigns can benefit from a top tier analytics program such as Omniture or Core Metrics while such programs would be cost prohibitive for smaller clients. However, given that Google Analytics is free, simple to install, and fairly powerful for the vast majority of e-commerce sites, we typically install Google Analytics for every client in addition to any other analytic programs they require. Google Analytics can quickly answer 90% or more of typical analytic queries with minimal effort or training. To illustrate that point, let’s look at a nifty report in Google Analytics that will help us answer the landing page effectiveness question very quickly. The report we want to look at is the Top Landing Page report within the CONTENT section of Google Analytics. When you first bring up the report, you will be looking at the default view.

Click on Image for Full Size

The first thing we need to do is to change the view. Note the 4 VIEWS icons at the top right of the report. We want to change the VIEW setting so that we look at the tree like icon that is the icon at the right end of the list of icons (These views can be referred to as Grid, Pie, Bar, Tree views respectively). The tree icon allows us to see how individual landing pages perform against the site average.

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Now we just need to set the parameters we want from the 2 drop-down menus that are now available within the report header. Each drop-down menu has the same 3 choices: Entrances, Bounces, Bounce Rate %. For the purpose of this report, we want to measure bounce rate % for each landing page against the site average bounce rate, and we wish to view this information from most entered page to least entered. To do this, simply set the first drop-down menu to ENTRANCES, & set the second drop-down menu to BOUNCE RATE % (note how the second menu has “compared to site average” next to the menu). Bounce Rate % will tell us what percentage of visitors hit the landing page and then immediately leave (bounce off) the site. The resultant report should look something like the image below.

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Now, you should have an easy time picking out under performing landing pages. By using the top landing page report and the tree view, under performing landing pages will appear with red bars, while well performing landing pages will appear with green bars. The bars simply represent how much better or worse than site average each page performs when it comes to visitors bouncing off the landing page. Google Analytics also lets you jump straight to the offending page in question by clicking on the “double box” link icon just to the left of the url page link (if you click on the url page link itself, you will be taken to a summary Google Analytics report page for that landing page, NOT to the landing page itself). If we look at the same info using the “BAR” view, we can see the actual bounce rates for each page, but the TREE view works best for the identification stage.

Click on Image for Full Size

Before heading off to redesign all your under performing landing pages, it is important to realize the limitations of Google Analytics, or any analytic program for that matter. Analytics programs are great at pointing out non conforming data. In other words, the value and purpose of an analytics program is to allow the analyst the ability to spot inconsistencies in data. The data point(s) can be positive or negative indicators, but in either case, the data point in question appears to be out of place or outside the realm of typical expectations. What an analytics program cannot do is determine the cause of the obscure data point. This is the role of the analyst. It is important to realize this distinction when working with analytics because many people are under the impression that analytic programs can fix websites. They can’t, people fix websites.

Why spend a paragraph explaining a seemingly obvious point of fact? Because, the first thing you should do when analyzing your underperforming landing pages is to ignore analytics for a moment and ask yourself whether there are any simple marketing, technical, or other simple reason a page is bouncing. For example, it is not uncommon for a page to have a high bounce rate do to the fact that it is image or data heavy (the size of the page in Kb, or Mb(let’s hope not Mbs!)). Google Analytics will never be able to tell you that your landing page is 500k and take forever to load. This is something a human must deduce. Another example would be a search results page with no search results or a page that cannot be found. Again Google Anaylitics cannot tell you that this is the issue, but it can point out to you that something is amiss with that page.

Hopefully the Top Landing Page report in Google Analytics can help you fine tune your site’s landing pages. Just remember, while Google Analytics can find the land mines on your site, it is up to you to disarm them. Most times, a simple explanation or small fix will be enough to guarantee safe landings for all your future visitors.

Google has rolled out a new Ad Manager service targeted at the small to mid sized publisher sites.

Google Ad Manager offers a wide array of inventory management, trafficking, targeting and reporting tools normally found in premium ad serving software or services for free.

Currently the list of features implemented in Google’s Ad Manager service includes:

Inventory Management

- Inventory levels: Maximize traffic and efficiency with granular level inventory management. Ad slots in Ad Manager allow for simple tag generation, and the ability to bundle and sell inventory packages with the same targeting and cost criteria.

- Simple Integration- Ad Manager will generate all the tags needed for implementation. Simply copy and paste the tags into your html. No need to ever re-tag and i-frame tags are available upon request.

- Inventory tracking: Google Ad Manager makes it easy to confirm available ad inventory based on specific dates, placements, and targeting criteria. No worries about overbooking ads or underselling your ad serving capacity.

Yield Optimization

- Google Ad Manager will allow for Google Ad Sense integration for filling unsold inventory or to compete against other revenue streams.

Ad Targeting

- Targeting options: Google Ad Manager will allow you to target ads based on several visitor metrics including: geography, bandwidth, browser, browser language, operating system, and domain.
- Custom targeting: Target ad impressions by developing and installing your own ad serving criteria to Ad Manager.

Trafficking, Ad Delivery, and Order Booking

- 5 Types of Delivery Options: Set delivery type to one of 5 levels: exclusive, priority, standard, remnant, or house. Google Ad Manager will determine, automatically, how ads may be delivered.
- Pricing models: Ad Manager supports cost/thousand impressions (CPM), cost/click (CPC), and cost/day (CPD) pricing models.
- Frequency Levels: Google Ad Manager allows multiple levels of frequency capping, which limit the number of ads the same visitor sees over a predetermined unit of time (hour, day, week, etc…).
- Google Infrastructure: Google’s technology and resources should ensure fast, reliable ad serving.

Creatives and Rich Media Management

- Rich media support: Google Ad Managers tags support a variety of rich media formats.
- Redirect Support: Ad Manager tracks ads from a third-party network, affiliate provider, or other URL you provide.
- Free Ad Hosting: Google will host ad creatives. Save bandwidth and associated costs.
Reporting

- Fast, Sortable Reports: Run reports on inventory performance, overall sales, order delivery. Break down reports by date, advertiser, line item, and placement. Ad Manager creates reports in seconds and allows sorting & other edits without leaving the page or running a new report.
- Media Rating Council (MRC) accredited: Google Ad Manager is accredited by the Media Rating Council to be fully compliant with Interactive Advertising Bureau standards.

User Interface
- Search functionality: Search from any page in Ad Manager. Locate order, inventory, or advertiser data in seconds.
- Intuitive workflows: Simplistic but powerful interface allows quick and easy order creation, approval, & review.
- Browser session support: Use your browser’s navigation functions, such as the ‘Back’ button, without losing data.

Administration

- Access controls: Google Ad Manager allow you to set viewing and editing permissions & define individual responsibilities. Ad Manager will also store advertiser and agency company information allowing for easy management and reporting.

Google has recently announced the addition of analytic benchmarks to their Google Analytics service. This free service will require Google Analytics customers to opt in to “share the account data in an anonymous, aggregated format”.

Reporting will be limited in the beta version of this service. Benchmark metrics include: Visits, Pageviews, Pages per Visit, Bounce Rate, Average Time on Site, and New Visits. Your data will be measured against benchmark data from categories of other participating websites in your chosen vertical. Benchmark data will highlight strength’s and weaknesses compared to other websites in your market.

This new Google Analytics Benchmarking Service is located under the “Visitors” section of your Google Analytics reports. Simply select “Benchmarking” to view the report. Google notes that it may take up to two weeks for the data to appear since it will need to be categorized and collected to establish vertical benchmarks.

To enable the benchmarking service for your account, your Google Analytics account administrator must first opt in. In order to do this, select the option to share your Analytics data from the Edit Account and Data Sharing Settings page.

To get to this page, click the link that says “Edit Account and Data Sharing Settings” from the Analytics Settings page. One important thing to consider before opting in to share data is that if you opt in benchmarking will be enabled for all profiles in your account. Since the selection is at the account level, you cannot enable individual profiles while enabling others.

Both old and new Google Analytics customers may opt in to benchmarking without changing their existing analytics tags. Whether you’ve installed the older version of the tracking code (urchin.js) or the newer one (ga.js), you do not have to switch versions in order for benchmarking to work in your account.

Choosing a vertical to be benchmarked against is a simple matter. To change the industry vertical you want to compare your site against, navigate to the category picker from the Benchmark report by following these steps:

1. Log in to Google Analytics.
2. In the Visitors section, select Benchmarking.
3. On the Benchmarking report page, click “Open category list” to expand the list of categories.
4. Click the vertical you wish to compare your website against, then click “Select Category” to save your changes.
5. The report will automatically populate the graphs.

After enabling benchmarking, Google crawls the websites in the account then categorizes them by vertical and the amount of visits. For sites of a similar size, a category of industry verticals can be chosen when there is a sufficient number of accounts in that category. You can compare your website against any available category. Profiles within an account are categorized separately.

Each category can have anywhere from 100 to hundreds of thousands of websites per category, but there is a minimum of 100 accounts in each benchmarking category. The number of actual website may vary since many accounts will have multiple websites and new accounts are always being accepted into the benchmarking service.

Sites of similar sizes are grouped together under three classifications: small, medium, and large. This classification is based on the Visitors metric. In this manner, you will be benchmarked and compared to other similarly sized sites. You will not able to view benchmarking data for sites in other size classifications within your vertical. The benchmarking service will automatically check the latest number of visitors for each site to adjust the benchmarking data accordingly. As more sites participate, a wider variety of categories will be available in the benchmarking report. Google will limit the effects of ancillary sites from the aggregate data in each category to help ensure that the benchmarking data is most representative of the category you choose to compare your site against.

Much like Fireclick’s Index, Google Analytics’ new benchmarking service will be another tool in the data analysis box. How useful that tool will be remains to be seen, but no one can argue with the free price or good intentions.

News from Google that web page load times of landing pages will now be a component of your AdWords Quality Score. This information can be found be viewing your Quality Score on an Ad Group or individual keyword level.

Landing page: Your landing page is the page where users ‘land’ when you they click your ad. This is also called your destination URL.

From Google AdWords:

Your landing page quality is a crucial part of your Quality Score. The quality of a landing page is represented by such things as the usefulness and relevance of information provided on the page, ease of navigation for the user, page loading times, how many links are on the page, how links are used on the page, and more. If our system finds that your landing page isn’t highly relevant or loads slowly, you should optimize your landing page in order to improve your Quality Score and ad performance.

As you can see from the following list of Quality Score Calculations, landing page quality will now be a core component in virtually all quality score calculations.

Google Quality Score Calculation Components:

1) For calculating a keyword’s minimum bid:

* The keyword’s historical clickthrough rate (CTR) on Google; CTR on the Google Network is not considered
* The relevance of the keyword to the ads in its ad group
* The quality of your landing page
* Your account history, which is measured by the CTR of all the ads and keywords in your account
* Other relevance factors

2) For calculating a keyword-targeted ad’s position on a search result page:

* The historical CTR of the ad and of the matched keyword on Google; CTR on the Google Network is not considered
* The relevance of the keyword and ad to the search query
* Your account history, which is measured by the CTR of all the ads and keywords in your account
* Other relevance factors

3) For calculating a keyword-targeted ad’s eligibility to appear on a particular content site, as well as the ad’s position on that site:

* The ad’s past performance on this and similar sites
* The relevance of the ads and keywords in the ad group to the site
* The quality of your landing page
* Other relevance factors

4) For determining if a placement-targeted ad will appear on a particular site:

* The quality of your landing page

Google already visits landing pages on a regular basis. The frequency of the visits depends on the level of traffic to ads and the limits of the AdWords system. However, Google states that they plan on visiting landing pages once a month at a minimum, but they may increase that frequency during implementation and testing.

If you are using AdWords, the best course of action would be to immediately review your AdWords Account.

How do I know what my Quality Score is?

To see your keywords’ Quality Scores within your account statistics:

1. Sign in to your AdWords account at https://adwords.google.com.
2. Select the campaign, then select the ad group for which you’d like to see keyword Quality Scores.
3. Click Customize columns at the top of Keywords tab in the ad group table.
4. Select Show Quality Score from the drop-down menu.
5. Click Done when you’re finished.

You can also evaluate each keyword’s Quality Score by looking at the Keyword Analysis page or at the keyword’s minimum bid.

Next, run a site crawl program that examines all of your website’s pages and their respective page size and load times. Make sure that any high traffic and/or crucial AdWords landing pages have optimized images and code to allow quick page loads. If you find a landing page with slow load times that cannot be modified quickly or easily, simply change the destination URL for any ads pointing to that page to a faster loading page, until such time that offending page can be edited.

1. Soft/Even lighting – Photographers use contrast and shadows to create atmosphere, but for product shots, ditch the art for clarity. Dark shadows and bright highlights can influence the appearance of a product which can prove to be deceptive to a customer. To avoid this kind of lighting, bounce light towards an object, pull the light away or even try lighting from above. This will provide the necessary illumination, but won’t create a harsh glare.

2. A Steady Hand – If you’re using a digital camera (which, let’s face it, you are) the LCD display on the back of your camera is what you check to see how the shot turned out. The problem with that, however, is you can’t always see camera shake on your 2”x 2” screen. With product photography you’re looking for product detail, so the closer you take the photograph, the more obvious the blur will be. Go out and get a tripod and, if you have one, use a remote shutter release for even more stability. Steadiness is key. If you follow this rule, you’ll see an immediate difference in the sharpness of your images.

3. Focus/Zoom – Zooming in before taking a photograph has its pros and cons. The pro is that you reduce the distortion from the lens, and it becomes more like a telephoto lens. The con is that you lose your depth of field and, depending on the product, parts of your image may be out of focus. The solution is to find a balance in the middle and refocus your camera before shooting each product. Also, putting your camera in aperture priority mode will help you attain the largest in-focus area, especially if you’re getting up close and personal with the product.

4. Over/Under Exposure – Similar to the first tip, misusing over or under exposure can cause your image to lose important details like the contours, edges and color strength. Under expose one or two stops when shooting on white and over expose one or two stops when shooting on black to retain the integrity of your product against the background. You can always go back and doctor an image before it goes live, which leads me to my last tip.

5. Image editing software –Photoshop. Learn it. If you’re good at it, you can transform a terrible image into a decent product shot. Just don’t forget that the more you shop your image, the more quality you’ll lose. So if you’re shooting the photos yourself, save yourself the post production time and work and shoot your photos better.

Terms, Terms, Terms
Section 508 - In 1998, Congress amended the Rehabilitation Act to require Federal agencies to make their electronic and information technology accessible to people with disabilities. Inaccessible technology interferes with an individual’s ability to obtain and use information quickly and easily. Section 508 was enacted to eliminate barriers in information technology, to create new opportunities for people with disabilities and to encourage development of technologies that will help achieve these goals. The law applies to all Federal agencies when they develop, procure, maintain, or use electronic and information technology. Source: http://section508.gov

ADA - Americans with Disabilities Act of 1990 - The ADA is a wide-ranging civil rights law that prohibits, under certain circumstances, discrimination based on disability. It expands upon the protections in the Civil Rights Act of 1964, which made discrimination based on race, religion, sex, national origin, and other characteristics illegal. Source: http://wikipedia.org

W3C - World Wide Web Consortium - The World Wide Web Consortium (W3C) develops interoperable technologies (specifications, guidelines, software, and tools) to lead the Web to its full potential. W3C is a forum for information, commerce, communication, and collective understanding. Source: http://w3.org

WAI - W3C Web Accessibility Initiative - The Web Accessibility Initiative (WAI) works with organizations around the world to develop strategies, guidelines, and resources to help make the Web accessible to people with disabilities. Source: http://w3.org/wai

WCAG - W3C WAI Web Content Accessibility Guidelines - The Web Content Accessibility Guidelines (WCAG) documents explain how to make Web content accessible to people with disabilities. Web “content” generally refers to the information in a Web page or Web application, including text, images, forms, sounds, and such. Source: http://w3.org/wai

The Breakdown
Definitions are helpful, but you’re probably still scratching your head. I’ll try and simplify it more for you… First and foremost, the Americans with Disabilities Act focuses more on discrimination of people with disabilities in the real world, not the electronic or virtual one. You can read more about the ADA on their web site, http://ada.gov.

Section 508 of the Rehabilitation Act forces all Federal agencies to provide electronic information in an accessible format. The Assistive Technology Act of 2004 (an amendment to Section 508) requires many state level agencies to comply with Section 508 as well. But, what they don’t tell you is that Section 508 is based off of the W3C WAI WCAG; did you catch all that? That’s the World Wide Web Consortium (W3C) Web Accessibility Initiative’s (WAI) Web Content Accessibility Guidelines. So, if you are compliant with WCAG, then you are compliant with Section 508 (for the most part). There are few differences between Section 508 and WCAG, but the important thing to note is that WCAG will offer more up to date guidelines to follow.
Jim Thatcher has put together a side-by-side comparison of Section 508 and WCAG 1.0 if you’re interested in seeing the differences. http://www.jimthatcher.com/sidebyside.htm.

How does accessibility apply to your online presence?
Online accessibility is as important to your web site as ramps and automatic doors are to a brick & mortar business - it needs to be accessible for people with disabilities in order for them to purchase your product or service. If you choose to disregard people with disabilities when building a store or web site, it could have serious ramifications. For instance, a class action suit against Target.com (Target’s ecommerce web site) was brought about in California last year. These types of law suits against major retailers have increased in recent years and are prompting many ecommerce retailers to overhaul their sites to include accessibility features.

Many organizations, like the National Federation of the Blind (NFB), are pushing for legislation to require all web sites to be accessible for people with disabilities - similar to the Section 508 requirements placed on federal & state agency web sites.

What does it all mean?
Whether you’re publishing a small blog (about that weird mole on your back), or running a multi-million dollar ecommerce web site, accessibility is important. People with disabilities should be able to navigate your site, read your content, and purchase a product with ease. Developing a site that enables people with disabilities to do that should be a fundamental tool in a web developer’s tool belt.

In the upcoming posts in this series we’ll be covering what goes into making a site accessible for people with disabilities and examining some assistive technologies.

Page depth is simply the average amount of pages a visitor sees during a session on your website. It should be fairly obvious that higher page depth is better than low page depth, but how to figure the metric correctly and determining a page depth baseline can be a bit more involved. For this exercise we will look at some actual PPC data from a major online retailer, but first let’s talk about how to measure page depth accurately.

We know minimum page depth must be 1.0 as it is impossible for any visitor to see less than 1 page. Most people would think page depth is simply calculated by: (Total Number of Page / Number of Visitors). While this is correct in the general sense, page depth should be adjusted to eliminate shopping cart pages. Let’s look at a hypothetical example before proceeding to an actual data set.

Suppose your website showed 10,000 pages last month to 2,000 visitors. Let’s also assume that your website converted those 2,000 visitor into 200 sales. Finally let’s assume that your shopping page is 3 pages long (this means that it takes 3 pages to fill out personal & billing info, and a confirmation page).

Using the traditional Page Depth formula, Page Depth would be calculated as:
10,000 pages / 2000 visitors = 5.0 Page Depth

Now let’s look at a calculation for page depth that adjusts the page depth calculation to remove shopping cart pages. The reason for this is that visitors who convert are forced to view 3 more pages, 1 of which (the confirmation page) is completely superfluous. The reason for this is that these pages do not measure the depth of a visitor’s session because they happen after the visitor has converted. Page depth as a metric should measure how far into a site a visitor goes regardless of conversion or no conversion. What Page Depth should be measuring is how conducive your website is to dispensing information about products or services you offer. Also, service websites typically do not have a shopping cart while e-commerce site do. By adjusting page depth to exclude shopping cart pages, page depth can be compared between types of sites without a shopping cart bias “helping” e-commerce sites.

So let’s do the Page Depth Calculation again and exclude shopping cart pages:
(Total Pages - (Conversions * Shopping Cart Page Length)) / Visitors
(10,000 - (200 * 3)) / 2,000 = 9,400 / 2,000 = 4.7 Page Depth

Notice that page depth dropped from 5.0 to 4.7 using the adjusted page depth formula. However this 4.7 pages calculation tells us that any average visitor will typically see 4.7 pages before either leaving or converting. If the 5.0 figure were used, it would be skewed by shopping cart pages that happen after the visitor has already been converted. Also all we could say for certain is that visitors who do not convert see less than 5 pages and those that do convert see more than 5 pages, but it does not tell us what the average visitor sees whether they convert or not. If you have a long shopping cart process or if you were to convert a high percentage of visitors, the traditional formula of [Total Pages/Total Visitors] would become even more skewed. The adjusted page depth calculation gives a more accurate indication as to how many pages a typical visitor views since we do not know beforehand if they will convert or not.

Developing a baseline page depth figure should be done over time and should be done for each engine or campaign separately. You will also have an overall page depth figure for all campaigns but by using this figure it will be more difficult to spot meaningful fluctuations as high traffic campaigns will be weighted far more heavily in the overall Page depth figure. One month is a good amount of time to collect data in order to calculate reliable Page Depth figures for each natural and PPC campaign. However, there are red flags to look for that can indicate a problem in less time than a month.

Let’s look at the PPC campaign data from a major online retailer doing around $10 million in gross revenues.

Notice the Raw (Unadjusted) Page Depth Figures for Kanoodle & Enhance [Not surprisingly, this figure also happens to be the adjusted Page Depth as neither engine converted a single visitor]. Enhance has a page depth of 1.34 and Kanoodle a rather unbelievable 1.10! Kanoodle’s Page depth figure says that for every 10 people that visit the site, 9 of the 10 bounce (Bouncing is a visitor who sees only the landing page they are directed to and then leave), and the tenth sees a second page and then bounces! This is the telltale sign of poorly qualified traffic or click fraud. Be aware that the smaller PPC engines and Shopping feeds are notorious for click fraud. Among these would be Kanoodle, Enhance, & Findwhat. Not only do they send unqualified traffic, but many of them also charge for 200-300% more clicks than any analytic program tracks. The Page Depth metric is an excellent tool for spotting these types of fraudulent traffic sources. Statistically speaking, it is highly unlikely for any visitors to convert from sources that generate a raw(unadjusted) Page Depth of less than 3.0. Why? Well because most e-commerce site have anywhere from a 2-5 page shopping cart, so a raw Page depth of less than three indicates that few if any visitors from that sources are making it to or through the shopping cart. If they were converting, raw Page Depth would have to be higher due to the additional pages a shopping cart adds to the page depth metric.

Hopefully this gives you an idea on how to calculate and use Page Depth as a significant metric when evaluating your campaigns. Remember, that it could be your site’s architecture (confusing navigation), bad landing page choices, or your site’s appearance that could be hindering visitors from seeing more pages. Assuming that there are no appalling usability issues plaguing your site, Page Depth can be an invaluable tool for measuring the quality of leads coming from your different traffic generating sources. Being that it is a simple calculation to gain Page Depth figures, take an hour or so and examine this metric to determine which campaigns are working for your site, and which are simply trying to get into your wallet.

Modifying & Testing

Once data has been gathered, it will need to be analyzed. Analytic programs capture, store and arrange data, but they are not capable of the analysis. This is the human element in analytics. Theoretically, the data collected by the analytics program is always correct. The program is not capable of producing erroneous data, though it could fail to capture some data due to bad tags. Assuming it does collect all the data, there is no questioning the validity of the data. What needs questioning is why that particular data was collected and to find ways to produce data that reflects the wants and needs of the E-commerce site.

Through analysis, hypotheses are born. These hypotheses will need to be tested, measured, and reanalyzed. This is the role of the analytics team. First they must analyze the data collected for trends, as well as direct & indirect relationships. This analysis will lead to conclusions that may or may not be true. Thus, a hypothesis is born and now needs to be tested. Once the changes are made, the analytics program captures the new data produced, it is compared to the data pre-hypothesis, and the hypothesis is proven true, proven false, or is inconclusive. Regardless of the result of the testing, it is the testing itself that is most important. There will be many a hypothesis that is proven false, but it is not time wasted. It simply proves that a relationship exists that is different from the one the hypothesis presumed.

Without modifications and testing, websites become stale and stagnant. Even tests that produce adverse effects have value in that they show a relationship that previously was not known. Clearly, had the analyst known that the changes would produce detrimental results, he/she would not have suggested the changes. So in failure, knowledge is gained. Likewise, when modifications produce positive results, knowledge is gained. Whether X produces more of Y or less of Y, we now know something about X we did not know before. This new knowledge can be developed and implemented if good, or it can be noted and avoided if bad.

The role of the analytics program is not just to collect data, but to measure changes in data. The more powerful the program, the more ways the data can be measured, stored and tested. This flexibility allows for deeper analysis and greater revelations. The data created by visitors is all there for analysis, but the power of the analytics tool determines how much can be seen.

Repeat

This section is fairly self explanatory. The process of collecting data, analyzing it, formulating a hypothesis, making modifications, and testing the hypothesis should be in perpetual motion. There is such a wide array of factors that induce conversion and no one hypothesis can account for them all. Rather, it will be a series of hypotheses that lead to small changes. Each small change could have a small or large effect on conversion, but it is the sum total of all changes that will bring prosperity. Sometimes it may be a matter of taking a step back before taking a leap forward, but it is the willingness to take the step in either direction to learn something that is most important.

The best E-commerce sites are constantly being modified and tested. They are not afraid to test and make modifications to portions of the website that are already working well in the hopes of making them even better. Naturally, one should first concentrate on areas that are shown to be working poorly or not at all. However, the only way to prove something cannot be done any better is to test it and show any or all modifications to it prove to be worse. Just because something is working fine, does not mean it cannot be made more efficient.

Summary

The quality of the analytics tool can affect every level of the E-commerce conversion funnel. From acquisition to cross selling to conversion, the analytic tool should facilitate each stage of the process. Analytics allow for the creation of metrics which can then be tracked and measured for changes. The changes in these metrics are the breadcrumbs on the path to profits. The better the analytics program the easier the path is to follow.