“I can’t find anything!”

This is the most common response we came across during the scoping and implementation of Search and Promote as the new internal search for Murdoch University.

Hardly surprising, given the issues with internal search that I covered in my previous post, but amazingly consistent!

In fact, one of the great truths we found during this project is that people truly don’t care where content is located, or whether it’s authenticated and/or accessible – they just wanted to type something in the search box, immediately find what they’re looking for, then carry on with their work.

We’ve now completed the implementation across our internal sites, and it’s working really well – so well that we’re now 2-3 weeks away from covering our external sites.

In my last post I promised to run through the implementation, however there’s a lot to talk about, so today I’ll cover SEO metatags (or the lack thereof), using multiple content sources, and how we integrated Search & Promote with SiteCatalyst to dynamically alter search result ranking.

Given the issues with internal search across campus and the wide range of staff and students that were more than happy to tell us just how bad it was, we decided to first implement Search & Promote across the internal sites where our primary audience are current staff and students.

Through the implementation of SiteCatalyst a few years back  across our network sites we have been able to segment our staff and student traffic, so we knew from the onset just how many searches each segment were doing, and how long on average they were taking.

Looking specifically at staff, approx 2,400 people collectively performed 234,131 searches in 2010, spending an average of 202 secs per search. Wow!

That equates to 13,137 hours, which, at an average of $40/hr, comes out to a $524,498 productivity cost. This figure alone should catch the attention of your key stakeholders and finance people.

Armed with that knowledge, we set the following key objective for the  Search & Promote trial across our internally facing sites;

• Reduce time staff spent searching by 10% by delivering a single set of filterable results, transparent of source, influenced by recent traffic.

Now that we had a clear objective, we could begin on the planning and implementation. We were greatly aided by a project team at Search & Promote – thanks John, Wally and Richard; you were all very helpful, and it was great working with each of you.

The first step was to set up the organic crawl of our internal sites, which largely consisted of listing the appropriate entry points;

Image: URL entry points in Search and Promote

And their corresponding URL masks (note the test feature that allows you to try your masks before saving them);

Image: URL masks in Search & Promote

Search & Promote works on a number of pages crawled – your licensing allows you to go to a certain number of pages, and after that the pages are not added to your index. There was a bit of tweaking to figure out what that level was, however there’s a cool feature in Search & Promote that allows the crawl to continue and count the number of pages that you’ve gone over by so you at least have an idea of where you are. From there you can either increase your licensed limit, or identify the larger than expected sites and par down the number of pages found by using the error logs and URL masks.

Compensating for the lack of SEO content

One of the issues I’d talked about previously was a lack of the bare minimum SEO metadata across many sites, most of which we had no direct control over. We tackled this by using the metatag injection feature in Search & Promote, which can be configured to dynamically inject metadata during a crawl, based on a URL pattern. This metadata is then included in the index as if the metadata was already embedded within each page, and can range from standard title/description metatags, to custom tags that can be use to create search filters (facets).

We soon found, however, that a significant portion of internal content required authentication to access, which meant that the crawler could not get in to that content. The Search & Promote crawler can be given credentials to access that content, however our concern was that content was authenticated for a reason, and to show even a title or extract from authenticated content on a public search may give away too much.

Given that the “we can’t find anything!” comment included authenticated content and applications, we needed an alternate option for this implementation to be successful.

At Murdoch we have a database called the A-Z index, which is maintained by our IT area, and over the past 5-6 years has grown to include an entry for most of our authenticated content and applications. This was a perfect source of information, now we needed to somehow incorporate this content into our search results.

Enter a feature in Search & Promote called ‘index connectors’.

Incorporating multiple sources of content

The index connector feature within Search & Promote allows you to define a third party xml feed, xml file, or comma/tab delineated file as an alternate source of content to be crawled.

The IT at Murdoch team were able to provide us an xml feed out of the A-Z index which allowed the Search & Promote crawler to include each entry/link within the feed in its scheduled crawls, together with custom mappings for each tag within the entries  to predefined custom metatags;

Image: Sample from our A-Z Flat XML feed

Image: Setting up the A-Z Flat XML feed as an index connector

Not only were we able to crawl the feed and include all the authenticated content as separate entries (‘restricted’ in the above screenshots), but we were able to alter the look and feel of the specific A-Z results within the wider search results, and account for a lack of  description within the feed.

The side-effect that we hadn’t counted on, but worked to our benefit, is that the A-Z index had entries for related non-Murdoch sites that were still of value to staff and students.

By having entries for the non-Murdoch sites in the A-Z as wayfinders, we didn’t need to crawl the actual sites themselves. This resulted in a significant reduction in the number of sites/pages we needed to organically crawl, while still providing our audience with a complete set of search results.

Using this same index connector functionality we were also able to incorporate the university’s campus directory listings via a new xml feed; whereas with the A-Z feed we only wanted to incorporate the results within the wider results set, we wanted results from the campus directory to always be the first results and be displayed in a table format, but more on the styling and positioning of these multiple content sources later.

Allowing for cyclical requests to ensure the most relevant results appear

In my previous post on Search & Promote, one of the key advantages the product had over its competitors was the ability to natively integrate with SiteCatalyst.

Via SiteCatalyst we already knew that our internal search terms follow highly cyclical patterns as our student (and staff) needs change over the semester. For example, the term ‘timetable’ is searched for throughout the semester, however the anticipated result changes as the semester progresses. At the beginning of semester, people are looking at for their semester timetable and towards the end their exam timetable.

In the past we’ve used custom coded mechanisms to help staff and students find what they’re looking for, however with Search & Promote we can take that to a whole new level!

Search & Promote allows you to define a data source within SiteCatalyst, in our case Global Production > Page Views, and then add ranking weight based on those values – the higher the weight, the higher the impact the SiteCatalyst data will have over your search results.

We defined s.prop41 under our Global Production suite in SiteCatalyst as SearchPromoteURL, and then used it to cross reference the Search & Promote crawled URLs with the associated Page Views data in SiteCatalyst;

Image: Using page view data from SiteCatalyst to influence ranking

Now, every day the last seven days worth of aggregated SiteCatalyst page view data is automatically downloaded and fed into the Search & Promote custom defined field SearchPromoteURL, which in turn is used in a ranking rule that increases the relevance of highly trafficked pages in the last seven days;

Image: Aggregated page view data in Search & Promote

A good example of this in action are our sample and past exam papers in our Library website, where there is a separate page per letter – with the SearchPromoteURL ranking rule disabled, the pages are literally ranked A through to Z, as the other active ranking rules see them as equally relevant. However when the SearchPromoteURL ranking rule is in place, the top ranked exam page is Exams B, followed by P and I.

In the admin data report for “exams” below you can see how the ranking, relevance and score metrics are all the same for the exam paper pages, and that the differentiating ranking  factor is delivered by the page views;

Image: Admin view of results for 'exams' and the different ranking scores that order them

The same ranking results can be seen on the front-end at http://search.murdoch.edu.au/?q=exams;

Image: Corresponding public search results for 'exams'

This is exactly what we set out to achieve, and it’s so far looking to have worked pretty well!

In part 2 of this post, I’ll cover how we combined all our sources of search results into a single set of user-centric, filterable search results, well as how we fared against our original objective of reducing time our staff spent search by 10%.

Many companies struggle putting together an effective digital measurement strategy, often due to the lack of resources and/or the lack of understanding how it can provide an effective return on the investment.

And it is an investment.  Generally you’ll incur people and training costs, licensing costs for the various platforms and other ongoing costs – some of which are internalised.

But you can demonstrate an ROI, that will far outweigh the costs incurred, if you spend the time and effort in putting a solid strategy together.

Digital media will continue to grow.
Our audiences are growing online.
It’s pervasive in our everyday lives.

A good digital measurement strategy should be the desire within any business to enable more precisely targeted and measured results of marketing investments.

But effective digital measurement is not plug-and-play, nor should it be plug-and-pray, even with the most sophisticated or automated tools.

We now have the capability to capture millions of customer interactions, across multiple platforms (mobile, web, video, audio etc) and use that data to garner insights into customer behaviours online, so that we can optimise how we communicate with them.

But to do so, significant planning and organisational coordination is necessary to manage the sheer volume of data produced, and then, to put this data to work throughout an organisation. In addition, different types of vertical industries use digital marketing in different ways to achieve different business goals. In other words, digital measurement strategies look different for different types of organisations and is rarely achieved overnight.

But the fundamentals remain the same, irrespective of the industry vertical.

The key elements

A good digital measurement strategy includes the following 6 key elements:

1. Overall measurement strategy
2. Resources and skills
3. Data integration and visualisation
4. Data analysis and insights
5. Ongoing optimisation
6. Adoption and governance

Overall Measurement Strategy

An overall measurement strategy should align to your overall business objectives.  This helps ensure all digital marketing activities contribute to your bottom line – and demonstrates the value of digital measurement to executive management.

There’s really only three things that form the foundation to the overall measurement strategy:

1. What’re your business objectives?
2. Who is your audience?
3. What does success look like?

Most marketers answer those questions when they put a marketing brief together, so answering them at a higher level (the business reason for being) and converting those to a measurement strategy shouldn’t be a challenge.  There’s a lot of measures available for different verticals, but if you start here, you’ll be well on your way to defining a strategy.

Resources and skills

People determine the success of a digital measurement strategy: the number of employees dedicated to measurement and analysis, the resources at their disposal and their ability to troubleshoot issues and respond to requests throughout your company.

Data integration and visualisation

Effective digital measurement (not just of digital marketing) often requires companies to integrate multiple sources of data to create a more complete picture of their customers and business. Data integration – the passing of key values between systems – enables companies to create a more complete picture of their digital efforts.

Then there’s visualisation, which is the presentation and delivery of digital marketing data to meet the needs of different groups throughout the business.  These come in many forms, from dashboards to campaign summary reports to alerts.  The important thing here is to make sure that your recipients understand what it is they’re looking at, and, if they’re making decisions based on the data, they are interpreting it correctly.

This is commonly one of the areas where the biggest mistakes are made – misinterpreting the data.  Ensure that you don’t just report on reports…customise them to ensure that your executives have the information that they are looking for.  They probably aren’t looking for in-depth reports…they won’t have time to analyse them (that’s your job).  They’ll likely want trends and summaries.

Data analysis and insights

Data analysis skills are essential to turn web-based data into the understanding companies need to optimise and drive smarter marketing and business decisions.

Data analysis tends to be an ad-hoc activity, usually includes segmentation and quite often requires specialised software, such as Omniture Discover.

Ongoing Optimisation

Ongoing optimisation ensures the data measurement processes that you put in place are consistently applied over time. This includes using digital measurement data to identify optimisation opportunities and test different iterations of content. Mature optimisation should span all digital marketing channels, from web sites to paid search, and include automated A/B testing of multiple marketing updates prior to implementation.

Adoption and governance

The final part is to ensure that measurement is adopted across everything you do.

Digital marketing data has little value unless rules are are in place to ensure its consistency and quality over time – and that it gets to the right people at the right time throughout your business. Training is essential to ensure people who need to use the data know how to – and can interpret it accurately.

Governance provides defined processes for managing various aspects of digital marketing programs, including implementation and change management, security, data and measurement consistency.

Who’s responsible

Companies are.  Maybe you are, if you’re reading this.

You may need (or want to have) a central group responsible for it.  They’ll be responsible for the distribution of and insights to the data, to all levels of your organisation.  They’ll also be responsible for the platform, the implementation, the ongoing change management and so forth.

Don’t expect (or even request) your digital, or traditional, agency to be responsible for this.  That’s not what they are there for.  But, frankly, they should be asking you about measurement.  They should have a vested interest in ensuring everything they do (and especially recommend) is adding value to the bottom line.  If they’re not interested in how things are performing, you should consider another agency!

Two final thoughts

Defining your overall measurement strategy comes before selecting your measurement platform.  There’s no point in paying for a measurement platform when you don’t have the strategy in place.   You’ll find it very difficult to justify the costs if you approach it that way and you’ll likely get very little out of it.

And, finally, the data should be used pervasively across the business to make business decisions at every levels of the organisation.

One of the little-used nuggets in SiteCatalyst is “participation”.

It’s a given that you want to know how many sales you’ve made, or how much revenue you’ve generated, but what about which pages have helped to contribute to that conversion.  Not every visitor follows the same path through the content, and it’s therefore beneficial to be able to see which pages are more likely to drive a conversion than others, thereby exposing your most valuable pages.

And some surprising results may surface; some pages that you thought were key pages, may not be; others that you thought weren’t, may well be contributing more to the purchase or conversion event.

Armed with this knowledge, you can further optimize your site.

Enter Participation

Basically, this little-used metric helps you to assess whether your content is participating in conversion events or not.

There are in fact two metrics that can help – linear allocation or participation (I prefer participation).

Linear allocation provides each page or variable value that contributes to the completion of a success event (e.g. revenue or cart additions) with a partial credit for the conversion. For example, if a user navigates through five pages of your site, and the visit results in a purchase, linear allocation divides the 1 purchase across each of the five pages so that each page receives credit for 0.2 of the purchase.  If conversion is enabled, then allocation for pages is also automatically enabled.

The downside to this type of allocation, in my opinion, is that you don’t necessarily see the true value.  If there are two visitors and two purchases, but one visitor sees 4 pages and the other visitor sees 2 pages, the allocation can get confusing…especially when you multiply that out by the variations of pages, visitors and the path length (number of pages they viewed).

Participation metrics, on the other hand, assign full credit to each page or variable value that contributed to the conversion. In the example above, a visitor navigates through five pages of your site, which results in a purchase. A participation metric gives credit to each page used in the purchase process. If any events have participation enabled, then the pages participating in the event also have participation enabled.

The result would be that “1″ is assigned to every page they visited (even over multiple visits).  Eventually what surfaces, is high value pages – those pages that contribute the most to a visitor purchasing something.

Looking at a real world example of this, the following shows Applications Submitted Participation metric, against each page, with Page Views and Page Bounce Rate.

In the above report, the top performing page that contributes the most to applications submitted is a page of content describing the application process.   Almost 52% of visitors who have submitted an application have gone through this page.

I’ve also created a custom metric – App Submitted Conversion Rate (Participation / Visits), which shows that nearly 6% of visits to that page result in an application being submitted.  So that, for us, is a key page.

What’s also apparent is that #8 has a relatively low participation rate (14.1%).  That page is one of the “parent” pages to the best performing page, which indicates that the path that is being followed does not take people through the parent page, otherwise, the participation would he higher.  (That makes sense to us as we drive people to the top performing page from a multitude of sources, such as course pages).

Using a pathing report, we can also validate that assumption, as we can see where they came from and where they went to on their journey for this key page.

Participation also crosses multiple visits – providing your configuration is set to ensure that cookies don’t expire on the end of the visit, so you’re then able to see how many times people return before they submit an application, or purchase something.

To some extent, the above result is expected (and desired).  Likewise for the homepage (#2).  Looking down the list, it’s a little surprising to see that the search page (#9) actually beats out some of the other pages, from a participation rate, but not an overall conversion rate.

So, it would be interesting to find out what they are searching for…

Slice and dice with Omniture Discover

Using Omniture Discover, we can dig into this data further.  Discover helps you answer the questions that you ask when you get the first answer – because the answer inevitably leads to other questions.

So, based on segment which we created on the fly called “visitors who have submitted an application” we can see what search terms they are using.  The results are shown below:

And what we see is that 25 applications were submitted from people searching for “honours” – which is interesting because honours content is not readily available on our site.

Learnings from Participation

Using Participation metrics can help determine the “value” of pages.  Pages that have low participation rates (that you think should have higher rates) are often good candidates for further optimization to assist in the conversion process.  Likewise, the same goes for pages that have low overall conversion rates (from the calculated metric).  Only you’ll know which pages they are.  Participation can be viewed as a kind of re-enforcement of the path you anticipate them to take.

By using Participation, you can determine the unbiased influence of any page on success and use it to further optimize your site.

One of the nice things about Omniture is the ability to export information out to other systems.  We use this feature to generate tag clouds on our site, based on the most popular courses viewed over the last 30 days, segmented for different audiences.

In order to do this, there are a few things that need to be done first.

Firstly, we report course views as products, passing a shortened name of the course from our content management system and database, to the s.products variable, such as:

s.products = “;Marketing-and-the-Media”;
s.events = “prodView,event5″;

We have set up event5 as a success event, signifying a course view.

As we have multiple pages associated to a course, we make sure that we only pass the s.products and s.events values once per course view, irrespective of the page within the course a user is looking at.  This is done by using some custom code within our s_code file.

In SiteCatalyst, we then use SAINT classifications to generate Course-based reports, associated to schools, faculties, type of course (undergrad or postgrad) etc.  This allows us to get in-depth information on our course activity, along with conversions etc.

Audience segmentation

A common reporting segmentation for us is to compare Australian traffic to International traffic, so we have created two segments, using the segment builder.

The Australian segment includes any visit where the GeoCountry was Australia.  The International segment includes any visit where the GeoCountry was not Australia.

Exporting the data

We then use DataWarehouse to create two reports, based on the last 30 days of activity.  Each report uses the segment defined above, with the Course name and the number of Product views (as we use the product variable to set course views).

These two reports are scheduled on a daily basis to export the data to our FTP servers as a CSV file.

Once we have the files, we import the data into a database along with the date of the file, so we can use that later.

Now we have the last 30 days of activity, by each course, by traffic source as a dataset that we can use on our site.  It’s then a fairly straightforward process to match the course name with the URL of the actual course, so it can be used as the link on the tag cloud.

The end result

Each day we query the database and using standard tag cloud calculations, we are then able to re-produce the data back out onto our site.  We currently feed the data back out as an XML file which is read by our Course Browser flash tool – showing both a Domestic and an International view of the most popular courses.

We’re also working on something similar for internal search terms, which will be used to populate a “search as you type” functionality on our search forms, but it will be segmented by audience type – Staff, Student or Anonymous (being general traffic).  That one is a little tougher, because we have to associate the most common destination clicked on, with the searched-for term.  But more on that in a later posting, once we have it working.

So, using a combination of Omniture SiteCatalyst, DataWarehouse and segmentation, we’re able to easily offer our users with quick navigation methods to various pieces of content, thereby enhancing their user journey.

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.

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.