Sep 032014
 

Last week I posted an article looking at the decline in survey research, which included some data from ESOMAR and some predictions.

This week, ESOMAR posted the latest Global Market Research Report and it includes some interesting figures on data collection modes. Figures which are broadly in line with my predictions.

The table below is mostly a repeat of the one I included in my previous post. It shows the data from the ESOMAR reports for 2007, 2010, and 2013, along with my forecasts for 2016 and 2019.

In this version, I have added the data from the 2014 ESOMAR Global Market Research report at the bottom.

Surveys 2014
Note, the ESOMAR data refer to the final figures for the previous year, so the 2014 report is based on the completed returns for the whole of 2013.

The decline in research spending on projects where the data was collected via surveys, from 53% in the 2013 report to 48% in 2014, is a very large drop and is even faster than implied by my predictions. The ESOMAR Pricing Study would suggest that some of the drop is due to falling costs for online research and a continued switch to online from face-to-face and CATI. However, the ESOMAR Global Market Research report also highlights the growth of non-survey alternatives.

The change in other quant is broadly in line with my predictions, and the 1% change in qual could be more wobble than message. The climb in Other is, however, large, and larger than my prediction, and is one of the drivers of the fall in survey research as a proportion of the total. The key elements in Other are desk research and secondary analysis and are an indication of the move away from data collection to analysis.

BTW, if you are interested in this topic you might want to read Jeffrey Henning’s riposte, Surveys A Century From Now.


 

Sep 022014
 
Coloured Rhino

One of the most frequent lamentations at market research conferences relates to the boardroom. Market researchers are not well represented in the boardroom and many seem to think this is proof of our weakness as a profession/industry. However, I think this is mistaken, I think that market research should only rarely be involved in boardroom decisions, and indeed that majority of what we do should be tactical not strategic.

Boardrooms are not places where many decisions are taken, and those decisions tend to be about issues such as mergers and acquisitions, accounts related issues, strategic decisions about estate management, strategic decisions about issues such as outsourcing etc.

The management of companies is not, typically, achieved at the boardroom level; it is provided by the managers and the specialists. Market research is at its most powerful when it is integrated into the wider knowledge base and information system of the organisation, and this integration happens best when done by the people working with the information, not externally, and not at a level too senior to understand the complexity.

Similarly, most companies make 1000s of tactical decisions for every strategic decision. If a company is making a large number of strategic decisions, they are not actually strategic, they are more likely to be panic. Market researchers certainly want to be involved in the strategic decisions, we have a lot to add and they tend to be interesting projects. But the bulk of the industry should be focused on the tactical if it is going to grow and be profitable.

If we look at the ESOMAR Global Market Research report we can see that the continuous projects account for the bulk of market research spending by clients, including audits, market measurement, customer satisfaction, brand and advertising tracking, usage data. All of this data is used strategically occasionally, but it is principally used to manage the delivery of services and products – i.e. it is used tactically. Ad hoc research such as product testing and ad testing are, in most cases, tactical. A company makes a strategic decision to launch X new products a year, the NPD, the pre-testing, the testing, the comms testing, the monitoring of sales and advertising are all (mostly) tactical. Of course, we would encourage a company to review its tactical data to gain inputs to its strategic thinking, but that is in addition to using the data tactically.

Am I talking about me or about the industry?
One of the reasons I think the MR industry gets confused about whether its core target should be the boardroom or senior management, and about whether its bread and butter should be strategic or tactical, is down to the opinion leaders in market research. Most of the opinion leaders are more strategic than tactical, they personally do more big picture work, and they do less testing whether the font on the pack should be serif or sans serif.

I worry that too many people who do the big thinking (or who try to do the big thinking) are generalising from their own particular. If the market research industry were to focus on the strategic and the boardroom, to the exclusion of the tactical and the everyday, the market research industry would be much, much smaller, many people would have to lose their jobs, and another business sector would need to do the tactical research that clients need.

The importance of the tactical and practical
The ability of some market researchers to focus on the strategic, to offer consultancy services, rests on the scale of the market research industry and its reputation for measurement, independence, and relative objectivity. The stars in our industry are there because of the field managers, the interviewers, the programmers, the operations staff, the coders, and research executives that facilitate the scale of the MR industry.

Yes, let’s keep developing the consultancy services, let’s keep trying to garner a bigger role in strategic decision making, let’s embrace insight management, but let us also keep developing the tactical, the practical, the everyday. We need a parity of respect for all aspects of the market research profession.


 

Jun 282014
 

This week’s Economist has an interesting article about the founders of Napster (Shawn Fanning and Sean Parker) and the difficulty they have had in coming up with a successful second presence in the market. Towards the end of the article the Economist refers to one of my favourite terms in the area of new business, “First-mover disadvantage”.

First-mover advantage?
Whenever I meet start-ups, or people back from the latest hi-tech innovation fest, the talk is often about first-mover advantage. The idea is that a company gets in first and secures a long-term advantage. However, although there are examples of first-mover advantage (e.g. when a first mover can tie-up the market for scarce materials), it is much more common to see first-mover disadvantages.

First-mover disadvantage
Examples of first-mover disadvantage go back at least as far as the printing press, noting that in the 16 Century Gutenberg died bankrupt). The economist article quotes Motorola and the mobile phone along with Netscape and the browser. To this list we could add:

  • Alta Vista had first mover status in search engines, but was overtaken by Yahoo! and then Google.
  • When personal computers first appeared the early advantage was with companies like Commordore, then Apple, then IBM, and now the PC is largely a commodity item, with a range of manufacturers, and most of the early leaders no longer in the market (Apple is still making personal computers, but has a relatively small market share).
  • Henry Ford appeared to have secured a first-mover advantage in 1908 with the Model T, but was overtaken in the 1920s by Chevrolet.

The awareness of first-mover disadvantage dates back a long way, for example here is a Forces article on it in 2007. In 2001 the Harvard Business Review reported a study that found that first movers in consumer goods and industrial goods tended to have a 4% LOWER ROI than later entrants to the market.

There are numerous causes of first-mover disadvantage, most of which relate to second mover advantage. The second mover can see what is working, they can aim to meet the unmet needs of the incumbent (which often means cost, but can mean efficacy, range, style etc).

Another source of first-mover disadvantage is that if a first mover is making money from its current model it often neglects the need to change, to disrupt itself, leaving it open to be disrupted by others.

So the next time somebody is pitching a product, investment, or job opportunity, watch out for that use of first-mover advantage.

In-and-Out
When somebody is talking about first-mover advantages. It can be a good idea to check whether it represents and in-and-out opportunity. An in-and-out opportunity is where there is a short-term first mover advantage, and there is an understanding by the people running it that the optimum strategy is to ramp it up quickly, generate revenues, and then get out.

Other Examples?
What are your examples of first-mover disadvantage?


 

Jan 112014
 

Google’s standing with privacy groups and legislators has probably never been lower. Problems include: the recent news that some of Google’s activities have been ruled illegal by four countries (France, Netherlands, Germany, and Spain – with fines being levied by Spain and France), following fast on the heels of Google’s problems in Europe with how little tax it pays, $40million dollar fines in the US over ‘cookiegate’, $7million fine in the US for Wi-Fi data collected illegally from its street view cars, and most recently the concern that Google’s integration of Google+ and Gmail means that people can send messages to you without knowing your email address.

Does any of this matter? Sure Google has been fined, but the sums only account to small change for a company as large and successful as Google. Privacy campaigners are outraged, but usage of Google’s services continue to grow (look at the way Android has quickly become the leading operating system on new phones and tablets). But would governments really try to tackle Google? Could Governments try to tackle Google?

Perhaps there are some interesting lessons in history, especially in the United States, consider two important examples.

Standard Oil
Standard Oil began in 1870 and was a massive success. Standard Oil got rich by increasing the availability oil and by driving the price of it down. By its developments it enhanced the growth of the US, its scientists developed key technologies, and the end customers benefitted. However, its competitors did badly. Using techniques that were legal at the time, and common practice at the time, Standard Oil crippled its competitors and made life very hard for its suppliers – for example giving discounts (rebates) to rail companies for their oil in return for better treatment by the rail companies for Standard Oil, which meant worse treatment for its competitors. From 1906 to 1911 the US authorities prosecuted Standard Oil, using anti-trust legislation, resulting in the breaking up of Standard Oil.

AT&T
AT&T was a powerhouse of US telecommunications, but was derailed by government action. In 1956 anti-trust rulings prevented AT&T from entering non-regulated parts of the IT and telecommunications industry, but by 1982 it had developed a monopolistic hold on parts of the US telephone business. Following action by the government and courts AT&T (‘Ma Bell’) was forced to created seven regional telephone companies (‘Baby Bells’).

So, will any of this happen to Google? Or, will action be taken by Governments elsewhere (either in terms of restrictions or in terms of the promotion of a competitor in the way the European governments helped Airbus compete with Boeing)? It is impossible to say at the moment.

Action was nearly taken against Microsoft in its heyday. Some of its actions were trimmed, billions of dollars were paid in fines, but the wheels moved very slowly. By the time the US and European governments were getting close to real action, Microsoft’s power had already started to wane.

But, if I were to advise Google I would suggest being a better citizen. If push ever comes to shove it is better to have the public on your side.

 

Jan 062014
 

Have you ever stopped to wonder how many of your Twitter followers are fake? Or, more importantly, when you or your client are buying endorsements from somebody with a mega number of followers, are they real. Or, if you are trying measure influence, what figure should you attribute somebody with?

Back in November of last year, StatusPeople.com did an analysis of Katie Perry and come up with an estimate that 42% of her followers were fake, 36% were inactive, and 22% were good. Of course with nearly 50 million followers, even 22% good produces quite a few people.

For the loss of a small amount of privacy (you have to sign in with your Twitter account), you can check your own ratio of fake followers with StatusPeople – my score showed that I had 5% fake followers. So, you can get fake followers without having to buy them.You can also find out more about your followers, or somebody else’s follower using SocialBakers’ FakeFollowers (they had me at 6% fake, but 90% active) – again you have to sign in with your Twitter account. But, as Chereen Zaki posting on Forbes pointed out, back in March, buying followers could cost you your job!

Dec 232013
 
The material below is an excerpt from a book I am writing with Navin Williams and Sue York on Mobile Market Research, but its implications are much wider and I would love to hear people’s thoughts and suggestions.

Most commercial fields have methods of gaining and assessing insight other than market research, for example testing products against standards or legal parameters, test launching, and crowd-funding. There are also a variety of approaches that although used by market researchers are not seen by the market place as exclusively (or even in some cases predominantly) the domain of market research, such as big data, usability testing, and A/B testing.

The mobile ecosystem (e.g. telcos, handset manufacturers, app providers, mobile services, mobile advertising and marketing, mobile shopping etc) employs a wide range of these non-market research techniques, and market researchers working in the field need to be aware of the strengths and weaknesses of these approaches. Market researchers need to understand how they can use the non-market research techniques and how to use market research to complement what they offer.

The list below cover techniques frequently used in the mobile ecosystem which are either not typically offered by market researchers or which are offered by a range of other providers as well as market researchers. Key items are:

  • Usage data, for example web logs from online services and telephone usage from the telcos.
  • A/B testing.
  • Agile development.
  • Crowdsourcing, including open-source development and crowdfunding.
  • Usability testing.
  • Technology or parameter driven development.

Usage data

The mobile and online worlds leave an extensive electronic wake behind users. Accessing a website tells the website owner a large amount about the user, in terms of hardware, location, operating system, language the device is using (e.g. English, French etc), and it might make an estimate of things like age and gender based on the sites you visit and the answers you pick. Use a mobile phone and you tell the telco who you contacted, where you were geographically, how long the contact lasted, what sort of contact was it (e.g. voice or SMS). Use email, such as Gmail or Yahoo, and you tell the service provider who you contacted, which of your devices you used, and the content of your email. Use a service like RunKeeper or eBay or Facebook and you share a large amount of information about yourself and in most cases about other people too.

In many fields, market research is used to estimate usage and behaviour, but in the mobile ecosystem there is often at least one company who can see this information without using market research, and see it in much better detail. For example, a telco does not need to conduct a survey with a sample of its subscribers to find out how often they make calls or to work out how many texts they send, and how many of those texts are to international numbers. The telco has this information, for every user, without any errors.

Usage data tends to be better, cheaper, and often quicker than market research for recording what people did. It is much less powerful in working out why patterns are happening, and it is thought (by some people) to be weak in predicting what will happen if circumstances change. However, it should be noted that the advocates of big data and in particular ‘predictive analytics’ believe that it is possible to work out the answer to ‘what-if’ questions, just from usage/behaviour data.

Unique access to usage data
One limitation to the power of usage data is that in most cases only one organisation has access to a specific section of usage data. In a country with two telcos, each will only have access to the usage data for their subscribers, plus some cross-network traffic information. The owner of a website is the only company who can track the people who visit that site (* with a couple of exceptions). A bank has access to the online, mobile and other data from its customers, but not data about the users of other banks.

This unique access feature of usage data is one of the reasons why organisations buy data from other organisations and conduct market research to get a whole market picture.

* There are two exceptions to the unique access paradigm.
The first is that if users can be persuaded to download a tracking device, such as the Alexa.com toolbar, then that service will build a large, but partial picture of users of other services. This is how Alexa.com is able to estimate the traffic for the leading websites globally.

The second exception is if the service provider buys or uses a tool or service from a third party then some information is shared with that provider.

A complex and comprehensive example of this type of access is Google who sign users up to their Google services (including Android), offer web analytics to websites, and serve ads to websites, which allows them to gain a large but partial picture of online and mobile behaviour.

Legal implications of usage data
Usage data, whether it is browsing, emailing, mobile, or financial, is controlled by law in most countries, although the laws tend to vary from one jurisdiction to another. Because the scale and depth of usage data is a new phenomenon and because the tools to analyse it and the markets for selling/using it are still developing the laws are tending to lag behind the practice.

A good example, of the challenges that legislators and data owners face is determining what is permitted and what is not, are the problems that Google had in Spain and Netherlands towards the end of 2013. The Dutch Government’s Data Protection Agency ruled in November 2013 that Google had broken Dutch law by combining data together from its many services to create a holistic picture of users. Spain went one step further and fined Google 900,000 Euros for the same offence (about $1.25 million). This is unlikely to be the end of the story, the laws might change, Google might change its practices (or the permissions it collects), or the findings might be appealed. However, they illustrate that data privacy and protection are likely to create a number of challenges for data users and legislators over the next few year.

A/B testing

The definition of A/B testing is a developing and evolving one; and it is likely to evolve and expand further over the next few years. At its heart A/B testing is based on a very old principle, create a test where two offers only differ in one detail, present these two choices to matched but separate groups of people to evaluate, and whichever is the more popular is the winner. What makes modern A/B testing different from traditional research is the tendency to evaluate the options in the real market, rather than with research participants. One high profile user of A/B testing is Google, who use it to optimise their online services. Google systematically, and in many cases automatically, select a variable, offer two options, and count the performance with real users. The winning option becomes part of the system.

Google’s A/B testing is now available to users of some of its systems, such as Google Analytics. There are also a growing range of companies offering A/B testing systems. Any service that can be readily tweaked and offered is potentially suitable for A/B testing – in particular virtual or online services.

The concept of A/B testing has moved well beyond simply testing two options and assessing the winner, for example:

  • Many online advertising tools allow the advertiser to submit several variations and the platform adjusts which execution is shown most often and to whom it is shown to maximise a dependent variable, for example to maximise click through.
  • Companies like Phillips have updated their direct mailing research/practice by developing multiple offers, e.g. 32 versions of a mailer, employing design principles to allow the differences to be assessed. The mailers are used in the market place, with a proportion of the full database, to assess their performance. The results are used in two ways. 1) The winning mailer is used for the rest of the database. 2) The performance of the different elements are assessed to create predictive analytics for future mailings.
  • Dynamic pricing models are becoming increasingly common in the virtual and online world. Prices in real markets, such as stock exchanges have been based for many years on dynamic pricing, but now services such as eBay, Betfair, and Amazon apply differing types of automated price matching.
  • Algorithmic bundling and offer development. With services that are offered virtually the components can be varied to iteratively seek combinations that work better than others.

The great strength of A/B testing is in the area of small, iterative changes, allowing organisations to optimise their products, services, and campaigns. Market research’s key strength, in this area, is the ability to research bigger changes and help suggest possible changes.

Agile development

Agile development refers to operating in ways where is it easy, quick, and cheap for the organisation to change direction and to modify products and services. One consequence of agile development is that organisations can try their product or service with the market place, rather than assessing it in advance.

Market research is of particular relevance when the costs of making a product are large, or where the consequences of launching an unsatisfactory product or service are large. But, if products and services can be created easily and the consequences of failure are low, then ‘try it and see’ can be a better option than classic forms of market research. Whilst the most obvious place for agile development is in the area of virtual products and services, it is also used in more tangible markets. The move to print on demand books has reduced the barriers to entry in the book market and facilitated agile approaches. Don Tapscott in his book Wikinomics talks about the motorcycle market in China, which adopted an open-source approach to its design and manufacture of motorcycles, something which combined agile development and crowdsourcing (the next topic in this section).

Crowdsourcing

Crowdsourcing is being used in a wide variety of way by organisations, and several of these ways can be seen as an alternative to market research, or perhaps as routes that make market research less necessary. Key examples of crowdsourcing include:

  • Open source. Systems like Linux and Apache are developed collaboratively and then made freely available. The priorities for development are determined by the interaction of individuals and the community, and the success of changes is determined by a combination of peer review and market adoption.
  • Crowdfunding. One way of assessing whether an idea has a good chance of succeeding is to try and fund it through a crowdfunding platform, such as Kickstarter. The crowdfunding route can provide feedback, advocates, and money.
  • Crowdsourced product development. A great example of crowdsourcing is the T-shirt company Threadless.com. People who want to be T-shirt designers upload their designs to the website. Threadless displays these designs to the people who buy T-shirts and asks which ones people want to buy. The most popular designs are then manufactured and sold via the website. In this sort of crowdsourced model there is little need for market research as the audience get what the audience want, and the company is not paying for the designs, unless the designs prove to be successful.

Usability testing

Some market research companies offer usability testing, but there are a great many providers of this service who are not market researchers and who do not see themselves as market researchers. The field of usability testing brings together design professionals, HCI (human computer interaction), ergonomics, as well market researchers.

Usability testing for a mobile phone, or a mobile app, can include:

  • Scoring it against legal criteria to make sure it conforms to statutory requirements.
  • Scoring it against design criteria, including criteria such as disability access guidelines.
  • User lab testing, where potential users are given access to the product or service and are closely observed as they use it.
  • User testing, where potential users are given the product or given access to the service and use it for a period of time, for example two weeks. The usage may be monitored, there is often a debrief at the end of the usage period (which can be qualitative, quantitative, or both), and usage data may have been collected and analysed.

Technology or parameter driven

In some markets there are issues other than consumer choice that guide design and innovation. In areas like mobile commerce and mobile connectivity, there are legal and regulatory limits and requirements as to what can be done, so the design process will often be focused on how to maximise performance, minimise cost, whilst complying with the rules. In these situations, the guidance comes from professionals (e.g. engineers or lawyers) rather than from consumers, which reduces the role for market research.

Future innovations

This section of the chapter has looked at a wide range of approaches to gaining insight that are not strengths of market research. It is likely that this list will grow over time as technologies develop and it is likely to grow as the importance of the mobile ecosystem continues to grow.

As well as new non-market research approaches being developed it is possible, perhaps likely, that areas which are currently seen as largely or entirely the domain of market research will be shared with other non-market research companies and organisations. The growth in DIY or self-serve options in surveys, online discussions, and even whole insight communities are an indication of this direction of travel.


So, that is where the text is at the moment. Plenty of polishing still to do. But here are my questions?
  1. Do you agree with the main points?
  2. Have I missed any major issuies?
  3. Are there good examples of the points I’ve made that you could suggest highlighting/using?

Dec 132013
 

Yesterday, at the BAQMaR Conference, the Fringe Factory launched its study into what young graduates are looking for in an industry and what is their perception of market research.

The Fringe Factory surveyed over 1800 graduates across nine countries. The report produced five “eye-catching insights and recommendations”. But for me one of the key points was that only 13% of the young people surveyed said they would consider a job in market research, and only 3% listed it as the best sector.

To find out more about the study, the Fringe Factory, and the other insights and recommendation, look at the presentation below. The presentation is hosted via SlideShare – this means you can advance the slides and by click on the four arrows in the bottom right of the presentation window, turn it into a full screen presentation.

The Fringe Factory is supported by ESOMAR. To find out more about the Fringe Factory, visit their website.

Dec 062013
 

Posted by Nikki Lavoie, Chief Commercial Officer, Sky Consulting, France.

We know that research participants sometimes cannot or will not be honest in their responses. We know about behavioral economics. We know all the things to say to encourage open and honest discussions and survey responses. But what about our online and social media-based conversations?

I’m a Second Generation Facebook user. By this I mean that I’ve been around on Facebook since almost immediately after it was released to universities in the Greater Boston Area (I’ll refrain from listing the year so you can’t do the math). What started out as a site intended to allow students to evaluate one another’s’ attractiveness has become a global commodity used for connecting, promoting, expressing, sharing, and now for market research.

One of the interesting trends that has come up in relation to social media outlets, and Facebook in particular, is something I’m going to call “mediawashing” (you heard it here first, write that word down). Similar to greenwashing, mediawashing is the dissemination of disinformation that a person chooses to put forth, typically about themselves or their lives, using social media. In laymen’s terms: people paint pretty pictures of their lives, but it’s often not the whole picture.

Numerous studies have been published demonstrating that not only is there a link between social media use and things like depression or lack of self-esteem, in some cases there is a causal effect due in large part to comparisons made between one’s real life and the bits and pieces of someone else’s life that have been shared.

A recent article in Newsweek points out how mothers on Facebook are battling increased stress and pressure thanks to constant boasting and bragging about achievements, development, and even things like a baby’s sleep habits, while conveniently failing to mention any hardships or struggles. Although most recognize logically that this is a “presentation of perfection” and is not a true reflection of reality, the effects on both the reader and the poster are dramatic. The interactions that would, at one time, impact the perceptions and behaviors of parents on a weekly or monthly basis are now happening several times a day for those who are using social networks.

This is, of course, one category of examples, but the point is clear: no one’s life is perfect. No one’s days are only filled with sunshine and rainbows and happy, helpful people who do everything they can to help a person succeed. Life is hard, and many people edit those parts out of what they choose to share.

For market researchers, this poses a particular problem when using social media and similar platforms (like communities, bulletin boards or online focus groups). While it’s true that anonymity, in these cases, offers respondents the chance to express themselves with a hopefully refreshing degree of honesty, one has to wonder: how much has mediawashing trained us to edit how we present ourselves to the world?

A measuring stick of the mediawashing effect could be the following: have you ever started to write something (a comment, a status, a tweet, a caption) on a social media platform, only to erase and begin again, in order to adjust your wording or tone? Have you ever started to write something and, in the end, decided not to post at all? Have you considered uploading a photo only to hesitate or stop because it doesn’t portray you or someone else in the best light?

As people and professionals who are dedicated to unearthing human truths from the respondents we connect with, we need to not only be aware that mediawashing exists, but to actively fight against it in our data collection processes. Whether we are scraping Facebook or Twitter or running a community, the risk that we, as researchers, only see the edited and refined version of someone’s life, their preferences, their behavior or their opinions is real. But so is the opportunity for us to allow our respondents the freedom of candid, open conversations where honesty is more valued than socially desirable responses.

So now it’s time we have an honest conversation among ourselves: how do we combat the effects of mediawashing in our research practices?

Click here to read other posts in this series.

Dec 052013
 

Post by Sally Joubert, founder and CEO of Luma, Australia.

The Biggest Threat

We become irrelevant. If we don’t attract, train and develop the business leaders and thinkers of the future we will become the “typing pool” of 2010s. Businesses have changed and new business models are evolving all the time. We know business decisions are made on the basis of anything from gut feel (or someone else’s “gut feel”) to highly complex models based on more data than some of us could ever dream of getting our hands on in an entire lifetime. To help businesses make these decisions we need to be there at every step of the way. So as researchers/data scientists/marketers/leaders/entrepreneurs/gurus or whatever we want to call ourselves we need to be experts at uncovering, synthesising and most importantly communicating our ideas so that the best decisions can be made. If we continue to focus on teaching traditional narrow vocational skill sets at schools, university and in our companies we just won’t have the thinkers and doers to keep us relevant.

The Biggest Opportunity

To combine traditional MR with everything we can possibly think of to make a much smarter world. The technology we have created or have access to can collect, ask and simulate just about anything we might dream of finding out. It can also automate so much of this that the we can make decisions literally in real time or even better the decisions can be made for us. This headline from the Wall Street Journal sums it up…’Tired of Thinking? Google says we won’t have to’. Is that really true? In the new world someone has to be thinker and be able to hold on to the lateral and creative application of ideas. We can be those thinkers, we are the human element that will design the technology and the information models that will help businesses become smarter.

Click here to read other posts in this series.

Dec 012013
 
Posted by Jane Frost, CEO of MRS, The Market Research Society, UK.
 

Market research has a great future if it is brave enough to change. This was the challenge laid down by MRS Patron and Dunn Humby co-founder Clive Humby to a packed committee room at the House of Commons last week. The occasion was the MRS sponsored debate which asked whether big data was the death knell for market research.

The challenge is valid. Last year MRS commissioned PWC to produce a report on the size of the market for research in this country. It was deliberately called “the Business of Evidence”, because I believe that only collectively and only by defining ourselves by our client value can we build on what has been historically, and remains as we speak, a world leading sector.

We need to adopt the language of the people who pay us. We should not be asking our clients to do our work for us in promoting the value of what we do. You rarely hear the finance director defining himself by his accountancy qualification. I have rarely heard a marketing director do so either. So how come we as sector manage to promote so many labels which are of relevance only internally?

We are a service industry which develops the intellectual capital that businesses and policymakers need to take decisions. The customer understanding supplied by us can transform businesses, increase revenues and cut costs. That customer understanding can come from any source. So-called big data, for example, is just one supply stream. As a sector we should embrace it, use it and shape it by our standards. To our clients “big data” is a shiny new toy: one they know will be fun, but they don’t quite know how to use. By running scared or by ignoring its glitter and promise we do start to render ourselves out of touch. Big data is not even new, I can certainly make a case for it going back to the Magna Carta and many of you may argue that the census was its real genus.

As I write this, the label “big data” is showing some signs of going out of fashion. However data analytics teams are growing, and if we can’t prove the value of professionalism and creating an integrated customer view using all the knowledge streams at our disposal , current research and insight teams may be renamed customer data teams.

We have some key messages to deliver, and we are more than capable of doing so. We can own the use of data as a research methodology rather than an independent idea. My own experience in speaking to clients shows that they welcome an authoritative contribution to the data debate. Collectively we need to speak with one voice on four key messages:

1) Quality: reinforcing the value of having trained and qualified professionals working for you. MRS recent successes in, for example, gaining government recognition for the importance of accreditation in research procurement shows that this can be done.

2) Managing data risk: the use of personal data, and big data in general are potentially a significant risk to clients. There are the legal and ethical risks, the increasing threat of legislation, and the increasing potential cost of large datasets without a defined value or use. Many people do not recognise how much effort needs to go into creating reliable data. Misuse of personal data, and general decline in trust is starting to create new “hard to reach consumers”, increasingly high value groups, who work at avoiding identification. I believe that personal data is potentially a material risk that should be on the radar of every company’s audit committee.

3) Corporate social responsibility: the management of personal data needs to have the same value as the management of ingredient sourcing and environmental impact. Unilever’s Polman believed that procurement would be an important part of Brand in future lets ensure this includes procurement of data.

4) Controlling the question and the costs: the benefit of helping understand the questions that data should be answering will clearly have a cost benefit to clients and help the utility of their data investments. This is a key role for qualitative research for example, but it needs explaining.

We have first mover advantage in the Fairdata Mark. Use it. We know that it is a good way into clients when used to address these issues. In the UK we are world leaders in research training and accreditation, and MRS will shortly launch a CPD scheme. If we collectively support this it will become more important to clients.

We believe the UK market for evidence is £3 billion big. Statistics show it is back on the road to growth .To meet the opportunity and the challenge we need collectively to adopt data sciences as our own, addressing misconceptions about the status of data, and the best way to exploit it.

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