What Differentiates a Good Search Engine from a Bad One?

That was one of the questions the UIE research group asked themselves when conducting a study of on-site search. One of the things they discovered was that the choice of search engine was not as important as the implementation. Most of the big search vendors were found in both the top sites and the bottom sites.

So even though the choice of vendor influences what functionality you can achieve and the control you have over your content there are other things that matter, maybe even more. Because the best search engine in the world will not work for you unless you configure it properly.

According to Jared Spool there are four kinds of search results:

  • ‘Match relevant results’ – returns the exact thing you were looking for.
  • ‘Zero results’ – no relevant results found.
  • ‘Related results’ – i.e. search for a sweater and also get results for a cardigan. (If you know that a cardigan is a type of sweater you are satisfied. Otherwise you just get frustrated and wonder why you got a result for a cardigan when you searched for a sweater).
  • ‘Wacko results – the results seem to have nothing in common with your query.

So what did the best sites do according to Jared Spool and his colleagues?
They returned match relevant results, and they did not return 0 results for searches.

So how do you achieve that then? We have previously written about the importance of content refinement and information quality. But what do you do when trying to achieve good search results with your search engine? And what if you do not have the time or knowledge to do a proper content tuning process?

Well, the search logs are a good way to start. Start looking at them to identify the 100 most common searches and the results they return. Are they match relevant results? It is also a good idea to look at the searches that return zero results and see if there is anything that can be done to improve those searches as well.

Jared Spool and his colleagues at UIE mostly talk about site search for e-commerce sites. For e-commerce sites bad search results mean loss of revenue while good search results hopefully give an increase in revenue (if other things such as check out do not fail). Working with intranet search the implications are a bit different.

With intranet search solutions the searches can be more complex when information not items, is what users are searching for. It might not be as easy to just add synonyms or group similar items to achieve better search results. I believe that in such a complex information universe, proper content tuning is the key to success. But looking at the search logs is a good way for you to start. And me and my colleagues here at Findwise can always help you how to get the most out of your search solution.

How Many Users Can You Afford to Annoy?

The second keynote at the Human Computer Interaction conference in Lancaster was given by Jared Spool who talked about Breaking through the invisible walls of usability research. Jared is a very inspiring and entertaining speaker. If you have the chance to listen to him, take it!

One of the things he talked about was the fact that the usability techniques that are widely used today were in fact not designed for large amounts of users. We have all kinds of data about the users’ behaviors online, but can we really use that data in a productive way? As Jared said;

“there is a big difference between data and information, we don’t know what inferences to make from the data we have.”

He also gave examples from a couple of large american ecommerce sites that have millions of users every day. With traditional usability measures you, according to Jacob Nielsens report, can identify 80% of the usability problems with as few as five users. But if you have one million customers, then you could say that 200.000 of the customers would be annoyed. Imagine how much money’s worth of lost revenue 200.000 users is. So how many nines to we need? (90, 99, 99,999?) How many percent is enough? It is apparent that we need to find methods that can solve these problems with usability evalutations and testing.

Jared Spool visualizes how few users actually spend money on an ecommerce site, and how few users the company relies on for their revenue.

Jared also talked about the consequences that web 2.0 have had for web applications and communities. He talked about what things that make people want to use “extra functionality”, as for example review functionality; what things delight people. Things that are excitement generators today soon come to be expected in every application. And when, as Jared said, HCI becomes HHHHHCI; when social networks are widely used, things that delight us or aggravate us, spread very fast. So instead of thinking about the five user rule, think about this next time you plan a release of a new product or application: How many users can you afford to annoy?