Google Search Appliance (GSA) 6.12 released

Google has released yet another version of the Google Search Appliance (GSA). It is good to see that Google stay active when it comes to improving their enterprise search product! Below is a list of the new features:

Dynamic navigation for secure search

The facet feature, new since 6.8, is still being improved. When filters are created, it is now possible to take in account that they only include secure documents, which the user is authorized to see.

Nested metadata queries

In previous Search Appliance releases there were restrictions for nesting meta tags in search queries. In this release many of those restrictions are lifted.

LDAP authentication with Universal Login

You can configure a Universal Login credential group for LDAP authentication.

Index removal and backoff intervals

When the Search Appliance encounters a temporary error while trying to fetch a document during crawl, it retains the document in the crawl queue and index. It schedules a series of retries after certain time intervals, known as “backoff” intervals. This before removing the URL from the index.

An example when this is useful is when using the processing pipeline that we have implemented for the GSA. GSA uses an external component to index the content, if that component goes down, the GSA will receive a “404 – page does not exist” when trying to crawl and this may cause mass removal from the index. With this functionality turned on, that can be avoided.

Specify URLs to crawl immediately in feeds

Release 6.12 provides the ability to specify URLs to crawl immediately in a feed by using the crawl-immediately attribute. This is a nice feature in order to prioritise what needs to get indexed quickly.

X-robots-tag support

The Appliance now supports the ability to exclude non-html documents by using the x-robots-tag. This feature opens the possibility to exclude non-html documents by using the x-robots-tag.

Google Search Appliance documentation page

Delivering Information Where It is Needed: Location Based Information

I recently started working at Findwise after having finished my thesis on location based information delivery in a mobile phone. The purpose of my thesis was to:

  • Investigate how location based information (as opposed to fixed locations) could be connected to search results
  • Improve quality of location based information by considering the course and velocity of the user

To start with, I created an iPhone application with a location-based reminder system. The reminders described location constraints and users could create reminders with single locations (at home) or groups of locations (at any pharmacy). To find these groups of locations, the system searched for locations with associated information (like nearby pharmacies) and delivered this information without users having to click Search repeatedly.

This is an unusual approach to search as the user is passive, instead the system is performing searches for the user. However, to make search results relevant one has to add contextual constraints to describe when, where and to whom a piece of information is relevant. When all constraints are met, information should be relevant. If not, the system lacks some crucial contextual constraints.

When search is automated, the importance of relevant search results increases and the more you know of the users world, the better you can adjust the results. However, traditional search can also benefit from contextual information. It can be used as a filter where search results that are irrelevant in the current context are removed. Alternatively it could be a part of the relevance model, improving search results by reordering them according to context. Hence, whereas automatic information delivery is probably undesirable for many types of information – contextual constraints can still be of good use!

The people who tested my application created 25% of their reminders as groups of locations and found it useful as it helped them find places they weren’t aware of, facilitating opportunistic behavior. The course and velocity information reduced the number of false-positive information deliveries. Overall, the system worked well as a niche product.

Findability on an E-commerce Site

Findability on any e-commerce site is a beast all on its own. What if visitors’ searches return no results? Will they continue to search or did you lose your chance at a sale?

While product findability is a key factor of success in e-commerce, it is predominantly enabled by simple search alone. And while simple search usually doesn’t fulfill complex needs among users, website developers and owners still regard advanced search as just another boring to-do item during development. Owners won’t go so far as to leave it out, because every e-commerce website has some kind of advanced search functionality, but they probably do not believe it brings in much revenue.

Research shows:

  • 50% of online buyers go straight to the search function
  • 34% of visitors leave the site if they can’t find an (available) product
  • Buyers are more likely than Browsers to use search (91%)

What can’t be found, can’t be bought:

  • Search is often mission critical in e-commerce
  • Users don’t know how to spell
  • Users often don’t even know how to describe it

First of all, Findability can accelerate the sales process. And faster sales can increase conversions, because you will not be losing customers who give up trying to find products. Furthermore, fast, precise and successful searches increase your customers’ trust.

On both e-commerce and shopping comparison sites, users can find products in two different ways: searching and browsing. Searching obviously means using the site search whilst browsing involves drilling down through the categories provided by the website. The most common location for a site search on e-commerce sites is at the top of the page, and generally on the right side. Many e-commerce sites have a site search, user login, and shopping cart info all located in the same general area. Keeping the site search in a location that is pretty common will help it to be easier to find for some of your visitors who are accustomed to this trend.

Faceted search should be the de facto standard for an e-commerce website. When a user performs a simple search first, but then on the results page, he or she can narrow the search through a drill-down link (for a single choice) or a check box selection (for multiple non-overlapping choices). The structure of the search results page must also be crystal clear. The results must be ranked in a logical order (i.e. for the user, not for you) by relevance. Users should be able to scan and comprehend the results easily. Queries should be easy to refine and resubmit, and the search results page should show the query itself.

Spell-check is also crucial. Many products have names that are hard to remember or type correctly. Users might think to correct their misspelling when they find poor results, but they will be annoyed at having to do that… or worse, they might think that the website either doesn’t work properly or does not have their product.

Query completion can decrease the problems caused by mistyping or not knowing the proper terminology. Queries usually start with words; so unambiguous character inputting is crucial.

Search analytics, contextual advertisement and behavioral targeting is more than just finding a page or a product. When people search they tell you something about their interests, time, location and what is in demand right now, they say something about search quality by the way they navigate and click in result pages and finally what they do after they found what they were looking for.

A good e-commerce solution uses search technology to:

  • Dynamically tailor a site to suit the visitors’ interests
  • Help the user to find and explore
  • Relate information and promote up- and cross sales
  • Improve visitor satisfaction
  • Increase stickiness
  • Increase sales of related products or accessories
  • Inspire visitors to explore new products/areas
  • Provide-increased understanding of visitor needs/preferences

–> Convert visitors into returning customers!

Search Conferences 2011

During 2011 a large number of search conferences will take place all over the world. Some of them are dedicated to search, whereas others discuss the topic related to specific products, information management, usability etc.

Here are a few that might be of interest for those of you looking to be inspired and broaden your knowledge. Within a few weeks we will compile all the research related conferences – there are quite a few of them out there!
If there is anything you miss, please post a comment.

March
IntraTeam Event Copenhagen 2011
Main focus: Social intranets, SharePoint and Enterprise Search
March 1, 2 and 3, 2011, Copenhagen, Denmark

Webcoast
Main focus: A web event that is an unconference, meaning that the attendees themselves create the program by presenting on topics of their own expertise and interest.
March 18-20 , Gothenburg, Sweden

Info360
Main focus: Business productivity, Enterprise Content Management, SharePoint 2010
March 21-24, Walter E. Washington Convention Center, Washington, USA

April
International Search Summit Munich
Main focus: International search and social media.
4th April 2011, Hilton Munich Park Hotel, Germany

ECIR 2011: European Conference on Information Retrieval
Main focus: Presentation of new research results in the field of Information Retrieval
April18-21, Dublin, Ireland

May
Enterprise Search Summit Spring 2011
Main focus: Develop, implement and enhance cutting-edge internal search capabilities
May 10-11, New York, USA

International Search Summit: London
Main focus: International search and social media
May 18th, Millennium Gloucester Hotel, London, England

Lucene Revolution
Main focus: The world’s largest conference dedicated to open source search.
May 25-26, San Francisco Airport Hyatt Regency, USA

SharePoint Fest – Denver 2011
Main focus: In search track: Enterprise Search, Search & Records Management, & FAST for SharePoint
May 19-20, Colorado Convention Center, USA

June
International Search Summit Seattle
Main focus: International search and social media
June 9th, Bell Harbor Conference Center, Seattle, USA

2011 Semantic Technology Conference
Main focus: Semantic technologies – including Search, Content Management, Business Intelligence
June 5-9, Hilton Union Square, San Francisco, USA

October
SharePoint Conference 2011
Main focus: SharePoint and related technologies
October 3-6, Anaheim, California, USA

November
Enterprise Search Summit Fall Nov 1-3
Main focus: How to implement, manage, and enhance search in your organization
Integrated with the KMWorld Conference, SharePoint Symposium and Taxonomy Bootcamp,

KM-world
(Co-locating with Enterprise Search Summit Fall, Taxonomy Boot Camp and Sharepoint Symposium)
Main focus: Knowledge creation, publishing, sharing, finding, mining, reuse etc
November 1 – 3, Washington Marriott Wardman Park, Washington DC, USA

Gilbane group Boston
Main focus: Within search: semantic, mobile, SharePoint, social search
November 29 – December 1, Boston, USA

Why Web Search is Like a Store Clerk

When someone is using the search function on your web site, your web search, it tells you two things. First of all they have a specific need, expressed by their search query. Second, and more importantly he or she wants you to fulfill that need. If users didn’t care where the service was delivered from, they would have gone straight to Google. Hence, the use of your search function signals trust in your capabilities. This means that even if the majority of your website visitors doesn’t use the search function, you know that the ones who do have a commitment to you. Imagine you are working in a store as a clerk; the customer coming up to you and asking you something is probably more interested in doing business with you than the ones just browsing the goods.

This trust however, can easily be turned to frustration and bad will if the web search result is poor and users don’t find what they are looking for. Continuing our analogy with the store, this is much like the experience of looking for a product, wandering around for a few minutes, finally deciding to ask a clerk and getting the answer “If it’s not on the shelf we don’t have it”. I certainly would leave the store and the same applies for a web site. If users fail when browsing and searching, then they will probably leave your site. The consequence is that you might antagonize loyal customers or loose an easy sale. So how do you recognize a bad search function? A good way to start is to look at common search queries and try searching for them yourself. Then start asking a few basic questions such as:

  • Does the sorting of the search results make sense?
  • Is it possible to decide which result is interesting based on the information in the result presentation?
  • Is there any possibility to continue navigating the results if the top hits are not what you are looking for?

Answering these questions yourself will tell you a lot about how your web search is performing. The first step to a good user experience is to know where your challenges are, then you can start making changes to improve the issues you have found in order to make your customers happier. After all, who wants to be the snarky store clerk?

Bridging the Gap Between People and (Enterprise Search) Technology

Tony Russell-Rose recently wrote about the changing face of search, a post that summed up the discussion about the future of enterprise search that took part at the recent search solutions conference. This is indeed an interesting topic. My colleague Ludvig also touched on this topic in his recent post where he expressed his disappointment in the lack of visionary presentations at this year’s KMWorld conference.

At our last monthly staff meeting we had a visit from Dick Stenmark, associate professor of Informatics at the Department of Applied IT at Gothenburg University. He spoke about his view on the intranets of the future. One of the things he talked about was the big gap in between the user’s vague representation of her information need (e.g. the search query) and the representation of the documents indexed by the intranet enterprise search engine. If a user has a hard time defining what it is she is looking for it will of course be very hard for the search engine to interpret the query and deliver relevant results. What is needed, according to Dick Stenmark, is a way to bridge the gap between technology (the search engine) and people (the users of the search engine).

As I see it there are two ways you can bridge this gap:

  1. Help users become better searchers
  2. Customize search solutions to fit the needs of different user groups

Helping users become better searchers

I have mentioned this topic in one of my earlier posts. Users are not good at describing which information they are seeking, so it is important that we make sure the search solutions help them do so. Already existing functionalities, such as query completion and related searches, can help users create and use better queries.

Query completion often includes common search terms, but what if we did combine them with the search terms we would have wanted them to search for? This requires that you learn something about your users and their information needs. If you do take the time to learn about this it is possible to create suggestions that will help the user not only spell correctly, but also to create a more specific query. Some search solutions (such as homedepot.com) also uses a sort of query disambiguation, where the user’s search returns not only results, but a list of matching categories (where the user is asked to choose which category of products her search term belongs). This helps the search engine return not only the correct set of results, but also display the most relevant set of facets for that product category. Likewise, Google displays a list of related searches at the bottom of the search results list.

These are some examples of functionalities that can help users become better searchers. If you want to learn some more have a look at Dan Russells presentation linked from my previous post.

Customize search solutions to fit the needs of different user groups

One of the things Dick Stenmark talked about in his presentation for us at Findwise was how different users’ behavior is when it comes to searching for information. Users both have different information needs and also different ways of searching for information. However, when it comes to designing the experience of finding information most companies still try to achieve a one size fits all solution. A public website can maybe get by supporting 90% of its visitors but an intranet that only supports part of the employees is a failure. Still very few companies work with personalizing the search applications for their different user groups. (Some don’t even seem to care that they have different user groups and therefore treat all their users as one and the same.) The search engine needs to know and care more about its’ users in order to deliver better results and a better search experience as a whole. For search to be really useful personalization in some form is a must, and I think and hope we will see more of this in the future.