I’m experimenting with the format of UNCX. Feel free to reply to this email to tell me what you think.
I example Nokia, Netflix, McDonald’s and Samsung and their use of Thick vs. Thin Data to supercharge customer understanding and growth. (It doesn’t go well for all of them). I show how in our data-driven world that the very essence of (our overused) phrase ‘to walk in the customer’s shoes’ really can be meaningful.
Plus, learn how to compete on your experience type, the friction versus memorable grid, a LinkedIn poll result, a book to read, and in Trends, the decline of the nice-to-have economy.
Hi all!
Here’s your regular dose of out-of-the-box CX thinking focusing on the new consumer, new trends, new strategies, plus what I’m exploring and thinking about. Feel free to forward this along to friends. They may thank you!
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Through Thick and Thin
Thick Data is qualitative, often unstructured, and subjective. Use it when you want a more complete understanding of your customer’s behaviours, experiences, and motivations. You collect it through ethnographic research methods, such as participant observation, in-depth interviews, and focus groups.
Thin data (aka Big Data) is collected and analysed through automated processes and statistical models. In 2018, the total amount of data ever created, captured, copied and consumed in the world was 33 zettabytes (ZB) – one zettabyte is 8,000,000,000,000,000,000,000 bits.
If like me you need help to understand such a big number, imagine that each bit is a £1 coin, around 3mm thick. One ZB made up of a stack of coins would be 2,550 light-years away. Each year we produce 59 times that amount. It’s predicted to reach a mind-boggling 175ZB by 2025.
Big data tells us the What, and Thick data the Why.
Thick data will give you context and insight into the nuances of behaviours. It will help you understand the cultural, social, and emotional factors influencing your customer’s decisions, values, and beliefs, and often, how these factors interact with your technology, products, and services.
Thick data complements big data. It’s a more holistic view to help you make more informed decisions about how to improve your products and services, and why your consumers act in the ways they do.
Big data alone may not provide the insights needed to understand that human context. Sometimes, big data users may even derive insights that are false - seeing patterns where they don’t exist, simply because enormous amounts of data can offer spurious connections.
In one example, data mining techniques showed a strong but spurious correlation between the changes in the S&P 500 stock index and butter production in Bangladesh.
So, enter thick data. We can get at not just the What but the Why.
Thick data is qualitative research that emphasises the subjective experience. Such data is often rich with detail and nuance, giving a deeper understanding of the cultural, social, and emotional factors that drive behaviour.
One of the key advantages of thick data is its ability to uncover the ‘Why’. The ‘Why do they do this or that’ in behaviours.
Enough with the explainers. Let’s get to some real-world examples.
Thick Data Examples
Nokia, Netflix and McDonald’s all learnt that Big Data doesn’t always have the answers.
Nokia
At the time the world’s largest cellphone company in emerging markets was selling expensive smartphones for elite users in the Chinese market and had data telling them the market wasn’t growing. But they were being persuaded to pivot.
Why? A Nokia ethnographer researcher, living with migrants, working as a street vendor and living in internet cafés, saw many cultural indicators that convinced her there existed a new unmet demand for affordable smartphones for low-income users.
She had qualitative data covering a few hundred consumers versus Nokia’s quantitative sample size of several million data points.
And Nokia rejected the idea, believing the sample size was weak and small compared to their data informing them no such demand existed.
They were wrong. They put a higher value on quantitative data over cultural research - they didn’t know how to handle data that wasn’t easily measurable. What could’ve been uniquely competitive intelligence was ignored. It ended up being their eventual downfall as a few years later, with Nokia’s China market share down below 3%, Microsoft bought them.
The term ‘Thick Data’ was coined by the ‘she’ in the Nokia story above, Tricia Wang, and you can watch her in this TED talk.
Netflix
Netflix has always been creating smart algorithms and gathering user data to drive viewing demand. And they’re very good at it.
They were even offering $1mill for the best coders to improve the algorithms. This was a few years ago when the common perception of binge-watching was a weekend-long, pyjama-wearing marathon of TV viewing that few viewers would admit to.
To better understand why, Netflix began working with cultural anthropologist Grant McCracken, who went into the living rooms to explore TV behaviours.
McCracken showed that the majority of streamers would actually prefer to have a whole season of a show available to watch at their own pace.
‘TV viewers aren’t zoning out as a way to forget their day, they are zoning in, on their personal schedule, to a different world. Getting immersed in multiple episodes or even multiple seasons of a show over a few weeks is a new kind of escapism that is especially welcomed today,’ he reported.
In response, Netflix redesigned their front end, started dropping complete shows into schedules and directly influenced the way future shows were scripted and filmed.
McDonald’s
They wanted to sell more milkshakes than Burger King and other competitors but they still couldn’t shift the needle. They already had tons of data, telling them customers were buying early morning, a single purchase milkshake to take out. To improve sales they started experimenting with price, flavours, colours and shape, all to no effect. They finally sought help from a social anthropologist, who walked in the customer’s shoes to understand what wasn’t happening. The answer? They found they were actually competing with their own products - doughnuts, cakes, bars and coffees that made customers feel guilty, got cold, made a mess on their lap, didn’t last the commute or left them hungry. Customers wanted a cold drink that lasted the drive to the office, filled them up, and was easy to consume in the car. Enter a thicker longer longer-lasting shake. Enter a 400% growth in shake sales.
How did Samsung use Thick Data to Thrive?
Samsung relied on external help for conducting hours of interviews, analysing videos and listening to conversations looking for an answer to ‘What does the TV mean in the modern household?’
Ethnographic research revealed that to most people, TVs aren’t electronics, but furniture.
From this insight, Samsung redesigned their TVs, going for a modernist approach and changing their marketing strategy, all based on this customer insight.
Be more curious.
Learn in new ways. Do away with assumptions and measured big data answers, and be willing to adopt an ethnographic approach that strives for deeply personal insight into experiences. This requires mining and digging—not of data that can be measured, but of data that are valuable because of the fact that it can’t be measured in the way that ‘big data’ can.
You’ll start discovering the personal stories, experiences, interactions, and emotions that resist quantification and modelling. The power of the insights this data can generate is its subtlety—deciphered by taking an authentic and humble walk in the customer’s shoes.
Thick Data Summary
Thick data is qualitative data
It can provide rich insights into human behaviours, experiences, and motivations.
In my view, a ‘data only’ focus can mislead or give an incomplete picture - the What without the Why.
Unlike Big Data, which focuses on quantitative data such as numbers and statistics, thick data involves collecting and analyzing qualitative data such as text, images, conversations, actions, and videos.
Thick data is usually collected with qualitative research such as interviews, focus groups, and ethnography, and requires human involvement and interpretation to identify the most relevant insights.
Why is thick data important? Because regardless of its predictive power thin (big) data does have limitations. First, it’s best as a lagging indicator, telling us the are doing and the have done. It’s also weak in explaining why we do what we do and, often, doesn’t have strong future-focused insight.
My belief? Big data alone cannot solve consumer problems.
I believe strongly in getting a nuanced understanding of customers. I hate how we often flatten everything to a statistical measure. My call is to not sacrifice business accuracy for statistical acceptability.
Sometimes too, statistical rigour may not matter — you may get statistical significance about something unimportant. And data can only tell you about the past. It lags. And if it looks at the future it can’t know what it doesn’t know, so tends to determine how to extend the present.
It’s even more important now to study consumers when they are pivoting in their wants and needs in the midst of the permacrisis.
Get closer to your customers, understand them and their world, and listen to them. In doing so you get away from ‘the average customer’, those terrible ‘personas’ the all-knowing, chino-wearing, flat-white coffee-carrying marketers bring to you.
If you’d like to read more about ethnography here are some sites to explore.
How big data and thick data inform design thinking projects
The Frictionless-Memorable Continuum
All brands’ experiences compete on a continuum of being predominantly frictionless to predominantly memorable. Amazon vs. Ritz Carlton.
Conventional wisdom is that a strategy aimed at reducing friction and a strategy aimed at increasing memorability offer equal opportunities for gaining market share. However, data keeps showing diminishing returns as brands are viewed as more memorable. Brands with high market share tend to be more frictionless, whereas more memorable brands tend to have lower market share with little appreciable growth above a certain threshold.
Does that mean you should abandon a focus on memorable experiences and instead make your customer experiences as friction-free as possible?
No, and presumes your brand can easily migrate from being memorable to being friction-free, or vice versa without risking destroying brand strategy and positioning. So you should instead embrace your fundamental brand characteristics and subsequently plot the best course for improving experiences, and business outcomes, according to your brand DNA.
More on CX Strategy: Competing on Experience
The first step to a successful customer experience strategy is to be clear about what type of brand you are.
In one sense it’s simple: every brand exists on a continuum from big established brands to small challenger brands, and every brand competes on a continuum of friction-free to memorable. Both determine the type of customer experience that is most likely to have the greatest impact on customers’ buying behaviour.
By incorporating a brand’s market share and how customers perceive their experiences with the brand (as either more friction-free or more memorable), it helps to place your brand into one of four categories, as shown in this “Customer Experience Matrix”:
Courtesy HBR
So what kind of experience management strategies should you apply to these different segments? Can they be the same? (Hint: Not usually). Can there be exceptions (Hint: Always, but not many).
Mass Market Brands
Oh, to be a mass-market brand. It’s so much simpler for a brand with a high market share and frequent usage. It drives your growth, and in growing, you need to keep making everything simpler to ensure your availability, your placement, and your agility. Making the consumer experience as frictionless as possible is part of that because memorable experiences in a mass market is difficult to maintain, as customers quickly get used to them.
Convenience Brands
Convenience brands largely compete on the ease with which customers can meet their needs. Convenient, frictionless experiences are expected. Unlike their mass-market counterparts, there are typically barriers to further scaling their service environments, such as geographical or market size limits. Convenience brands often have opportunities to have more balanced frictionless and memorable customer experience strategies, but they win a share of wallets on their frictionless qualities.
Boutique Brands
Boutique Brands compete primarily on the memorability of their experiences. Sometimes, certain types of friction help improve the memorability and value of these experiences. In most cases, memorability is enhanced through well-planned, immersive customer journeys. While there is an opportunity to remove friction, it should be done to make it easier for customers to become immersed in the experience.
Aspirational Brands
These brands are much rarer. Some think of them as Gravity Brands, because they are able to raise their market share despite the natural forces that tend to limit the growth of companies whose strategy focuses on creating memorable experiences. They are often iconic, with high emotional resonance, and operate in unique competitive environments that allow them to distinguish themselves and attract customers. Building memorable experiences is typically achieved through investing in superior hiring and training processes, high-quality experience components, and great physical environments.
Regardless
No company should forget that managing the customer experience is equivalent to managing customers for growth. The path to winning in business has remained constant even if the strategies for achieving it over time have changed. Make certain that your customers want to keep coming back.
Last month I ran a LinkedIn survey asking cx pros in what way they compare their customers’ experiences to their competitors.
The majority went for Distinctive and Remembered, and I’d agree (though there are exceptions). So here are three steps to help you get there.
1. Use the peak-end rule
Customer journeys, whilst a helpful framework, can become complex (too many variables) and abstract (removed from reality).
I often recommend you adopt the peak-end rule, which states that we don’t remember experiences accurately and that we tend only to recall the highlights and how things end. Great dinner but the waiter spilt the wine bottle over your new clothes - what will you recall 2 weeks later? A pretty good flight, especially when on disembarking the pilot thanked you and the air hostess gifted you chocolates and an umbrella to protect you from rain/sun - what will you recall 2 weeks later?
So in your customer’s typical journey ask yourself: what are your two memorable moments – what’s the end and what’s the highlight?
2. Experiment with memorability
Experiment, test hypotheses, and try new stuff. We all need to do more to understand the cause and effect of memorability in customer experience. We should be identifying the memorable (sometimes counter-intuitive) moments that we can test to gauge the impact on customer experience metrics as well as brand tracking metrics. Scale up the experiments that work, and discard the ones that don’t. Rinse, repeat.
3. Strike the right balance
All that being said, it’s important to understand that not everything needs to be memorable. The role of a brand is often to get out of the way and help a customer do quickly what they need to do, especially in task-based experience. The balance between fun and friction needs careful management. And that’s where experimentation comes in - helping us find the right balance.
Memorability at scale
We need to be bolder and more ambitious. If we could re-orientate focus to delivery of memorability instead of optimisation at scale, well, I think cx would be in much better health.
So let’s get to it; let’s use our imagination to create experiences that people remember.
Starbucks: customer complexity is weighing them down with too many drink options
The Future. Starbucks is doing just fine, but skyrocketing demand for insanely complicated drinks is overwhelming both employees and customers who say orders are taking too long. So they want to go even faster, but with 74% of orders now coming from drive-thrus, delivery, and pick-up, Starbucks may be on the verge of changing the flavour of its stores’ customer experience with new tech and systems - and maybe it’s vibe because it’s tough to make drinks quickly and keep the connection with customers.
Read more (no paywall)
Does this ad connect with you emotionally?
Or, does it rationally? Or not at all? Do you think it is designed for awareness, persuasion, or for a promise?
Behind my questions is some fascinating behavioural thinking going on - something I’ll be explaining in my next newsletter. I think you’ll be surprised!
What I’m reading
Elon Musk by Walter Isaacson: Love or loathe him, a fascinating study of someone hooked on taking huge risks, missing the empathy gene, but also with a broad, rich, view of ‘good’ innovation, the future and where we are all going. You can’t make some of his thinking up.
Trends
The Decline of the Nice-to-Have Economy
You might have been reading articles about The Decline of the Nice-to-Have Economy showing the increasing problems of brands providing increasingly superfluous offerings. They are symptoms of consumer shifts that have been underway for a few years, which are now boiling over into financials, product demands, and new tailwinds.
I’ve been tracking these shifts. It’s leading us to the rise of the new kind of consumer — generally more pragmatic, with mounting fatigue for hyper-consumerism, too much digital, social media-fueled exuberance and envy-driven commerce we’ve seen the past 5+ years.
Consumers today are turning away, putting energy into the old-fashioned, pure parts of life, which are increasingly seen as the modern — and even exotic — consumer aspirations in today’s world.
It focuses on things like a good night's sleep, walking 10k+ steps and other health and wellness, conspicuous commitment, a rise in DIY activities and hobbies, greater attention to personal and financial stability, stronger local communities, digital detox groups, the maturing of slow commerce, and true contentment across foundational life tenants.
It’s a what’s-old-is-new-again, a craving for back to basics. Because in periods marked by so much change and complexity, traditional life fundamentals become increasingly fragile and uniquely coveted — in themselves, they become the new luxuries.
Smart Thinking
“Part of being an authentic leader is knowing what you don’t know and accepting lessons from all directions”. Carol Cohen, Senior VP Global Talent @ Cognizant.
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- Michael
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