Here’s another really simple customisation that you can and should do as part of your basic implementation, which helps you to further understand attribution.

Attribution is probably one of the hardest and most contested measurements available…which “thing” led your customer to do something.

Campaign Stacking

In SiteCatalyst, that’s called Stacking.  And there’s really no end to things you can “stack”.

Stacking essentially means that you store different values in the order that they occurred – and you can do it across multiple visits as well.  So, for example, if you’re stacking campaign codes, you’ll see in your reports:

campaign1> campaign2 > campaign3 > etc

From there, you can tie the success event, such as Lead, or Purchase, to the individual variations and have some visibility around how many times they interact with different elements before they convert.

Granted, it doesn’t generate the cleanest of reports, but there is insight to be gained from it.

At Murdoch Uni, we’ve done that for a number of different views:

1. Campaigns (the obvious one)
2. Internal Campaigns (the second obvious one)
3. Courses viewed (see the order of courses viewed before a conversion)
4. Lead Type (as we have multiple ways to generate leads, we want to know which tools they go through)

An example of campaign stacking report, broken down (due to full sub-relations being enabled on the eVar) is:

The above report has been filtered on “>” to only show those that have interacted with more than one campaign.

If you’re an avid reader of my blog, you’ll remember an earlier post of “People who liked this, also liked”, where I showed how to achieve the same for product views.

The above shows the unique ID of the course (or product), the number of times we saw that same sequence, the number of leads and apps generated from that sequence.  As I indicated in the previous post – our users don’t exhibit the behaviour of viewing multiple courses…

If we look at which tools (aka forms or flash devices) they interact with and become a lead through (as they can do it through multiple tools, we see the following:

Mmm, well, not a lot of data in this one as we’ve only just turned this one on – but you get the idea.

Getting smarter…

Another way that you could do it fairly easily, with a bit more custom code, is to stack not only campaign codes, but the referring domain, typein, paid search, organic search, etc instead of just leaving it at known campaign codes. 

And so, to the nitty gritty

You use the plugin s.crossVisitParticipation.

The following is an example for traditional campaign code stacking:

/* Campaign Stacking */
s.eVar36=s.crossVisitParticipation(s.campaign,'s_evar36','90','10','>','');

The values in the plugin are as follows:

1^st = value to pass into the stack.

2^nd = Name of the cookie to set that stores the stack

3^rd = Days the cookie will last for

4^th = Number of things to store in the stack

5^th = Delimiter in stack

Can’t for the life of me remember what the final element is though (but whatever it is, we don’t use it).

You’ll also need an eVar to put it into, which you should add in via your Admin – enable full sub-relations if you can.

As with all of these, you should contact Client Care or Consulting to make sure you can get the plugin and that you implement it correctly.

Final thoughts

If you’ve got Test and Target too, you’re laughing!

You can target for re-engagement if they’ve met certain criteria (or haven’t met a certain criteria).  So, if someone’s got campaign code 1 and campaign code 2, but hasn’t converted, show them a different offer.

Discover also allows you to further gain insights by analysing results and traffic against this eVar.

That’s it really.  Happy stacking.

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.

You’re optimizing content to drive relevance for your visitors. So why don’t you optimize your menus in SiteCatalyst for your users too? Make them more relevant – you’ll be thanked for it.

One of the lesser used capabilities in SiteCatalyst is the Custom Menu. They make reports easier to find for your users.  Makes sense and only takes two minutes.

Out of the box, the menu structure is designed to accommodate most reports, but they can’t take into account the subtleties of your reports.

For example, if you’re measuring blogs, there’s no mention of Posts or Authors, Tags or Categories.

Creating custom menus

Custom menus allow you to rename, move, hide or delete items from the menu.  In the admin, select the report suite you want to modify, then click on Edit Settings > General > Customize Menus.  From there you can modify your menu structure.

Some ideas

If you’re measuring Twitter, you might consider having items in your menu such as Tweets, Keywords, Authors etc.

If, like us, you don’t really have “products” in the true sense of products, but you’re using the s.products variable to measure things, rename it to something else. We renamed ours to Courses.

You can also create a series of custom reports and move them into the main menu structure, hiding other items in the process.

By default, there’s also a number of reports that you may not ever use. Just hide them. There still there, and you can un-hide them in the future if you need to, but it cleans up the menu.

One final thought

Don’t forget to tell your users that you’re changing the menu structure…you don’t want to confuse them!

I recently read a great blog post about Cohort Analysis – measuring engagement over time from 52 weeks of UX and it got me thinking how to achieve this within Omniture SiteCatalyst.

As it turns out, with a bit of custom code, it’s pretty easy to do, and what an opportunity it opens up.

Cohort Analysis allows you to look at a group of people who start something at a specific time and monitor them over time to see whether their engagement increases or decreases.  Then you can also compare them with people who start the same thing at a different point in time.

It also reminded me about Survival Analysis – which is a key type of analysis that any data-driven marketer would understand.  Survival Analysis allows you to estimate the time a customer will remain a customer before they disengage. This information allows a company to introduce an appropriate loyalty offer, or incentivise the customer, just before they abandon.  I’m not sure we can do a true Survival Analysis (that would be like a little holy grail – but I’m working on it) so I’ll save that for a future post.

Why you need to do this…

So back to Cohort Analysis.  Say you run an awareness campaign and want to monitor engagement before, during and after, to see whether those that came to your site during the campaign were more or less engaged than those that came before or after the campaign, and what triggers disengagement.

To quote 52 weeks of UX “One reason why the cohort analysis is valuable is because it helps to separate growth metrics from engagement metrics.”

The example given in the UX blog is:
The people who joined our service in January make up the January cohort, the people who joined in February make up the February cohort, and so on. We then investigate how each cohort stays engaged over time, comparing the cohorts against each other to make sure that the people who joined in February are more engaged than those who joined in January, for example.

SiteCatalyst doesn’t natively allow you to do it – but that’s the beauty of being able to customise your implementation.  You can make it do it.

So, in the following example, we’re grouping new visitors by the week (or month) that they became new visitors, and then watching them, compared to other groups, over time.  We can now measure these different groups of people on things like page views, time on site, number of interactions, leads, etc, which allows us to better understand the impact of our marketing, or even the changes we make to our site, without being impacted by traffic growth.

So what do you see…

Once you’ve got it all set up and reporting, you can trend engagement over time.  I think the trended engagement over time is the best use of these metrics rather than the ranking.

For example, the following shows (will show) the trended report for New Visitors Week traffic prop, with Average Time on Site as the measure.

Given that I was over-excited by this prospect, and couldn’t contain myself any more, there’s virtually no data in this (sorry, I’ll update this as we get more)…but…

The above shows average time spent on the site for visitors who started with us in week 44 was around 2 minutes. Week 45 starters spend about 7 minutes.

If we trend that over time, we’ll be able to see whether their engagement is increasing or decreasing over time.  Next week, running the same report will again show the Week 45 group against the Week 44 group against the new group Week 46, as they’ll all have activity as we progress forward in time.

What you can do with this…

Look for the disengagement points or trends.  After some time has passed, you’ll start to see trends in user disengagement.  Those are the groups of people for whom engagement starts to slip.  Then you can try to re-engage them with an offer or something.

You could also use this to monitor and react to conversion rates for different groups over time.  You might see that conversion rates increase over time, as they become more familiar with your brand.  You can use that in your next marketing campaign – you’ll know when to beginning serving content that will aid them to convert better, if for example, during the earlier visits they are “just browsing”.

Now it gets interesting…

Let’s assume you’ve noticed that there’s a significant change in engagement (or conversion) just before week 5 for many visitors – across all cohorts.

Use Test and Target to pick up the value of the month they started against the current month and give them a timely offer.  Try to re-engage them.  Test and Target, coupled with this SiteCatalyst data, can “see” the same profile information for each user and can use that to target them.

So many possibilities – just go out and explore them.  Unleash the elephant!

So, now to the nitty gritty, techno mumbo jumbo of it all…

In our implementation, we’re using 2 s.props and 2 eVars.  One to track the New Visitor Month value, and the other to track the New Visitor Week value.  And now that we have lots of new s.props and eVars courtesy of Omniture we’re happy to use them.

We use Month as a long term indicator and obviously, Week as a bit of a shorter term indicator.

We assign every visitor a Month value and a Week value.  If they don’t have a value (most likely because they are a new visitor), they get the current Month and Week value, which they keep with them in their cookiejar, presenting it back to us each time, so that we can then apply measures against those specific values.

We’ll treat everyone without a cookie as a new visitor.  That way, everyone gets a cookie (ok, for the first little while, your new visitors may not technically be new visitors due to when you implement the code) but as we want to populate a cookie with the value of the current month (or week, depending how you want track it), that’s probably the best way to do it.

So, using the getAndPersistValue plugin you can set those two values into two s.props, and then set eVars from the s.props.  In SiteCatalyst Admin just create your s.props and eVars like you normally would – we’ve named ours New Visitor Month and New Visitor Week.  You’ll also want to turn on Pathing across the props and if you can, set Full Sub Relations on the eVars.

The getAndPersistValue plug-in obtains a value of your choosing and causes it to be populated into a SiteCatalyst variable for a determined period of time.

We’ve used the following code to figure out the current month and we’ve used s.prop34 and eVar44 for our New Visitor Month values:

//Set the NewVisitorMonth
s.prop34=s.getAndPersistValue(s.eVar44,'s_prop34',365);
if(!s.prop34&&!s.eVar44);
{
var thisdate=new Date();
var thismonth=new Array(12);
thismonth[0]="January";
thismonth[1]="February";
thismonth[2]="March";
thismonth[3]="April";
thismonth[4]="May";
thismonth[5]="June";
thismonth[6]="July";
thismonth[7]="August";
thismonth[8]="September";
thismonth[9]="October";
thismonth[10]="November";
thismonth[11]="December";
s.prop34 = thismonth[thisdate.getMonth()]
s.eVar44=s.prop34;
}

//Set persisting prop34 to value of the eVar44.
s.prop34=s.getAndPersistValue(s.eVar44,'s_prop34',365);

So what we get in the reports are the names of the months and any measures we can apply against them.

If, like us, you’re wanting to do it by week as well, you can use the following code – we’ve used s.prop35 and eVar45 for New Visitor Week.  This code is a little trickier as there’s not a nice easy way to get the value of the current week…but some rummaging around via Google led me to this code:

//Set the NewVisitorWeek
s.prop35=s.getAndPersistValue(s.eVar45,'s_prop35',365);
if(!s.prop35&&!s.eVar45);
{
Date.prototype.getWeek = function() {
var onejan = new Date(this.getFullYear(),0,1);
return Math.ceil((((this - onejan) / 86400000) + onejan.getDay()+1)/7);
}
var thisdate = new Date();
s.prop35 = thisdate.getWeek();
s.eVar45 = s.prop35
}

//Set persisting prop35 to value of the eVar45.
s.prop35=s.getAndPersistValue(s.eVar45,'s_prop35',365);

So the code basically says if s.prop34 (or 35) doesn’t exist already and neither does eVar44 (or 45), then go figure out what month it is (or week) and set the s.prop to the correct value, then set the eVar to the value in the s.prop, then persist the s.prop for 365 days (yeah – good luck with that cookie sticking around).  Still with me?

One of the problems of the above code (which could probably be better I know), is that it relies on the users computer to have the correct date set – and it’s amazing that some people don’t appear to have that !!!

Note that s.getAndPersistValue has three arguments:

1. Currently populated variable or value to persist (s.eVar44 and eVar45 above).
2. Cookie name; used to store the value (s_prop34 and s_prop35 above).
3. Period of time for persistence, in days (“365″ above would cause the value to be populated into the selected variable on every page view made by the given user for the next 365 days). If omitted, defaults to session which will totally negate what you’re trying to achieve.

The reason that you need to use both an s.prop and an eVar is that in SiteCatalyst, you can then see Time Spend, Page Views, Visits, Visitors and Calculated metrics against the traffic reports, and all your success events, leads, sales etc, participation measures and so forth, against your conversion reports.  Just remember with your full sub relations, if you want to break down one against the other, you need full subs against both eVars you wish to see.

That’s about it really.  Pretty insightful and a little bit fancy.

Just a quick post…finished presenting at the Perth Think Tank (#perththinktank), talking about the value of measurement and measuring user engagement.  Around 220 people were there, including the Lord Mayor of Perth!  I’m honoured.

Many thanks for all the kind comments from everyone afterwards and the encouraging tweets during!

120 slides delivered in just over 7 minutes…

I’ve uploaded the presentation to SlideShare, and I’ve put it below too.