Searching for Curriculum Development Course Insights

For almost as long as I can remember (?! e.g. Search Powered Predictions), I’ve had the gut feeling that one of the most useful indicators about the courses our students want to study is their search behaviour, both in terms of searches that drive (potential) students to the OU courses and qualifications website from organic search listings, as well as their search behaviour whilst on the OU site, and whilst floundering around within the courses and quals minisite.

A quick skim through our current strategic priorities doc (OU Futures 2008 (internal only), though you can get a flavour from the public site: Open University Strategic Priorities 2007) suggests that there is increased interest in making use of data, for example as demonstrated by the intention to develop a more systematic approach for new curriculum developments, such that the student market, demography and employment sectors are the primary considerations.

So, to give myself something to think about over the next few days/weeks, here’s a marker post about what a “course search insights” tool might offer, inspired in part by the Google Youtube Insights interface.

So, using Youtube Insight as a starting point, let’s see how far we can get…

First off, the atom is not a Youtube video, it’s a course, or to be more exact, a course page on the courses and quals website… Like this page for T320 Ebusiness technologies: foundations and practice for example. The ideas are these: what might an “Insight” report look like for a course page such as this, how might it be used to improve the discoverability of the page (and improve appropriate registration conversion rates), and how might search behaviour inform curriculum development?

Firstly, it might be handy to segment the audience reports into four:

  • people hitting the page from an organic search listing;
  • people hitting the page from an internal (OU search engine) search listing;
  • people hitting the page from an ‘organic’ link on a third party site (e.g. a link to the course page from someone’s blog);
  • people hitting the page from an external campaign/adword etc on a search engine;
  • people hitting the page from any other campaign (banner ads etc);
  • the rest…

For the purposes of this post, I’ll just focus on the first two, search related, referrers… (and maybe the third – ‘organic’ external links). What would be good to know, and how might it be useful?

First off, a summary report of the most popular search terms would be handy:

– The terms used in referrers coming from external organic search results give us some insight into the way that the search engines see the page – and may provide clues relating to how to optimise the page so as to ensure we’re getting the traffic we expect from the search engines.

– The terms used within the open.ac.uk search domain presumably come from (potential) students who have gone through at least one micro-conversion, in that they have reached, and stayed in, the OU domain. Given that we can (sometimes) identify whether users are current students (e.g. they may be logged in to the OU domain as a student) or new to the OU, there’s a possibility of segmenting here between the search terms used to find a page by current students, and new prospects.

(Just by the by, I emailed a load of OU course team chairs a month or two ago about what search terms they would expect potential students to use on Google (or on the OU search engine) to find their course page on the courses and quals site. I received exactly zero responses…)

The organic/third party incoming link traffic can also provide useful insight as to how courses are regarded from the insight – an analysis of link text, and maybe keyword analysis of the page containing the link – can provide us with clues about how other people are describing our courses (something which also feeds into the way that the search engines will rank our course pages; inlink/backlink analysis can further extend this approach.). I’m guessing there’s not a lot of backlinking out there yet (except maybe from professional societies?), but if and when we get an affiliate scheme going, this may be one to watch…?

So that’s one batch of stuff we can look at – search terms. What else?

As a distance learning organisation, the OU has a national reach (and strategically, international aspirations), so a course insight tool might also provide useful intelligence about the geographical location of users looking at a particular course. Above average numbers of people reading about a course from a particular geo-locale might provide evidence about the effectiveness of a local campaign, or even identify a local need for a particular course (such as the opening or closure of large employer).

The Youtube Insight reports shows how as the Google monster gets bigger, it knows more and more about us (I’m thinking of the Youtube Insight age demographic/gender report here). So providing insight about the gender split and age range of people viewing a course may be useful (we can find this information out for registered users – incoming users are rather harder to pin down…), and may provide further insight when these figures are compared to the demographics of people actually taking the course, particularly if the demographic of people who view a course on the course catalogue page differs markedly from the demographics of people who take the course…

(Notwithstanding the desire to be an “open” institution, I do sometimes wonder whether we should actually try to pitch different courses at particular demographics, but I’m probably not allowed to say things like that…;-)

As well as looking at search results that (appear) to provide satisfactory hits, it’s also worth looking at the internal searches that don’t get highly relevant results. These searches might indicate weak optimisation of pages – appropriate search terms donlt find appropriate course pages – or they might identify topics or courses that users are looking for that don’t exist in the current OU offerings. Once again, it’s probably worth segmenting these unfulfilled/unsatisfactory courses according to new prospects and current students (and maybe even going further, e.g. by trying to identify the intentions of current students by correlating their course history with their search behaviour, we may gain insight into emerging preferences relating to free choice courses within particular degree programmes).

To sum up… Search data is free, and may provide a degree of ‘at arms length’ insight about potential students before we know anything about them ‘officially’ by virtue of them registering with us, as well as insight relating to emerging interests that might help drive curriculum innovation. By looking at data analysis and insight tools that are already out there, we can start to dream about what course insight tools might look like, that can be used to mine the wealth of free search data that we can collect on a daily basis, and turn it into useful information that can help improve course discovery and conversion, and feed into curriculum development.