Quirkos is in Toronto!

Canadian flag in Toronto

This week’s Quirkos blog comes live from the IIQM Qualitative Health Research 2015 conference, in lovely Toronto. It’s been fun talking to people who are coming to the city for the first time, going up the CN Tower, watching the Blue Jays, and seeing the election results come in!

The conference has had a couple of themes, one of which was realist synthesis and evaluations, kick started by a keynote talk from Geoff Wang. He outlined his interpretation of the realist approach, and examining the world in terms of context, mechanisms, and outcomes. In this way we can plan and evaluate intervention strategies, and break down complex systems and interactions.

Integrating a qualitative approach into this method was alluded to in the talk, but with a focus in his view on realist synthesis using mixed methods. The debate and discussion in the afternoon continued this theme: for me the challenge is keeping a person and actor centred view.

I’ve also had the pleasure of meeting again with colleagues from the UK working on many qualitative different health issues, and also a chance to meet new faces from around the world. QHR is a very accessible and engaging conference, and people from all stages of their research career are both presenting and attending in force. It’s great to hear from research in so many different areas, and there is a really strong focus on experience in clinical settings.

And of course Quirkos is here as a sponsor! We have an exhibition stand in next to all the food (dangerous) and have been giving demonstrations to people from all over the world. And today we also have a demonstration session over lunch, which gives people a chance to see Quirkos in action.

So a big thank you to the whole conference team from the University of Alberta Institute of Qualitative Methods, especially Yvette, Bailey and Alex for running such a smooth ship, and making us all feel so welcome.



Tips and advice from one year of Quirkos

birthday cake CC by theresathompson


This week marks the one-year anniversary of Quirkos being released to the market! On 6th October 2014, a group of qualitative researchers, academics and business mentors met in a bar in Edinburgh, and at 8pm, version 1.0 of Quirkos was launched to the world. We then drank the bar dry of Prosecco (Champagne being much too expensive). Now Quirkos is being used in more than 30 universities across the world, and it's so exciting to see how people have used it for their PhDs, or in major research projects.


Obviously, the story didn't begin on that October night. It was the cumulation of nearly 2 years of planning, testing and development, not just of software, but of the skills and networks of many people behind the scenes. This blog post is mostly intended to share some of the things that went wrong, what went right, and to provide encouragement to those starting down the road to their own business for the first time.


There are frightening statistics about how many start-ups fail in the first few years. Some say 20% in the first year, others as high as 50% in the first two years. Whomever you believe, the rates are high, and this has to be expected. It's a competitive world out there and the cost of starting a business is high, nearly always higher than people anticipate (Quirkos included in this).


Now, 3 years after I quit my job to work full time on Quirkos, it feels like we have beaten the odds (so far). I also know many start-ups that didn't make it, many colleagues in Edinburgh who were embarking on their own adventures, who saw their business fade during that time. But it's interesting that all those people have still done well individually. Whatever gave them that entrepreneurial desire has led them all to new and different things, just maybe not what they originally planned!


At the risk of adding to the 3752 (est) other lists of start-up advice on the internet, here are some numbered pointers:

1. Don't develop qualitative research software
This is annoyingly specific advice, but has become a bit of a running joke for me. If you want to get poor quickly, qualitative analysis software is ideal for you, there is not a lot of money in it. It's a niche, and a very un-sexy one at the moment too. People always suggest that Quirkos should branch out into 'big-data' or add more quantitative features, but this is not really what I want to do.


Qualitative research is what I am passionate about, and what I know best. I didn't start this project to make a fortune, but because I felt software was holding people back from better understanding the world, and that was a gap in the market (my pain point).


2. Advice is free, but guidance is invaluable
Fortunately, it's really easy to get advice and support. Government initiatives (at least in Scotland and the UK) provide lots of basic training workshops and materials for free. We've benefited from advice from Business Gateway and Scottish Enterprise and their partners on strategy, funding, IP, you name it. However, these people won't tell you what to do, and obviously don't have very specific knowledge for your industry.


That is where our great mentors have come in, with knowledge from our specific area (software) and in working with our main markets (public sector and academic). This allowed us to plan a lot better, and make much more realistic projections about things like conversion rates, lead times, and even cultural differences selling abroad.



3. Awareness is everything
Insulting though it may be, people don't go out looking for your product. They are looking for a solution to that problem, and at first they don't know your name is Quirkos. They search for 'qualitative analysis software' in Google, go to qualitative research conferences, and read journals on all manner of related disciplines. It is never enough to 'build it and they will come' – you have to go to where your potential users will be.


Awareness is just the first step, then you need people to believe that you can help them. That can only be done by yourself to a certain extent, word of mouth and recommendations are much more important than corporate-sponsored hearsay. That's why I think that quality and customer happiness are so important, because people don't really believe what they read in adverts (I know I don't).



4. You ultimately invest in yourself
The last few years have been a roller-coaster, but I have learned so much. I learnt about running a business, accounting, tax, sales, marketing, search engine optimisation, PHP, Javascript, SSL certification, social media, software testing, promotional printing, exhibitions, conferences, planning, strategy, and on and on.


I've always thought at the back of my mind, what if this fails? Is all that time and money lost? Well, yes, but through the experience I have learnt so much, and developed real skills in real situations. I can't say I was worried about finding employment afterwards, since I was always adding so much to my CV.



5. Getting funding costs money and time
However you want money: grants, competitions, loans, equity investment, all these things are very expensive in terms of time and paperwork. We spent a long time going to the final (term-sheet) stages of angel investment, before deciding that the timing wasn't right, and the costs of the transaction were going to be too high.


So you need to pick your battles carefully, but plan for redundancy. Assume that only 1 out of 3 sources of funding will come through, so always have a back-up ready to pursue. For Quirkos, a friends and family round worked really well for our first funding cycle, and allows us flexibility in the future.


6. Critical Path Analysis
I'm a little obsessed by this, but I have to admit, I actually learnt it from a children's book decades ago. It was 'Truckers' by Terry Pratchett, and it describes it thus: “It’s something called critical path analysis. It means there’s always something you should have done first. For example, if you want to build a house you need to know how to make bricks, and before you can make bricks you need to know what kind of clay to use. And so on”.


I actually do this in my head all the time now, whether I am doing a marketing strategy, releasing software or even making dinner. It just means working backwards from what you want to achieve, and working out the things that will hold you back if you don't get them done first. For example, if I am having flyers handed out at a conference, they need them 3 days before the conference. To get there, they have to be in the post 5 days before that. They take 3 days to come back from the printer, take me 1 day to design, and my colleague who has agreed to proof read them is on holiday next week. So quickly I can see that the last day I can do the first draft of the flyer is 17 days before the conference!


In a small business you end up doing everything, so being able to plan your time like this is essential. With experience, you also learn that the uncertain part in the chain is always when you have to rely on other people (who can be late, sick, forgetful) so you always factor in more time for the post, printers, and proof readers. Not that you won't be late, sick or forgetful yourself sometimes, but generally you know when this is happening. It's no coincidence that most of the 'Truckers' book is actually about managing people (seriously, it's the best management book I've ever read).


7. Network, network, network
Actually, I hate netwo rking, or at least that kind of endless socialising in large groups without direct purpose . But very targeted networking is essential to getting the word out, and cultivating positive relationships with key people and organisations is essential. A case-study or positive review is always more valuable than just a quick sale, and there are always influential people in any industry who have a large audience. Engaging with these networks is essential.



8. Love, love, love
I couldn't have done this on my own. Over the years so many people have given time, support, money and advice, and I can't thank them all here. If I was thinking in terms of social capital (Putnam style) I would have used up a lifetime of favours and goodwill. To be honest, I don't think I could have got this far without them, and the  love and belief from friends, family, colleagues and spouse. So I'm going to finish on a song, and say “Thank You!”


  “When you were giving me advice, that I seldom ever took
  But your head never shook - That's love


  Both knowing you were right, never shook it left and right
  Just gave me that look - That's love


  When I had to learn the hard way, and you would let me fall
  But never did it out of spite - That's love


  You told me never burn a bridge
  If you build it, then you need it
  Whether a river or a brook”


That's Love – Oddisee (from the album The Good Fight)
Performed live here from the awesome NPR Tiny Desk series!



Play and Experimentation in Qualitative Analysis

by Artaxerxes @ commons.wikimedia.org/wiki/File:Our_Community_Place_Sandbox.jpg

In the last blog post article, I talked about the benefits of visualising qualitative data, not just in the communication and dissemination stage, but also during data analysis. For newcomers to the world of qualitative research, the analysis process often seems intimidating and mysterious. How is the coding framework created? How are decisions made about categorising quotes? How do I know I have taken the right approach? When do I know when I am finished?

But as qualitative researchers will often tell you, the analysis process is so much more than a step-by-step regulated process. It is often like an exploratory journey, during which connections will be discovered, hypotheses challenged, and new unexpected paths will be taken. Personally I feel that qualitative analysis is a very creative process, something that Patton (2014) describes as drawing from “both critical and creative thinking – both the science and the art of analysis”.

Play is often the best way to work with qualitative data. Somehow it often feels more enlightening to explore themes and codes with Post-it notes, and manipulate them in a physical way – moving them around as part of a discussion and experimentation in grouping. The thematic bubbles in Quirkos can be manipulated in the same way, grouped and ungrouped by pulling them around, endlessly rearranged or grouped by colour.

I use the term play deliberately, as informal experimentation with data can uncover new things, and encourages the user to try different approaches. I really wish to encourage this during qualitative analysis, because it is so often productive. The graphical and interactive interface in Quirkos is key to this, as is the instant undo and redo buttons: it’s important to be always able to go back, because play so often leads nowhere, but occasionally somewhere very valuable.

Even in adults, this play and experimentation is important part of learning and enacting (Malamed 1987*), whether it is in formal education classes, museums, or in coaching and mentoring.

Because of this, I have long believed that visualisation should be an integrated part of the analysis process, because it is inherently iterative and interactive. I know I am not alone on this: Bradley, Curry, Devers (2007) state that “there is general agreement that analysis is an ongoing, iterative process”. This applies to developing a coding structure, as well as the act of categorising text. For that reason, any approach that not only keeps researchers close to their data, but allows them to play with it, I find inherently beneficial.

The limitation with most software approaches is that they treat these exploratory steps as distinct events and phases, not as part of the process. So if you want to see connections in a data – run a report. If you want to see the text under a code - generate a summary. To visualise a topic, generate a graph of a particular node: all through a series of button clicks and separate windows. To me, this interrupts the discovery process in the same way that a scratched CD track stops the flow of music.

We designed Quirkos to help people play with their data. To make visualisations live and interactive, and to make it touch-friendly, colourful and forgiving. We try not to limit how researchers can sort and group their themes, but make flexible tools that people can adapt to their own preferred ways of working. And of course, to let people share their work with others and extend that creative process to teamwork, because the discussion and challenge that comes from engaging with other researchers is often as valuable as hours (or days!) of solitary coding.

Most of all though, we wanted software that freed the imagination to take more creative approaches, rather than tying researchers down to literally thinking inside a box or spreadsheet. Rather than a node-tree, the primary interface in Quirkos is called the canvas, and for a deliberate reason. It’s a sandbox for creative play, and space for that ingenious combination of art and science.

*Melamed, L. (1987). ‘The role of play in adult learning’, in Boud, D. & Griffin, V.(eds.), Appreciating adults learning: from the learner’s perspective, London: Kogan Page, pp13–24


Freeing qualitative analysis from spreadsheet interfaces

spreadsheets and quirkos to visualise qualitative data

The old mantra is that a picture tells a thousand words. You’ve probably seen Hans Rosling’s talks on visualising quantitative data, or maybe even read some of Edward Tufte’s books on data visualisation. The thrust of the argument is clear: “Good displays of data help to reveal knowledge relevant to understanding mechanism, process and dynamics, cause and effect.” (Tufte 1997).

This chapter also describes the dangers of obscuring data in large amounts of text. He provides examples of the reports that were used to decide to launch the Space Shuttle Challenger on a morning that dipped below freezing, despite concerns that the rubber O-rings in the rocket booster would not function at this temperature. They failed, leading to the death of the crew.

Tufte produces a graph of temperatures at which the shuttle had been previously launched, visually showing how far below previous experienced temperatures this launch was: a vast improvement over the cold technical language presented to management. This illustrates the challenge in summarising and presenting not just quantitative statistics, but also the qualitative world of meetings, discussion and decision making.

However, why shouldn’t this apply during the analysis of qualitative data? Obviously it does, we can quickly identify visual elements like graphs, and relative size, and so word clouds and graphs are all popular export methods from qualitative software. But that analysis process, not just the end product is a very complicated cognitive process, and where it is important for researchers to see the big picture; to get an overview of how things are emerging. Visual representations here can show the researcher what is emerging from the data, and a birds-eye view of the project. The difficulty is that at the same time, there is a need to drill down, and examine the minutiae of one quote or connection.

So how can we get a graphical approach during the analysis process as well as the reporting and summaries? Generally software packages use a spreadsheet-style interface, where working with qualitative data is restricted to columns and rows, quickly collapsed into quantitative representations and overviews.
A project like ‘nineteen’ aims to go part way to address this: by making quantitative and qualitative data from spreadsheets more visual. It turns data into more graphical and colourful representations, which help users see patterns and connections in the data.

To a certain extent, this approach can be done in Excel, using Pivot tables and conditional formatting. It can really help tabulated data ‘pop’, and even simple things like colour coding for particular respondents or themes can make it much easier to find quotes and similarities in qualitative data. (Some day, I am going to have to write a blog post on using Excel for qualitative research!). However, this is actually one way in which most qualitative software is inferior to Excel, because it is very difficult to apply any sort of dynamic visualisation or colour to the data while you work with it to illuminate it in different ways.

Quirkos makes not just reports and summaries visual and engaging, but also the analysis interface itself. I think this is vital, because users need to get constant feedback during the analysis process. If a researcher is forced to generate a new graph in a new window to get a project overview, they are taken out of the flow of the process. Results must be live and interactive, and Quirkos aims to provide that as much as possible.


The same goes for search and retrieve, a separated list of results is not illuminating to the researcher, the user is presented with compartmentalised data which begins to lack context. Nearly all the other qualitative software packages have this model: a query is a process, and the results another window of data. In Quirkos, we designed a separate query view that is dynamic and interactive. Results are shown again with colour coded bubbles representing number of hits, and the quotes are integrated into the screen to connect back to the full data source. That way, you get the overview, and the context of the data together. I know that people really love the side-by-side comparison view in this screen too, because again it is about getting that context, and again in a visual way.

All the qualitative analysis software out there will let you generate reports based around graphs and visual methods to communicate qualitative data. However, only Quirkos integrates this into the analytical process, making sure you get constant feedback. For myself, and many other qualitative researchers, this is the most important (and lengthy) part of a project, and ways to help people to spot important findings in the data should be fully integrated into the workflow, not delivered as a side-step.


10 reasons to try qualitative analysis with Quirkos

10 quirkos qualitative bubbles

Quirkos is the newest qualitative research software product on the market, but what makes it different, and worth giving the one-month free trial a go? Here’s a guide to the top 10 benefits to switching to Quirkos:


1. Ease of Use
When we ask people what they like most about Quirkos, we hear one word: ‘intuitive’. We find that most people can get going after just watching a 5 minute video, since the interface is so graphical.

2. Everything is Visual
Bubbles grow as data is added. Colours help your group your themes, and clusters move bubbles together as connections emerge. Graphs show you key stats from your sources. This is not like working with a spreadsheet, Quirkos turns exploring text into an immersive process.

3. Speed of coding
Researchers spend most of their time coding sections of text, so we try and make it as quick as possible. Adding text to a theme is a simple drag and drop operation, but there are also keyboard shortcuts that can make adding text to multiple themes a breeze (or a whirlwind!).

4. Visual exploration
Of course Quirkos has great tools to explore your data once it is coded. But they are all based around visual feedback, giving you an instinctive feel for emerging findings. For example, side-by-side comparisons let you see how different groups of participants are responding.

5. Custom reports
Your work is not useful unless you can share the results. Our reports are very customisable, letting you choose which sections and detail to show, and naturally are full of graphical ways to represent your text data.

6. Connect with other applications
Researchers need to be flexible in how they work, which is why Quirkos supports bringing text in from all kinds of software like Word, PDFs and on-line survey platforms. But it also lets you get data out as well, to explore further in Excel, SPSS or even back to Word.

7. Free training and support
All our support options are available on-line with no subscription or fee. This includes detailed manuals, one-minute video guides, and interactive tutorials, as well as example projects to experiment with. Save time and money in training with software you can teach yourself. If you get stuck, e-mail or Skype the developers directly: qualitative researchers who are there to make your research go smoothly.

8. Cross-platform with no bumps
Work on Windows, Mac or Linux with an identical interface and features everywhere. You can save work on one system and keep going on another with no issues.

9. Cheap as chips
We think we are the cheapest qualitative software around, especially for our student licence. Also, our licences don’t expire, so you can keep working on your data for year after year.

10. Try for free
Our free trial is exactly the same as the full version, and gives you a month to try before you buy. If you like working with Quirkos, you can just buy and enter the licence code, and away you go.

We are proud of our software, which is why we always like people to try before they buy, and see the benefits for themselves. Download the free trial from here, and make your qualitative analysis a less stressful process!


Fracturing and choice in qualitative analysis software

broken glass CC by Jef Poskanzer


Fundamental to the belief behind starting Quirkos was a feeling that qualitative research has great value to society, but should be made accessible to more people. One of the problems that we frequently saw with this was the difficulty that qualitative researchers had in choosing and using qualitative analysis software. Choice is great, but social scientists have to choose between many different software packages, and IT departments have to provide installations and technical support for the systems that different users want.

This month the market leader QSR International will release a new version of their Nvivo software for Windows, with a very different model – it will be split into three different versions, ‘Starter’, ‘Pro’ and ‘Plus’. Each version has a different features enabled or disabled, and will be offered at a different price point. This seems potentially laudable, for example introducing a new basic version that is (hopefully) cheaper, should allow more people access to this well-known qualitative software.

However, it also seems to greatly complicate the position for users, systems administrators and educators, who now have to deal with no less than five different versions of Nvivo! In addition to the Starter, Pro and Plus for Windows, there is a separate version for Mac (with different capabilities, interface and file format), as well as the server based Nvivo for Teams. It raises many difficult questions: Where should new users start? What versions should institutions and IT departments purchase and support? How can those offering training provide sessions that will be useful to all these disparate users?

At the same time, I understand that the new Windows versions have had all the icons redesigned, breaking continuity for existing users, and instantly making textbooks and teaching materials obsolete (yet again: I remember the complaints about the new layout when the last-but-one version of Nvivo came out). Of course guides always need to be updated to take account of new features, but changing the icons means that materials covering even basic functions will need to be reworked, or will become confusing.

Obviously I am discussing a competitor’s project here, but one that I find useful, and have personally used many times in different research projects. I can’t help the feeling that the additional fracturing of the Nvivo user-base will further complicate the situation for end users, especially those in large organisations. These may or may not upgrade to the latest version, and I know there is always a few years of grief trying to work with other teams who have a different and incompatible version, as well as finding training for the version you are working with.  But in addition, it may not always be clear for students what version their department has access to (or that they can take home), and so which features will be available to them.

Yet it doesn’t have to be this way, MAXQDA for example manages to provide the same software for Windows and Mac, with the same interface and compatible files. Yes, they also have options for a ‘pro’ and ‘free’ read-only version, but I feel the differentials are much clearer, and from a IT and support point of view, rollout is much simpler.

Quirkos continues to have just one version of the software, offering all the same features to everyone. It also has exactly the same capabilities and interface on all platforms, Windows, Mac and Linux, and uses files that are an open standard, and immediately compatible across all operating systems. We also make our updates free, to help everyone to work on the same version of the software, and don’t break compatibility with older versions! We think that this is the best way to develop and release software, and will continue to do so – none of our users will be seen as poor-cousins.


Levels: 3-dimensional node and topic grouping in Quirkos

levels and groups in Quirkos


One of the biggest features enabled in the latest release of Quirkos are 'levels', a new way to group and sort your Quirks thematically. While this was always an option in previous versions, they are now fully integrated into the search and query views, making them much more useful. However, this is a tricky thing to describe conceptually, so this post will give a few use-case scenarios.


In Quirkos, the topics or themes that you code to (called nodes in Nvivo) are represented as bubbles. These can be moved around the canvas to be grouped by location, given similar colours, or arranged alphabetically or by size. However, they can also be grouped into topics with sub categories, by dragging a bubble onto another one. This creates a parent-child relationship where the parent category, say 'Drinks' can have any number of sub-categories, such as Juice, Tea, Water etc. It is also possible to have sub-sub categories (grandchildren), so in this example, you might have types of Juice such as Orange, Apple and Cranberry.


So far so good – this allows you to quickly see the quotes you assigned to all types of Drinks, or just the Juices using the Hierarchy view. However, this parent-child grouping has a limitation, in that a sub category, say Orange Juice, cannot belong to more than one parent. So we can't describe Orange Juice as being a type of Drink, as well as a form of Fruit.


This is where the 'level' function comes in. A Quirk can belong to any number of levels, which can contain any number of Quirks. So if you created a level called Fruit, by right clicking on any Quirk, selecting the Quirk Properties, you will see all the levels defined in the project, and the Quirk can belong to any number of them. So Orange Juice can belong to a level called 'Fruit', along with Apples, and Oranges, while also being defined as a sub-category of Drink. Alternatively, you could have a level for Drink, and describe some Quirks as being a Drink as well as a Fruit.


The other way that the levels can be helpful is when working on a large project that might have multiple outputs. If you are working on a PhD thesis, or a long report, you might have chapters that only cover certain themes. With the levels function, you can define Quirks that will be relevant to a particular chapter or topic, and see results or reports for just that level. This way, if you are writing about nutrition, the Orange Juice theme can belong to the chapter for Drink and for Fruit, and you will see relevant quotes for each chapter.


To work with levels, just right or long click on any Quirk, and select the Quirk properties. In this box you will see a button for 'Levels Editor', this can be used to define, change or remove levels in the project. Click Save once you are done. Once some levels have been created, you can use the slide toggles shown above in the Quirk Properties dialogue to assign that Quirk to any number of levels. You will obviously need to go though and do this for all the Quirks in the project you want to put into a level.


the levels assignment in quirk properties


Once you have done this, you can choose the corresponding level as a filter option in the Query view (LV) or in the search results, to generate reports or see text search results from text coded in one or more levels.


Everyone likes to work with their themes or nodes differently, and now we have many more ways to group and sort them. You can arrange them physically around the canvas, give them meaningful colours, create a grouped stack with sub-category relationships, and also group them by 'level' like an overlapping Venn diagram.


We are going to improve the ways you can work with levels in the future, including visualisations of levels on the canvas, but we want your feedback for the best way you would like to see this! Should Quirks belonging to a level get a certain colour halo, or be shown in a literal 3D level view like levels in a building? Should the canvas rearrange on command to group all Quirks belonging to certain levels together? Is the term 'levels' the right one to use in this situation? The more people are using Quirkos, the more different ways people are working with it, and we want to choose the best and most flexible ideas, so let us know!



Quirkos for Linux!

quirkos loves linux


We are excited to announce official Quirkos support for Linux! This is something we have been working on for some time, and have been really encouraged by user demand to support this Free and Open Source (FOSS) platform. Quirkos on Linux is identical to the Windows and Mac versions, with the same graphical interface, feature set and file format, so there are no issues working across platforms.

Currently we are only offering a script based installer, which can be downloaded from the main download page. In the future we may try and offer some packaged based deb or rpm downloads, but for the moment there are two practical reasons this is not feasible. First, it is much easier for us to provide one installer that should work on all distributions, regardless of what package manager is utilised. Secondly, Quirkos is build using the latest version of Qt (5.5) which is not yet supported in most stable distributions yet. This would either lead to dependency hell, or users having to install Qt5.5 libraries manually (which actually take up a lot of space, and are themselves based around a script based installer). However, we will revisit this in the future if there is sufficient demand.


Most dependencies can be solved by installing qt5 from your repository, although most KDE desktops will already have many of the required packages.


Once downloaded, you must make the installer file executable. There are two ways to do this, either by running “chmod +x  quirkos-1.3-linux-installer.run” from the shell in the directory containing the installer, or an alternative GUI based method in Gnome is to right click on the file in the Nautilus file browser, select the properties tab, and then tick the 'Allow executing file as program' box.

Once you've done this, either double click on the file, or run in the bash terminal with “./quirkos-1.3-linux-installer.run”. Of course, if you want to install to a system wide folder (such as /opt/bin) you should run the installer with root permissions. By default Quirkos will install in the user's home folder, although this can be changed during the install process. An uninstaller is also created, but all files are contained in the root Quirkos folder, so deleting the folder will remove everything from your system. After installing, a shortcut will be created on the desktop (on Ubuntu systems) which can be used to run Quirkos, or dragging the icon to the Unity side-bar will keep the launcher in an accessible place. Otherwise, run the Quirkos.sh file in the Quirkos folder to start the application.

If you are looking for FOSS software for qualitative research, try RQDA, an extension for the versatile R statistical package, an open source alternative to SPSS. There is also Weft QDA, although this doesn't seem to have been updated since 2006. It's worth noting that both have fairly obtuse interfaces, and are not well suited for beginners!

We have tested Quirkos on numerous different systems, but obviously we can't check all iterations. So if you have any problems or issues, PLEASE let us know, this is new ground for us, and indeed is the first 'mainstream' qualitative analysis software to be offered for Linux. In fact, tell us if it all works fine as well – the more we hear people are using Quirkos on Linux, the better!



Quirkos 1.3 is released!

Quirkos version 1.3 on Linux

We are proud to announce a significant update for Quirkos, that adds significant new features, improves performance, and provides a fresh new look. Major changes include:

  • PDF import
  • Greater ability to work with Levels to group and explore themes
  • Improved performance when working with large projects
  • New report generation and styling
  • Ability to copy and paste quotes directly from search and hierarchy views
  • Improved CSV export
  • New tree-hierarchy view for Quirks
  • Numerous bug fixes
  • Cleaner visual look


We’ve made a few tweaks to the way Quirkos looks, tidying up dialogue boxes and improving the general style and visibility, but maintaining the same layout, so there is nothing out of place for experienced users.


There is once again no change to Quirkos project files, so all versions of Quirkos can talk to each other with no issues, and there is no need to do anything to your files – just keep working with your qualitative data. The update is free for all paid users, and a simple process to install. Just download the latest version, install to the same directory as the last release, and the new version will replace the old. There is no need to update the licence code, and we would recommend all users to move to the new version as soon as they can to take advantage of the improvements!


Lots of people have requested PDF support, so that users can add journal articles and PDF reports into Quirkos, and we are happy to say this is now enabled. Please note that at the moment PDF support is limited to text only – some PDF files, especially from older journals that have been scanned in are not actually stored as text, but as a scanned image of text. Quirkos can’t read the text from these PDFs, and you will usually need to use OCR (optical character recognition) software to convert these (included in some professional editions of Acrobat Reader for example).


We have always supported ‘Levels’ in Quirkos, a way to group Quirks that can work across hierarchical groupings and parent-child relationships. Many people desired to work with categories in this way, so we have improved the ways you can work with levels. They are now a refinable category in search results and queries, allowing you to generate a report containing data refined by level, and a whole extra dimension to group your qualitative themes.


Reports have been completely revamped to improve how you share qualitative data, with better images, and a simpler layout. There are now many more options for showing the properties belonging to each quote, streamlined and grouped section headings, better display of hierarchial groupings, and a much more polished, professional look. As always, our reports can be shared as PDF, interactive HTML, or customised using basic CSS and Javascript.


Although the canvas view with distinctive topic bubbles is a distinguishing feature in Quirkos, we know some people prefer to work with a more traditional tree hierarchy view. We’ve taken on board a lot of feedback, and reworked the ‘luggage label’ view to a tree structure, so that it works better with large numbers of nodes. The hierarchy of grouped codes in this view has also been made clearer.


There are also numerous bug fixes and performance improvements, fixing some issues with activation, improving the speed when working with large sources, and some dialogue improvements to the properties editor on OS X.


We are also excited to launch our first release for Linux! Just like all the other platforms, the functionality, interface and project files are identical, so you can work across platforms with ease. There will be a separate blog post article about Quirkos on Linux tomorrow.


We are really excited about the improvements in the new version, so download it today, and let us know if you have any other suggestions or feedback. Nearly all of the features we have added have come from suggestions made by users, so keep giving us your feedback, and we will try and add your dream features to the next version...



Bing Pulse and data collection for market research

bing pulse example


Judging by the buzz and article sharing going on last week, there was a lot of interest and worry about Microsoft launching their own market research platform. Branded as part of ‘Bing’, their offering, called ‘Pulse’ has actually been around for a while, and is still geared around collecting feedback from live events, especially political discussions.

I can see why this move might have a lot of companies worried, it seems to me that the market research arena is crowded with start-ups and established firms offering platforms, or ‘communities’ for collecting participant data. There’s LiveMinds, Aha!, VisionLive, a quick search will bring up dozens of competitors. So an entry into the market from an organisation with deep pockets and brand awareness like Microsoft may well have many looking to see how this develops. However, with my own limited time with Pulse, I don’t think there is much to worry about yet.

First of all, Pulse is currently entirely focused on one niche, feedback on live events. There are no tools to do anything like advert or creatives validation, no proper survey tools or interactive online focus groups. The MO is very much quantitatively focused, with very little option to capture qualitative feedback at this time. Secondly, it seems to have a lot of limitations, and in this beta state, almost no documentation.

I quickly got stuck trying to create a real-time voting question, with a mandatory box for ‘response theme’ that was greyed out, but wouldn’t continue without being completed. The ‘help’ tools just link to a generic Bing help website, which don’t contain any content about Pulse. The layout is a little confusing, getting you stuck in a strange loop between the ‘Live Dashboard’ and ‘Pulse Options’, and it’s also slow: get used to seeing the little flapping loading logo after every action.


As for integration, the only option at the moment seems to be the API, which only has four available calls. There doesn’t seem to be any way to get results (especially those not covered by those API calls) out from the platform: I can’t see any CSV export or the like. Also, considering the powerful analytic options available through the Azure platform, it’s disappointing not to see any easy integration there. In short, far from being a quick DIY solution, you will need someone to programme yet another API into your platform to do anything more than look at a few graphs on the Pulse platform.


I want to stress that this was hardly a detailed review and test of the capabilities of the platform, my opinions are based just on playing with it for an hour or so. However, it is nice to be able to try it out with just a registration, personally I don’t like products where the demo is locked away and difficult to try out. It’s a competitive market, and I feel more inclined to trust software that the developers aren’t shy of showing off!


Now, I understand that most market research providers are not so much worried about the current feature set of Pulse, but what this entry into the field means in the future, especially for a product that Microsoft is content to offer for free at this time. But I would echo some of the comments made in the Greenbook article by Leonard Murphy, that it usually doesn’t make sense for market research firms to do their own their own quantitative data collection. The future, he says, is integrating with data collection tools and adding value in terms of insight, custom development and consultation.

And that is the crux with all these market research platforms: they are primarily data collection tools, with limited analytics. Pulse doesn’t seem to have anything on this front at the moment, but with too many of these solutions, the insight stops with a couple of graphs or statistics. I feel there is still the need to integrate with another tool, or draw from extensive market research analytic experience to make anything from the data once it has been collected. It maybe that most clients don’t expect or require any kind of rigour in the breakdown of project results, especially when it comes to qualitative data. I am still yet to see anything that looks to me like a true end-to-end platform for market research, but am willing to be proved wrong!


At the moment, there are some great and flexible tools for collecting customer data online, be it quantitative or qualitative. But these are ubiquitous, and very cheap to run – we host an online survey platform for our customers for free, just as a convenience. Yet getting to answers and insight from that data usually requires an additional analytical step, especially for qualitative research. As I’ve said before,  the most difficult step is understanding the data and how you integrate analytics into your workflow. Increasingly the data collection platform you choose, and how much you pay for it will not be an issue.