Design Elements of Search – Zero Results Page

The sixth and last part in this series, Design Elements of Search is dedicated to the zero results page. This lonely place is where your users end up when the search solution doesn’t find anything. Do your best to be friendly and helpful to your users here, will you?

A blog series – Six posts about Design Elements of Search


A word on Technology and Relevance – a disclaimer

Equally important as having a good user interface is having the right technology and the right relevance model set-up. I will not cover technology and relevance in this blog series. If you wish to read more, these topics is well covered by Findwise since before: Improve search relevancy  and Findwise.com/technology.


Designing Zero Results Page

The design, function and layout of your zero results page gossip about the quality of your search solution. This page is often forgotten and discussed last (like in this series). Whenever I review existing search solutions, this is where I start, because a lot of problems with existing search solutions show up here. You need to understand that from the user’s perspective, ending up on a zero results page can be a frustrating experience. You need to help the user recover from this state. Below is a good example from one of our clients. The intranet of the Swedish courts. The page clearly explains what has happened, No documents were found.

zero results page clearly explains what has happened

A good zero results page that clearly explains “No documents were found”.

Providing further Help

Sometimes there is nothing the system can do to deliver results. The last resort is when it’s time to ask your user to alter their query. Sometimes the query is misspelled or otherwise not optimal. You can copy and use this text on your own zero results page if you like.

  • Check that all words are spelled correctly
  • Try a different search
  • Try a more general search
  • Use fewer search terms

Avoid digging a deeper hole

Microsoft’s OneDrive provides a beautiful zero results page below, but they make a big mistake by showing filtering options in this state. This makes no sense, if there already are no results, there will definitely not be more by narrowing down the search scope further. Avoid this mistake!

avoid providing more filtering options on you zero results page

Pretty looking, but bad zero results page because of the filters on the right hand side.

That was it! The whole Design Elements of Search series is done. This is not everything however, designing a search solution is deeper than this. Me and my friends at Findwise will gladly help you realize all of your dreams. Ok maybe not all of them, but your search related dreams maybe? Ok, that was awkward.

See you in the future, best regards //Emil Mauritzson

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Design Elements of Search – Landing Page

We have just covered the area of results in the previous post, I hope that was fun, you are still here. That means you are ready for more, awesome! Let’s get into it. Here is the fifth part in the series Design Elements of Search, landing pages, whatever can it be?

A blog series – Six posts about Design Elements of Search


A word on Technology and Relevance – a disclaimer

Equally important as having a good user interface is having the right technology and the right relevance model set-up. I will not cover technology and relevance in this blog series. If you wish to read more, these topics is well covered by Findwise since before: Improve search relevancy  and Findwise.com/technology.


Designing Landing Pages

What normally happens when you click a search result? The answer seems obvious, you are sent to that document or that webpage or that product. Easy peasy.

diagram for how traditional search sends users to another webpage when clicking results

Traditionally you leave the search solution when clicking results.

However, during my years of consulting, I have come across multiple cases where we don’t know where to send users, because there is no obvious destination. Consider a result for an employee, a product, a process or a project. Sometimes there is no existing holistic view for these information objects. In these cases, we suggest building that holistic view in something we at Findwise call landing pages. When we use landing pages for certain results, users remain inside the search application when they click a result like this. Unlike a traditional search interfaces that sends users away to another application, or document.

design landing page ux diagram for how modern search can send users to a landing page

Get to the landing pages from the ordinary results page.

Paving the path

On landing pages, we show relationships between a variety of information objects we have in the search index. Let me describe it this way.

Sarah works as an architect. In her daily work she needs to be up to date regarding certain types of projects within her area of expertise. Therefore, Sarah is now doing research on how a certain material was used in a certain type of construction. She searches for “concrete bridges” and sees that there are 12 project results. Sarah looks over the results and clicks the third project and sees the landing page for that project. Here, she can see high level information about the project, and also see who the project members have been. Sarah sees Arianna Fowler and also more people. Sarah is curious about the person Peter Fisher because that name sounds familiar. She now sees the landing page for Peter. Here she can see all the projects Peter has been working on. She sees Peters most recent documents. She sees his close collogues. Sarah sees that Peter has been working in multiple projects that has used concrete as the main material. However, when she calls Peter, she learns he is not available right now. Therefore, Sarah decides to call Peters closest colleague. The system has identified close colleagues by knowing how many projects people have been working on together. Sarah calls Donna Spencer instead, because Donna and Peter has collaborated in 12 projects in the last five years. Sarah gets to know everything she needed and is left in a good mood.

Interesting paths

Your specific use case determines what information makes sense to show in these landing pages. Whatever you choose, you will set your users up for interesting paths of information finding and browsing, by connecting at least two information objects with landing pages. See illustration below.

diagram for how modern search can set users up for content discovery

Infinite discovery made possible by linking landing pages together.

When you look past the old way of linking users directly to documents and systems and instead making it possible to find unexpected connections between things. You have widened the definition of what enterprise search can be. This is a new way of delivering value to your organization using search.

This marks the end of the fifth part, next up you’ll read about what happens when a search yields zero results, and what you should do about that.

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Contact Emil Mauritzson

Design Elements of Search – Results

You are currently reading the fourth part in the series Design Elements of Search. This part is about the search results. The actual results certainly is the most central part of an entire search solution, so it’s important to get this part right. Don’t worry, I’ll show you how.

A blog series – Six posts about Design Elements of Search


A word on Technology and Relevance – a disclaimer

Equally important as having a good user interface is having the right technology and the right relevance model set-up. I will not cover technology and relevance in this blog series. If you wish to read more, these topics is well covered by Findwise since before: Improve search relevancy  and Findwise.com/technology.


Designing Results

Let’s say you are satisfied with the relevance model for now, how on earth do you design good looking and good performing results? If your indexed information mostly is text documents, your results will likely have a title and a snippet, that’s good – But it’s all the other things you include in the result that make it great. For each content source you have, you’ll need to think about what your target audience want to see. You’ll want your users to be able to understand if this seem like the right result or not.

Snippet

A snippet is the chunk of text presented on search results, usually below the title. If you have a 1000 words long PDF, and the user search for a word in a document. The search engine will show some words before the search term, and some words after. These snippets usually start with three dots … to indicate that the text is cut off. Snippets helps your user understand what this document is about. If it seems interesting, the user can decide to click on the result.

A regular search result

A regular search result from www.startpage.com.

Context

If you have indexed documents from a file share, provide the folder structure as breadcrumbs. Bonus points for making the individual folders clickable. If you have indexed webpages, show the URL as breadcrumbs. Make the individual pages clickable. Not all subpages make sense to navigate to, depending on your structure. Bonus points to you if you exclude these from being links. Below you see a webpage being located in “University -> Home -> Departments -> Mathematical Sciences -> Research”. This context is valuable information that helps your user understand what to expect of this search result.

providing the url for context is good on a search result

The url is used to communicate context, answering the question “where is this page located on the site”.

What Type is this Result?

When you index data sets from different sources and make them findable in a common search interface, you need to be as clear as possible about helping your user understand – “What is this result?”. Show clearly with a label if the result is a guide, a blogpost, a steering document, a product, a person, a case study, and so on. You want to have descriptive labels, not general ones like document, webpage or file. These general labels seldom make sense to users. Again, your labels and how you enable slicing and dicing of the data is the result of the IA work done, and not directly covered in this series.

Filetype

I just said above that the label “Document” doesn’t make much sense. That’s not the same thing as showing what filetype the current document has. It is sometimes helpful to know if this File is a PDF-file or a Word-file. Like Google and other search engines, show the filetype to the left of the title, in a little box. If your company uses the Microsoft Office, you can have labels like Word, Excel, PowerPoint. If you design for a general audience it makes more sense to use labels like DOC, XLS, PPT.

This is a good place to use colors, most word processors icons are blue, like Microsoft Word and Google Docs. Excel and Google Sheets is green. Adobe Reader is red. Regarding variations of filetypes, help your users by not bothering them with the difference of XLS and XLSX, or DOC and DOCX and so on. Just call them XLS and DOC. Since filetype also often is a filter. Excluding the different variants of the same file format will reduce the number of options in the list. Below we use colors, icons and labels to communicate filetype.

Showing the file extension and icon and a color is good for filetypes of a result

The filetype is clearly visible and communicated through text, icon and color.

Highlighting

Showing your users how results are matching the query is a key component of a well-liked and well understood search solution. In practice, highlighting means that if the user search for “summer vacation”, you provide a different styling on the words “summer” and “vacation” on the result. Most of the time, snippets come standard with highlighting, either in bold or in italics. In order to provide meaningful results, show highligting everywhere on the result. This means that if the matching terms are in the title, highlight that. If it’s in the breadcrumb, highlight that. Also, you can get creative and highlight in other ways than bold or italics, just see below.

showing where the search term matched os good

Search result with “summer” highlighted.

Here we try to mimic the look and feel of an actual highlighting pen, pretty neat.

highlighting looks like an actual pen

Highlighting up-close.

Time

When you are searching a webpage, an intranet or something else for that matter. Always show date of publication, or date of revision if you have that. Otherwise how would you know if the document “Release tables March 29” is recent, or very old? Many people get this basic thing wrong, don’t be one of them!

Be bold, but be Right

In order for your users to understand what data you are showing on the result, the data need a label describing it, like “Author: Emil Mauritzson”. All good so far. The most important thing is the data (Emil Mauritzson), not the label (Author). I see many getting this wrong and highlight the label. Highlight the data instead.

Visual focus on the data not the label is a best practice for search results

Make the most important thing most visible.

So, there’s that. The part about results is complete. If you are ready for more, get on to the next part, the one about what we call landing pages, whatever that can be…Exciting!

Get in touch

Contact Findwise

Contact Emil Mauritzson

Design Elements of Search – Filters

Hey, I’m happy you have found your way here, you are currently reading the third part in the series Design Elements of Search. This part is dedicated to filters, tabs and something we like to call filter tags.

A blog series – Six posts about Design Elements of Search


A word on Technology and Relevance – a disclaimer

Equally important as having a good user interface is having the right technology and the right relevance model set-up. I will not cover technology and relevance in this blog series. If you wish to read more, these topics is well covered by Findwise since before: Improve search relevancy  and Findwise.com/technology.


Designing Filters

When setting up new search solutions, we tend to spend a lot of time with the data structure. How should our users slice and dice the search-results? What makes sense? What does not? This is the part of the job sometimes classified as Information Architecture (IA). This text focuses more on the visual elements, the results of the IA work you can say.

Don’t make it difficult

The biggest pitfall when designing search is to overwhelm the user with too many options.

You got a million hits! – There are 345566 pages – Here are some results, Do you only want to see People results? – Sort by Price, Ascending or Descending?! – Click me – Did you mean: Coffee buns? – Click me – CLICK MEEEE! Yep, try to tone this down if you can.

Below you’ll see a disastrous layout. There is so many things screaming for users’ attention. If you look really hard, you can see a search result all the way down in the bottom of the picture.

image of a busy search interface

The original interface, very little room for results.

I said above that we spend a lot of time on the structure (IA). And we generally spend a lot of time on filters as well. This time is well spent. However, we need to realize that what is most important for our users. Do they find what they are looking for, or not? The order of the search results, i.e. the relevance is most important. Therefore, the actual search results should be totally in focus, visually in your interface.

Make it Easy

Instead of giving your users too many options up-front, consider hiding filters under a button or link. The button can say “Filter search results”, or “Refine results” or “Filter and Sort”. I’ll show you what I mean below. I have removed and renamed things from the above example, creating a design mockup. It’s not a perfect redesign, but you get my point, hopefully. All of a sudden there is room for three results on screen, success!

image of a not so busy search interface

A cleaned up interface, more room for results.

The second example is a sneak peek of White Arkitekter internal search solution. Here we can follow the user searching from the start page and applying a filter. The search results are in focus, and at the same time it’s easy to apply filters when needed. A good example.

animated gif showing a search interface and filters

Showing how easy a filter is applied.

Search inside Filters

In the best case, a specific filter will contain a handful of values that are easily scanned just by looking at the list. In reality however, often these lists of filter values are long. How should you sort the list? Often, we sort them by “most first”, sometimes alphabetically. When the list is not easily scannable, provide a way to “search” inside the filter. Like this:

animated gif showing a how to search inside filters

Typing inside this filter is helping the user more quickly find “Sweden”.

Filters values with Zero Results

Hey, if a filter value will yield zero results, like Calendar, Local files and Archived files below. Show the filter value but don’t make it clickable! Why on earth would you want that? You don’t want to send your users to a dead end. Sometimes they will end up there anyway, and then you have to help. Skip ahead to the part about the Zero Results Page to learn about how to help users recover.

You should not be able to click a filter with zero results

A filter with some values returning zero results. Good to show them, but important to make them not clickable.

Filter tags

I said above that the results should be the graphical element that stands out the most. And also, that making the first refinement should be easy to make. Well, this will mean that the filters will be hidden behind something. This does not mean, by the way, that the filter selection made by the user, should be hidden. On the contrary. You definitely want to be clear about what things affect the search results. This is normally the query, the filter selections and the sorting. A filter tag is simply a graphical element that is clearly visible above the search results when activated. It is also easy to remove it, simply by clicking on it. Below, I show you an example when the user has filtered on “News”.

filter is apllied and renders a filter tag

“News” is the active filter. A green filter tag is visible and is easy to see and easy to remove.

If you are up to a third example of filters check this case study out about Personalized search results in Netflix-style user interface.

This was all I had for you regarding filters. I hope some of it made sense, if not let’s get in touch, you can ask me about more details. Or perhaps tell me something I have missed. Always be learning! Next post will discuss results, see you over there.

Further reading

Information Architecture Basics

Filters vs. Facets: Definitions

Mobile Faceted Search with a Tray: New and Improved Design Pattern

Get in touch

Contact Findwise

Contact Emil Mauritzson

Design Elements of Search – Autocomplete Suggestions

You are currently reading the second part in the series Design Elements of Search, the one about autocomplete suggestions. When you’re typing text into the search bar, something is happening just below. A list of words relevant to the text appears. You probably know this from Google and around the web. I will share my findings and some best practices for autocomplete suggestions now. Call me a search-nerd, because I really enjoy implementing awesome autocomplete features!

A blog series – Six posts about Design Elements of Search


A word on Technology and Relevance – a disclaimer

Equally important as having a good user interface is having the right technology and the right relevance model set-up. I will not cover technology and relevance in this blog series. If you wish to read more, these topics is well covered by Findwise since before: Improve search relevancy  and Findwise.com/technology.


Designing Autocomplete Suggestions

I bet you recognize this? It just works right. But how do you get here? Read on and I will tell you.

animated god showing google autocompleter

How autocomplete works at google, a solid experience.

Instant Search

Autocomplete suggestions is a nice feature to offer when you expect your users to execute the query by clicking the search-icon or pressing the enter key. However sometimes your search solution is set up in such a way that for each character the user enters, a new search is performed automatically, this is called instant search. When this is the case you do not want autocomplete suggestions. Google experimented with instant search a few years ago. Google decided to revert back due to a few reasons. However, providing instant search in your use case might still be a good idea. In my experience instant search works well for structured data sets, like a product catalogue, or similar. When your information is diversified, the results could be either documents, web pages, images, people, videos and so on, you are probably better of providing traditional search in combination with autocomplete suggestions.

Suggestions based on User Queries

In my experience, using queries as the foundation for suggestions is the way to go. You can’t just take all queries and potentially suggest it to your entire user base though. What happens if you have a bad actor who want to troll and mess up your suggestions? Let’s say a popular query among your users is “money transfer” and your bad actor searches for something as nasty as “monkeyballs” 100 times. How do you make sure to provide the right suggestion when your user types “mon” in the search bar? You definitely don’t want your search team to actively monitor your potential autocomplete suggestions and manually weed out the bad ones.

One effective method we use is to check if the query matches any document in the index. Hopefully (!?) you do not have any document containing the word “monkeyballs” in your index, and therefore these terms will not be suggested to your users in the autocomplete suggestions. Using this method will make sure your suggestions is always domain specific to your particular case.

Another safeguard to ensure high quality suggestions is to have a threshold. A threshold means a query need to be performed X amount of times before it ends up as a potential suggested term. You can experiment with this threshold in your specific case for the best effect. This threshold will weed out “strange” queries like seemingly random numbers and other queries entered by mistake, that happens to yield some results.

Here is a high-level architecture of a successfully implemented autocomplete suggester at a large client.

architectural image showing autocomplete behind the scenes

Architectural overview of a good performing autocomplete suggester implemented at a client.

Right information, in the right time

So far, I have explained how to weed out the poor and nasty terms. More importantly however, how do you suggest terms in a good order? Basically, to achieve this, we consider the more people searching for something, the higher up the term will be in the list of suggestions. How do you solve the following case? Let’s say summer is coming up, and people are interested in “Vacation planning 2020”, how do you provide this suggestion above “Vacation planning 2019” in the spring of 2020? The term “Vacation Planning 2019” have been searched for 10.000 times and “Vacation planning 2020” only have been searched for 200 times?

Basically, you need to consider when these searches have been performed, and value recency together with number of searches. I don’t have an exact formula to share, but as you can see in the high-level architecture, we divide the queries on “last year, last month, last week”. Getting a good balance here will help boost recent queries that will be of interest to your users.

Add Static lists

Sometimes, you possess high quality lists of words that you want to appear in the autocomplete suggestions without the users first searching for them. Then you can populate the suggestions manually once. You may have a list of all the conference room names in your building, you may have a list of subjects that content creators use to tag documents. Please go ahead and use lists like this in your autocomplete suggestions.

Highlight the right thing

When presenting search results on the results page, you want to highlight where the query matched the document. Read about Results in the fourth part in this series. In the autocomplete suggestions however, you want to do the opposite. In this state, users know what characters they just entered, they are looking for what you are suggesting, this is what you highlight.

example of do and dont - highlight

Highlighting what comes after, not what the user has already entered.

Here we are, right at the end of autocomplete suggestions. Coming up in the next part, I will give you details about filters. Filters is surprisingly difficult to get right. But with some effort, it’s possible to make them shine. See you on the other side.

Further reading

13 Design Patterns for Autocomplete Suggestions

Get in touch

Contact Findwise

Contact Emil Mauritzson

Design Elements of Search – The Search Bar

Time for the first part in the series Design Elements of Search. How do you design a search solution so that it provides value to your organization? How do you make sure users enjoy, use and actually find what they expect? There are already so many great implementations of successful search applications, what can we learn from them? If these questions are in your domain, then you have reached the right place. Buckle up, you are in for a ride! Let’s dive into it right away by discussing the search bar.

A blog series – Six posts about Design Elements of Search


A word on Technology and Relevance – a disclaimer

Equally important as having a good user interface is having the right technology and the right relevance model set-up. I will not cover technology and relevance in this blog series. If you wish to read more, these topics is well covered by Findwise since before: Improve search relevancy  and Findwise.com/technology.


Designing the Search Bar

To set the scene and get cozy, here are some search bars.

Animated gif showing a variety of different search bars

A selection of search bars, for your pleasure.

Placing the search bar in the “right” place

Before discussing the individual graphical elements of the search bar, let’s consider where a search bar can be placed. On the search page itself, it normally resides in the top of the page (think Google). However, consider the vast landscape of your digital workplace and you might understand where I am going. A search bar can be placed on your intranet, usually in the header. It can be placed in the taskbar of your workforces’ computers. It can be placed in multiple other business applications in your control. From our perspective this is called entry points. It is well worth following up where your users come from. This is only one data point, you definitely want to follow up more usage statistics. You want to be data informed. In our client projects we usually use Kibana for statistics, showing graphs in custom dashboards. Before redesigning something, we first analyze existing usage statistics, and then follow up with users to draw conclusions that will inform design decisions. I’ll stop talking about usage statistics now, let’s go ahead and break down the search bar.

Placeholder Text

A placeholder text invites users to the search bar. The placeholder text explains what your users can expect to find in this search solution. While respecting the tone of voice of your application, it doesn’t hurt to be friendly and helpful here. Examples of good placeholder texts is: “What are you looking for today?” “How can we help?”  “Find people, projects and more”. H&M, the clothing store have implemented a dynamic placeholder text that animates in a neat way.

Placeholder text from IKEA that animates

Animated placeholder text that sparks interest in the different kind of things you can search for at IKEA.com

Google Photos is switching it around and suggests what you can search for based on the meta data of your uploaded photos, here are a few examples.

placeholder text from google showing a variety of different texts

A variety of placeholder texts helping the user discover what can be searched for. The text is also personalized.

The placeholder text should be gray, so that the text is not mistaken to be actual data entered into the search bar. The placeholder text should immediately disappear when your user starts typing.

Contrast

Make sure the color of the search bar and the background color of the page provides enough contrast so that the search bar is clearly visible. It’s is also fine to have the same color if you provide a border around the search bar with enough contrast. Here a few good examples, and some bad.

High Contrast

screenshot of bing start page

Clearly enough contrast on Bing.com

screenshot of Dustin.com providing good contrast

Easy to find the search bar on Dustin

Low Contrast

Google actually have low contrast on the border surrounding the search bar. The search bar also has the same color as the page. Normally this is something to avoid. There is few items on the page, and users expect to search at Google.com, so they get away with low contrast I guess. Still, Bing is better in this regard.

screenshot of Google.com providing poor contrast

Too little contrast on Google.

Screenshot of search bar with too little contrast

Where is the search bar? Look hard.

If you are unsure, check if your current colors provide enough contrast using an online Contrast Checker.Chances are your contrasts are too low and need improvement.

The Search Button

This is the button that performs the search. Many people use the Enter key on their keyboard instead of clicking this button. However, you still want to keep the search button for clarity and ease of use. Generally, all icons should have labels. The search button is one of the few icons for which it´s safe to skip the label. I can argue that the search icon is generally recognized, especially in the context of search. On the other hand, if you have the room. Why not use a label? I mean it cannot be clearer than this:

Screenshot of Försäkringskassan having good labels

Clearly labeled buttons, easy to comprehend.

Clear the search bar easily with an “X”

As frequently implemented on mobile applications, you should provide an easy way of clearing the text-field on your desktop application. This is accomplished by an “X”-icon. As discussed above, not many icons are recognized by majority of users. Therefore, it is common practice to provide labels for icons. For the “X”-icon in this specific context, is also fine to skip the label.

a search bar that makes it easy to remove the typed text

Make the text easy to remove.

Number of Results

After the query has been executed and results are showing, it is helpful to communicate how many results that were returned. This provides value in itself, and in combination with filters it is even more powerful. Telling the users how many results were returned is helping them understand how your search application is working, especially in combinations with applied filters. Skip ahead to Filters and read all about it. Avoid sounding like a robot, don’t say “Showing 10 of 28482 results on Pages 1-2849. Plainly say “Showing 123 results” or “123 results found”.

example of do and dont - number of results

Make your search solution friendly and approachable, not robotic and stiff.

Did you mean

Use the power of search technologies and query analysis to give your users the option to adjust the initial query for the better. Sometimes you will suggest a correctly spelled query when your user misspelled, or you can suggest alternative phrases or other related terms.

did you mean example

The search solution can help you spell words correctly.

Here we are, right at the end of the first part. I hope it was compelling, there is more where this came from, so keep on reading. To sum up this first part, when designing the search bar, just the obvious things need to be right. In the second part, you’ll get to know something called autocomplete suggestions. This feature helps your users formulate better queries, and that really is a good start.

Further reading

How to design: accessible search bars

Design a Perfect Search Box

Get in touch

Contact Findwise

Contact Emil Mauritzson

Gamification in Information Retrieval

My last article was mainly about Collaborative Information Seeking – one of the trends in enterprise search. Another interesting topic is the use of games’ mechanics in CIS systems. I met up with this idea during previously mentioned ESE 2014 conference, but interest is so high, that this year in Amsterdam a GamifIR (workshops on Gamification for Information Retrieval) took place. IR community have debated about what kind of benefits can IR tasks bring from games’ techniques. Workshops cover gamified task in context of searching, natural language processing, analyzing user behavior or collaborating. The last one was discussed in article titled “Enhancing Collaborative Search Systems Engagement Through Gamification” and has been mentioned by Martin White in his great presentation about search trends on last ESE summit.

Gamification is a concept which provides and uses game elements in non-game environment. Its goal is to improve customers or employees motivation for using some services. In the case of Information Retrieval it is e.g. encouraging people to find information in more efficient way. It is quite instinctive because competition is  an inherent part of human nature. Long time ago, business sectors have noticed that higher engagement, activating new users and establishing interaction between them, rewarding the effort of doing something lead to measurable results. Even if quality of data given by users could be higher. Among those elements can be included: leaderboards, levels, badges, achievements, time or resources limitation, challenges and many others. There are even described design patterns and models connected with gameplay, components, game practices and processes. Such rules are essential because virtual badge has no value until being assigned by user.

Collaborative Information Seeking is an idea suited for people cooperating on complex task which leads to find specific information. Systems like this support team work, coordinate actions and improve communication in many different ways and with usage of various mechanisms. At first glance it seems that gamification is perfect adopted to CIS projects. Seekers become more social, feeling of competence foster actions which in turn are rewarded.

The most important thing is to know why do we need gamified system and what kind of benefits we will get. Next step is to understand fundamental elements of a game and find out how adopt them to IR case. In their article “Enhancing Collaborative Search Systems Engagement Through Gamification”, researchers of Granada and Holguin universities have listed propositions how to gamify CIS system.  Based on their suggestions I think essential points are to prepare highly sociable environment for seekers. Every player (seeker) needs to have own personal profile which stores previous achievements and can be customized. Constant feedback on progress, list of successful members, time limitations, keeping the spirit of competition by all kinds of widgets are important for motivating and building a loyalty. Worth to remember that points collected after achieving goals need to be converted into virtual values which can distinguish the most active players. Crucial thing is to construct clear and fair principles, because often information seeking with such elements is a fun and it can’t be ruined.

Researchers from Finnish universities, who published article “Does Gamification Work?”, have broken down a problem of gamifying into components and have thoroughly studied them. Their conclusion was that concept of gamification can work, but there are some weaknesses – context which is going to be gamified and the quality of the users. Probably, the main problem is lack of knowledge which elements really provide benefits.

Gamification can be treated as a new way to deal with complex data structures. Limitations of data analyzing can be replaced by mechanism which increase activity of users in Information Retrieval process. Even more – such concept may leads to more higher quality data, because of increased people motivation. I believe, Collaborative Information Seeking, Gamification and similar ideas are one of the solutions how to improve search experience by helping people to become better searchers than not by just tuning up algorithms.

Why search and Findability is critical for the customer experience and NPS on websites

To achieve a high NPS, Net Promoter Score, the customer experience (cx) is crucial and a critical factor behind a positive customer experience is the ease of doing business. For companies who interact with their customers through the web (which ought to be almost every company these days) this of course implies a need to have good Findability and search on the website in order for visitors to be able to find what they are looking for without effort.

The concept of NPS was created by Fred Reichheld and his colleagues of Bain and Co who had an increasing recognition that measuring customer satisfaction on its own wasn’t enough to make conclusions of customer loyalty. After some research together with Satmetrix they came up with a single question that they deemed to be the only relevant one for predicting business success “How likely are you to recommend company X to a friend or colleague.” Depending upon the answer to that single question, using a scale of 0 to 10, the respondent would be considered one of the following:

net-promoter

The Net Promoter Score model

The idea is that Promoters—the loyal, enthusiastic customers who love doing business with you—are worth far more to your company than passive customers or detractors. To obtain the actual NPS score the percentage of Detractors is deducted from the percentage of Promoters.

How the customer experience drives NPS

Several studies indicate four main drivers behind NPS:

  • Brand relationship
  • Experience of / satisfaction with product offerings (features; relevance; pricing)
  • Ease of doing business (simplicity; efficiency; reliability)
  • Touch point experience (the degree of warmth and understanding conveyed by front-line employees)

According to ‘voice of the customer’ research conducted by British customer experience consultancy Cape Consulting the ease of doing business and the touch point experience accounts for 60 % of the Net Promoter Score, with some variations between different industry sectors. Both factors are directly correlated to how easy it is for customers to find what they are looking for on the web and how easily front-line employees can find the right information to help and guide the customer.

Successful companies devote much attention to user experience on their website but when trying to figure out how most visitors will behave website owners tend to overlook the search function. Hence visitors who are unfamiliar with the design struggle to find the product or information they are looking for causing unnecessary frustration and quite possibly the customer/potential customer runs out of patience with the company.

Ideally, Findability on a company website or ecommerce site is a state where desired content is displayed immediately without any effort at all. Product recommendations based on the behavior of previous visitors is an example but it has limitations and requires a large set of data to be accurate. When a visitor has a very specific query, a long tail search, the accuracy becomes even more important because there will be no such thing as a close enough answer. Imagine a visitor to a logistics company website looking for information about delivery times from one city to another, an ecommerce site where the visitor has found the right product but wants to know the company’s return policy before making a purchase or a visitor to a hospital’s website looking for contact details to a specific department. Examples like these are situations where there is only one correct answer and failure to deliver that answer in a simple and reliable manner will negatively impact the customer experience and probably create a frustrated visitor who might leave the site and look at the competition instead.

Investing in search have positive impacts on NPS and the bottom line 

Google has taught people how to search and what to expect from a search function. Step one is to create a user friendly search function on your website but then you must actively maintain the master data, business rules, relevance models and the zero-results hits to make sure the customer experience is aligned. Also, take a look at the keywords and phrases your visitors use when searching. This is useful business intelligence about your customers and it can also indicate what type of information you should highlight on your website. Achieving good Findability on your website requires more than just the right technology and modern website design. It is an ongoing process that successfully managed can have a huge impact on the customer experience and your NPS which means your investment in search will generate positive results on your bottom line.

More posts on this topic will follow.

/Olof Belfrage

Search Driven Navigation and Content

In the beginning of October I attended Microsoft SharePoint Conference 2011 in Anaheim, USA. There were a lot of interesting and useful topics that were discussed. One really interesting session was Content Targeting with the FAST Search Web Part by Martin Harwar.

Martin Harwar talked about how search can be used to show content on a web page. The most common search-driven content is of course the traditional search. But there are a lot more content that can be retrieved by search. One of them is to have search-driven navigation and content. The search-driven navigation means that instead of having static links on a page we can render them depending on the query the user typed in. If a user is for example on a health care site and had recently done a search on “ear infection” the page can show links to ear specialist departments. When the user will do another search and returns to the same page the links will be different.

In the same way we can render content on the page. Imagine a webpage of a tools business that on its start page has two lists of products, most popular and newest tools. To make these lists more adapted for a user we only want show products that are of interest for the user. Instead of only showing the most popular and newest tools the lists can also be filtered on the last query a user has typed. Assume a user searches on “saw” and then returns to the page with the product lists. The lists will now show the most popular saws and the newest saws. This can also be used when a user finds the companies webpage by searching for “saw” on for instance Google.

This shows that search can be used in many ways to personalize a webpage and thereby increase Findability.

Design Principles for Enterprise Search – The Philosophy of UX

In May I attended An Event Apart in Boston (AEA). AEA is a 2-day (design) conference for people who working with websites and was created by the father of web design Jeffrey Zeldman and the CSS guru Eric Meyer. The conference has a broad perspective, dealing with everything from how to write CSS3 and HTML5 to content strategy and graphic design. This post is about an AEA topic brought up by Whitney Hess: Create design principles and use them to establish a philosophy for the user experience.

Hess wants to create universal principals for user experience to communicate a shared understanding amongst team members and customers and to create a basis for an objective evaluation. The principles suggested by Hess are listed below along with examples of how these can relate to search and search user interfaces.

Stay out of people’s way

When you do know what people want stay out of their way

Google knows what to do when people visit their search at Google.com. They get out of the way and make it easy to get things done. The point is not to disturb users with information they do not need, including everything from modal popup windows or to many settings.

Create a hierarchy that matches people’s needs

Give crucial elements the greatest prominence

This means that the most used information should be easy to find and use. A classic example is that on most university webpages – it is almost impossible to find contact details to faculty members or campus address but very easy to find a statement of the school philosophy. But the former is probably what users mostly will try to find.

university website -  xkcd.com/773/

Limit distractions

This principle means that you should design for consecutive tasks and limit related information to the information you know would help the user with her current task. Don’t include related information in a search user interface just because you can if the information does not add value.

Provide strong information scent

There should be enough information in search results for users to decide if results are relevant. In an e-commerce site this would be the difference between selling and not selling. A search result will not be perceived as cluttered if the correct data is shown.

Provide signposts and cues

Always make it clear how to start a new search, how to apply filters and what kind of actions can be applied to specific search results.

Provide context

Let the user know that there are different kinds of search result. Display thumbnails for pictures and videos or show msn availability in people search.

Use constraints appropriately

Prevent errors before they happen. Query suggestion is a good way as it helps users correct spelling error before they happen. This saves time and frustration for the user.

Make actions reversible

Make it obvious how to removes filters or reset other settings.

Provide feedback

Interaction is a conversation so let the user know when something happens or when the search interface fetches new search results. Never let the user guess what happens.

Make a good first impression

You only have one time to make a first impression. It is therefore important to spend time designing the first impression of any interface. Always aim to make the experience for new users better. This could mean voluntary tutorials or fun and good-looking welcome messages.

So now what?

Are universal principles enough? Probably not. Every project and company is different and need their own principles to identify with. Hess ended her presentation with tips on how to create company principles to complement the universal principles. Maybe there will be future blog posts about creating your own design principles.

So what are your company’s principles?