Why is Search Easy and Hard?

Last year my colleague Lina and I went to the Workshop on Human Computer Interaction and Information Retrieval (HCIR) in Washington DC. This year we did not have the possibility to attend but since all the material is available online I took part remotely any way. I wanted to share with you what I found most interesting this year. (Daniel Tunkelang who was one of the organizers also posted a good overview of the event on his blog.)

This years keynote speaker was Dan Russell, a researcher from Google. He talked about Search Quality and user happiness; Why search is easy and hard. The point I found most interesting in his presentation was how improvement is not only needed when it comes to tools and data but also improving the users’ search skills. My own experience from various search projects is similar; users are not good at searching. Even though they are looking for a specific version of a technical documentation for a specific product they might just enter the name of the product, or even the product family. (It’s a bit like searching for ‘camera’ when you expect to find support documentation on your Dioptric lens for you Canon EOS 60D.) So I agree that users need better search skills. In his presentation Russell also presented some ideas on how a search application can help users improve their search skills.

Search is both easy and hard. Perhaps this is one of the reasons for the introduction of the HCIR Challenge as a new part of the workshop . From the HCIR website:

The aims of the challenge are to encourage researchers and practitioners to build and demonstrate information access systems satisfying at least one of the following:

  • Not only deliver relevant documents, but provide facilities for making meaning with those documents.
  • Increase user responsibility as well as control; that is, the systems require and reward human effort.
  • Offer the flexibility to adapt to user knowledge / sophistication / information need.
  • Are engaging and fun to use.

The winner of the challenge was a team of researchers from Yahoo Labs who presented Searching Through Time in the New York Times. The Time Explorer features a results page with an interactive time line that illustrates how the volume of articles (results) have changed over time. I recommend that you read the article in tech review to learn more about the project, or try out the Time explorer demo yourself. You can also learn more about the challenge in this blog post by Gene Golovchinsky.

All the papers and posters from the workshop can be found on the new website.

Evaluate Your Search Application

Search is the worst usability problem on the web according to Peter Morville (in his book Search Patterns). With that in mind it is good to know that there are best practices and search patterns that one can follow to ensure that your search will work. Yet, just applying best practices and patterns will not always do the trick for you. Patterns are examples of good things that often work but they do not come with a guarantee that your users will understand and use search simply because you used best practice solutions.

There is no real substitute for testing your designs, whether it’s on websites intranets or any other type of application. Evaluating your design you will learn what works and does not work with your users. Search is a bit tricky when it comes to testing since there is not one single way or flow for the users to take to their goal. You need to account for multiple courses of actions. But that is also the beauty of it, you learn how very different paths users take when searching for the same information. And it does not have to be expensive to do the testing even if it is a bit tricky. There are several ways you can test your designs:

  • Test your ideas using pen and paper
  • Let a small group of users into your development or test environment to evaluate ideas under development
  • Create a computer prototype that is limited to the functionality you are evaluating
  • You can also evaluate the existing site before starting new development to identify what things need improvement
  • Your search logs are another valuable source of information regarding your users behaviors. Have a look at them as a complement.

And the best part of testing your ideas with users is, as a bonus you will learn even more stuff about your users that will be valuable to you in the future. Even if you are evaluating the smallest part of your website you will learn things that affects the experience of the overall site. So what are you waiting for? Start testing your site as well. I promise you will learn a lot from it. If you have any questions about how to best evaluate the search functionality on your site or intranet, write a comment here or drop me an email. In the meanwhile we will soon go on summer holiday. But we’ll be back again in August. Have a nice summer everyone!

Combining Search and Browse – Integrated Faceted Breadcrumbs

Finding information can be tricky and as I have written about in one of my previous posts improving findability is not about providing a single entrypoint to information. Users have different ways of finding information (browsing, searching and asking). They often combine these techniques with each other (berrypicking) and so they all need to be supported. Peter Morville states that.

“Browse and Search work best in tandem… the best finding interfaces achieve a balance, letting users move fluidly between browsing and searching.”

A lot of sites are improving their search experience through the implementation of faceted search. However, very few successfully integrate faceted search and browsing on their site. Searching and browsing are treated as two separate flows of interaction instead of trying to combine them which would provide the users with a much better experience.

That is why I was glad to learn about an idea from Greg Nudelman which he presented in his session at the IASummit which I attended last week. In his session Greg introduced his idea about Integrated Faceted Breadcrumb. According to him breadcrumbs are intuitive, flexible and resourceful and they are design elements that don’t cause problems but simply work. To test his idea he conducted usability tests on a prototype using the Integrated Faceted Breadcrumb. According to his evaluation the integrated faceted breadcrumb has a lot of advantages over other faceted solutions:

  1. Combine hierarchical Location & Attribute breadcrumbs
  2. Use Change instead of Set-Remove-Set
  3. Automatically retain relevant query information
  4. Label breadcrumb aspects
  5. Make it clear how to start a new search
  6. Allow direct keyword manipulation.

I find this idea interesting and I am currently thinking about whether it could be applied into one of my own projects. (According to Greg it has not been implemented anywhere yet even though the findings from the usability testing were positive.) However I wonder if this is a concept that works well only for sites with relatively homogeneous content or if it would also work on larger collections of sites such as intranets? Can it be used in an intuitive way with a large number of facets and can it cope with the use of more complex filtering functionalities? For some sites it might not be the best idea to keep the search settings when the user changes search terms. These are some things I would like to find out. What do you think about this? Could you apply it to your site(s)? I recommend that you have a look at Greg Nudelman’s presentation on slideshare and find out for yourself. You can also find an article about the Integrated Faceted Breadcrumb on Boxes and Arrows. I look forward to a discussion about whether this is any good so write me a comment here at the findability blog or find me on twitter.

IASummit – Information Architecture and Search

This upcoming week my colleague Lina and I will participate in the IASummit in Phoenix Arizona. Search, information architecture and user experience and the relationships between them is the focus for us this upcoming week. We look forward to hearing a lot of great talks, meeting interesting people and enjoying the sunny weather in Arizona.

We will be blogging from the conference but if you don’t want to wait for that you can follow me, Maria on twitter or follow the hashtag for the IASummit #ias10 so see what everyone is tweeting about.

Faceted Search by LinkedIn

My RSS feeds have been buzzing about the LinkedIn faceted search since it was first released from beta in December. So why is the new search at LinkedIn so interesting that people are almost constantly discussing it? I think it’s partly because LinkedIn is a site that is used by most professionals and searching for people is core functionality on LinkedIn. But the search interface on LinkedIn is also a very good example of faceted search.

I decided to have a closer look into their search. The first thing I realized was just how many different kinds of searches there are on LinkedIn. Not only the obvious people search but also, job, news, forum, group, company, address book, answers and reference search. LinkedIn has managed to integrate search so that it’s the natural way of finding information on the site. People search is the most prominent search functionality but not the only one.

I’ve seen several different people search implementations and they often have a tendency to work more or less like phone books. If you know the name you type it and get the number. And if you’re lucky you can also get the name if you only have the number. There is seldom anyway to search for people with a certain competence or from a geographic area. LinkedIn sets a good example of how searching for people could and should work.

LinkedIn has taken careful consideration of their users; What information they are looking for, how they want it presented and how they need to filter searches in order to find the right people. The details that I personally like are the possibility to search within filters for matching options (I worked on a similar solution last year) and how different filters are displayed (or at least in different order) depending on what query the user types. If you want to know more about how the faceted search at LinkedIn was designed, check out the blog post by Sara Alpern.

But LinkedIn is not only interesting because of the good search experience. It’s also interesting from a technical perspective. The LinkedIn search is built on open source so they have developed everything themselves. For those of you interested in the technology behind the new LinkedIn search I recommend “LinkedIn search a look beneath the hood”, by Daniel Tunkelang where he links to a presentation by John Wang search architect at LinkedIn.

Search Driven Portals – Personalizing Search

To stay in the front edge within search technology, Findwise has a focus on research, both in the form of larger research projects and with different thesis projects. Mohammad Shadab and I just finished our thesis work at Findwise, where we have explored an idea of search user interfaces which we call search driven portals. User interfaces are mostly based on analysis of a smaller audience but the final interface is then put in production which targets a much wider range of users. The solution is in many cases static and cannot easily be changed or adapted. With Search driven portals, which is a portlet based UI, the users or administrators can adapt the interface specially designed to fulfill the need for different groups. Developers design and develop several searchlets (portlets powered by search technology), where every searchlet provides a specific functionality such as faceted search, results list, related information etc. Users can then choose to add the searchlets with functionality that suits them into their page on a preferred location. From architectural perspective, searchlets are standalone components independent from each other and are also easy to reuse.

Such functionality includes faceted search which serves as filters to narrow a search. These facets might need to be different based on what kind of role, department or background users have. Developers can create a set of facets and let the users choose the ones that satisfy their needs. Search driven portals is a great tool to make sure that sites don’t get flooded with information as new functionalities are developed. If a new need evolves, or if the provider comes with new ideas, the functionality is put into new searchlets which are deployed into the searchlet library. The administrator can broadcast new functionality to users by putting new searchlets on the master page, which affects every user’s own site. However, the users can still adjust new changes by removing the new functionality provided.

Search driven portals opens new ways of working, both in developer and usage perspective. It is one step away from the one size fits all concept, which many sites is supposed to fulfill. Providers such as Findwise can build a large component library which can be customized into packages for different customers. With help of the searchlet library, web administrators can set up designs for different groups, project managers can set up a project adjusted layout and employees can adjust their site after their own requirements. With search-driven portals, a wider range of users needs can more easily be covered.

Query Suggestions Help Users Get Unstuck

Several papers at the HCIR09 workshop touched on the topic of query suggestions. Chirag Shah and Gary Marchionini presented a poster about query reuse in exploratory search tasks and Diane Kelly presented results from two different studies that examined people’s use of query suggestions and how usage varied depending on topic difficulty. (Their papers are available for download as part of the proceedings from the workshop.)

According to Shah and Marchionini users often search for the same things. They reuse their previous queries e.g. search for the same things multiple times. Users use their previous searches to refind information and also to expand or further filter their previous searches by adding one or more keywords. There is also a significant overlap between what different users search for suggesting that users have a tendency to express their information needs in similar ways. These results support the idea that query suggestions can be used to help users formulate their query.  Yahoo and YouTube  are two of the systems that uses this technique, where users get suggestions of queries and how they can add more words to their query based on what other users have searched for.

Diane Kelly concludes that users use query suggestion both by typing in the same thing as shown in the suggestion and by clicking on it. Users also tend to use more query suggestions when searching for difficult topics. Query suggestions help users get “unstuck” when they are searching for information.  It is however hard to know whether query suggestions actually return better results. The users expectation and preferences do have an effect on user satisfaction as well. User generated query suggestions are also found to be better than query suggestions generated by the search system. So the mere expectation that the query suggestions will help a user could have an positive effect on his or hers experience…

Query suggestions are meant to help the users formulate a good query that will provide them with relevant results. Query suggestions can also work as with yahoo search where query suggestions both suggest more words to add to the query but also provides the users with suggestions for other related concepts to search for. So searching for Britney Spears will for example suggest the related search for Kevin Federline (even though they are now divorced) and searching for enterprise search will suggest concepts such as relevance, information management and off course the names of the different search vendors.

If you apply this to the enterprise search setting the query suggestion could provide the user with several different kinds of help. Combining the user’s previous searches with things other users searched for but also providing suggestions for recommended queries or concepts. The concepts will be high quality information and suggestions controlled by the team managing the search application. It is a way of combining quick links or best bets with query suggestions and a way to hopefully improve the experienced value of the query suggestions. The next step then is to work with these common queries that users search for and make sure that they return relevant results, but that is an entirely different topic…

The Future of Information Discovery

I recently attended the third annual workshop on Human Computer Interaction and Information retrieval ( HCIR 2009) in Washington DC together with my colleague Lina. This is the first in a series of blog posts about what happened at the workshop. First up is the keynote about the Future of Information Discovery, by Ben Shneiderman.

Ben Shneiderman, professor at the University of Maryland and founding director of the Human Computer Interaction Laboratory held the workshop keynote. He started off by talking about what he called the elephant in the room, Google. Because whenever you talk about search these days you have to talk about Google. Google has become the baseline for search and the system that users relate other search experiences to. Almost all of our customers’ users has in one way or another asked “why can’t our intranet be more like Google?” (Read more about expectations to Googlify the company in a previous blog post by Mickel. You can also download the slides to Ben Shneidermans keynote presentation.)

As Ben Shneiderman said, Google does actually do the job, finding facts work. However searching for information can be dangerous. Google does well on handling simple fact-finding tasks but we need better tools to handle other types of searches such as:

  • Extended fact finding tasks where the queries are often vague
  • Tasks involving exploration of availability where the requested results can be vague
  • Open ended browsing and problem analysis where there can be hidden assumptions
  • Mismatch between the users information needs and the available metadata which will require exhaustive searching.

One of the points that I appreciated the most in this keynote was that systems that support searching for information not only need to support simple known-item searches, which Google does well. They also need to support other things:

  • Helping users enrich query formulation
  • Expanding result management
  • Enable long-term effort
  • Enhance collaboration

I am especially pleased by this statement since these are some of the important issues that we are working with in our customer projects. You will also learn more about query formulation in one of our upcoming blog posts from HCIR.

Supporting these cases are important for supporting users in their information seeking tasks and, according to Shneiderman, this should also be done while enabling users to deal with specific cases of search, concerning:

  • Completeness – Do I have all the information on a specific topic? This is especially important in for example legal or medical cases.
  • Absence of information – proving non-existence of information is very difficult but needed when applying for a patent or registering a trademark.
  • Outliers – making unexpected connections between information and finding and learning new  things that you would not have expected to find.
  • Bridging – Connecting different disciplines with each other.

This is very important because when users search the goal is not the information itself. No users go to a search interface just for the fun of searching for information. They need the information for a purpose. Search therefore needs to support things such as decision-making, collaboration, innovation and societal improvement. Search will only be of true value to users when it not only searches the simple fact-finding tasks but when it helps users solve the real problems in the real world. And good tools can force people to reframe their thinking and see things in a different light. That is the kind of tools that we should be designing.

Findwise is attending and Publishing a Paper at HCIR 2009

I’m glad to announce that Findwise is attending HCIR 2009, Human Computer Interaction with Information Retrieval, in Washington DC on October 23. Our paper about designing for Enterprise Search has been accepted to the conference so we (Maria Johansson and Lina Westerling) are going to Washington to attend the workshop and discuss HCIR with the researchers and practitioners most prominent in this area.

HCIR is a field bridging Human Computer Interaction with Information Retrieval. The design of usable search interfaces is off course a focus area in this field.

HCIR 2009 Article

The proceedings from the workshop has already been published on the HCIR 2009 conference website. You can also download our article “Designing for Enterprise Search in a Global Organization” from the Findwise website. We hope you enjoy it.

If you have any questions or topics you would like to know more about, send us an email with a question before October 21 and we’ll take it with us to the workshop. Stay tuned for more about what happened at HCIR 2009.