While Jerome is busy posting about the in’s and out’s of implementing Search&Promote, I thought I’d wade in with a post on why businesses should consider their search as a missed opportunity.

I’ve previously posted on what I think is a hidden gold mine of information called internal search.  It’s an area of the site that many companies, quite frankly, ignore.

Not too sure how to do anything with it, we assume it’s working just fine serving up results to random queries, so we’ll leave it alone and focus on our core purpose, driving people into our conversion funnel.

Or something along those lines.

If that’s you, go stand in front of a mirror and slap yourself a few times!  Wake up and smell the coffee…there’s much more to search than that!  And while you’re busy trying to optimise other areas of your site, you’re also blindly missing a massive opportunity for conversion optimisation.

The usual culprits

Almost all internal search engines (those used to search your own content) rely heavily on the traditional methods used for SEO – namely optimised pages of content.  They will dutifully rummage around your content on a predetermined frequency, building indexes that are searchable by the masses.

But there’s a whole land of missed opportunity if you rely on just organic searching.

Some of the more advanced search engine appliances will be able to up weight & down weight those results.  Some of them include facets (those subcategory links on the left hand side that are quite popular these days, especially amongst retail sites).  Most of them include some form of miss-spelt word or Did You Mean… capability.

Your opportunity to Search&Promote

You’re presented with a golden opportunity here.

Search&Promote can make your existing search engine look like it’s a digital yellow pages.  And how many people really want to use Yellow Pages nowadays?

What if you want to group certain types of results, such as content or products, and display them first.  What if you want to rank results, or in fact pre-filter results based on what the user has searched for, or interacted with, previously?

What if you wanted to display a different set of results for customers versus non-customers?

What if, by doing the above, you could marginally lift conversion rates?  Would that make a difference?

This opens up a whole new level for internal search.  You begin to have some control over the content that is actually displayed, rather that letting the search engine determine it.  And you can then begin to have your search contribute more to your conversions.

Make search work for you

If you’re already running SiteCatalyst and Test&Target, then adding Search&Promote really seems to be a no-brainer.

How much traffic do you get across your search pages?  Go and have a look.  How much of that traffic ultimately converts?  Take a look (you can use participation metrics to check that one out).

Now compare that to traffic that didn’t search internally.  How do they compare?

Given the volume of traffic across your search page, are there opportunities to engage them further?  If you could optimise your search page and influence conversions, what would be needed before you can show a return on investment.  I’ll bet it’s not much.

Optimisation Calculator

I’ve included as part of this post an Optimisation Calculator (excel spreadsheet) that can help you determine annual incremental revenue from optimisation efforts.

To use it, just put in your traffic, conversion and revenue amounts in the coloured cells, as well as a “what if we could it increase it by…” percentage rate.

In the example I’ve used, suppose you have 40,000 unique visitors to your internal search page.  Suppose they contribute to only 77 purchases, with $36,500 revenue generated from them.  That’s a search conversion rate of about 0.19%.  Not too much.  Some companies would think it’s not worth it.  They’re not there for that reason.

Think again.

If you could lift search conversions by an incrementally small amount, say 17% overall (taking the conversion rate from 0.19% to 0.23%, then you incrementally add nearly $100,000 to your annual revenue, given the example above.

If you can achieve the same conversion rate that your site gets overall (in the example, I’ve used 2.78%) you’d incrementally add a whopping $5.8million.

Did that make you sit up and look closer?

It’s a “suite” integration

If you have SiteCatalyst and Test&Target then you’re definitely one step ahead of your competition.  If you add in Search&Promote and spend the time to integrate all three products, so they leverage each other, you can, without a doubt influence internal search conversions.

With Search&Promote, you can do all of this and more – up weight/down weight results based on SiteCatalyst data such as top content; integrate external datasources such as product databases into the search results and have a different look and feel for those results, placing them at specific locations on the page.  You can target offers or promotions to users based on their search terms or previous browsing history by adding mboxes to the results page.  You can even change the entire search filter based on things like the last product type they viewed – why show them mens pants when they previously viewed female pants, and came back to do a search.

We must open the doors of opportunity.
But we must also equip our people to walk through those doors.
Lyndon B. Johnson

Well, the doors are wide open.  You’re suddenly in the land of opportunity.  Are you going to step through?

Remember, content relevance is just as, if not more, important on the search results page as it is across your other pages.  But many companies just forget about it assuming their search engine is doing a reasonable job.

Take a look at exit rates from search.

The other very much overlooked area for internal search is staff-based applications.  How many companies run intranets?  How many of you have multiple search boxes, searching different things across your company?  I’ve seen companies with between 3-10 different search types available to them, from internal product database, customer databases, content, FAQs, manual lists of links, and so on.  Search&Promote can integrate all of those into one easy to use search tool – saving hours of frustration for staff who can’t find the thing they wanted.

A small percentage increase in conversions, in a segment of traffic that virtually everybody forgets about (or discounts as not worth it) can make a whole heap of difference to your business.

Internal search…it’s an internal gold-mine waiting for you to excavate.  And the excavator is Search&Promote.

I challenge you to go take a look – spend an hour analysing your internal search traffic and play with a few “what if’s”.  Then decide if you can afford to ignore your internal search.

“I can’t find anything!”

This is the most common response we came across during the scoping and implementation of Search and Promote as the new internal search for Murdoch University.

Hardly surprising, given the issues with internal search that I covered in my previous post, but amazingly consistent!

In fact, one of the great truths we found during this project is that people truly don’t care where content is located, or whether it’s authenticated and/or accessible – they just wanted to type something in the search box, immediately find what they’re looking for, then carry on with their work.

We’ve now completed the implementation across our internal sites, and it’s working really well – so well that we’re now 2-3 weeks away from covering our external sites.

In my last post I promised to run through the implementation, however there’s a lot to talk about, so today I’ll cover SEO metatags (or the lack thereof), using multiple content sources, and how we integrated Search & Promote with SiteCatalyst to dynamically alter search result ranking.

Given the issues with internal search across campus and the wide range of staff and students that were more than happy to tell us just how bad it was, we decided to first implement Search & Promote across the internal sites where our primary audience are current staff and students.

Through the implementation of SiteCatalyst a few years back  across our network sites we have been able to segment our staff and student traffic, so we knew from the onset just how many searches each segment were doing, and how long on average they were taking.

Looking specifically at staff, approx 2,400 people collectively performed 234,131 searches in 2010, spending an average of 202 secs per search. Wow!

That equates to 13,137 hours, which, at an average of $40/hr, comes out to a $524,498 productivity cost. This figure alone should catch the attention of your key stakeholders and finance people.

Armed with that knowledge, we set the following key objective for the  Search & Promote trial across our internally facing sites;

• Reduce time staff spent searching by 10% by delivering a single set of filterable results, transparent of source, influenced by recent traffic.

Now that we had a clear objective, we could begin on the planning and implementation. We were greatly aided by a project team at Search & Promote – thanks John, Wally and Richard; you were all very helpful, and it was great working with each of you.

The first step was to set up the organic crawl of our internal sites, which largely consisted of listing the appropriate entry points;

Image: URL entry points in Search and Promote

And their corresponding URL masks (note the test feature that allows you to try your masks before saving them);

Image: URL masks in Search & Promote

Search & Promote works on a number of pages crawled – your licensing allows you to go to a certain number of pages, and after that the pages are not added to your index. There was a bit of tweaking to figure out what that level was, however there’s a cool feature in Search & Promote that allows the crawl to continue and count the number of pages that you’ve gone over by so you at least have an idea of where you are. From there you can either increase your licensed limit, or identify the larger than expected sites and par down the number of pages found by using the error logs and URL masks.

Compensating for the lack of SEO content

One of the issues I’d talked about previously was a lack of the bare minimum SEO metadata across many sites, most of which we had no direct control over. We tackled this by using the metatag injection feature in Search & Promote, which can be configured to dynamically inject metadata during a crawl, based on a URL pattern. This metadata is then included in the index as if the metadata was already embedded within each page, and can range from standard title/description metatags, to custom tags that can be use to create search filters (facets).

We soon found, however, that a significant portion of internal content required authentication to access, which meant that the crawler could not get in to that content. The Search & Promote crawler can be given credentials to access that content, however our concern was that content was authenticated for a reason, and to show even a title or extract from authenticated content on a public search may give away too much.

Given that the “we can’t find anything!” comment included authenticated content and applications, we needed an alternate option for this implementation to be successful.

At Murdoch we have a database called the A-Z index, which is maintained by our IT area, and over the past 5-6 years has grown to include an entry for most of our authenticated content and applications. This was a perfect source of information, now we needed to somehow incorporate this content into our search results.

Enter a feature in Search & Promote called ‘index connectors’.

Incorporating multiple sources of content

The index connector feature within Search & Promote allows you to define a third party xml feed, xml file, or comma/tab delineated file as an alternate source of content to be crawled.

The IT at Murdoch team were able to provide us an xml feed out of the A-Z index which allowed the Search & Promote crawler to include each entry/link within the feed in its scheduled crawls, together with custom mappings for each tag within the entries  to predefined custom metatags;

Image: Sample from our A-Z Flat XML feed

Image: Setting up the A-Z Flat XML feed as an index connector

Not only were we able to crawl the feed and include all the authenticated content as separate entries (‘restricted’ in the above screenshots), but we were able to alter the look and feel of the specific A-Z results within the wider search results, and account for a lack of  description within the feed.

The side-effect that we hadn’t counted on, but worked to our benefit, is that the A-Z index had entries for related non-Murdoch sites that were still of value to staff and students.

By having entries for the non-Murdoch sites in the A-Z as wayfinders, we didn’t need to crawl the actual sites themselves. This resulted in a significant reduction in the number of sites/pages we needed to organically crawl, while still providing our audience with a complete set of search results.

Using this same index connector functionality we were also able to incorporate the university’s campus directory listings via a new xml feed; whereas with the A-Z feed we only wanted to incorporate the results within the wider results set, we wanted results from the campus directory to always be the first results and be displayed in a table format, but more on the styling and positioning of these multiple content sources later.

Allowing for cyclical requests to ensure the most relevant results appear

In my previous post on Search & Promote, one of the key advantages the product had over its competitors was the ability to natively integrate with SiteCatalyst.

Via SiteCatalyst we already knew that our internal search terms follow highly cyclical patterns as our student (and staff) needs change over the semester. For example, the term ‘timetable’ is searched for throughout the semester, however the anticipated result changes as the semester progresses. At the beginning of semester, people are looking at for their semester timetable and towards the end their exam timetable.

In the past we’ve used custom coded mechanisms to help staff and students find what they’re looking for, however with Search & Promote we can take that to a whole new level!

Search & Promote allows you to define a data source within SiteCatalyst, in our case Global Production > Page Views, and then add ranking weight based on those values – the higher the weight, the higher the impact the SiteCatalyst data will have over your search results.

We defined s.prop41 under our Global Production suite in SiteCatalyst as SearchPromoteURL, and then used it to cross reference the Search & Promote crawled URLs with the associated Page Views data in SiteCatalyst;

Image: Using page view data from SiteCatalyst to influence ranking

Now, every day the last seven days worth of aggregated SiteCatalyst page view data is automatically downloaded and fed into the Search & Promote custom defined field SearchPromoteURL, which in turn is used in a ranking rule that increases the relevance of highly trafficked pages in the last seven days;

Image: Aggregated page view data in Search & Promote

A good example of this in action are our sample and past exam papers in our Library website, where there is a separate page per letter – with the SearchPromoteURL ranking rule disabled, the pages are literally ranked A through to Z, as the other active ranking rules see them as equally relevant. However when the SearchPromoteURL ranking rule is in place, the top ranked exam page is Exams B, followed by P and I.

In the admin data report for “exams” below you can see how the ranking, relevance and score metrics are all the same for the exam paper pages, and that the differentiating ranking  factor is delivered by the page views;

Image: Admin view of results for 'exams' and the different ranking scores that order them

The same ranking results can be seen on the front-end at http://search.murdoch.edu.au/?q=exams;

Image: Corresponding public search results for 'exams'

This is exactly what we set out to achieve, and it’s so far looking to have worked pretty well!

In part 2 of this post, I’ll cover how we combined all our sources of search results into a single set of user-centric, filterable search results, well as how we fared against our original objective of reducing time our staff spent search by 10%.

When it comes to searching across the web, we all know that Google is king, but does this still hold true across your own internal network?

Over the past 12 months we have wrestled with this question, particularly in an environment with multiple search mechanisms, manually maintained indexes, and masses of sites that were created when metadata was primarily used to categorise instead of search.

In a series of posts, I’m going to go through our experiences in improving search across our internal network – I’m not suggesting we have found the magic search bullet, or that we’re anywhere near finished tweaking and tinkering, but I do know we’re a hell of a lot closer than where we were at this time last year.

The problem

In our travels across campus, we kept hearing “I can’t find what I’m looking for!”  – not surprising, given that we had;

1. 500+ individual sites, ranging in age (earliest was 1997), metadata (none to Dublin Core to ‘something’) and ownership
2. Inconsistent use of key SEO elements, such as title, headings, tags and meta descriptions across the majority of our sites
3. Multiple sources of content and internal search mechanisms, each with their own set of search results
4. Manually maintained indexes, all categorised and sub-related, together with an in-house redirect mechanism
5. An internal audience of staff and students with heavily cyclical search requests – a search for ‘physics’ at the beginning of semester is more likely to be for text books, and at the end of semester past exam papers

Image: Multiple source-centric result sets;

Given Google’s dominance in search, we quickly went down the path of a Google Search Appliance, or ‘Mini’, which is a self contained rack mounted system that gives you God-like powers over the Google algorithm. We were bringing in a little bit of Google in to magically transform our disparate set of sites into a cohesive set of search results.

Once plugged in, the Mini worked really well – for pages that were properly formatted for organic search.

Pages that were missing or incorrectly using titles, headings and metadata didn’t fare so well, and we found the search results were not the most relevant, as the Mini couldn’t make much sense of most of the content it crawled. We also found that there was no clear way to incorporate the feeds from other systems, with the “how do I…” answers primarily provided by a community of Search Appliance users and resellers, and not Google themselves.

Given the wide ownership of the sites we were working with, updating each with appropriate SEO friendly content was unrealistic. What we needed was a way to;

1. compensate for the lack of SEO content,
2. incorporating multiple sources/ formats of content,
3. allow for cyclical requests to ensure the most relevant results appear, and
4. combine all the different sources of search results into a single set of user-centric search results.

Enter Adobe Search&Promote

If you’re a regular visitor to this blog, it will come as no surprise that Tim is a power user of Omniture products, steadily working his way around the product wheel. We became aware of the Search&Promote product (then called SiteSearch) which promised to solve our key internal search issues.

Search&Promote uses a search algorithm to organically crawl your sites, in addition to ranking rules based on a wide range of configurable data. Once you’ve defined your rules, you can adjust the overall balance between your ranking rules and natural search relevance.

Where there is a lack of metadata, Search&Promote can be configured to dynamically inject metadata on crawl, based on a URL pattern. Additional custom metadata can also be injected to create facets (filters) that allow users to drill further down into predefined categories.

If your multiple sources of content can be transformed into XML feeds, then that content can be crawled, categorised, and integrated with the organic results by Search&Promote.

Yes, there are other internal search products on the market that will do the above, however there is one thing that Search&Promote has over its competitors – the ability to tightly integrate with SiteCatalyst and Test & Target.

We’ve known for some time that internal search terms follow highly cyclical patterns as our student (and staff) needs change over the semester. We’ve helped them find what they’re looking for using of real-time SiteCatalyst data in search-as-you-type and tag cloud mechanisms, however with Search&Promote we now have the opportunity to take internal search to the next level.

In the report below (7 day moving average) you can see two popular search results across three semesters peaking at different times during the semester;

Notice how ‘bookshop’ peaks at the beginning of semester, then dies down, only to peak again at the beginning of the following semester. No surprises here, but it does coincide with a significant increase in page views across the Bookshop website.

Then look at the results for ‘timetable’ – there’s a peak at both the beginning and end of semester. The difference here is that people are actually looking for two different pieces of content – their semester timetable at the beginning, and their exam timetable at the end – using the same keyword. Again, the rise in search terms coincides with increased page views across each piece of content.

So, in theory, by looking at the last week’s worth of traffic across our group of sites, we should be able to determine what content students are looking for, then re-rank the search results accordingly. For example, the term ‘timetable’ at the beginning of semester will push results related to the semester timetable to the top, and at the end of the semester push results related to the exam timetable to the top.

Exciting stuff!

Next post – the implementation.

As I’ve written in previous posts, internal search provides great insights into so many aspects of your site, and is one area that you should definitely focus measurement on.

Aside from the usual keywords that people are searching on, and whether or not those keywords lead to a conversion of some sort, there’s other measures that can be used to show whether your internal search is working.

For example, if you segment your audience type (as we do into Staff, Students and Anonymous traffic), you can see the different searches those audiences conduct.

Some measures to understand the effectiveness of search results would be:

• Time on the search page – a large amount of time would indicate they are not finding the result
• Search bounce – a high bounce would indicate poor results
• Number of searches per session – while not a direct indicator, could indicate poor results
• Keyword pathing – shows refinement of searches
• Number of Results – look for the zero’s in this one

Sometimes, no matter what you do, your organic search results just don’t cut the mustard – especially in a distributed content model where the content owners are less inclined or less experienced to think about SEO.  If you find yourself in this situation, there’s a number of different things you can do to help.  Half the battle though is realising that your natural search results are going to be poor (garbage in, garbage out) and any change is likely to be a slow burn.

One option to assist would be Omniture SiteSearch, which will allow you to do all sorts of things, including influencing results based on previous search data from SiteCatalyst, integrated with Test & Target…but we’ll save that for a future post.

Number of Searches

On the flip side, to get more insight, let’s look at the number of searches per session.

You can implement that very easily by using what’s called a counter eVar.  You simply want to know the number of times something happens, before something else happens.

In SiteCatalyst, you can create a counter eVar (simply select the type of eVar as counter).  Each time something happens, such as a search, we pass in the value of the keyword and we pass in a special value “+1″ to the eVar.

SiteCatalyst then allows you to see reports based on those different values.

Our internal search tracking code looks like this:

/* Internal Search Event Setting */
if(s.prop5&&s.prop5=="0"){s.prop5=""}
if(s.prop5) {
s.events=s.apl(s.events,"event1",",",1);
s.eVar39="+1";
}
if(s.prop5&&!s.eVar5) s.eVar5=s.prop5;


We set s.prop5 with the keyword on the search page – everytime a keyword is present.

eVar39 is our counter eVar.  It basically captures the number of times that we have searched for something.  Each time we do another search, the value in SiteCatalyst is incremented by 1 and then we end up with a report that shows the number of searches during a session (as we have set the eVar to expire on a visit).

So in this, albeit very limited result set, it shows that there were 184 searches on the first attempt.

There were 53 searches done on the third attempt, and so forth.

Interestingly (sadly), one search term was searched for on a 17th attempt – someones keen, but likely couldn’t find the result they were looking for, and they continued to search until they found some decent results.

You can also break down (providing you have full correlations on search terms), on each attempt to see what they were searching for.

In the instance where the person conducted 17 searches, the 17th search was for the term “vbs location”

I’ve also illustrated here that keywords can be broken down by the number of searches conducted.  In the example above, Bookshop was searched for 205 times in total, but featured as someone’s 2nd, 3rd, 4th and 5th search attempt (the none is because it’s got previous data prior to my eVar being put in place).

Monetising Search

For most companies, search conversion is key – revenue generation from search.  However, for the most part, our internal search does not “convert” to a sale of something.  It’s mostly used to find content, so we’re keen to understand what that costs us (not how much revenue is being generated).

If you’re looking for a way to calculate a cost for search, here’s a “back of the envelope” calculation…

The average time spent by Staff on our search results page is around 208 seconds.
The average number of annual searches by Staff alone is 124,600…
therefore…
25,916,800 seconds expended using search annually
= 431,947 minutes expended using search annually
= 7,199 total hours expended using search annually
(that’s a phenomenal number when you think about it… that’s 960 working days at 7.5 hours a day)

If the average cost per hour of a resource is $ 40.00
then…
$ 287,960 is the total cost of resources who spend their time searching

If you can decrease search time spent by just 10% (21 seconds), you theoretically save around $29,000 – or you increase productivity availability by 96 days…food for thought!

A few fancy calculated metrics in SiteCatalyst and you could probably put cost of search against each keyword for a specific audience as well…but we’ll leave that for now.

On the plus side, if you do the above, you’ll conversely be able to see conversions from search, enlightening you as to which search terms are driving revenue, or leads etc.

Search is a veritable gold mine that is frequently ignored.

I’m not talking about Search Engines and Keywords, I’m talking about your internal search. Providing you track internal keyword searches, you can gain a wealth of understanding.

Internal search is generally used as a quick wayfinding method, highlighting areas of content that are well used, but are not readily available.  And more often than not, it’s seasonal as well.

The following report shows the top 5 keywords used by students on our University website, smoothed using a 21 day moving average.

Two things immediately jump out.  Firstly, notice how searches for Bookshop increased dramatically in late February, then declined, then Library picked up substantially in March, followed by Exam Timetable in late April (spiking suddenly in late May).

Very seasonal activity, centered around the Student’s life cycle at the University.  In February, having started a new semester, they all needed books.  Then as semester progressed, they all needed access to the Library, and lastly, as exams approached, they all wanted to know their Exam Timetables.

Great – but how can we use this?

Well, firstly this points to the fact that there is no clear navigation on our site to these destinations.  There’s actually a reason for that – our public site is not designed for active current students as they should be using the Student Portal.  That aside, we can assist though in making these destinations easier to get to.

One thing we can do with Omniture is to export these top keywords to our database on a daily basis and then represent them on the site, through things like tag clouds and quick search results, making their lives easier in the process.

By using real data and automating the process, the seasonality of searches will also come through to the site as well.

The other interesting thing about the above chart is their search for timetable, as opposed to exam timetable.  When they start a new semester, they are interested in their class timetables and frequently search for them.  As time progresses and the memory kicks in, that activity slows down.  Again, this can be used in a number of ways – not only online, but through mobile apps and offline support media as well.

In order to track search keywords, simply put the keyword into an s.prop.  You might also want to put the number of results into another s.prop so that you can cross-reference the results on a keyword by keyword basis.  This would highlight any search terms  that return no results.

Segment your keywords

As always, understanding your audience is critical online.  If you segment your audience types, you’ll also be able to see the different searches conducted by different audiences.  We do this and the results are (obviously) very different.  But, without the ability to do it and show it, you’ll be taking an educated guess that they are different.

To do this, put the audience type into another s.prop and use the getAndPersist() plugin to set a cookie.  That way, all activity can actually be segmented by audience type.

Now you can provide some really smart assistance

When you start to build your tag clouds or your quick search lists, you can base the results on the value in the cookie, thereby customizing the information to the user and making it more relevant to them.  Just a few little tricks like this and you’ve helped to increase the usability of your site, which will go along way in driving customer loyalty (and hopefully revenue).