Tag Archives: behavioural psychology

Listen less, observe more. Human-centred designers must ask deeper questions

One of the most oft-repeated tropes of human-centred design is that we must pay attention to a person’s needs. These needs are often said to be identified through the observation of past behaviour. In digital (whatever that means these days) this is typically through the gathering of usage data. Sit in any pitch or briefing and it won’t be long before someone starts talking about dwell times, form drop offs and so on an so forth. Often a well-meaning ‘user experience’ staffer will pipe up about the need to develop personas, and a marketeer will add “based on our segmentation of course!” “of course!” they reply. Data is incontrovertible.

Really, businesses don’t like anecdotes. They’re not keen on stories (even if the managers are consuming books on storytelling and the engineers are developing use cases), so they rely on the known knowns – how people are using their site or service. It’s this, they say which informs us how people will use our experiences in the future.

I’m unconvinced. Increasingly I find myself resisting the temptation to read much into past behaviour. The empirical psychologist in me knows that, to be a predictor of future behaviour, fellow researchers have come to some agreement that there really are quite strict conditions for this to be the case:

  • The behaviour has to occur rather often (i.e. it’s high frequency).
  • The prediction is most accurate if based on a short time frame.
  • The predicted situation must be a close match for the past situation that the observation was made from.
  • The behaviour must not have been influenced by negative or corrective feedback.
  • The person must be unchanged and, finally,
  • The person must be generally consistent with their behaviours.

That’s quite a set of experimental conditions to maintain. Consider this, if your customer bought from your site or interacted with your brand once before, can you honestly assume that they will meet all those conditions on their return visit? Even with high-traffic repeat visits I’d contend that there’s sufficient variance to make predictions at the very least, wobbly. Add in a timeline of a few weeks or months (like financial services sites, for example) and your prediction is looking essentially worthless.

Demographics are not behaviours
Quite apart from the predictive past performance within your own brand experience, what does this mean in terms of inferring behaviour from others’ actions? One of my bugbears is the regurgitation of segmentation and demographic-led personas. Passed on from media buying and market research these exhibit the classic failure of data vs. insight, that is they offer no illumination. As an identical twin who shares the same postcode, age, socio economic group and racial profile as my brother, the lazy marketeer assumes I have the same needs and behaviours as he. Though there is some cross-over, there is much that is also different and to paint with broad strokes is to miss the kind of detail in human-centred design that creates real breakthroughs. Repeat after me: demographics are not behaviours.

In 2016 where profiling and polling were shown to be so woefully ineffective at determining voter action (c.f. Brexit, Trump), isn’t it time we took a long hard look at the way in which we interrogate and model human behaviour? Fortunately some are doing this and we might look to important contexts like criminology, where they are identifying the desistance curve as offenders age and applying Bayes’s theorem to calculate offenders’ likely behaviour.

Will it rain today?
Where this leaves us is in the area of accuracy. Ultimately, as Rory has asserted in the past, analogous to our weather forecasting, we’re getting better at predicting short term behaviours but still a long way off high-fidelity predictions for weeks and months ahead. What’s helped Dare and other progressive human-centred design teams is looking at what are the stable traits of human behaviour and, furthermore, rigorously considering what is the relevance and integrity of data that forms the inputs of our predictions; we should never draw general conclusions from specific observations and it is this inductive reasoning that plagues our profession.

Nate Silver’s seminal ‘Signal and the Noise’ is undeniably popular and his models had much early success but criticisms begin to be levelled quite fairly when attempts are made to model personal and social behaviour not financial markets. I wonder if, dear reader, you’ve read Taleb’s “Black Swan“? (If you have I wonder if you read all of it? I’ve met few people that have and if you’re like me you found it’s autobiographical style impenetrable, obfuscating and bombastic. Even the Wikipedia summary suffers a similar fate) in short Taleb makes the same point, we care way too much about the inputs to our black box of analysis and truthfully understand very little of what’s going on in incredible complex systems. Taleb also points us at another user-centred design bear pit: the narrative fallacy. We construct user journeys, use cases and flows in narratives that serve to over emphasise what we think we know and bring with them all the confirmation bias of author and reader combined. How often do we still read that it’s important we design brilliant experiences that delight? You’ll see testimonials plastered on the walls of Customer Experience Officers’ offices and headline grabbing responses from frontline staff going above and beyond, and yet research has shown for some time that exceeding some expectations does no more for loyalty than a comprehensive approach to meeting most of them. But it’s just such a nice story isn’t it?

I don’t believe that the way human-centred designers unquestionably use the tools our industry have been using for the last 20-odd years gets us to great solutions.

I believe we need, like Khaneman did, to take the lessons from Taleb and stir in even more psychology, evolutionary psychology.

The answers are in our past, our prehistoric past
I’ve found comfort in developing an approach based on two seminal statements on consumer behaviour: The late David Ogilvy’s famous quote questioning the value of market research: “people don’t think how they feel, they don’t say what they think and they don’t do what they say.” and further Theodore Levitt’s “People don’t want to buy a quarter-inch drill, they want a quarter-inch hole“. I would go one step further than Levitt and suggest that they want to hang that shelf that their spouse has been hassling them about so they can unlock a little more affection. Our modern age skulls house stone age minds and, as far as I’m concerned, a ludicrously overlooked truth is that we are a species that was for a very very long time motivated by procreation, the next meal and the next opportunity to rest. These basic needs of simple satisfaction surely form the basis of our the vast majority of our motivations and when we understood the roots of our behaviour we begin to unlock some truly creative solutions to our clients’ problems (there’s a reason everyone’s talking about Lagom and Hygge, simple satisfaction is incredibly human). We don’t get there by asking our customers this stuff, we get there only through anthropology and ethnography level observations: facial coding, eye tracking, galvanic skin response, neuromarketing. I’ve yet to see a CV where a UXr tells me they’re fascinated in anthropology or they’re fluent in FACS taxonomy, when I do I’ll hire them.

Research and analysis like this doesn’t come cheap and it doesn’t come quickly but tools like iMotions and IBM Watson have the potential to do for behaviour modelling what supercomputers have done for weather forecasting. Interpretation by inquisitive and analytical strategists that are comfortable asking ‘5 whys‘, doing field observations and contextual inquiries will guide us far better than fire hosing strategy and Ux teams with web analytics. To be clear, I am not dismissive of the role of usage data, I simply insist that it augments a broader collection of data gathered from IRL observations and a contextual understanding of human behaviour.

Bury the cliches
Henry Ford never said he didn’t listen to customers (I happily correct anyone who regurgitates the Faster Horse quote), Schiller never said Apple don’t do customer research (rather they do deep ethnographic studies and are ferociously tracking observed behaviour). I’m not saying we won’t learn from customer behaviour but rather, in order to get us to innovative, creative human experiences and behaviour change we must go beyond a facile and shallow observation of customer segments. We must build intelligent teams, use tools and encourage methodologies that give us the time to build upon the evolutionary roots of human behaviour and, whilst doing so, accept that our view extends no further than the horizon, we are powerless to know if it will snow next Christmas.

In a future post I will explain why I believe an automated approach to predicting and ‘optimising’ human behaviour through so-called personalisation offered by web platforms is not helpful at advancing our online experiences.

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It’s really easy to make stuff persuasive: A story of linguistics, prototypes and Dare.

Picture from Fine Country Lifestyle – Devon Farm Shop

I’ve done the same presentation about psychology, seduction and persuasion several times. It changes a bit here and there depending on the audience. I include a few more contemporary examples, add a few gags and throw in the odd bit of data to back things up.

At one part of the presentation I talk about how adding largely meaningless adjectives to products makes them more appealing – so pepper becomes hand-cracked pepper or we add a provenance like Suffolk honey. I’d always think of these off the top of my head during the presentation and, for the sake of a little humour, would try and invent outlandish examples to make the point (an in so-doing probably dilute it). Then last year I was watching the inestimable Stewart Lee when he amusingly parodied the craft-beer industry with some ludicrous names: Gandalf’s Memory Stick, Hogwarts Bukkake and it inspired me to keep doing the same gag.

I must have been holding on to this idea for a while and I got chatting to Dare’s technical director, Charlie, in a cab. Charlie’s got an academic background in English and a similar sense of humour so we naturally came round to the idea that this generation of novel food labels could be done in a random fashion. It seemed so simple to concoct the recipe: take a foodstuff, add a method and a provenance and the result takes an ordinary staple and turns it into a farm shop or artisan product that can be sold with a healthy mark-up.

Persuasive marketing nomenclature, automated with a tinge of comedy.

So we (well he) started building it. A simple JavaScript took items from three arrays (lists of data) and combined them at random in the order: Provenance, Method, Foodstuff. It worked quite well. But, thinking about the old adage of garbage-in, garbage-out, we noticed that some of the combinations didn’t work.

Does it feel right?
At this point we should stop and consider what we mean by work. It’s quite subjective, but you have to think about it a bit. The comedy is about the combinations appearing almost right but a bit outlandish. If you go too far toward the outlandish then it just feels wrong. In some cases this is obvious – the pairing of methods with foods that don’t make sense hand-reared houmous, pulled briochegrass-fed asparagus. So we started to think about what it was about these pairings that made them wrong and how we could eliminate them. Do you, for example, identify a matrix where methods applicable to foods are deemed ok/wrong? So hand-reared is relevant to all animal products? line-caught is relevant to seafood only? Or do you simply manually edit the list to exclude methods that are too niche? The trouble with doing that is that you reduce the serendipitous moments that make this work. Trying to avoid creating a behemoth that relies on learning or crowd-sourcing inappropriate pairings I set about building an Excel sheet with a series of lookup tables that allowed me to fettle with the source lists and try out combinations without relying on a very busy Charlie to repopulate his script.

Syntax is important
Creating the spreadsheet opened up even more questions. Taking a leap from an unconnected musing I had on Twitter last week, it occurred to me that order – syntax – is an important part of the output. Food will always come at the end but does changing the position of provenance affect the humour or the apparent luxury of the item? To use an example, is Newlyn fried corn a different product to fried Newlyn corn? So the method seems more artisan and niche if it’s Newlyn fried (presumably only a handful of people know how to fry the Newlyn way) as opposed to the corn being from Newlyn and then simply fried? It’s almost the difference between an item being at the bottom of the prestige retail hierarchy and the top.

Aside: Could you put the following retailers in hierarchy of perceived prestige? Tesco Finest, Waitrose Seriously, Marks & Spencer, Whole Foods, Borough Market, Artisan Farm Shop, Selfridges …

Provenance and terroir
Looking at the list we’d made for provenance it was clear there were two things going on. Once was about the association a place had with the growing or raising of food and the other was about what this meant by association. So the concept of terroir is that the geography, geology and climate of a place affects a foodstuff. It’s hugely important in wine and coffee to know the place it’s come from, but also in items like meats or vegetables (Hereford beef, Norfolk turkey). It gets more complicated when you add in the method of preparation or the regional significance of a recipe (A Bakewell tart, a Cornish pasty) or get super-niche and choose a specific producer Blacker Hall quiche. Consequently, the list we compiled is composed of places that have strong associations with food – largely agricultural counties, coastal locations and regional recipes. I then scoured a list of Britain’s top 50 farm shops and delicatessens for examples of artisan-sounding producers

What’s a method, what’s a foodstuff?
Related to our thinking about ordering and the awkwardness of pairings it became apparent that the foodstuff could be the array that includes a variety of methods specific to that food. So, instead of simply putting pork we could add pulled pork to the list. We could have scallops and hand-dived scallops. This would mean that we wouldn’t need to worry about hand-dived pork coming up but we could keep the fancy-pants descriptor of hand-dived to make the scallops seem more interesting. It’s fair to say it had stepped away a little from the original plan to have a simple 1+1+1 = 3 pattern (but that was about to have another twist anyway). We started to think a bit more about what constitutes a food and that complicated dishes don’t work so well as items that are atomic or simple but this wasn’t clear cut. Bakewell vanilla-infused cupcakes works but Jersey broiled yoghurt doesn’t. For every decent example involving brioche, sourdough, quiche, pasties there were far more decent examples involving single ingredients – asparagus, quinoa, lentils, beans, chicken. Once again, order plays a part here and having categories might help solve this. Hold that thought.

Something extra
Finally, after about two days fiddling about in Excel and chatting to Charlie we decided to throw in another part to the concatenated string, a garnish perhaps. We had a randomly-appearing descriptor that affected the overall product. It could be vegan or gluten-free or giant. So, not so-much a method or a provenance but in the spirit of the type of thing that gets added to nomenclature to change the perception Clearly the taxonomic importance of vegan/gluten-free over micro/giant is worth bearing in mind. It many cases it works wonderfully: Giant sugared Herefordshire pudding in others not so well Salt-Baked Pommery Vegan Steak Pies, so it’s fair to say that becomes a matter of user preference. Which leads us neatly on…

Getting it out there
After a while you realise there’s loads more you can do and several of these things made great sense. I always loved the Urban Spoon app that helped you find a restaurant matching a series of criteria at random, the trick was that you could lock down the most important part of your criteria – for example price, and then leave the random bit to choose the genre, location or both. It strikes me that this might be a nice add-on to our generator. You might lock-down the foodstuff and just play around with random combinations of qualifiers – the most fancy chicken product you can find for example. Then there was the consideration that this could have a crowd-sourced element; users could work in volume to rate the best combinations or highlight ones that don’t work. Clearly this would mean a lot more coding effort than we could afford to spend. What about supporting unique URLs for each combination so they could be shared or copied straight into a tweet link. And finally, what about categorisation? would this be better if you could focus-in on drinks, ingredients or prepared products like quiche, cakes, pastas.

Everything’s a remix
Back to reality and I realised fairly early on that this wasn’t that new. There are about ten thousand ‘generator’ sites that compose sitcom and film character names, craft beers and, perhaps channelling a little of the Bill Bryson observation on British place names, a village name generator. What I rather like about all this is that it seems to be most effective with our wonderful language here in Britain. I hastily trimmed out provenances that weren’t British and have tried to keep the foodstuffs a little native, scattering a bit of brioche or salami here and there does work but one must be parsimonious. when the strings get a bit long and they pick up quite specific methods like -infused or cold-pressed it can definitely feel a bit Heston Bloodyhell (sic)

To what end?
So, where does this leave us? Perhaps one day Charlie and I will get a public facing version up, designed hopefully around a style that befits the point-of-sale references we see in hipster marketplaces. A tool that uses some of the functionality we’ve mused about and ultimately becomes a playful little twitter stream. I like the idea that you could run this for 6 months with a voting mechanic, gather the data and establish a shop somewhere in a quaint Cotswold market town (Greater Drowsisle?) that sells products derived entirely from this output.

In the meantime it has given me a great chance to revisit ontological thinking, nomenclature and linguistics and logic. Any opportunity to play around in those fields can’t help but contribute to my understanding and enjoyment of the job I do on a daily basis.

A selection of how it works (or doesn’t).

  • Irish air-dried kale
  • Ballymaloe thin-sliced mackrel
  • Hand cut Suffolk micro couscous
  • Fermented Worcestershire buffalo
  • Pressed Derbyshire giant pheasant
  • Castleford dried rye bread

UPDATE: Now showing on Twitter@shinyplums
A Daily Mail headline generator and a direction to consider the writings of Brian Wansink concerning food psychology , thanks to Juliet Hodges.

UPDATE: Try it out for yourself with our artisinal food generator

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Experience design is rocket science

Back in January I posted an assertion that customer service isn’t hard to do. Sometimes I leave people wondering why I get paid a nice salary to pontificate on this stuff as it’s all pretty easy and largely the articulation of common sense. It’s the same argument I used to hear when telling people about the ‘obvious’ results of academic psychology studies. It’s easy to start believing this stuff and even though certain designs and designers are lauded for their pursuit of the obvious, others are called out as snake oil salesmen. Krug‘s done a nice line in books that make it plain how simple this all is.

This week, however I read two important posts. The first being from Harry Brignull, Senior UX at Brighton’s Clearleft. In his posts (slides and notes) he explores the mistakes he and the team made on the way to delivering the successful app experience for The Week. It rang true to read of his frustrations as blindingly obvious interface and navigation elements were wilfully ignored by apparently stupid users. How I nodded along recalling my recent experience with Treejack when my simple and straightforward site architecture for a major British institution was exposed as confusing and muddling one to users in a 500-person remote test. The second post, far more important and sobering, was the analysis of the last moments of Air France flight  447 (Popular Mechanics and Telegraph articles). With the recover of the various voice & data recorders a clearer picture of what happened on the flight deck emerged but, crucially, why the pilots behaved the way they did in the face of apparently obvious warnings and information has proved both incredibly complex and rather contentious.

This is where cognitive psychologists, engineers and really incredibly talented people are earning their crust. Analysing, exploring, experimenting and evaluating the hugely complex elements at work when we interact with systems. Our irrationality and unpredictability are being explored in light hearted ways as we persuasionists are asked to design new campaigns and digital experiences but when these forces work against us in catastrophic ways it causes us to pause and remember our colleagues and peers’ role in solving these riddles.

I might not be designing an error-proofed flight deck any time soon but I think it’s about time I stopped underselling our value quite so much. The work we do is complicated and rewarding, whether it’s saving lives, producing a digital magazine or shifting some more products. One of the final persuaders for me to transition from psychology to HCI was James Reason’s book Human Error and my course under Dr. Phillip Quinlan at York where we explored a variety of complex scenarios leading to catastrophic human error. Understanding the part designers had to play in helping us protect us from ourselves was a strong motivator. The book still sits on my shelf and I would heartily recommend it to anyone in this business.

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Seduction & Persuasion

A seductive look from French actress Audrey Tautou

This week I had the pleasure of presenting to our Planning department at Dare and, whilst it’s not a new topic to many readers of this blog, it’s certainly rather popular – in fact, one could say this tool is sine qua non to the kit-bag of any Experience or Strategic planner in the advertising industry. And so it came to pass that I spent 45 minutes talking about seduction.

Firstly I’d like to express my thanks to Stephen P. Anderson without whom much of this presentation would not have existed. It was inspired and informed by his excellent book Seductive Interaction Design which is currently trading at an excellent price on Amazon in paperback & Kindle editions.

I presented not in terms of rules or mere anecdotes but tried to provide practical examples of where we have been and could be seduced into acting on – and this is important – hitherto-unexplored motivations. I chunked the slides into a series of moments in our encounters:

From the utilitarian beauty of Google and Craigslist, to the the viscocity of the Apple iOS and taking in examples such as the role of female faces in encouraging ‘LiveChat’ encounters, I hope my audience could see the value in paying attention to what our experiences look like and what this says about our brands and the memories users take with them.

The ‘Stop Looking at my bottom‘ line on Innocent smoothies was a good example of being playful in seducing people, I’m sure there are plenty of quirky examples of this sort of stuff digitally. Sadly many of these are Error 404 pages that – if we’re good our jobs – our users shouldn’t see very often. After writing the presentation I came across this great example of copy on an Ocado email which represents a playful tease. Then there’s more obvious playful activities like the randomising functions you find on Wikipedia, Google’s Lucky button and so-on. Though few will ever beat Ben Fold’s Ode to Merton chat roulette.

I always like the anecdote that Apple had to make their random function on the iPod less random in order for it to feel more random.

“As humans, when we come across random clusters we naturally superimpose a pattern. We instinctively project an order on the chaos. It’s part of our psychological make-up. For example, when the iPod first came out and people started to use the shuffle feature, which plays songs in a random order, many people complained that it didn’t work. They said that too often songs from the same album, or the same artist, came up one after another. Yet that’s what randomness does – it creates counter-intuitively dense clusters.

‘We’re making it (the shuffle) less random to make it feel more random’: Apple CEO Steve Jobs changed the feature on the iPod after complaints from users In response to complaints from users, Jobs changed the programming behind the feature: ‘We’re making it (the shuffle) less random to make it feel more random.’  In other words, each new song now has to be significantly different from what came before, so as to conform to our expectation of randomness. Which isn’t really random at all.” – Alex Bellos

Then it was nice chance to show how figuring out and being stimulated by patterns can create compelling interfaces – which clearly meant reminding people of my award-winning work with Stefanie Posavec on myFry. I talk a lot about intentional friction when reminding people that user-centred design isn’t always about simplicity. After all, we all love a good poka-yoke, and so a bit of mystery like the Hot Wheels mystery car or the don’t open reward envelope is another example of intentionally making life (achievably) difficult in order to deepen the sense of engagement.

I closed this section by talking about how Cityville and Good Reads are great examples of interactions that allow users to play and be themselves, expressing themselves and their creativity. Cityville is a much bigger topic in terms of (eugh I hate this term) gamification which I didn’t have time to go into.

As Stephen points out, it’s all well and good talking about CityVille  and Innocent and seeing how fun brands can apply such approaches but what about when you’re dealing with a major financial services provider? It’s important to demonstrate that you don’t need to change the copy throughout your site or develop a game but rather just look at the little moments that make a difference in terms of perception and play to our existing biases. The classic Leventhal, Singer & Jones (1965) study at Yale led me in to showing two coffee loyalty cards for Cafe Gibbo. Both needed 10 stamps to achieve a free cup but one had the first two (of 12) stamped whilst the other was simply 10 blank circles. I asked the group to think about the behaviour that might result if the former card was stamped in front of you by a staff member who looked like they were doing you a favour whether that sense of reciprocity would be a sufficient nudge to you continuing to use that card. Perhaps it would. Pointing out that our decisions are not always economically perfect (both cards had the same economic effort to complete them) was important in establishing our irrationality.

Two coffee loyalty cards showing one with two circles of 12 complete, the other with all ten blank

Which would you be more likely to complete?

Of course this kind of stuff is nothing new to people in the hospitality industry; salting (or seeding) the tip jar, applying choice architecture to restaurant menus, this kind of thing shows the history of the real world application of persuasive techniques. techniques we consumers readily accept as fair game. In restaurants it might even be as minor as putting a glass seeded with an empty monkey nut shell next to the dish of unopened kernels to suggest where to put one’s wasteOn the web we see the value of order bias in the fact that Google and SEO companies makes a living from people clicking the first thing they see on the search results page and that having something visually promoted has a powerful effect.

Here I showed our own bit of choice architecture where we reduced the overwhelming choice offered by Standard Life’s Investment ISA to present 5 ‘bundled’ simple choice offers on the application form. Option one is to take one of these pre-packaged solutions, Option two [the ‘experts’ choice] was to select from a supermarket of funds. Not only did we hierarchically structure the page to promote the path of least resistance, but we used strong visuals and human-centred introspective copy: “Comfortable choosing from a wider range?”.

A screen grab of the application form for a Standard Life Stocks & Shares ISA

Making choices easier

Even something as simple as Facebook showing you the friends you will lose touch with when you deactivate your account is a clear example of using loss aversion (our tendency to disproportionally value things we have above those we do not)  reciprocity (your friends have shared their information with you..) and social proofs (everyone else is here) to – in their case – significantly reduce the number of deactivations per year. A few words about the power of emotionally intelligent signage and hopefully the point was made, this doesn’t need to be massive.

I couldn’t resist pointing out the classic HCI logic in the goal-architecture that means you get your card back at the ATM before your cash so that you don’t walk off with money and forget your card if the sequence was the other way around. A simple sequence decision.

Making a commitment
To close my 45 minutes I wanted  to touch on how making people do something different for a second, a few minutes even, can be incredibly powerful but that long-lasting behavioural change is incredibly difficult and complex. Perspective and influence over time from the herd and an array of variables means that designing such solutions is fraught with challenges. Though I didn’t mention it at the time I have talked before about my relationship with my energy supplier. Having used an energy monitor and post-usage data I was able to reduce the amount of gas and electricity I used at home, but after a while I realised I wasn’t getting any better. I’d reached a  plateau in savings, all my devices were low energy or used at their most efficient settings and so-on. I lost interest and stopped looking at the monitor or my reports. My usage crept back up. The classic YoYo seen in dieters and addictive behaviour like smoking.

It’s not enough to take these examples above and apply them to solutions as varied as increasing up-sell on insurance products, shifting metallic paint on new car configurations, moving people to a different mobile tariff, quitting smoking or eating more fruit and veg. Each instance requires a deep understanding of the specific problem, it’s motivators and triggers.

Which seemed a perfect time to call on Fogg. Running out of time now so if you want to know more about the application of behaviour change then do seek out these useful kits:

In the coming months I hope to be able to share with you some of the excellent work my team (Aarti Dhodia and Tom Harle) have been  producing to bring behavioural influence to an exciting service to be launched by one of Dare’s clients. Until then, I hope you find inspiration and enjoyment in the examples here.

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Behavioural Economics / Psychology of Persuasion & Influence Reading List

Thanks to a Quora answer from Rory Sutherland I stumbled across this excellent (and lengthy) starter reading list for those interested in the sociology, psychology and economics of persuasion. Well worth looking at for the people that have said ‘I’m done with Nudge, anything else I should read?’

ASIDE: This is probably the first time I’ve found myself on Quora and learned something. That’s not to say it’s rubbish (and who’d care about my opinion anyway) just that I’ve been a member of it for about 6 months but don’t bother checking so I only discovered this when it popped up on Twitter. So Quora made it happen, Twitter made me find it.

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Carrots and Sticks Wielded at the RSA

In doing a little research for some behavioural change theory as part of my day-job I came across this wonderfully brief talk that Ian Ayres did at the RSA back in April. I’ve been toying with carrots and sticks (I think both approaches can be wonderfully split-tested online) in my own work particularly around financial services. However, Ian introduces the idea of the anti-incentive and it’s a bit of a head-scratcher that I’m going to spend some time exploring for my clients. I think it’s got some potential but it’s perilous in terms of setting oneself up for quite the outlay should it be implemented incorrectly. So, without further ado, take a moment:

> More on anti-incentives found by Liz Danzico

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