Collaborative, Social and Adaptive Relevance in Enterprise Search

Posted on June 30, 2011 by

Providing spot-on results with good relevance in Enterprise Search solutions is one of the hardest tasks when working with findability. Sure, it is doable to work out a generic model for ranking results based on the organization’s most common requirements on findability in conjunction with available metadata of the information made findable. But is it enough?

The burning question is: How can you ensure that the generic relevance model does not get outdated once the Findability solution has been in use for a month, half a year, a year and the implementation crew is long gone?

Findwise recently released a large Enterprise Findability solution at a customer in the electrical power industry in Sweden. In the project we identified personalized and adaptive relevance as two key requirements for the findability solution to provide real, future-proof value-in-use to a large set of people with fundamentally different roles within the company. This blog post will focus on the latter requirement, adaptiveness: How can we make sure that an Enterprise Findability solution returns search results that become better and better as the solution is used?

Let user behavior improve the behavior of the search tool

The Enterprise Findability solution rolled out at the power company contains two features that, put together, build the foundation of a continuously improving relevance model:

A feature that promotes popular content given a query term – “social relevance”
A feature that continuously changes the relevance model by boosting the relevance of popular documents – “adaptive relevance

Social relevance

Inspired by e-commerce actors on the web, the delivered Enterprise Findability solution uses the logged behavior of its users to promote popular content. When an end-user searches for, e.g. “terawatt hours”, the solution by default offers search results ranked and sorted according to the generic relevance model. This is what any search tool would do. But this solution also uses search logs to promote popular content just as e-commerce sites have been doing for years – “Other people searching for ‘terawatt hours’ viewed ‘Current power production’ (intranet page), ‘Definition of terms in the electrical power industry’ (PDF document)” etc.

By combining the intel of the search logs (where the end-user behavior of an Enterprise Findability solution is constantly collected) and the best bets (editorially provided “sponsored links”) with the regular search result, end-users are presented with a rich set of information answering their original question from different angles. And the best part of it is that the social relevance feature constantly improves as the tool is used. People get better results as time goes by.

Adaptive relevance

In addition to the social relevance feature, the vast amount of real search behavior compiled in the search logs is used for improving the generic relevance model as well. The solution tracks changes in popularity of content and adapts the document-level scores of documents and web pages in the search index accordingly. If a document is accessed often through the search tool, the document will be deemed “more important” and start climbing towards top positions in the search result. And if a previously popular document becomes less popular as time goes by, the document’s impact on the relevance model is decreased. In the end, content that has great importance for a limited amount of time (such as news items and weekly lunch menus) will first peek and then dip in the search index. The search index and the generic relevance model attached to it will stay fresh.

From generic to personalized search experience

This blog post has pinpointed a couple of solutions for a continuously-improving, generic relevance model in an Enterprise Findability solution. Obviously, generic models are generic, i.e. good enough for the many, not perfect for the few. There are great ways to address personalization solving many of the role-based challenges of Enterprise Findability, but let’s leave that to another, future blog post. Stay tuned!

Findability on an E-commerce Site

Posted on March 13, 2011 by

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!

Why Web Search is Like a Store Clerk

Posted on February 4, 2011 by

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?

The Difference Between Search and Findability

Posted on January 23, 2011 by

Enterprise Search and Findability What is Different?

Is “Findability” only a buzzword to describe the same thing as before when talking about search solutions, or does it bring something new to the discussion? I’d like to think the latter and this week I read a blog post describing the difference between search and findability in a very good way. I couldn’t have written it better myself.

For the lazy one, I’ve picked a quote that is the key element in the post:

Findability: introducing the robot waiter

Imagine you’re in a futuristic restaurant and when the robot waiter approaches, you ask for ‘ham and cheese omelette’. In response he just shrugs his robotic shoulders and says ‘not found – please try again.’ You then have to keep guessing until you find a match for something you’d like to order.

Now imagine a second futuristic restaurant where the robot waiter says ‘Mr Grimes, how lovely to see you, the last time you visited you had A and B and gave them a 5 star rating. People who ordered x, also ordered y and found that the wines a, b and c went really well with it.’At first restaurant the menu was searchable (though regrettably the ‘ham and cheese omelette’ query didn’t match anything), at the second restaurant the menu was findable.

To me, this analogy is spot-on. I dare to say that making content searchable is more of a technical issue while reaching great findability requires understanding of the business. Why is that?

Well, making a content repository searchable you “only” need to hook up a connector, index the repository and display a search box to the users. To succeed with this, it doesn’t matter if the content is movie reviews, user manuals, recipes, a product catalog or whatever. What you need to know is the format of the repository (is it a SQL database, file system, ECM, etc.).

But if you want your users to find what they want in your repositories, business knowledge is a requirement. It’s true that you help your users find information by implementing technical stuff like query completion, facets, did-you-mean, synonym dictionaries, etc. But if they are to be of any help you need to present facets that are useful, populate the synonym dictionary with terms used in your organisation,etc. For example, a good synonym file targeted towards nurses and doctors would be very different compared to one targeted at employees at an insurance company.

If a Piece of Content is Never Read, Does it Really Exist?

Posted on December 10, 2010 by

Since ancient times, information technology has developed from carvings in rock and wood to cell phones and Facebook. Still, the basic purpose remains the same; to facilitate communication between people separated by space and time. Therefore one can measure the successfulness of any information tool by two axes: how easy it is to create information and how easy it is to consume it. Being a Findability expert, I spend a large part of my life focusing on the latter. Therefore it troubles me that so many organizations wait so long when they are introducing new content management systems before looking at search. If I had a nickel for every time I heard “we are currently busy with building our new intranet/web page/collaboration tool and will look at search when the project is finished” I would definitely have had a few quarters by now.

I like to say that I am in the information marketing business. What I mean by that is that Findability is all about marketing information so that the consumers, your employees, can find the piece of information they need. And just as an industrialist would not construct a factory before doing a marketing plan, you should not build a new information repository without thinking about how the content created in that repository will reach its target audience. When marketing information, search is one of your most important channels.

While a enterprise search solution can definitely smooth out imperfections in information structure and quality using intelligent algorithms, spending a little time thinking about how you can make it easier for a search engine to deliver relevant results presented in a user friendly way can really make it shine. Some questions you can ask yourself are:

How can we make tagging so convenient that we have good metadata for presenting and filtering results using facets? Many search solutions have automated tagging functionality to take load off users.
How can we use search as an integration platform to pull in content from other sources instead of making costly one-time integrations?
How will the new information repository fit into an existing search solution, for example are we changing the metadata model and how should the documents be ranked compared to other sources?
Should we migrate content from an old system to the new one or just freeze information creation in the old one and have a search box that let’s the user find information from both?
Can we use search to avoid creating duplicate information by encouraging users to make searches before typing new content or even doing implicit searches while the user is typing?

So does a piece of content that no one ever reads exist? Well in terms of bits on a disk in a data center, yes, but in terms of business value definitely no. Designing your information repository for Findability will have great returns in improved efficiency and user satisfaction.

Bridging the Gap Between People and (Enterprise Search) Technology

Posted on December 6, 2010 by

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:

Help users become better searchers
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.

Google Instant – Can a Search Engine Predict What We Want?

Posted on September 26, 2010 by

On September 8th Google released a new feature for their search engine: Google instant.
If you haven’t seen it yet, there is an introduction on Youtube that is worth spending 1:41 minutes on.

Simply put, Google instant is a new way of displaying results and helping users find information faster. As you type, results will be presented in the background. In most cases it is enough to write two or three characters and the results you expect are already right in front of you.

The Swedish site Prisjakt has been using this for years, helping the users to get a better precision in their searches.

At Google you have previously been guided by “query suggestion” i.e. you got suggestions of what others have searched for before – a function also used by other search engines such as Bing (called Type Ahead). Google instant is taking it one step further.

When looking at what the blog community has to say about the new feature it seems to split the users in two groups; you either hate it or love it.

So, what are the consequences? From an end-user perspective we will most likely stop typing if something interesting appears that draws our attention. The result?
The search results shown at the very top will generate more traffic , it will be more personalized over time and we will most probably be better at phrasing our queries better.

From an advertising perspective, this will most likely affect the way people work with search engine optimization. Some experts, like Steve Rubel, claims Google instant will make SEO irrelevant, wheas others, like Matt Cutts think it will change people behavior in a positive way over time and explains why.

What Google is doing is something that they constantly do: change the way we consume information. So what is the next step?

CNN summarizes what the Eric Schmidt, the CEO of Google says:

“The next step of search is doing this automatically. When I walk down the street, I want my smartphone to be doing searches constantly: ‘Did you know … ?’ ‘Did you know … ?’ ‘Did you know … ?’ ‘Did you know … ?’ ”

Schmidt said at the IFA consumer electronics event in Berlin, Germany, this week.

“This notion of autonomous search — to tell me things I didn’t know but am probably interested in — is the next great stage, in my view, of search.”

Do you agree? Can we predict what the users want from search? Is this the sort of functionality that we want to use on the web and behind the firewall?

Findability and the Google Experience

Posted on September 2, 2010 by

In almost every findability project we work on, users ask us why finding information on their intranet is not as easy as finding information on Google. One of my team members told me he was once asked:

”If Google can search the whole internet in less than a second, how come you can’t search our internal information which is only a few million documents?”

I don’t remember his answer but I do remember what he said he would have wanted to answer:

”Google doesn’t have to handle rigorous security. We do. Google has got millions of servers all around the world. We have got one.”

The truth is, you get the search experience you deserve. Google delivers an excellent user experience to millions of users because they have thousands of employees working hard to achieve this. So do the other players in the search market. All the search engines are continuously working on improving the user experience for the users. It is possible to achieve good things without a huge budget. But I can guarantee you that just installing any of the search platforms on the market and then doing nothing will not result in a good experience for your users. So the question is; what is your company doing to achieve good findability, a good search experience?

Jeff Carr from Earley & Associates recently published a 2 part article about this desire to duplicate the Google experience, and why it won’t succeed. I recommend that you read it. Hopefully it will not only help you meet the questions and expectations from your users; it will also help you in how you can improve the search experience for them.

Enterprise Search and why we can’t just get Google.

Structured and actionable search results – there is more to presentation than blue links

Posted on June 22, 2010 by

Search patterns are standardized patterns describing search functionality as well as human information seeking behavior. Earlier this year Peter Morville and Jeffery Callender released a book about search patterns. Morville also gave a presentation based on the book at the IA Summit 2010 (slides, mp3), which my colleague Maria and I attended. Among the patterns Peter Morville mentions, my favorite ones are structured and actionable search results.

Structured search results

Let us start with structured search results. You might have seen that for certain queries you submit on Google, you get a richer results presentation than for other results. For example, typing the query ‘weather stockholm’ gives a basic weather forecast for the upcoming four days, directly visible in the results list. Other examples include local movie showtimes and stock information. It is even possible to use google as a calculator or a currency converter by typing in certain kinds of searches. For the curious, here is a list of all google.com search features. Structured results is about offering a more informative presentation of search results than just a title, summary, and possibly some basic metadata. It is also about not presenting all information in the same way, because the information in itself differs. Richer results presentations speeds up the process of finding relevant information since the system has already done some pre-processing for user.

Structured metadata is a prerequisite for structured search results presentation. Web pages and documents normally come with standard metadata such as date and author, but in some cases they will have to be augmented with additional information in order to create a more useful presentation. Presenting results in a custom way requires some extra development effort, especially if the structure is not initially available. However, I believe it creates much value to the user. Also, this need not be done for all types of contents. My advice would be to identify the cases where a more elaborate results presentation would be most usable. Which information is frequently requested by many people and perhaps also difficult to find because it is embedded in pages with lots of text or other contents? Search logs and user feedback in combination with thorough knowledge about the contents provides a key basis for the selection.

Actionable search results

Related to structured results are actionable search results. Entries in the search results list can be more than just displays of information; they can also be means of performing tasks. Common examples found on the web include printing, saving or sharing the search result directly from the results list. Other examples include adding to shopping cart, commenting and rating. Within the enterprise or organization additional relevant actions could perhaps be checking in or out a document, add an event to the personal calendar, starting a chat with a co-worker, and so on. As with structured results, it is about identifying the cases where it would add most value. What are the most common tasks and possibly also what tasks are complicated to perform in the source system? Structured and actionable results share the advantage that users do not have to open the actual results web page or download the document to find or do what they need. Speeding up information seeking and other tasks in this way is not only valuable in web search, it can also be very useful within the enterprise or organization. Search results lists in enterprise search solutions still look quite homogeneous and there are lots of opportunities for improvement.

To conclude, there can and should be more to search results presentation than just a snippet. I believe we will benefit from putting focus on the results presentation, and not only on tools surrounding it (filtering for example). After all, the list of results is where the user’s attention is first drawn. What do you think? How can your organization benefit from working with structured and actionable search results? If you are curious about this approach, we would be happy to help you look into what can be done in your organization.

Quick Website Diagnostics with Search Analytics

Posted on June 3, 2010 by

I have recently been giving courses directed to web editors on how to successfully apply search technology on a public web site. One of the things we stress is how to use search analytics as a source of user feedback. Search analytics is like performing a medical checkup. Just as physicians inspect patients in search of maladious symptoms, we want to be able to inspect a website in search of problems hampering user experience. When such symptoms are discovered a reasonable resolution is prescribed.

Search analytics is a vast field but as usual a few tips and tricks will take you a long way. I will describe three basic analysis steps to get you started. Search usage on public websites can be collected and inspected using an array of analytics toolkits, for example Google Analytics.

How many users are using search?

For starters, have a look at how many of your users are actually using search. Obviously having a large portion of users doing so means that search is becoming very important to your business. A simple conclusion stemming from such evidence is that search simply has to work satisfactorily, otherwise a large portion of your users are getting disappointed.

Having many searchers also raises some questions. Are users using search because they want to or because they are forced to, because of tricky site navigation for example? If you feel that the latter seems reasonable you may find that as you improve site navigation your number of searchers will decrease while overall traffic hopefully increases.

Just as with high numbers, low numbers can be ambiguous. Low scores especially coupled with a good amount of overall site traffic may mean that users don’t need search in order to find what they are looking for. On the other hand it may mean that users haven’t found the search box yet, or that the search tool is simply too complicated for the average user.

Aside from the business, knowing how popular search is can be beneficial to you personally. It’s a great feeling to know that you are responsible for one of the most used subsystems of your site. Rub it in the face of your colleague!

From where are searches being initiated?

One of the first recommendations you will get when implementing a search engine for your web site is to include the search box on each and every page, preferably in a standardized easy-to-find place like the top right corner. The point of having the search box available wherever your users happen to be is to enable them to search, typically after they have failed to find what they are looking for through browsing.

Now that we know that search is being conducted everywhere, we should be keeping an eye out for pages that frequently emit searches. Knowing what those pages are will let us improve the user experience by altering or completing the information there.

Which are the most common queries?

The most frequently issued queries to a search system make up a significant amount of the total number of served queries. These are known as head queries. By improving the quality of search for head queries you can offer a better search experience to a large amount of users.

A simple but effective way of working with search tuning is this. For each of the 10, 20 or 50 most frequent queries to the system:

Imagine what the user was looking for when typing that query
Perform that query yourself
Examine the 5-10 top results in the result list:
- Do you think that the user was content with those results
- If yes, pat your back 🙂
- If not, tweak using synonyms or best bets.

Go through this at least once a month. If the information on your site is static you might not need to change a lot of things every time, but if your content is changing or the behavior of the users you may need to adjust a few things.

The Findability blog

the enterprise search and findability blog by Tietoevry Findwise

Tag Archives: Web search engine