I was chatting with one of our School Deans today about various results and he posed the question “Is it possible to see which courses people viewed after seeing one course?”.  His interest was based on the fact that the user doesn’t always purchase the “most frequently visited course”.  They often view one thing, but end up purchasing something else, and our reporting doesn’t highlight that behaviour.

Now, that got me thinking…that’s probably pretty common behaviour.  So how can we make that visible?

Pathing is common

Of course, it’s easy to show page pathing (which pages are viewed before and after a certain page), section pathing (similar but for a section), but pathing isn’t available across multiple visits (for the obvious reasons).  Traffic pathing is available on s.props, so as long as you report something into an s.prop, you can generate paths to/from it.  Paths are very valuable to see where a user goes after visiting a specific item such as a page, or how they got to a specific page.

However, the problem arises when you want to see something across multiple visits.

We’ve just had a similar problem with multi-visit campaign results, where the success event was being attributed to the latest campaign id, which wasn’t neccessarily what we expected.  In our case, due to the sales cycle being long (typically 1-3 months), many visits will occur and the user won’t always come in with the same campaign code.

For example, we might send them an email which drives them to the site.  The user engages, finds out what they need, but doesn’t convert.  They then come back a few days or weeks later by either typing in our web address directly, or come in through a search engine.  In either case, the success event (if they convert) would be attributed to the latest campaign, for example, Google or Direct/Typein (as we also have a VISTA rule).

Enter Campaign Stacking…

So, to provide some visibility to this activity, we worked with our consultant who recommended we implement Campaign Stacking, which, through the use of a cookie, appends a different campaign code (if they have one) to any previous one.

So, in the above example, we now have reports which show conversions by campaign combination.  We accomplished this by setting up a new eVar and writing a cookie (through an s_code plugin) appending the next campaign code to a previous campaign code.

Now we should be able which campaign combinations are driving conversions, over multiple visits.

Now stay with me…

I’ll bet we can do the same thing to understand product view combinations over multiple visits, leading to conversion.

In our case, a product is a course, but no reason this couldn’t work for any product category.  In our case, we don’t want to see which course “pages” they visited (we have that through course page pathing).  We want to see course pathing across multiple visits (or the same visit).

By setting an eVar with the name of the course, and using the same methodology as above, we should be able to get a view on this activity and user behaviour.

In theory, we should then be able to export the data and generate promo-type content that says “People who liked this course, also liked these courses…”

That will then help us to cross-promote “related” courses – not what we think are related, but what users are thinking are related.  Do that on an automated, daily basis and you really start to apply some value for the user.

That’s one of the great things about Omniture – flexibility to do this.

Guess what I’ll be trying over the next few days…I’ll update this one over time, if we get it working.

Search is a veritable gold mine that is frequently ignored.

I’m not talking about Search Engines and Keywords, I’m talking about your internal search. Providing you track internal keyword searches, you can gain a wealth of understanding.

Internal search is generally used as a quick wayfinding method, highlighting areas of content that are well used, but are not readily available.  And more often than not, it’s seasonal as well.

The following report shows the top 5 keywords used by students on our University website, smoothed using a 21 day moving average.

Two things immediately jump out.  Firstly, notice how searches for Bookshop increased dramatically in late February, then declined, then Library picked up substantially in March, followed by Exam Timetable in late April (spiking suddenly in late May).

Very seasonal activity, centered around the Student’s life cycle at the University.  In February, having started a new semester, they all needed books.  Then as semester progressed, they all needed access to the Library, and lastly, as exams approached, they all wanted to know their Exam Timetables.

Great – but how can we use this?

Well, firstly this points to the fact that there is no clear navigation on our site to these destinations.  There’s actually a reason for that – our public site is not designed for active current students as they should be using the Student Portal.  That aside, we can assist though in making these destinations easier to get to.

One thing we can do with Omniture is to export these top keywords to our database on a daily basis and then represent them on the site, through things like tag clouds and quick search results, making their lives easier in the process.

By using real data and automating the process, the seasonality of searches will also come through to the site as well.

The other interesting thing about the above chart is their search for timetable, as opposed to exam timetable.  When they start a new semester, they are interested in their class timetables and frequently search for them.  As time progresses and the memory kicks in, that activity slows down.  Again, this can be used in a number of ways – not only online, but through mobile apps and offline support media as well.

In order to track search keywords, simply put the keyword into an s.prop.  You might also want to put the number of results into another s.prop so that you can cross-reference the results on a keyword by keyword basis.  This would highlight any search terms  that return no results.

Segment your keywords

As always, understanding your audience is critical online.  If you segment your audience types, you’ll also be able to see the different searches conducted by different audiences.  We do this and the results are (obviously) very different.  But, without the ability to do it and show it, you’ll be taking an educated guess that they are different.

To do this, put the audience type into another s.prop and use the getAndPersist() plugin to set a cookie.  That way, all activity can actually be segmented by audience type.

Now you can provide some really smart assistance

When you start to build your tag clouds or your quick search lists, you can base the results on the value in the cookie, thereby customizing the information to the user and making it more relevant to them.  Just a few little tricks like this and you’ve helped to increase the usability of your site, which will go along way in driving customer loyalty (and hopefully revenue).

Having been asked a number of times to speak with potential Omniture customers, I’ve heard that they believe it’s hard to set up and maintain.

Well, that’s a myth.

Omniture is in fact relatively easy to get set up and maintain.  It’s code based, so you just pop the code into your page:

• At the top of the page, just after the <body> tag, add your call to load the s_code.js
• At the bottom of the page, just before the </body> tag, add in the rest of the Omniture code, which then executes the s_code.js on each page load.

Easy.

But, you really want to engage their Professional Services team during the initial configuration as they will customize your s_code file to support your online strategy, add any custom variables (props, evars and events), etc which will then ensure that you get the most bang for your buck.

I’ve spoken to a number of Omniture customers who implemented without assistance.  What they face now is two things:

1. Measurement that doesn’t quite match their online strategy/needs
2. Tough questions asked by their managers as to why they are using Omniture instead of Google Analytics.

What they now need to do is engage with Professional Services so that they can understand their online strategy and align their measurement strategy to their online strategy and then tweak their s_code.

So, it’s always worthwhile doing that before you implement.

And it really doesn’t take long.  2-3 weeks of assistance and you end up with a great “playbook” which documents the implementation and how you can use it to answer those top questions.  The value is absolutely in the customization.  But I’ll talk a little about that in another post.

From that point on, it’s pretty much easy sailing.

I got asked today to provide a benchmark value for time on site for a competitor of ours.  They asked me if I thought that 3 minutes and 41 seconds was a good time for someone to be on their site.

Users are here for a good time, not a long time.  Get them to where you want them.  Quickly.  Then cross-promote them.  Engage them.  Then the good time can turn into a long time.  But Time on Site certainly won’t tell you.

Time on site can be a misleading metric – very often taken out of context.  Unfortunately the metric on its own has little value.  It depends where the 3:41 was spent.

If they spent it on the page that you want them to get to, then that’s probably a good indication that they are at least reading the content.

If they spent it on the homepage and went nowhere else, then it’s not such a good time…it’s a long time on the wrong content.

So, you have to look at time in conjunction with many other metrics.

Instead of looking at time on site, look at time on page.  How much time is spent on each page, through to your target page for the user journey.  Ideally, only a few seconds should be needed on each page prior to the destination.  This is generally facilitated through good navigation or calls to action links.

Remember, home pages are really just waypointing devices these days.  You don’t want users to dwell on the homepage – if they are, you should consider changing it becuase it probably means they can’t find the thing it is they are looking for.

Then you’ll need to consider page bounce rate.  Home pages naturally have fairly high bounce rates – somewhere in the region of 60% is not unusual.

But inner pages should have a lot lower bounce rates.

Bounce rates can be calculated in two ways:

• Page Views / Number of times this was the last page seen on the site
• Single Page Entry / Exits from this page

I prefer to use the first method when I want to see how well the page is performing at driving the traffic on to a new page, as the latter only considers when a page is an entry page (first page seen in the site).

These two metrics will provide more insight to the question than Time on Site will.

Then it really depends on what the content is.  If the goal is to have them complete a form of some type, then you’ll want to look at conversions and a funnel of the steps.  You should also consider looking at form field abandonment.

If the content is interactive, that will naturally boost time on page results.

So, unfortunately, the answer to the question is “it depends”…  But you certainly can’t use that metric in isolation of others to determine whether it was a good time or long time.

And you can’t use that to try to benchmark yourself against other sites.  The content, user journey, engagement and interactions are all very different.

It would be better to say “Ok, they’re here for an average of 3:41 this time.  In the future, how can I improve on that.  Where else should I be sending them?”.  Then review you navigation and cross-promotions for other areas of the site to try to engage them further.  Use it as an internal benchmark and improve on it.

You can then measure path length.  How many go on to do other things?  Where do they go when from this page?  Do they leave the site?  Was this an expected exit point?

So, definitely a tricky one to answer.

So, there’s lots of metrics and lots of terminology. Understanding the meaning is the first step to understanding what’s important.

This post is for those of you who want a quick primer into what’s important and what’s not. It doesn’t however talk about the “why” – that’s for a future post.

Forget about these…

1. Hits
   Hits were all the rage in the 90′s. “100,000 hits yesterday!” was often heard. Wow. Problem is, a ‘hit’ counts any hit to the web server, like images, not just pages. So, pages with images received more ‘hits’… so it was a pretty inaccurate/unfair metric… and a better metric to measure web popularity came along; the ‘pageview’ metric.
   
2. Web Counters
   Remember those? Again from a bygone age. No-one ever mentioned what time period the number was for, let alone what it actually measured. And those that did have them often got upset when the number stayed really really low…to the point where they would artificially inflate their own numbers.

Of limited value…

1. Browser Types
   Pretty much only good for knowing which browsers our users are using. But, today, every site should be made to render properly in multiple browsers.
2. Platform Types
   Likewise with the browser types, however, many providers now separate this out to mobile platforms, and as mobile platforms become more ubiquitous, we keep an eye on this. However, it’s important to see what content the mobile users are viewing and ensure it’s readily available to those platforms.
3. Resolution
   Again, good for understanding how to design the site with minimum widths in place. Note however, there’s a difference between screen resolution and browser size – two different values, two different results.

Basic, fundamental metrics…

1. Page Views
   This tells you the amount of views our site pages are getting – in particular, this allows us to see how the site fares over time. A view counts as a loading of a page. Still considered a very important metric, but the increasing amount of flash/AJAX built websites, and the increase in online video, means fewer page views are counted, even though the same amount of content is being looked at. Therefore, we need to consider our ability to track AJAX built sites, and Flash driven interactions. Any metrics platform worth it’s salt will be able to track this through custom tagging (which Omniture, of course, does).
2. Visits
   A ‘visit’ is the equivalent of when someone arrives at our site and starts looking at pages. A visit can consist of many pageviews, or just one. The industry standard is to expire the visit after 30 minutes of inactivity, or 12 hours of constant activity.
3. Unique Visitors
   A unique visitor counts the number of distinct people (well, really computers) that are visiting (making visits) our site in a particular time period. A unique visitor can make up many visits, each containing many pageviews. This is still one of the best metrics to use for site popularity. Bear in mind though that it’s important to understand the timeframe as well. Daily, weekly and monthly unique visitor metrics vary because of the reporting period.
4. Referrers
   This is a great metric – it tells us all the sites that people are finding our site and visiting from. If we don’t know where people are coming from, then we don’t know how our marketing efforts are doing, and where to spend additional money. There will also be Direct/Type In’s in this report, which provide a good indication of how many people start directly at our site (or from a bookmark). We seemingly get a huge amount of traffic from Google Organic search (which incidentally also has the best conversion rate – see below), but, read on…

   This is one to be slightly wary of as well… As this metric shows where a visitor originated from on the first visit, future visits can also be attributed to this original site. The wary part is that sites like Google write a cookie that hangs around for a really long time (6 months, versus the standard 1 month for media sites) and so if the first visit comes from Google, then two additional visits as direct type in’s, the referring domain will always show as Google (3 visits, whereas it should be 1 from Google and 2 Direct).

5. Search Engines
   This metric is a more detailed version of ‘referrers’ and tells us which search engines people are visiting our site from.
6. Keywords
   Hugely important metric. As it sounds, this metric tells us the top keywords that people are typing in at search engines and ultimately clicking through to our site. It’s basically an even more valuable, in-depth version of the ‘top search engines’ metric.
7. Geo
   Where are they coming from? Particularly useful for marketing overseas. You’d be surprised at how the content visited differs from country to country, and even regions within a country.

Spend more time looking at the following…

1. Average Time Spent
   This metric indicates the amount of time a visitor spends on our site and pages. It’s usually a good indicator of the quality of our website. The longer the time spent, usually, the better. However, a long number can be an indicator of a bad website experience and that people can’t find what they are looking for. It’s best to combine it with the bounce rate and exit pages (see below) to get a more accurate picture of the quality of site content. Also, the average time spent doesn’t take into account the last page seen (it has no way of knowing when the visitor closed their browser or walked away), so typically blog home pages suffer from this.
2. Entrance Pages
   All too often people just analyse and improve the homepage, because they think that’s where the majority of their traffic arrives from. However, the reality is that many people will arrive deep into the site through search engines. Looking at this metric reveals which of our pages are most often used as entrance pages. We look to improve these pages and make sure it’s easy for visitors to navigate from these pages – otherwise these entrance pages will become exit pages.
3. Exit Pages
   This metric indicates the amount of ‘exits’ from pages on our site. Therefore, it reveals the pages that drive people away. But remember, some exit pages are more natural exit pages, like purchase confirmation or ask for information signup confirmation pages. We look for the highest exited pages that seem to be an important path in our site flow (user journey), like course pages or information pages, and improve these.
4. Bounce Rate
   This is one of the most under-used, but most revealing metrics. To put it simply, it indicates the amount of people that, upon arriving at our site, immediately leave. Therefore, it’s a great indicator of the quality of our site. Bounce Rate is the percentage of single-page visits from entrance page visits for individual pages. A bounce rate below 40% for pages is considered good.
   
   While single-page visits / entrance pages is good, we also use page views / number of times this was an exit page…a slightly different view. This shows overall how much traffic left from this page.
5. Internal Search Keywords
   This is definitely a key metric and one of the most revealing and a subject of a future post. By looking at the keywords people use to search internally, it shows exactly what people are wanting/expecting to see on the site.
6. Multi Page Rate
   This is an interesting metric, used in combination with the Entry and Exit metrics. Basically, this one shows how well a page view contributes to a multi-page visit. Key pages should have a high multi-page rate percentage, as should key entry pages.
7. Repeat Visitor Rate
   This is another great metric to use, and is a great indicator of the quality of the site. Simply put, the more visitors return, the better the site is likely to be. The higher the percent of repeat visits versus first time visits is another great indicator to use for site quality.

The Holy Grail, well, definitely the most important…

1. Conversion
   Knowing the conversion rate is one of the most powerful things to know and act on. And not just conversion for the site as a whole but conversion rate by page or set of pages. Conversion doesn’t automatically mean that you have to be selling something. While it is the most common definition for conversion, it can also be a very powerful metric to highlight how user progress through content (pathing is similar but not quite the same). Ideally have a funnel for each conversion to understand where people are leaving before they convert – a prime candidate to analyze conversion rate and funnel is pages within an checkout form – traditional retail stuff.  However, any multi-page process will produce a funnel. Another important view is to look at conversion rates by referrers, which gives a good indicator of the value of various sources.We correlate conversions by country, by campaign, by promotion, by traffic source, by keyword (paid and organic), by path etc, which gives excellent insight and allows us to constantly look at ways to improve the conversion rates.
2. Value
   What is value? Value is many different things for many different reasons. Value might be an estimation of the value of a visitor, of a lead, of an application, of a purchase, of a request for information. You often hear that a company has lost millions of dollars when their site goes down. This is because they know on average how many orders might be placed and the dollar value of the orders…therefore they can calculate value.

   We also calculate value; the average value of a lead. Leads are a primary KPI on our site. Leads submit applications. Applications drive revenue. By reverse calculating through the funnel, we can calculate the value of a lead. Hence, the importance of leads. And hence the importance of understanding conversions.

In a future post I’ll explain why just looking at the numbers really doesn’t accomplish much. The value is in the strategy. Metrics are used to measure business goals and user goals – therefore, understanding both business goals and user goals is critical, as it helps to shape the information tracked, which ensures that you get the best value from the metrics provided, and ultimately the best insight and ROI.