πŸ’Ž On innocuous data signals predicting other behaviours (like your choice of browser and beer preference)

Dr Michael Housman, Chief Analytics Offices at Cornerstone OnDemand, pioneered the idea that people’s characteristics could be identified by their browser.

He analysed data from 50,000 people who his recruitment software company had helped find jobs and discovered that browser choice accurately predicted their performance. People who opted for a non-default browser, like Chrome or Firefox, lasted 15% longer in their jobs than those with a default browser, like Internet Explorer.

Housman attributed the difference to the fact that choosing Chrome or Firefox was an active decision — those workers were taking the effort to find a better browsing solution than the one pre-installed on their PC. That identified them as someone who wasn’t content with the default.

What’s the marketing application?

Clare Linford and I wondered if Housman’s finding could also be useful for marketers. Perhaps people who avoid the mainstream default browser choice, might do the same in other product categories?

We tested this hypothesis by questioning 22 lager drinkers about their brand of choice. When we split the results by their favoured browser the results were clear-cut. Only a third of lager drinkers who used Internet Explorer preferred a beer from outside the mainstream, top five lagers. However, 56% of those who didn’t use a default browser preferred a non-mainstream lager.

Excerpt from: The Choice Factory: 25 behavioural biases that influence what we buy by Richard Shotton

πŸ’Ž On information not being interpreted neutrally (we are swayed by contextual cues)

An experiment by Michael Deppe and his colleagues from the University of Munster, quantified the importance of media context. In 2005, the neurologists showed 21 consumers 30 new headlines. The respondents rated the believability of the headlines on a seven-point scale, with one being the most credible and seven the least.

The headlines appeared to come from one of four news magazines. Each headline was randomly rotated between the magazines so that each viewer saw the headlines in the context of every magazine. This allowed the researchers to address the effects of the context on the credibility of the headlines.

The scores were significantly influenced by the magazine. Headlines in the most respected magazine scored on average 1.9, compared to 5.5 in the least regarded magazine.

Information is not process neutrally. We are swayed by contextual cues.

Excerpt from:Β The Choice Factory: 25 behavioural biases that influence what we buy by Richard Shotton

πŸ’Ž On brands admitting a flaw (to make all their other claims more believable)

Guinness and AMV publicised the slowness of the pour with “Good things come to those who wait”. The National Dairy Council alluded to the high calorific content of cream cakes with “Naughty, but Nice”. (Incidentally, that strapline was coined by Salman Rushdie while working at Ogilvy & Mather.)

Admitting weakness is a tangible demonstration of honesty and, therefore, makes other claims more believable. Further to that, the best straplines harness the trade-off effect. We know from bitter experience that we don’t get anything for free in life. By admitting a weakness, a brand credibly establishes a related positive attribute.

Guinness may take longer to pour but boy, it’s worth it. Avis might not have the most sales but it’s desperate to keep you happy.

Excerpt from: The Choice Factory: 25 behavioural biases that influence what we buy by Richard Shotton

πŸ’Ž On the power of the media context to shape the message (it matters where you see it)

Information is not processed neutrally. We are swayed by contextual cues.

Jeremy Bullmore, former Creative Director and Chairman of JWT in London, notes that this affects not just headlines, but advertising too:

A small ad reading “Ex-governess seeks occasional evening work” would go largely unremarked in the chaste personal columns of ‘The Lady’. Exactly the same words in the window of a King’s Cross newsagent would prompt different expectations.

Excerpt from: The Choice Factory: 25 behavioural biases that influence what we buy by Richard Shotton

πŸ’Ž On the folly of hunting for a guaranteed formula for business success (because one does not exist)

Hunting for a guaranteed formula for success is a fool’s errand. As Phil Rosenzweig, Professor of Strategy and International Business at IMD wrote in The Halo Effect:

“Anyone who claims to have found laws of business physics either understands little about business, little about physics or little about both.”

Excerpt from: The Choice Factory: 25 behavioural biases that influence what we buy by Richard Shotton

πŸ’Ž On how too much data can make us overconfident in our predictions (rather than boost their accuracy)

The problem of more data was investigated by Paul Slovic, Professor of Psychology at the University of Oregon. He ran an experiment with professional horseracing handicap setters in which they were given a list of 88 variables that were useful in predicting a horse’s performance. The participants then had to predict the outcome of the race and their confidence in their prediction. They repeated these tasks with access to different levels of data: either 5, 10, 20, 30 or 40 of the variables.

The results were illuminating. Accuracy was the same regardless of the number of variables used. However, overconfidence grew as more data was harnessed. Experts overestimated the importance of factors that had a limited value. It was only when five data points were used that accuracy and confidence were well calibrated.

Marketers face a similar set of problems. They have access to more data than ever before and many believe that because the information exists they should use it. The Slovic experiment suggests otherwise. We shouldn’t harness data just because we can. Instead, as much time should be spent choosing which data sets to ignore as which to use.

Excerpt from: The Choice Factory: 25 behavioural biases that influence what we buy by Richard Shotton

πŸ’Ž On basing decisions on myths and anecdotes (bloodletting a prime example)

The study of marketing is so young that we would be arrogant to believe that we know it all, or even that we have got the basics right yet. We can draw an analogy with medical practice. For centuries this noble profession has attracted some of the best and brightest people in society, who were typically far better educated than other professionals. Yet for 2,500 years these experts enthusiastically and universally taught and practised bloodletting (a generally useless and often fatal ‘cure’). Only very recently, about 80 years ago, medical professional started doing the very opposite, and today blood transfusions save numerous lives every day. Marketing manager operate a bit like medieval doctors — working on anecdotal experience, impressions and myth-based explanations.

Excerpt from: The Choice Factory: 25 behavioural biases that influence what we buy by Richard Shotton

πŸ’Ž If a brand can change its comparison set it can change a shopper’s willingness to pay by orders of magnitude (a lesson in selling coffee)

Consider Nespresso. They sell in distinctive pods, which provide the right amount of coffee for a cup. Because they’re sold in that unit we compare their price to other places selling by the cup, such as Costa or Caffe Nero. When compared to the Β£2.50 Costa charge, Nespresso pods, costing 30p-37p, feel like a bargain.

But stop for a second and remember back to when they launched. If Nespresso had sold their coffee in standard packaging the natural comparison set would have other brands of roast and ground coffee, like Taylor’s or illy. Their price would have been judged against the norm for other coffees — roughly Β£4.00 for 227g. Even with tens of millions of pounds of advertising they could never have persuaded consumers to pay Β£34 for a 454g bag. But that Β£34 figure equates to 7p per gram, exactly what they’re charging now.

Excerpt from: The Choice Factory: 25 behavioural biases that influence what we buy by Richard Shotton

πŸ’Ž On the importance of providing a backstory to price cuts (plausibility of the deal)

But when Meghan Busse, Duncan Simester and Florian Zettelmayer, academics from MIT and the Kellogg School of Management, investigated they discovered a curious anomaly. In the previous weeks the car companies had been cutting prices so much that the employee discount was generally no better and occasionally more expensive, than existing deals.

The academics hypothesised that it was the price cue, not the price, which mattered. Consumers reacted to the plausibility of the deal rather than the actual discount. When consumers don’t trust brands they treat deals sceptically, but when they’re accompanied by a back story they have more heft.

When you are contemplating promotions don’t rely on an eye-watering discount. Numbers leave customers cold. We’re not natural statisticians – stories move us to action far better.

Excerpt from: The Choice Factory: 25 behavioural biases that influence what we buy by Richard Shotton

πŸ’Ž On why the mind is a lot like the human egg (confirmation bias)

The experiments prove that it’s hard to overturn negative opinions. Rejecters of your brand are difficult to convince because they interpret your message through a lens of negativity.

As the legendary stock market investor, Charlie Munger, said:

“The human mind is a lot like the human egg, in that the human egg has a shut-off device. One sperm gets in, and it shuts down so that the next one can’t get in. The human mind has a big tendency of the same sort.”

Excerpt from: The Choice Factory: 25 behavioural biases that influence what we buy by Richard Shotton

πŸ’Ž On why using claimed data in general to understand your audience can be misleading (Facebook likes vs. Spotify streams)

An example from SethΒ Stephens-Davidowitz illustates the problem. He looked at the gender of Katy Perry Facebook fans and found that they were overwhelmingly female. However, Spotify listening data revealed the gender split was much more balanced: Perry was in the top ten artists for both genders. If the music label used the Facebook data to target their advertising they’d be way out.

Does that mean the new data streams are junk and best ignored?

Not at all. Observed data is an improvement on claimed data, but it’s still flawed. To understand customers we need a balanced approach, using multiple techniques. If each technique tells us the same story then we can give it greater credence. If they jar then we need to generate a hypothesis to explain the contradiction.

Let’s go back to the Katy Perry example. A simple explanation would be that while both genders enjoy listening to her, far more women are comfortable expressing that publicly. If a record label wants to sell Katy Perry songs or encourage streaming, then Spotify data would be ideal. However, if they want to promote her concerts, it would be better to use the Facebook numbers. Neither data set is right in any absolutist sense – they are right in certain circumstances.

Excerpt from: The Choice Factory: 25 behavioural biases that influence what we buy by Richard Shotton

πŸ’Ž On obsessing over easily quantified data often having damaging results (the invention of the Tesco “Free From” range)

The obsession with easily quantified date crowds out the need for discretion and judgement.

Two examples illustrate the resulting issues. First is the experience of Terry Leahy who, when he was head of marketing at Tesco, analysed the performance of their gluten-free products. The sales data hinted it was an under-performing section – those that bought gluten-free goods only spent a few pounds on these items each shopping trip. A naive interpretation suggested de-listing them to free up valuable shelf space.

However, sceptical of the number, Leahy interviewed gluten-free shoppers and discovered that their choice of supermarket was determined by the availability of those products. They didn’t want to make multiple shopping trips, so the visited whoever had the specialist goods. After all, every shop had milk and eggs but only sone stocked gluten-free goods. Leahy used this insight to launch Tesco’s hugely successful “Free From” range long before the competition.

Excerpt from: The Choice Factory: 25 behavioural biases that influence what we buy by Richard Shotton

πŸ’Ž On how little shoppers notice when in store (sleep shopping)

One successful example was Sainsbury’s in 2004 who realised much supermarket shopping was done in a daze. “Sleep shopping” as they termed it. Shoppers were buying the same items week in, week out — restricting themselves to the same 150 items despite there being 30,000 on offer.

AMV BBDO, Sainsbury’s creative agency, went to great lengths to dramatise the extent of sleep shopping. They hired a man dressed in a gorilla suit and sent him to a Sainsbury’s to do his week’s shopping. They questioned shoppes as they were leaving the store and a surprisingly low percentage had noticed him. When shoppers are on autopilot it’s hard to grab their attention.

Excerpt from: The Choice Factory by Richard Shotton

πŸ’Ž On the danger of interpreting data at face value (Alex Ferguson’s mistake selling Jaap Stam)

Another example, this time involving Manchester United manager, Sir Alex Ferguson, didn’t have such a happy ending. Opta data showed that his star defender, Jaap Stam, was making fewer tackles each season. Ferguson promptly offloaded him in August 2001 to Lazio — keen to earn a high transfer fee before the decline became apparent to rival clubs.

However, Stam’s career blossomed in Italy and Ferguson realised his error — the lower number of tackles was a sign of Stam’s improvement, not decline. He was losing the ball less and intercepting more passes that he needed to make fewer tackles. Ferguson says selling Stam was the biggest mistake of his managerial career. From then on he refused to be seduced by simplistic data.

These criticisms don’t mean you should disregard tracking data. Expecting any methodology to be perfect is to burden it with unreasonable expectations. Instead, you need to be aware that it merely provides evidence to which you need to apply your discretion and judgement.

Excerpt from: The Choice Factory: 25 behavioural biases that influence what we buy by Richard Shotton

πŸ’Ž On the danger of uncritically listening to claimed data (you’ll be misled)

If Rudder’s study hunted at lying, the National Survey of Sexual Attitudes and Lifestyle (NATSAL) categorically confirms it. The survey, conducted among 15,000 respondents by UCL and the London School of Hygiene and Tropical Medicine, is the gold standard of research. In 2010 it found that British heterosexual women admit to a mean of eight sexual partners, compared to twelve for men. The difference is logically impossible. If everyone is telling the truth the mean for each gender must be the same.

All of this foes to show that advertisers trying to understand their customers have a problem: if they listen uncritically to consumers, they’ll be misled.

Excerpt from: The Choice Factory: 25 behavioural biases that influence what we buy by Richard Shotton

πŸ’Ž On how our expectations of a product shape our experience of it (our beliefs are hard to break)

Consider green goods. Rebecca Strong and I conducted an experiment to quantify the impact of labelling washing-machine tablets as β€˜ecologically friendly’.

We sent a group of consumers the same type of washing-machine tablet. They washed a load of clothes and reported back on the tablets performance. The twist was that half were told that they were testing a standard supermarket tablet, the other half a green variant.

Once again, there was an element of subterfuge. We didn’t ask consumers directly what they thought of green goods. Generally, they make positive noises. Instead, we monitored behaviour in test and control conditions.

The results were clear. Those who used the green variant rated the tablet as worse on all metrics.

Respondents scored the eco tablet 9% lower for both effectiveness and likeability, while the number who would recommend the product was 11% lower and the number who would buy it themselves, 18% lower than for the standard version.

Despite eco-friendly products often having a higher price, consumers who tested the green tablet were only prepared to pay Β£4.41 on average compared to Β£4.82 for the standard version. Consumers believe that products involve a trade-off: improved eco-friendliness entails corresponding loss in cleaning efficacy. This is a concern for any brand interested in a green variant. If brands in this category are going to successfully sell green variants, they’ll need to counteract these negative associations, or spend heavily to bolster their cleaning credentials.

Excerpt from: The Choice Factory: 25 behavioural biases that influence what we buy by Richard Shotton

πŸ’Ž On how much we’re prepared to pay for a product being partly determined by what we compare it to (beer versus wine)

I ran an experiment among my colleagues using King Cobra, a little known variant of Cobra lager. It’s a strong Indian beer, with an ABV of 7.5%, and it comes in a 750ml serving, the same size as a wine bottle.

A little subterfuge was required. I told my colleagues that we needed to run some tastings for a client. I organised two separate tastings of the beer alongside half a dozen other drinks. The participants rated the taste of the drinks on a scale from one to ten and said how much they’d be prepared to pay for each one in a supermarket.

The twist was that in each tasting Cobra was served alongside a different selection of drinks: in the first case bottled beers; in the second wines. The accompanying drinks had a significant effect on the amount people were prepared to pay for Cobra. When it was accompanied by bottled beers they offered Β£3.75, but when it was served with a selection of wines that rose, by 28%, to Β£4.80.

Excerpt from: The Choice Factory: 25 behavioural biases that influence what we buy by Richard Shotton

πŸ’Ž On how contactless payments reduce price sensitivity (beware overspend)

What about new payment technologies?

Recently we have seen a flurry of new payment methods – the most widespread of which are contactless cards. Gabrielle Hobday and I investigated how contactless cards affected price sensitivity by posing three questions to people leaving coffee shops in Central London:

How much did you spend?

What means of payment did you use?

Please can we see your receipt?

The last question was crucial, as it let us compare recollection with reality.

The findings were striking. People paying with cash typically overestimated their spend by 9%, whereas those using contactless cards underestimated by 5%. A stretch of 14 percentage points. Credit card estimates were, in contrast, spot on.

The variation is important: on a typical supermarket shop of Β£25, the 14% difference between recollections of spend on a contactless card and cash amounts to Β£3.50. Contactless cards could be the difference between remembering a shopping trip as expensive or cheap. It is this memory that determines whether shoppers return. A positive recollection can either be achieved by steep discounting, which erodes profits, or by an innovative approach to payment.

Excerpt from: The Choice Factory: 25 behavioural biases that influence what we buy by Richard Shotton