Picture of a bridge in Lisbon

Major update on mobile market research

For a few years there have been relatively few new findings about mobile market research. We have seen the share of online surveys completed via mobile increasing and we have seen the number of mobile only studies (studies that require a smartphone, for example location-based, in-the-moment and smartphone ethnography) increasing. But the overall picture has remained fairly constant in terms of advice and practice. However, the picture has now changed. Last week saw five days of short courses and presentations in Lisbon, Portugal at the ESRA Conference (European Survey Research Association). There were over 700 presentations and most of the leading names in survey, web, and mobile research were present (including: Don Dillman, Mick Couper, Google’s Mario Callegaro, SurveyMonkey’s Sarah Cho, Edith de Leeuw, Roger Tourangeau, GfK’s Randall Thomas & Frances Barlas, and my colleague Sue York). There were more than 20 presentations particularly relevant to mobile market research – making it one of the largest collections of reports and findings from experiments reported anywhere. In this post I set out my key takeaways from the ESRA Conference in terms of mobile market research. But, I may update this post when I get access to all of the presentations and […]

People falling asleep in a presentation

Why Use Bullets in a Presentation? The difference between good bullets and bad bullets.

Every so often there is an upsurge in criticism about the use of bullets in presentations, often linked to criticism of PowerPoint. I agree that any presentation that is not engaging, understandable, and memorable is likely to be a failure. But I do not think that means bullets do not have their place. Lets’ consider a famous and influential bullet list, at least for people who live in a culture or group for whom the Bible as a reference. The Ten Commandments are an example of a bullet list. Do you think these points would have lasted millennia if they were buried in the text, or depicted as an infographic? Another place where many of us see a bulleted list, indeed a list with sub-lists, is when we read a menu. The major list might be Starter, Main, and Dessert – with each of these three broken into several options. For example, the options for the Main Course bullet list might be Steak OR Cod OR Macaroni Cheese. Why do we use bullet lists? Although bullet lists are frequently criticized, they remain in very common usage. That is because, when used correctly, they fulfill a specific set of benefits. These benefits include: A.      Belonging […]

Image depicting Agile

What is Agile Market Research?

One of the hottest terms in market research at the moment is the word ‘Agile’. However, there is not a lot of clarity about what exactly it means and how it should best be utilised. Two definitions, with Two Different Derivations One of the reasons that there can be confusion around the term agile market research is that there are two separate definitions, based on two different perspectives and derivations. Agile, as in responsive, a term that has been used in research for many years. Agile, as in the Agile Movement, a modern method of project management often identified with the software industry and concepts like minimum viable product, sprints, and scrums. In this post, I am going to use agile with a lower case ‘a’ for the first of these meanings, and Agile with an upper case ‘A’ when referring to the adoption of the Agile Movement approach to market research. Responsive Research is Often Bespoke Research Using the word agile in its more traditional way, it is often used to describe research that is flexible in the sense of being designed specifically for the needs of a client/project. Whilst this form of research typically needed to move fast, […]

Image representing open data

Open data, what does it mean and why do we need it?

The post below is a guest post from Will Poynter, lead engineer at CLOSER Discovery, based in the UK. There is a common misconception that open data means making data public. This is one, very narrow, way of opening up data. What is open data? I prefer to refer to opening up data, an action, rather than open data, a noun. This is because open data suggests an absolute state, while openness is relative to the environment and user. I.e. data is not either open or not, it exists along a spectrum depending who you are, what you would like to do with the data and where we are in the timeline of the data. Before we get too abstract let me set out an example. Let’s use a teacher’s notebook. This notebook contains everything for our teacher, including comments on pupils, marking, ideas for lesson plans and personal notes. Currently our teacher keeps this notebook to himself and shares it with no one; definitely not open data. Now suppose our teacher would like to begin opening up the data inside his notebook so that he can share ideas for lesson plans with all the teachers in the school. Even though […]

Big Data

Big data, what is it and will it be here to stay?

The post below is a guest post from Will Poynter, lead engineer at CLOSER Discovery, based in the UK. Although the term “big data” has been in use since the 1990s, it has gained popularity massively over the last 5 years. Technological terms come in and out of fashion all of the time, e.g. we still have websites, but we do not call them the ‘World Wide Web’ anymore. We also see terminology evolve over time, e.g. ‘social network’ has been replaced by ‘social media’. So, why has “big data” become common parlance, and will it be fleeting or is it going to stay? Well, big data has been used to describe datasets of all shapes and sizes. But the key theme is datasets too large to be handled using conventional methods. Either the dataset has become too large to either be collected, analysed or managed efficiently, or a combination of all three. Therefore, big data indicates the need for new tools and methods for handling large quantities of data. One key area that generates “big data” is passively collected data. E.g. accelerometers. Accelerometers are being used to collect very useful information about; how active a person is, how much they […]

Picture of Chicago

Should Ambitious Market Research Companies Adopt the American Way?

Market Research is becoming more and more USA dominated. The ESOMAR revenue figures for market research show that in 2006 the USA accounted for 34% of all market research. By 2015, the USA accounted for 45%. By contrast, many other key countries have declined in terms of their share of the global total: France from 8% to 5%, Germany from 8% to 7%, Japan from 5% to 4%, and Brazil from 2% to 1%. Does this shift, from the rest of the world to the USA, indicate that the USA model is better? Should aspiring research companies, ones that want to expand internationally, become more like USA companies? In my opinion, there is some merit in the benefits of the USA model, but (as I will explain in this post), I think there are also benefits in what is sometimes called the ‘mid-Atlantic model’ – something that lives part way between Europe and North America. Why has the USA done so well? First, let’s look at why the USA has grown so strongly, in terms of market research. Key reasons include: The USA economy has grown, which facilitates growth in MR. The dollar has gone up in value – making […]

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Do you work internationally? Read ‘The Culture Map’ by Erin Meyer

I have just read The Culture Map by Erin Meyer and it has excited me more than anything I have read for several years (since Chip and Dan Heath’s Made to Stick in 2007). If you work internationally or if you manage cross-cultural teams I strongly suggest you read this book – it is useful, enjoyable, and an engaging read. The book is a forensic analysis of some of the key differences between cultures and how these differences create problems when people from different backgrounds work together. The book is also a manual for how to deal with many of these problems. I don’t want to steal any of the book’s thunder (I want you to buy it and read it), but a couple of examples will help illustrate the insight and usefulness of the book. 1) A French businesswoman in America. Early in the book Meyer uses an anecdote about a French businesswoman to illustrate a non-obvious clash between French and American styles. The businesswoman was transferred from Paris to the USA to lead a team of Americans. She was looking forward to the challenge as she appreciated the direct and honest style of Americans (e.g. ‘say what you […]

Scientific Method Flow

What is the scientific method, and how does it relate to insights and market research?

I often hear people grumble that researchers, marketers and insights professionals have forgotten (or have never learned) the ‘scientific method’. However, there is usually very little discussion about what the scientific method is and how it should be applied. In this post, I am going to share a definition of the scientific method and discuss how it can be applied to the process of finding insights in commercial organisations. A dictionary definition: Here is a definition of the scientific method from the American Merriam Webster dictionary: “Principles and procedures for the systematic pursuit of knowledge involving the recognition and formulation of a problem, the collection of data through observation and experiment, and the formulation and testing of hypotheses.” The definition is a start, but it is not a road map for teaching or using the scientific method, so let’s map it out and then explore how to use it. Scientific Method Flow Chart The scientific method uses systematic processes to move from the need to solve a problem, via the creation of a hypothesis (or hypotheses), to testing the usefulness of the hypothesis. The flow chart below spells out the key steps in this journey. 1 Defining the Problem The […]

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Politicised discourse – is Market Research Attuned?

The post below is a guest post from Edward Appleton, Director Global Marketing at Happy Thinking People, based in their Berlin office. We live in unsettled times – Brexit, Trump, opinions polarising and splintering… more and more aspects of life seem to becoming politicised. Whether it’s fake news, cultural appropriation, safe zones – public discourse is often charged, filtered. This “politicisation” – oblique or direct – is happening faster than we think and is pretty pervasive. Some examples: US retailer Nordstrom became part of a storm following its decision to de-stock Ivanka Trump’s fashion line The Budweiser 2017 Super Bowl TV ad sparked a wave of protest following what was perceived as a politicised, pro-immigration message. Consider what the use of capital letters on Twitter can easily suggest. Are we ready for this in market research? The filter bubble is a familiar concept in social media, but what about the interaction that goes on in a Market Research Online Community? Or a mobile chat? Groups? Do we capture authentically how peer-to-peer communication really happens – or are we “shut out” as external observers? The hypothesis is that people become more inhibited in expressing their true views, with multiple social pressures encouraging […]

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Should Market Research Still Be Using Significance Testing?

Over the last few years there have been many calls for market researchers to stop using significance testing based on assumptions of random probability testing to measure the potential impact of sampling error. For example, Annie Pettit writing in The Huffington Post asked “Stop Asking for Margin of Error in Polling Research”. But, despite the concerns about the correctness of using this technique, it seems to still be in common use. In this post, I briefly explain what significance testing is (experts can jump this bit), why it doesn’t do what people seem to think it should do, and the way I think we should be using it in the future. What Is Significance Testing? The type of testing I am talking about in this post relates to sampling error. In quantitative research, a sample is taken from a population and one or more statistics are calculated. These statistics are then used to estimate the values for the total population. For example, assume 1000 people are selected at random from a population of 20 million. Assume that 50% of the sample are female. The inference from this study is that it would be expected that 50% of the total population […]