In today’s day and age, blog platforms are becoming more popular in the corporate online presence.  Many employees blog professionally about their area of expertise, and many corporations run blogs beyond their official website.  Blog platforms can be used in a variety of ways – beyond the traditional blogging.  Many of us use the blog platform to house our News or Media sites and Event sites, and so forth.

But how do you measure them?

Well, you could measure them in just the normal way – looking at the page name and counting page views and so forth.  However, if you just measure page views in the traditional sense, you’re missing out on some key insights.

Blogging at the corporate level typically involves multiple authors.  And categories.  And tags.  And search terms. And posts.  And it’s in this information that you’ll gain insight…

Some key measures

Generally, you’re looking for user engagement and popularity.

A measure of popularity:

1. Unique visitors
2. RSS subscriptions and click throughs
3. Email notification signups (and then all of your traditional email metrics)
4. Comments on the blog – who is interacting with your content
5. Most popular blog topics, posts and authors

A measure of engagement

1. New vs. repeat visitors, especially around topics or authors
2. Time on site and page, and time reading posts by authors
3. Number of post views per visit – is this increasing?
4. Bounce – is your last post the only post they read, or do they go on to other posts?
5. Scrolling – blog posts tend to be long – does your audience get through it all?

An insight into influence:

1. Trackbacks and external links to your blog
2. Best time and day to update your blog
3. Conversions (Leads or sales)

While there’s typically no direct influence on conversions, one of the things you should be watching for is “does your blog drive traffic deeper into your site, or get them to convert on other things – such as becoming a lead, or purchasing a product”.  This is a long term measure.

Measuring blogs in SiteCatalyst is easy…just a few more eVars and events are used.

You’ll want to set eVars for the following:

1. Author – the name of the author when a Post is viewed
2. Post Name – the name of the Post
3. Category – the name of the category viewed (but not when a Post is viewed)
4. Tag – the name of the tag viewed (but not when a Post is viewed)
5. Search Term (possibly) – the search term used

Then you’ll want to set events each time something happens…the main ones we use are:

1. Author Views – When an Author’s bio is viewed, set the event
2. Category Views – When a Category Page is viewed, set the event
3. Tag Views – When a Tag Page is viewed, set the event
4. Post Views – When a Post is viewed, set the event

If you specifically measure Authors, Categories and Tags (topics) and Post Views, you can get the insights that you’re looking for.  You’ll be able to see who is your most popular author, which topics drive the most views, which posts lead to more engagement at a deeper level and so forth.

Ok, now for some boring tech stuff…below is a snapshot of our s_code that we use to set the eVars and events.  Don’t forget to set s.props as well. I haven’t gone into the full code, because it varies quite substantially from traditional measurement (and that would take way too long).  But the main thing is eVars and events.

if(s.pageName.indexOf("author") != -1){
s.events="event40"; // Author Event View
}
if(s.pageName.indexOf("category") != -1){
s.eVar42=s.thecategory;
s.events="event42"; // Category Event View
}
if(s.pageName.indexOf("tag") != -1){
s.eVar43 = s.thetag;
s.events="event43"; // Tag Event View
}

/* Set Author, Post Title and Post Read event */
if((s.post) && (s.post == 'true')){
s.eVar40 = s.theauthor;
s.eVar44 = s.thepostname;
s.events = "event44"; // Post Read Event View
}

In our blog templates we set s.theauthor, s.thecategory, s.thetag and s.thepostname on various pages (posts, tag pages, category pages and author pages).  We also set s.post to true on Post pages only.  Then in our s_code, we just pass those values into the correct eVars, setting events along the way too.  You’ll probably also want to enable Full Subrelations on Authors as well.

Now we’re able to see all of our key measures in SiteCatalyst – as well as all of our traditional things that we measure, such as Page Velocity, but from the perspective of the Author, the Post, the Category and so forth.

For RSS subscriptions, we use an onClick event on the RSS button links, and we use a campaign code on the RSS link back to the blog, which tells us click throughs from the RSS feeds.

We use pathing to understand cross-pollination of posts.

As we report this into both a separate report suite, and our global suite (dual reporting), we’re able to see traffic moving to and from the blog, back to main site, and understand if it impacts conversions.

Example of Author and Post report

In the above example, we’re looking at article popularity by author – to get some insights into which authors are getting the most views.

Below we’re looking at which categories people are clicking on to see post summaries within each category.  Seems they don’t really do it…

As always, there are learning’s we can take away from this, and use to our benefit.

Social Media Measurement and Monitoring

Of course, the flip side to all of this, is Social Media measurement (which this is not).

Twitter, Facebook, YouTube – SiteCatalyst can measure all of those – but I’ll save that for a future post.

And then there’s social media monitoring, such as ScoutLabs, BuzzMetrics, and Radian6 (which I’ve just learnt can incorporate up to 10 SiteCatalyst variables into the Radian6 reports, which would be very interesting to see).  However, again, I’ll save Social Media Monitoring for another day.

Some parting thoughts

Armed with this information, you’ll know who your popular authors are and what types of posts people keep coming back to read i.e. popular content for different segments.

You’ll also be able to promote this content elsewhere across your site to drive further awareness about it – and hence increase its readership and hopefully engagement.

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It often strikes me as strange that people still look at numbers in the aggregate.  Knowing that you get a certain amount of page views, or a certain amount of visitors and so forth, doesn’t really tell you anything.

In order to get some insights of value, things that you can really act on, you need to segment your traffic and conversions.

But so few people really do it, and even fewer do it really well.  And doing it really well can help you in so many different ways, from optimising your site, to optimising your marketing spend.

People are different; they do things differently.  They interact with your site differently.  Broadly speaking, online, people fall into segments, and segmentation can help you to understand those differences and give you a way to identify those people in the future, so that you can hopefully optimise the experience for them – whether it be through more relevant content, landing page optimisation, or keyword reinforcement etc.

The segmentation challenge

Part of the challenge in segmenting is that you don’t really know what you’re looking for, until you’ve found it.  And “it” is something that’s interesting.  Interesting enough that you can do something with it.  Interesting enough that it stands out from the crowd.

The problem with report based segmentation is that you create a segment (might be something along the lines of traffic from organic search) and you then have to wade your way through the static reports to figure out if there’s anything interesting in them.  In most cases, you will fail to find anything interesting, or usable, because your segment (organic search) is still too broad.

Segmentation is an ad-hoc activity

In reality, finding interesting segments is really an ad-hoc thing.  Interesting things tend to be found through trial and error; and report-based segmentation doesn’t make it easy at all, as you typically can’t dive into data and look at things from different angles.

One of the key tools in the Adobe suite of products that we, at Murdoch Uni use, is Omniture Discover (or more correctly Adobe Discover – powered by Omniture).  From it’s name, you should get that you can “discover” things, through ad-hoc segmentation.  Ad-hoc being segmentation on-the-fly.  Don’t see anything interesting?  Try something else.  Then, when you’ve found something interesting, you can save the segment that meets that same criteria and apply it to your reports in SiteCatalyst, so that you can monitor it over time.

Basic Rules

There’s some basic rules of segmentation though:

1. Segments need to be measurable and identifiable
2. Segments need to be accessible and actionable
3. Segments need to be large enough to be profitable

If your interesting segments don’t meet all three criteria, there’s a good chance that they’re not “interesting” segments.  In other words, a good chance you can’t really do anything with/to them.

Using Discover, we can take a look at traffic to the courses section of our site and do some ad-hoc segmentation to see if anything interesting comes out.  Taking a look at traffic in the aggregate, we see the following:

Which doesn’t really tell us much…  We got 1.67 million page views in a certain time period.

So let’s segment that by Visitor Loyalty – looking at First Time Visitors, versus Repeat Visitors, to see if there’s anything there.  Using Discover, you just drag over the segment First Time Visitor and Loyal Visitor onto the workspace and you instantly get the same metrics for those two additional “pre-configured” segments.

But that still doesn’t really tell us much, other than the obvious…first time visitors look at more pages than repeat visitors, probably because repeat visitors know where the content is they are looking for and can get to them quicker than browsing around.

Now lets segment that by traffic that comes to us from Google Organic search.  We just drill down on the section Courses, and look at our campaign traffic from Google Organic Search, which then segments everything.

Still doesn’t really tell us too much – they appear to be just a subset of the overall segment, behaving in a similar manner.  So we still can’t do too much with that information.

So we’ll segment by time spent, to see if there’s anything interesting in that.  Again, we just drill down on the Google segment showing Time Spent per Visit.

Ah, now that’s interesting…

There’s a high incidence of First Time Visitors from Google who spend between 1-5 minutes on our course pages, whereas, Repeat Visitors tend to spend 30-60 minutes (excluding those that spend 10-30 minutes).

Ok, so what…

Well, we can do something with that.

For instance, we can try to engage 1st Time Visitors from Google more…try to get fewer visitors to spend 1-5 minutes, maybe through cross-promoting content,  maybe through different calls to action.

We could use Test and Target to behaviourally target content at them.  Or we could test different page layouts, or different content altogether, or we could test different promo-modules.

There’s really no end to what we might want to try to do, armed with this information and the capability (and desire) to do something about it.

Segmenting your channel spend

Another way you should be using segmentation is to look at channel effectiveness.  Using ad-hoc segmentation you can see, for example, how many people convert from different segments. 

Let’s assume that you have a Display Campaign running.  You’re running display ads across many network sites, which are all driving clicks to your site. 

You’ll of course know you’re spend (if not, you should do!).

Let’s assume that you are looking for a conversion of some type – it might be a lead, or a sale.  Doesn’t really matter in this example.

And so you’ll ultimately be able to calculate cost per lead, or cost per sale.

However, your cost per lead or cost per sale will vary substantially by different segments.  Three key things that make up that variance are:

1. Sub-segment rates
2. Sub-segment bounce rates
3. Sub-segment conversion rates

Let’s assume that in this example our sub-segments are 1st Time vs. Loyal Visitors and that we get a 60/40 split.

From a bounce standpoint, your bounce rates might be 40% vs. 20% (by sub-segment)

Now factor in that only some of those remaining visitors will decide to start to convert, but they won’t all convert.  Let’s assume that 30% of 1st Time Visitors start to convert, and 40% of loyal visitors start to convert (start to buy something, or start to sign up for something).

Then you factor in your conversion rates.  Lets assume that only 35% of 1st time visitors actually convert, versus 40% for loyal visitors.

Those segments and rates are purely an example, but are feasible given the audience segment.

The following depicts what the above calculations translate into, if you start with a million impressions, on a CPM based display campaign.

Notice the Cost Per Conversion by Segment…$66.37 versus $32.57.

That’s twice as much to get a new customer to convert than a loyal customer. 

So, what can you do…?

How about trying to reduce the bounce rate for first time visitors.  If you can drop it to 20%, you reduce your acquisition cost to $49.67 (from $66.37).  And then you can try to increase your conversion start and completion rates for that specific sub-segment, which will all help towards reducing the cost of acquisition.

Discover Discover

Segmentation in Discover is incredibly easy.  But it doesn’t do only that – it allows you to visualize your traffic and conversions as well.  If you’re just using SiteCatalyst, you really should consider getting Discover – it will, I guarantee, blow your socks off!  It will give you access to view your data in ways that you have only imagined (and wished for).  It will save you time, and probably money in the long run.  It will help you vertically through campaigns and horizontally across campaigns.  (The graphic header to this blog is actually a visualisation of traffic across our website).

Segmentation is the key to success

Segmentation will help you out in so many different ways – and there’s virtually an unlimited number of ways to segment and get valuable insights on your user behaviour.

But the really important thing though, is what you do with it all. 

Once you’ve got the insights, don’t be afraid to try to improve things.  It’s measurable, actionable, and profitable!