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Breaking Blue is a full service market insight agency. We inspire organisations to make important decisions by shining a light on the big picture and the details that matter.

Which is why we're trusted research partners to so many leading organisations in the UK and across the globe.

Computers – hardware, Computers – software, FMCG – General, Food, Healthcare, Information Technology, Nutrition, Retail, Telecommunications, Transportation
Deliberative Research, Diary Studies, Ethnography, Executive/Industrial Interviews, Eye Tracking, Gamification, Group Discussions/Focus Groups, Online Communities, Qualitative, Quantitative
Behavioural Change, Brand/Branding, Business-to-Business, Consumer, Customer Satisfaction, Emerging Markets, New Product Development, Pricing, Product Testing, Usage & Attitude
Affluent, Digital Consumers, Ethnic Minorities, Hard-to-Reach, High Net Worth, Hispanic Markets, Indian, Kids, Senior Citizens, Youth/Teens
Africa, Central Asia, Central Europe, Middle East, Northern/Western Europe, Russia, South America, UK, USA, Worldwide
Senior Contacts

Kate Anderson ( Director)
Niall Baker (Research Director)
Rachel Cope ( Director)
Kate Downer (Research Director)

Breakdown of Personnel

Total Number of Employees: 51 to 100


11-13 Charterhouse Buildings
Tel: +44 (0)20 7627 7700
Establishment date: 1984

International Address

Breaking Blue
3955 N. Paulina
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Tel: +00 1844 815 8713

Breaking Blue
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Tel: +49 (0) 305 683 8577

All work and no play: A text analysis

Automated analysis of open-ended text survey data is an appealing prospect.  It offers benefits beyond cost savings and reduced lead times. Done successfully, it allows direct and in-depth access to participants’ views, expressed in their own words and without the intervention of an interviewer and a coder (which can lead to human error and variability).

Today, text analytics is a huge business and is among the most popular innovations within the current research landscape. However, within the research industry, there has been little change in usage in recent years, and awareness of the options available appears to be limited.   While just under half of research agencies report using, or are considering using, text analytics; awareness of the possibilities it offers appears to be somewhat limited, with many agencies describing straightforward coding exercises or Word Clouds.

We identified a need to look more closely at the true strengths of different approaches, the main barriers to their adoption, and how these might be overcome. For our experiment, we decided to use two approaches that can be applied easily to any sample of text—specifically, they both use a lexicon-based method rather than machine learning. This means that we focused on methods that any research company could apply “off the shelf” rather than methods that would need developing or adapting to the task in hand.

We also felt it would be useful to include more than one market. Leaving aside the issue of translation from other languages, we decided to include two countries that use different variants of English: the UK and India. We chose the UK and India because our technology clients have a specific interest in both of these markets, and we believed understanding more about general lifestyles in these markets would provide valuable background to the survey findings. 

We chose as our topic something that everyone understands and has an opinion about: work and leisure (or play).  In both India and the United Kingdom, we carried out more than 600 interviews with a sample of people aged between 18 and 65 years via a short online survey, including a spread of gender, age, and region in each market.  In the interview, we covered people’s attitudes to work and play, and the words they associate with each, alongside some contextual questions around demographics, Internet and app usage. The survey yielded a wealth of interesting data.

Using text responses we then contrasted two tools in analysing the output: Q’s text analysis component and Google Cloud Natural Language. We chose these tools as they can each be easily applied to survey data but are based on different analytic principles.

Analyzing our text data yielded learnings both about the associations with work and leisure in two contrasting cultures and about the understanding that analytics tools can bring to those associations. 

When it comes to work, some of the strong associations are not particularly surprising. The thickest line is between “money” and “time” because these are the two terms most often mentioned together. To many people, “work” means simply “time spent earning money.”  However, other associations are less predictable. For example, “hard” is linked to “boring” as we might expect but also to “fun.” While it might be initially surprising that “hard” is linked to “fun,” this association indicates the pleasure that can come from the challenge of hard work.  The word with the strongest relationship with work satisfaction is “boring,” and those using this word report much lower than average satisfaction.  Among the survey participants who do not use the word “boring,” the next most powerful word is “stress.” Those who mention “stress” but not “boring” report a higher level of happiness.

We conducted a similar analysis around leisure time, relating a scalar score that participants ascribed to their happiness with the amount of leisure time available to them, with their unprompted associations with leisure time.  Immediately, it is apparent that there are far fewer frequent associations in the top 10: people are much more varied in what they do and, therefore, associate many more words with the concept of “leisure.” As we might expect, “relaxing” and “fun” are mentioned frequently. “Friends” and “family” have a similar frequency, but the associations are different. “Family” has very strong links to both “fun” and “relaxing,” whereas “friends” is more weakly associated with these key features of leisure time; perhaps, the opposite of what we would expect. “Walking,” “reading,” and “TV” are all in the top 10 and have stronger links with each other than with “relaxing,” “fun,” or “enjoyment.” This exposes a difference in the way people respond: some provide emotions or feelings, and others specify activities.

We also found some surprising differences between the output of the two tools and between the text analysis metrics and scalar data.  For example, we see that the two approaches give different results when applied to the open-ended text from the UK. Q gives “leisure” a higher score than work, whereas Google does the opposite. In India, the scores are closer together, which reflects the general learnings from the study: work is generally more positively viewed in India than in the UK.

We concluded by discussing some of the key contemporary themes in text analytics and the likely future role of this method within market research and insight.  We believe there is clearly a need for some consensus on the processes and features of an optimum text analytic tool for insight researchers.  We have shown that different analytic tools can give different results when applied to the same data set. We encourage researchers across the industry to do more testing and exploration, as we have in this study.  We also concluded that there will almost certainly be some consolidation within the market of tools available. There is probably insufficient room for all of them and there will be more comparative evaluation, so that the more sophisticated and accurate tools survive.

 Click here to read the full article

Source: Breaking Blue

O2: “Brilliant to work with you all and can’t thank you enough for everything you did yesterday.  From beginning to end you’ve all been so easy to work with; totally professional and a huge amount of fun.  Potentially this will impact a huge amount of customers. Good result”

Dunnhumby: “I just wanted to say a massive thank you for all your hard work on the project, your contributions and the insights we have got off the back of them. We have had some really good feedback, with the senior stakeholder saying “We have the insight and traction to make a real difference to how we go to market and talks to our retail partners with the shopper at the heart of a multi-channel strategy.” This is huge testament to the hard work from the team at Breaking Blue: thanks for your continual consulting and advice. It’s been an absolute pleasure working with you all, and hopefully we will cross paths again soon.  Breaking Blue is one of a small number of suppliers who we partner with when we need high-quality, robust insights alongside our own analytics. We’ve commissioned Breaking Blue to deliver several projects since our working relationship began, and it’s been a really great experience.” 

Market Research Society: “As part of our training services, we deliver a series of webinars once or twice a year on various subjects, allowing attendees to dip into areas that they may be unfamiliar with or techniques that may help them in their work.   Breaking Blue have supported us in delivering some of these webinars over the last couple of years on topics such as Ethnography, Text Analytics, Eye Tracking and Digital Techniques in Online Surveys.   Delivered by practitioners who are working on current or recent projects with clients, means that their case studies and content is always relevant and pitched at the right level for our audience.   Their content is always appropriate to the short format of the webinars and the delivery is engaging, well-paced and attractive, with dual presenters using each other to add some interest to the delivery in an informal way.  The MRS is delighted with the support we receive from Breaking Blue and look forward to working with them again.” 

Deutsche Post – DHL: “The quality of work that BB produces for us is always high, even when working towards extremely tight deadlines. What is particularly impressive is their attitude – they are very flexible both in the way they work with us and in the way they answer research problems”

Canon Europe: “We’ve been working with Breaking Blue for several years now using different types of research. Throughout, we could always rely on BB’s professional attitude, quick response and willingness to go the extra mile. In the analysis and final presentation phases they really add value with their knowledge and experience of the industry.”

HP: “The rare ability to understand the details but to also understand how the research fits into the big picture market and business trends”

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