If you’re cur­rently mea­sur­ing var­i­ous kinds of out­comes on your site (orders, leads, micro-conversions, etc.) with SiteCatalyst’s cus­tom events (or default ecom­merce met­rics), you will want to know which con­tent on your site is influ­enc­ing them (suc­cesses or fail­ures). Some con­tent may be pulling more than their fair share while other con­tent may just be get­ting in the way of con­ver­sions. The term, “con­tent”, can span every­thing from pages to site sec­tions (groups of pages) to page types (e.g., arti­cle page, cat­e­gory page, prod­uct page, etc.), etc., but for the pur­poses of this post I’m going to stick to the stan­dard HTML page when I say content.

There are three dif­fer­ent approaches you can use to deter­mine con­tent effec­tive­ness (or inef­fec­tive­ness). The right method for mea­sur­ing con­tent may depend on the type of out­come you’re mea­sur­ing as well as the dif­fi­culty of imple­ment­ing the approach for your par­tic­u­lar site. Let’s run through the three dif­fer­ent options.

1. Event Par­tic­i­pa­tion (Indirect)

First, one of the best ways to eval­u­ate con­tent per­for­mance in Site­Cat­a­lyst is to use the event par­tic­i­pa­tion approach. Event par­tic­i­pa­tion essen­tially looks at the down­stream, indi­rect influ­ence of pages on sub­se­quent con­ver­sion events hap­pen­ing dur­ing the same visit. In the exam­ple below, each page that pre­ceded the order (rep­re­sented by the shop­ping bag) receives full credit for the pur­chase. Any pages viewed after the order wouldn’t receive any credit for the purchase.

On its own, the par­tic­i­pa­tion met­ric will tell you two things: what per­cent­age of the total events the page influ­enced and how many total events the page influ­enced. While this infor­ma­tion is use­ful, it will be skewed towards high-traffic pages (e.g., home­page), pages where the event actu­ally occurs (e.g., con­fir­ma­tion page), or multi-step process pages that always pre­cede an event (e.g., billing/shipping page, lead form page, etc.).

In order to find the golden nuggets amidst the ever-growing pile of pages on your site, you will want to cre­ate a cal­cu­lated met­ric which divides the par­tic­i­pa­tion met­ric by vis­its. Now you will have the aver­age rate in which the page influ­ences a par­tic­u­lar out­come if it is seen dur­ing a visit. Cer­tain pages will always out­per­form other pages due to their pur­pose or posi­tion; how­ever, the par­tic­i­pa­tion rate puts the low-traffic and high-traffic pages on more equal footing.

In a use case exam­ple, you might have sev­eral case study pages on your site and you’re try­ing to gen­er­ate trial soft­ware down­loads. Using the cal­cu­lated met­ric (trial down­load par­tic­i­pa­tion / vis­its), you can com­pare the dif­fer­ent case study pages side-by-side to deter­mine which ones have a higher rate of influ­ence on trial down­loads. If you iden­tify clear win­ners and losers amongst the case study pages, three actions can be taken.

First, you can fea­ture high-performing case stud­ies in more promi­nent posi­tions (e.g., home­page) to give them more expo­sure, which may lead to more trial down­loads. Sec­ond, you can rework low-performing case stud­ies to improve their per­for­mance. Third, you can remove the weaker case stud­ies if they just aren’t res­onat­ing with site vis­i­tors, which will mean fewer dis­trac­tions from your top-performing case studies.

Note: If you are inter­ested in event par­tic­i­pa­tion, you will need to have your account man­ager or con­sul­tant enable event par­tic­i­pa­tion for spe­cific cus­tom events and traf­fic vari­ables. Once event par­tic­i­pa­tion is enabled, it is not retroac­tive — it only rolls for­ward from the moment it was enabled. If you have Dis­cover, you auto­mat­i­cally have par­tic­i­pa­tion for all of your cus­tom events.

2. On-Page (Direct)

While event par­tic­i­pa­tion mea­sures the indi­rect influ­ence of a page or other con­tent on suc­cess events, you may want to know which spe­cific page has directly influ­enced an action or out­come. For exam­ple, you may want to know which pages are gen­er­at­ing video views or prod­uct ratings/reviews. In these sce­nar­ios, you don’t want any other pages to get equal credit for the action other than the page that the vis­i­tor was on when he or she insti­gated the action such as click­ing a link or but­ton. In the exam­ple below, the vis­i­tor passed through three pages before finally trig­ger­ing a video view on the fourth page (Page D), which is the only page that receives any credit for the video view.

In order to mea­sure the direct influ­ence of pages, you need to cap­ture the page name in an eVar on every page load. When­ever a cus­tom event fires, it will be attrib­uted to the last page that was loaded. If you would like to know at what point in the visit the vis­i­tor trig­gered the event, you will want to set a counter eVar that increases by one unit on every page load. This vari­able will give you a his­togram of the num­ber of page views that occur before the cus­tom event hap­pens. You can then man­u­ally cal­cu­late the aver­age num­ber of page views before some­one trig­gers the action in question.

In terms of direct influ­ence analy­sis, you’ll want to cre­ate a cal­cu­lated met­ric of the intended action divided by vis­its so you can com­pare the event con­ver­sion rates of var­i­ous pages. In addi­tion to com­par­ing indi­vid­ual pages against each other, you might also con­sider exam­in­ing dif­fer­ent groups of pages to spot action­able pat­terns or trends. For exam­ple, you might find that peo­ple are view­ing videos more fre­quently for a par­tic­u­lar prod­uct cat­e­gory (e.g., video games) or on a new page tem­plate that was just intro­duced. Based on these insights, you might con­sider cre­at­ing videos for other prod­uct pages within the same cat­e­gory that don’t yet have videos or adopt­ing the new page tem­plate more broadly on the site to increase over­all video views.


3. Pre­vi­ous Page (Origination)

In a related but slightly dif­fer­ent sce­nario, you may want to know which page orig­i­nated a spe­cific action such as an inter­nal search, a lead form start, or the use of a store loca­tor. Some­times it can be dif­fi­cult or impos­si­ble to track cer­tain actions with on-click trig­gers so the cus­tom event is set on the sub­se­quent page where the action actu­ally occurs. In the fol­low­ing exam­ple, inter­nal searches would be trig­gered on the search results page (Page D). How­ever, it’s more use­ful to know which page (Page C) the vis­i­tor was on when he or she ini­ti­ated the search query.

In these “look-back” sce­nar­ios, you will need to use the get­Pre­vi­ous­Value plug-in, which main­tains or per­sists the page name value through to the sub­se­quent page. Using this spe­cial plug-in, you can place the pre­vi­ous page name (or site sec­tion, page type, etc.) into an eVar vari­able. If you’re ana­lyz­ing con­tent per­for­mance, you’re going to cre­ate the same cal­cu­lated met­ric (action met­ric / vis­its) so that you can iden­tify low– and high-performing pages.

If you were to use the pre­vi­ous page approach for store loca­tor usage or lead form starts, pages with high actions per visit would be viewed favor­ably as the con­tent is dri­ving poten­tial offline sales through the store loca­tor or lead form. In the case of inter­nal searches, you will be look­ing for pages that have high inter­nal searches per visit, which indi­cates that the pages are fail­ing to present the right con­tent. Vis­i­tors are not find­ing what they expected and are being forced to search for what they really wanted. In the exam­ple below, the brack­e­tol­ogy page appears to be hav­ing some issues as it is expe­ri­enc­ing a higher than aver­age searches per visit.  Tip: With some addi­tional tag­ging that is rel­a­tively sim­ple, you will be able to tie search terms to spe­cific pages. You will then be able to see what types of key­words are being searched for, which will give you hints as to what infor­ma­tion may be inef­fec­tive or miss­ing from the page.


As you can see, there are many ways to ana­lyze the influ­ence of con­tent on suc­cess events, and dif­fer­ent approaches can yield dif­fer­ent insights. Hope­fully, shar­ing these dif­fer­ent approaches has gen­er­ated some new ideas for how your com­pany can bet­ter under­stand which con­tent is and isn’t con­tribut­ing to your online suc­cess. Good luck!

3 comments
Mikemorges
Mikemorges

Hi Brent, love the approach, thank you. 2 questions:

1. let's say you redesign multiple pages and launch the changes at the same time and want to compare before and after performance using participation. How to you measure the uplift knowing that your marketing people have dramatically changed the traffic composition just before the site redesign? In other words should you stabilise the traffic variable when you calculate participation conversion rate?

2. When you apply participation metrics in your page report, and you've changed a few pages, do you either 1. Sum up participation metrics (e.g. lead participation) for the modified pages using a filter and compare or 2. do you look at the total customer experience and sum up participation for all site pages as they all influence in a certain way your bottom line performance?

Brent Dykes
Brent Dykes

Jack, Can you be more specific about which option you could find in SiteCatalyst? Thanks, Brent.

jackmob
jackmob

well i just tried omniture but i cannot find one of the option which was mentioned in the above contents