From Market Research to Insight to Intel

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On the CBS show ‘Seal Team’ an elite US Navy Seal unit called ‘Team Bravo’ undertake dangerous missions in scary places taking down terrorists. Conveniently there seems to be one such mission every episode for the ‘Frogmen and Door-kickers’ with not too much hanging around. Think ‘Band of Brothers’ meets ‘Zero Dark Thirty’. Working hand in hand with the team are a military Field Intelligence Officer and a CIA agent. They don’t do much of the fighting, shooting and door-kicking but they are on the ground with them and provide Bravo with the intel they need to plan and execute the missions. This intel comes from the many sources they have at their disposal – databases of baddies, satellite reconnaissance, undercover operatives and lots more besides. They pull all this together under pressure, fast, in real time and their intel invariably proves vital to the success of the mission, particularly when the unexpected happens and new plans and ‘exfils’ (getting the hell out) have to be created. They have Team Bravo’s back and there’s strong mutual respect and trust. They hang out together, go drinking together in between missions and – plot spoiler – one of the Seals has a bit of thing for the Field Intelligence Officer. They are close, tight.

And that’s where ‘Market Research’ is heading. Not just integrated with the operational teams, in the fight.

Here is the briefest of history lessons. Market Research began with ‘mass observations’ of the type the US military carried out during the Second World War. They’d send people to observe the troops in the places they were stationed, observe what they were doing, how they were behaving, pull all the results together and draw conclusions on their fighting preparedness and morale. After the war someone had the bright idea to actually ask people rather than just observe and infer, either in small groups or as part of large surveys using the results to inform commercial rather than military decisions and the modern Market Research Industry was born.

I’ll skip very quickly through the next development which was an explosion of techniques and modelling to overcome the problem that people don’t always make good witnesses on their own lives. The problem is you just can’t trust what people tell you or even what you observe.

Picking through all this research was a job for experts and specialist market research agencies. Companies built up market research departments to translate the market information needs of the business into briefs for the agencies and then help convert their debriefs into actionable insight. Insight was the goal even though no-one ever succeeded in pinning down precisely the difference between ‘a finding’ and ‘an insight’. Lots tried, Procter & Gamble and Unilever, both heavy users of market research, developed several ring-binders full of best practice that sought to explain exactly what an insight was. Hell, even I had a go – discerning, actionable, inspiring, er….. a bit like a good idea, you’ll know it when you find it, although the proof of the pudding is in the eating. Something like that. Despite this slight confusion about exactly how to turn market research into insight, so attractive was the idea of insight (or the insight idea) that Market research departments and experts rebranded themselves as the “Customer/Consumer Insight Team”.

Next? The two D’s. The first is obvious – data, lots of data, big data, so big you need data warehouses and algorithms and all manner of human and artificial intelligence to turn data into information. The second D? “Do” – the advance of technology allows you to get lots of data on what people actually do (as well as where they go, where they get their information etc). With data on what they do you don’t need to rely on what they say they do. But you still need insights for data needs to become useful, actionable information.

Step aside market research agencies, and welcome in management consultancies. They love data and are really comfortable using it as long as this data is of the large numeric kind and requires little in the way of imagination to make sense of it but lots in the way of systems and technology. They are not so comfortable with what we used to call ‘qualitative data’, the soft stuff. Not just focus groups (in fact please, not focus groups) but depth interviews, ethnographic (modern term for mass obs) and cultural insights.

A recent report on trends in market research concluded that qual research is making a big comeback helped by technology to a large degree. Video platforms allow you do a lot of qual and do it cost effectively. So, you kind of get qual in quantity if that makes sense.

I am now going to play one of two “I told you so” cards here for anyone that cares. For the last 10 years as ‘big data’ has exploded I have been banging on about the need to use more ‘qual’ research. Put simply, numbers tell you what, they don’t tell you why. Qual tells you why but with no indication on materiality. Ergo, you need both – something I learned as best practice in my alma mater, Unilever, many moons ago.

There was another very interesting conclusion in this report. Two other trends were identified. Firstly, a trend to do more research/insight/qual/quant in-house. The new technologies often have such good CI (customer interface) they allow business to go DIY.

Secondly, the big new thing is empathy apparently. Business and brands need to build customer empathy. As someone who has always struggled to define the difference between sympathy and empathy, I’m not buying this. I can think of a lot of other ways to nail what is going on here without using the words ‘customer empathy’. Understanding, intimacy, affinity, nous. ‘Customer Empathy’ sounds a bit wokish to me, rather obtuse and a distraction from the real issue. For a long time, people have talked about the balance of power between ‘consumers’ (dreadful word) and brands shifting for a whole bunch of reasons but essentially because of technology generally and social media specifically. We can all share our views, review the opinions of others, get the low-down on anything, anywhere, anytime, maybe even become influencers, the arbiters of taste and choice. The ‘consumers’ are people and they are now empowered. If you already thought it was important to research what they do and think it’s a whole lot more important now and – if you know what you’re doing – easier.

What does this tell us about the future of ‘Insight Departments’ and Market Research Agencies? They have no future in their current form.

The Bravo Seal team don’t want just research, the don’t want just insight, they want intel and they want it as an integrated part of their team from people right there alongside them using every valuable source of ‘data’ they can, interpreted with intelligence, speed and commitment for the mission in hand.

Time to play my second and final “I told you so” card. Whereas you only have my word for the first I have documented proof for the second. Back at the end of 1999 the UK Marketing Society asked me to write a piece on the future of marketing in which I made the prediction that in the future Market Research would become Market Intelligence. It is fair to say a) even a broken watch is right twice a day and b) I did not entirely foresee the full impact of technology but even back then the idea of Intel made much more sense to me that Market Research or ‘Consumer Insight’.

What I did not foresee was that the line between qualitative and quantitative would blur. My model, as I have described above, was based on smaller scale qualitative research complimenting quantitative data by adding the ‘why’ to the ‘what’. I could see how video research platforms can reduce cost, extend reach and therefore allow us to do more qualitative research with the tech also facilitating faster analysis and sharing of findings. But the constraint is that qualitative research has to be moderated – someone, hopefully someone smart, has to ask the questions and react immediately to the responses – ask a follow up question, probe here, dig a bit more there. But what if you could break the link by conducting interviews without a moderator? This is sometimes called ‘asynchronous’ research because you do not have to synchronise a respondent with a moderator. The simple version – which is already used extensively in video recruitment interviews – is just to pop up written questions some of which are ‘open-ended’ (have you got a degree in maths? = closed ended question; why did you choose Finance? = open ended question). Great, you can just share the link, the respondent or candidate can record their answers whenever they choose and you can look at the results whenever you want. Without the need to schedule the interviews you can run as many as you want. As a rough rule of thumb you need circa 50 people in a chosen sample group to be able to get statistical significance. Typically, if you were running a study you’d want 3-5 different sample groups (e.g. young/old/users/non-users). So, if you want to run a study that has 150 – 250 interviews that is going to take several moderators and/or a long time. With ‘asynchronous interviews” you could do it in a day or so. But…. there’s always a but…..there are 3 problems with this.

  1. People respond better (more honestly and fulsomely) to people asking questions compared to an impersonal written question.
  • With no moderator you can’t change tack according to the responses – you can’t vary the question set, the order, the follow-ups
  • Somebody has to look at all the interviews – it might take just a couple of days to do them but you have to add on the time to analyse them and remember, video cannot be searched unless it is transcribed into words.

All of this, I’m pleased to say can be solved (to a large degree) by technology.

I’m not going to go in to too much detail because I’m currently working on bringing to market a platform that will do just this. But in headlines:-

  • You can have humans (recorded) to ask the questions
  • Using AI you can vary the question set
  • Using advanced sentiment analysis together with human over-sight you can process large volumes of video

This is a game changer that allows marketing and commercial teams to conduct a small-scale piece of video research then move seamlessly to a larger scale sample to provide not just ‘why’ but the statistical materiality. Or the other way around, start with a broad scale study to identify material issues then drop into more depth exploration. It is much more attuned to what product development teams and ‘user experience’ researchers need to do*(see footnote below). It can be run programmatically, it can offer a cost effective way to do ethnographic – in the moment – studies. It can be set up to run continuously, so the voice of the customer is always there, available to tune into for anyone in the business at any time.

This is next-level market intelligence where ‘qual and quant’ are working symbiotically to bring the customer right to the heart of decision-making, right to the heart of the mission. And all other things being equal, the business that’s closer to the market wins. The Seal teams would love it!

Footnote

This kind of ‘in the moment’ ethnographic research is even more expensive and even more time consuming if done conventionally. It is easier for digital products or experiences because the product development team and their User Researchers can set up tests and intercept the person at the moments they choose. Someone spends too long on one part of the site – PING – up pops a message, “Having problems?”. Someone gives you a low score in a customer survey – PING – up pops an open-ended question, “What could we improve?”.

But talk to the product development teams or marketing folk, and they’ll tell you what they really want is to see and hear the customer. They want video but they want it in the kind of numbers that allow them to understand statistical materiality. It is much easier to analyse numerical or written customer response, handling video is much more of a challenge. This is frustrating because my research* has shown there is a huge difference between what someone will write in answer to a question and what they will tell you face to face.

This is a real example. The intercept question was probing why a potential customer was failing to sign up and download an on-demand shopping app. When they were asked to write down their answer they said:-

“I found the address form complicated”

When the same person was asked to record their answer on video, with the web page live and visible alongside, this is the transcript of what they said:-

“You asked for my address here, but you didn’t make it clear whether I should just enter my post code or the full address. Then over here you had this map that asked me to move the cursor to my exact location. I did this and then without me spotting it you changed my address and I couldn’t see how to correct that. So I was trying to figure out whether I should just give up or put in a second address in the ‘work’ option but it’s not my work, it’s my home”.

If you were the dev team which would you find more interesting and useful? And would you like to know whether this was just one fat-fingered person or a problem lots of people were encountering?

Here is another real example, this time for a new kind of oat milk. The product was getting great customer reviews and in the surveys they were asked to say what they liked and what could be improved. One written response (typical of many) was this:-

“I really like the taste. Maybe the price could be cheaper”

The same person asked to record on video their reaction to trying the product and whether there was anything they’d improve. This is the transcription:-

“It’s kind of smooth and creamy, like milk. You get a hint of oat but it was not too strong like the others I’ve tried. They were watery and very oaty. This was delicious, something you could just drink on its own. If I had any suggestion maybe just a little too sweet.”

Quite a bit better, a lot more insightful.

Now imagine you that you could see and hear them at every stage of the customer journey. To stick with the last example, recruit someone who is interested in, but has not yet bought, plant-based milk alternatives and set them the task to go to a store, look on-line and then choose one to try other than your brand. When they’ve tried it, they then have to try your brand and compare the experience. They capture a minute or two of video at every stage of this process and you can prompt them with questions at any point.

*By the way, I was not telling the truth when I said this is based on my research. It was based on me, my personal experience with an on-demand grocery app and a new oat milk. The findings sounded very plausible though didn’t they? But I did warn you, you can’t trust what people say they do or what they say they think.

Solving the Social Dilemma

I’ve just finished my article on my response to the Netflix documentary, ‘The Social Dilemma’. I ran a small survey to help me in the writing of this and results are still coming in so there may be some further additions and editing to be done but I wanted to get this first version out there and see what people think. Please let me know.

Entrepreneurship & Covid19

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Brendan Harris is an old friend and colleague. He is that very rare animal, someone who had a very successful corporate career (first at Unilever, where we met, and then at Coca Cola) who then went on to be a successful entrepreneur. He built and sold a smoothie business in Scandinavia & Northern Europe, Froosh, and is currently building an Oat Milk business in Italy which I am sure will do well. I hope so because I’m a small investor but I really think it will. He has two very smart partners, a brilliant product and brand, a well-thought through ‘go-to-market’ strategy and the market for plant based alternatives is hot. That ticks all the boxes for me.

Brendan is one of the smartest people I know and he’s also a very good communicator. He recently did a video for McWhorter Driscoll who support young entrepreneurs all over the world. You can watch it here and it’s well worth doing so if you are thinking about starting a business in these challenging times (or trying to survive if you already did).

Solving the Social Dilemma

The recent release of Jeff Orlowski’s documentary ‘The Social Dilemma’ on Netflix may prove to be an even bigger deal than their 2016 film ‘The Great Hack’. The latter left you feeling that the villains of the piece were the businesses like Cambridge Analytica who malevolently manipulated social media data to change the political narrative, influence elections and threaten democracy. TSD points the finger squarely at big tech who purposefully design social media to feed their commercial model and in the process fuck up society and the whole of mankind.

 “If you don’t pay for the product, you are the product”.

Social media is not just abusing their tech to sell us stuff, they are selling us – our attention and our behaviour – without us knowing and to our detriment. TSD paints a scary future with overtones of the human batteries in The Matrix and Skynet from Terminator – AI may have started as a technology tool we used but it might become us that are the tools serving the needs of higher artificial intelligence. You think this is fantasy? Watch the documentary.

“Only two industries call their customers ‘users’: illegal drugs and IT” said Yale’s Edward Tufte.

Marketers (who pay for all this with their ad budgets) are trying to wean themselves off calling customers ‘consumers’. (If you drop the ‘m’ consumer is an anagram for ‘con user’). I think ‘people’ would be the best word because it simultaneously captures diversity and common humanity – the ‘we’. But I don’t think the lexicon is the issue and in fact I don’t think marketers or even the titans of big tech are the villains. They are people. A lot of the contributors to TSD, people like Tristan Harris or Justin Rosenstein, are from big tech. They have a conscience and know that many of their former colleagues do too. Marketers are not evil svengalis. They are paid to promote their products but most recognize that this increasingly means doing so in a sustainable and socially responsible way because that is what society wants. It is what will make their customers happy and they like happy customers. So what makes good people in marketing and tech do bad stuff? Two things:-

  1. Not recognizing the unintended consequences
  2. Not having a commercially attractive alternative

On the heels of ‘The Great Hack’, TSD can address the former. As ‘Inconvenient Truth’ was for climate change, this is a tipping point in the debate about social media and the issues around the misuse of the data it generates for the ‘attention extraction’ industry. We all know that something is wrong, we all know this is seriously fucked up and heading in a bad direction – but what is the alternative? What is the antidote? TSD is incredibly powerful and disturbing, very disturbing especially as it leaves you in no doubt things need to change but not much hope they will and no real solutions other than regulation (of some sort not defined) to disrupt the business model on which big tech has thrived.

Just as I concluded in my paper ‘Naked Economics; the new laws of the jungle’ the easy conclusion is that governments need to fix this – ‘they’ need to regulate. Easy but wrong because even if ‘they’ wanted to, ‘they’ can’t. It’s too complex, there is too much vested interest and there is no ‘they’. The legislation would need to be intricately drafted to cover every issue and avoid every unintended consequence. There are $ trillions at stake so expect some resistance and every government would need to act in lock step which they won’t/can’t.

So, as with the new economics, let’s focus on ‘we’ –  what we the people can do about the social dilemma that is social media data harvesting, processing and commercial application. For the wider economic context the macro levers to pull were the attribution of cost and ascribing of value to enable us to make better choices. In the specific area of data the micro levers are platforms that allow us as individuals to own, control and transact our own data.

The solution lies not so much in regulating the current business model, although that might have a role to play, but rather in creating a new business model that empowers people.

At the heart of the current model is data about 3 things:-

  • What you think
  • What you do
  • The connection between these

The tech, the algorithms, the UI and the AI that are all designed to do this can of course then be applied to change what you think and do, to get your attention and to persuade you. The business model is then to monetize this by selling it to people who wish to promote their business. It can also be sold to people wishing to change your politics but that will only ever be a small fraction of the billions social media earns. The big bucks come from big business.

The global industry for advertising and research is roughly $1 Trillion. That is how much business will pay to find out what you think and present the best version of themselves to you at the most opportune time.

What if we just told them? What if we offered the information they want to know and stuck our hand up when they had the best chance to sell something to us? Because if we did, en masse, then the revenues for facebook et al would start to evaporate.

Who would be prepared to do that? We all would. We do it all the time for purchases that are important to us and about which we are unsure. Say we want a haircut, a new car, expensive cosmetics, a new home, a piece of home electronics, a suit for our wedding. We pitch up, tell someone we are interested and then proceed to tell them everything they need to know about our lives, quite often more than they need to know. Yes we may do some research on-line and then purchase on-line but there are still many things where we meet people face to face, people that we know are there to sell us stuff, we tell them we are interested and we answer pretty much any question they care to ask. Why? Because it is in our interest to do so and we get something in return – help in making our best choice.

As long as we feel in control of the exchange of our information, our attention, our data, and this has material benefit to us we are happy to give business what they want.

I have been thinking about this for the last 5 years and I have ideas for two potential tech based platforms that would allow people at scale to exchange their ideas and their data – on their terms – with businesses and brands. These could divert a big chunk of the revenue Social Media generates directly into the hands of us, we the people, and offer what business wants quicker, cheaper and more effectively.

It would not stop the potential of big tech to produce addictive, manipulative social  platforms with the power to affect peoples’ physical and mental health, to undermine truth with fake news, to divide society and swing elections but it would take away their incentive to do so. They would eventually be left with only one option which is to make you pay for their service – and if we pay for it then we control it. It becomes the product, not us.

Let me know if anyone is interested to know more……..

The Roaring Twenties?

Interesting piece in the Telegraph this week from their highly distinguished economics journalist, Jeremy Warner, in which he speculates that the aftermath of this pandemic might be an economic boom as was the case after the 1918/19 Spanish Flu outbreak. The period that followed the post 1st WW pandemic was known as ‘The Roaring Twenties’. Might we be on the verge of a ‘New Roaring Twenties’ 100 years on?

JW quite rightly warns of the danger of historic comparisons. The Spanish Flu was far worse than Covid 19 (10 million people across the world died) so the scale of the disruption was more than comparable but the situation was different. It’s hard to separate the bounce back from Spanish Flu and the bounce back from the Great War. His point, nonetheless, is that economies can reinvent themselves after, or even because of, catastrophic events as resources flow into new and emerging industries. A lot of people hope that one driver of our economic recovery this time will be Green Energy – a booming industry that addresses a global challenge – but it will need to be more than that, more perhaps than we are capable of imagining. A century ago the industrial landscape was made up of coal and steel, railroads and ships. That was displaced by oil and plastics, cars and planes. There was leisure and entertainment but no-on thought of them as sectors capable of driving an economy. There was data in our parents’ generation but no-one envisaged it as an industry, the new oil.

So what awaits us? Clean energy we hope but also Fintech, Biotech, Robotics, AI we think (so maybe we won’t need to) . There’s no sign of population growth slowing, only shifting geographically. Economic growth is fundamentally fuelled by population growth. As social apes distinguished by three things – our ability to produce more offspring than we can feed, our ability to exist in larger groups and our ability to copy quickly – we have had to develop and been able to disseminate technology to support our growing numbers. From the wheel & fire to electricity & computers, as our numbers have swelled our technology has transformed and our economies have grown. In 1820 the world population was one billion, by 1920 it was 2 billion, in 2020 it is heading towards 8 billion and our global economy has grown by even more than that. In 1820 China accounted for nearly 40% of a global economy of roughly half a $ Billion. By 1920 the global GDP was more than half a $Trillion and USA had overtaken China. In 2020, before Covid hit, the global economy was worth $142 Trillion.

It’s not all about money. Creative expression has also evolved enriching us culturally but also economically. The creative industry is estimated to be close to 10% of the global economy. Charlie Chaplin didn’t see that coming.

Our predecessors in the early 1920’s could not begin to see the explosion in innovation and birth of new industries coming down the track. They would not even recognise most of the job titles that exist today – data scientist, influencer, epidemiologist (the science of epidemiology emerged as a result of Spanish Flu)

The notion that there could more than just an economic recovery from Covid 19, there could actually be an economic boom based on sectors and jobs we cannot even imagine, is perhaps not so daft. I would however make two important caveats. Firstly the dislocation from where we were to where we might be heading will be very painful for some, sadly the poorest and most disadvantaged in society. The medium term might be exciting but the short term could be social carnage, and we know the dangers of that. As a result of social depravation and the rise of populism, the world was at war again less than two decades after the end of the Great War and the subsequent outbreak of Spanish Flu  .

Secondly, as I write about in my paper Neo-naked Economics, the actual economic model has to evolve to meet new challenges, as it has always needed to over the centuries. The new economic model for a new global economy needs to get back to having a social purpose, something we’d lost sight of in business and something we need to rediscover to avoid history repeating itself in the wrong way.