Thoughts From The Cake Scraps

Conversion, however that is defined for a site, is always the reason the site exists.  For me, a conversion is a visitor viewing at least 2 pages.  If I can do that then I know that I have engaged the person enough to look around the site a bit more.  You probably have some other definition of a successful conversion on your site.

A fairly common conversion point for a website is account creation or e-mail capture (e-mail sign-up).  The most common way to look at how successful the sign-up process is is by using a fallout report.  A nice funnel that shows how many you started with and how many fell out at each step.  The bottom of the funnel is the total number of people that made it through the process.  This is a great way to look at things but there are two very different ways of doing it.

The first way is based on pages viewed.  This is a very common way to look at fallout.  People that made it from Page A to Page B to Page C.  This works nicely in a very straightforward way.  It gives you a nice view of the total performance of that site path.  Unfortunately, at least in some WA tools, that is about all you can get at with the basic reporting capabilities.  The problem with this is that you might be missing some huge cake scraps, or golden nuggets, of information by looking at the data in aggregate.

Setting a success event on each of these pages will provide a much greater degree of flexibility.  For instance you could very easily look at campaign tracking codes and see how many of each event was set for each tracking code.  This might give you information that you simply didn’t have before.

Say, for example, that you had both display advertising and paid search campaigns pushing traffic to your site.  In all likelihood you know what the conversion is off of each of these tracking codes but you might not know how many of your email sign-ups are coming from each campaign.   It is very easy to start setting a success event on the sign-up confirmed page so that now you can get a count of that event by campaign tracking code.  Perhaps you find out that your paid search converts better but they don’t come and sign up for email.  This might cause you to change the messaging that you are doing in paid search (perhaps message email strong to drive sign-ups or message something else since e-mail sign-up just didn’t work).

Similarly, if you had a 2-step process, and set a success event on each page, you would be able to see if one type of campaign had huge sign-up issues.  Perhaps you would learn that you want to create a different on-site expirence for that type of campaign to drive up sign-ups.

Another thing that is great about using events is that they are easy to trend across time whereas fallout reports based on page views can be a bit more difficult or time consuming to generate.  The downside is that you probably have a limited number of events, so use them wisely.

What type of conversion goal do you have for your website?

This has been a Thought From The Cake Scraps.

I have not had a post on some basic elements of Web Analytics in quite some time.  Previously I have talked about how a person is tracked on a web site both with internal campaigns and e-mails.  I think that stuff is great to know for anybody surfing the internet.  It gives you an idea of what all that stuff in the URL is.  Check it out if you haven’t.

Once question that comes up quite a bit centers around what a report or analysis means when it talks about Revenue Participation or Order Participation or other ‘Participation’ branded metrics.  The first thing you need to know is that it is not the same thing as non-participation branded terms (i.e. revenue <> revenue participation).  The second is that participation metrics are related to single pages within a website.

Simply put, when a metric has “participation” attached to it, the metric changes from being a distributed metric to a non-distributed metric.

Lets just concentrate on revenue, but know that the example is not specific to revenue.

Lets assume that I came to a site and purchased $100 worth of stuff.  Let us also assume that I saw 20 pages in that time, including checkout pages.  When an analyst is looking at reoprts on a page basis there are 2 ways to look at that $100 I spent.

The first way is to attribute (or distribute – however you want to think about it) that $100 across all 20 pages.  This means that each page gets $4 worth of demand.  This would include any page that I viewed, including the checkout pages.  This is nice because no matter how many pages I am looking at I am not double counting revenue.  It makes it simple.  You can just add up whatever pages you are interested in and you have your revenue number.

The second way is participation.  this would give each page that I saw $100 worth of revenue attributed to it.  You probaly don’t need me to tell you – but I will anyway – you cannot add up multiple pages with this method.  If you did that for my hypothetical purchase you would get $2,000 worth of revenue participation.

It seems a bit odd, but there are definite uses for each way of looking at revenue.  The first way – distributed – seems logical at first, but then you are giving revenue away from an index or homepage and giving it to a checkout page.  There is not $4 worth of demand on each checkout page.  With participation, each page gets full credit, but then you cannot add up multiple pages.  Each has its place.

I hope that that clears up the difference between participation metrics and non-participation metrics, at least as far as it relates to those metrics from a page within a website standpoint.

Do you have a preference between these metrics?

This has been a Thought From The Cake Scraps.

More often than not if you are somewhere you know how you got there.  Hopefully you don’t have too many weeknights (weekends I will exclude) where you just wake up and have no idea how you got to where you are.  You may be smart enough to know how you arrived at a particular location, but your website – at least by default – is not.

This post covers the principle of having a Product Page Finding Method (PPFM) tag on your site.  If your site was successful in getting a visitor to a product page, you should really know how they got there.  And if you are a visitor you should know that this is one more way you are being tracked.  For more information on being tracked check out my posts on Internal Campaigns and E-Mail tracking.  I will point out now that this post is less about describing to a visitor how they are being tracked and more about how a website should track the visitor.  This is because a PPFM tag is less common and may not apply to many sites a visitor may go to.  Nevertheless, it is still something to keep an eye out for.

Back to tracking how a visitor got to a product page.  The easy solution is a ‘Next Page’ or ‘Previous Page’ report.  This will tell you what pages a visitor was going to or coming from, respectively.  It may seem like the answer to our question of how the visitor arrived at a product page, and it does at a simplistic level, but is of no use for aggregating data.  Consider an index page that lists all of a companies laptops.  How often does a customer click through to an individual laptop (a product page)?  There is no easy answer to this if you have more than a few laptops displayed.  A PPFM tag will solve this problem.

If you add a PPFM – that’s Product Page Finding Method – tag to each link on the index page then when the visitor clicks through to a product page you can tell Omniture to look for PPFM=INDEX_Laptops01 and it will store it to an e.var ( a commerce variable).   Then you can run a report in Omniture and look for instances of INDEX_Laptops01.  Compare that to the Page Views for your laptop index page and you have the rate at which a person is clicking form that index page to a product page.

Another trick is to make sure that all of your index pages are tagged and have INDEX in the PPFM tag.  That way you can actually do a search to pull back all instances of an index page click on any index page.  With any luck you have your pages named in a similar fashion – so you can get total index page views – and you can then get a site-wide rate that people are clicking though to your products from your index pages.

Now that we understand the concept of a PPFM, lets look at a few other uses for it.

Basically, you should not have an instance where a customer navigated to a product page and you do not know how they got there.  Other ways they could get to that product page include a ‘direct to product page’ search and a cross-sell placement from another product page.

The ‘direct to product page’ is useful if you have a search box that will allow a customer to go directly to a product page without going through an index page.  An additional way to tag this would be to have a search results tag – for instances when a search returns many products – and then any click from that index/search page to a product page would give credit to the search tag.

The cross-sell tag would be used on any product page where you are displaying some other products the customer might also like to buy.  Any click on these links will bring the customer to another product page and then the cross-sell tag would get credit.  You might also have a similar tag for items displayed in the cart.

The last thing to discuss is credit.  On a $100 order who gets the credit.  The simple way to do it is the last used tag.  The bad part is that with this method if a customer uses and index for the first 3 items and the last item they clicked a cross-sell item, the cross-sell tag will get all of the $100 attributed to it.  That isn’t really accurate.  The better way is to distribute the $100 via linear attribution.  That means that in the example above each of the index pages would get $25 and the cross-sell would get $25.  The tricky part here is that if a customer is browsing they may click to 10 different products from 10 different index pages and each of the index pages would get 1/10 a share of the revenue even though the customer only bought from one of the index pages.  Just something to keep in mind.

With this tagging in place on your site you should always be able to answer how a customer arrived at your products.  It does not quite answer the question on a page by page basis – i.e. for Product A the PPFM tags used to arrive there were cross-sell 24%, indes 53% etc. – but it will give you a much better idea, on the whole, how your visitor is getting to your product pages.  Just a little tip that can save a ton of work

This has been some Thoughts From The Cake Scraps.

Most people probably already know that they are being tracked.  There are all sorts of programs and ways to do this at all sorts of levels.  For instance your ISP may track you and give (sell) your data to a company like Hitwise – privacy policy can be found here.  I actually saw this in a newscast last week.   They interviewed some guy about what popular search terms are and tried to make it sound creepy.  Amazing! People search for weird stuff on the internet like “how to make bombs” and *gasp* “porn”.  This guy must be some sort of genius!  And he looks at historical data! Brilliant!

Hopefully you know that Google keeps track of everything you have searched for.  Ever.  Anyway, the part that people probably don’t know as much about is how individual sites track you.  One way a site can track you is by tagging you when you click through on an e-mail they send you – the focus of this post.  Think of tags as dated stamps in your passport book.  Interestingly enough, some of this tagging can be easily found in the address bar of your browser.

When you see something in the address bar that looks like emid=584783 that is telling the website that your internal – meaning site specific- e-mail address ID is 584783.  This value is unique to a single e-mail address. Each e-mail sent to that e-mail address will have their unique emid attached to all links in the e-mail. This also allows a site to build a history of that e-mail address – not only for activity, but for response rate as well.  Now every time you click through an e-mail for that site they have more history.  Note that larger sites rarely look at individual behavior but instead classify a behavior and then analyze that group.  Still, the information is there.

In addition to an e-mail ID, there is usually a campaign variable such as cid=Sep08FreeShipping.  This allows the site to report on everything with Sep08FreeShipping stored in the cid variable. All of this information is contained within the link that you click from the e-mail. If you get the e-mail and directly load their site, not through the e-mail, the activity will not be tracked because in a direct load no value would have been assigned to cid.

These variables do not have to remain in the web address the entire time.  They are stored in the background after the initial click. So when you no longer see emid or cid in the address bar, but originally arrived at the site through the e-mail, you and your activity is still being tracked.

Look for at least one more installment of how you are tracked. There I will focus more on how a site tracks internal campaigns. Hope this helped give some people a better understanding of how websites track you.

I get all sorts of spam in my e-mail about making things bigger, but none of them are for the one thing I really want bigger: the interface for Omniture Excel Client.

It took me some time to get used to the Excel Client that Omniture offers.  Mostly it was because I was not sure what reports I needed or how I wanted the data.  That makes looking for an easy way to get the data difficult.  After a few weeks working with Omniture I was comfortable enough to begin using Omniture Excel Client (OEC) on a regular basis.  Life is filled with peaks and valleys from there on out.

Because the interface is connecting to Omniture it is inherently slow to do pretty much anything.  Now it is not horrible (most of the time) but when working in Excel changes are instant – think changing the font – and working in this slower interface takes some getting used to.  I will dedicate some future post to the issues and gleeful moments I have with the OEC but for now lets get back to the size issue.

OEC does not allow you to re-size the interface that you are working in.  So, for instance, if I am using the “Pages” or “Most Popular Pages” report and I see a list of page names, part of the names get cut off.  There is no side scrolling option to be found.  You just have to sit there and wonder what the full page name really is.  I will point out that this may not be an issue for lots of people, but if your site is large enough page names can get pretty long.  Also, I am a fan of descriptive page names so that when you see just the page name it is informative.  Names such as “Brand” “Item” “Size” or “Gender” “Size” “Shirt Type” are much better than a product number for page names.

So the real question here is why is the interface of OEC set up this way?  Did they not do QA testing on this?  I don’t have the answers.  All I know is that adding a side scrolling bar – not my favorite option but better than nothing – cannot be all that difficult to add into the interface.  Never mind that this issue persists in the newest version of OEC. Long page names are a reality and while you can use the search or advanced search to narrow your results it is a pain to have to do. Plus, OEC doesn’t save your advanced search so if you get results and need to edit it – such as exclude an additional word or phrase – be prepared to re-enter the entire search. Lots of NOT fun here too.

I am not sure what it will take for Omniture to fix this.  Apparently they have not got the notice that size matters.