- Trussst is what stops people buying online, as customer service/delicvery etc is unclear. Consumer reviews are good at creating trust, also earned media. Using recognised logos eg paypal also helps
- Often need to give people some sort of value upfront as unknown/ untested vendor (Freemium, 30 day trial etc)
- 30% of online shoppers and rising worried about privacy (about bloody time too)
- When they scanned websites to get missing f2f trust cues, they found yellow was the worst colour for trust, followed by red
- Websites need a very defined call to action button (Now this is really Web 1.0 old hat, but since Nathalie's talk, I've become really aware of how many sites still do not do this)
- Using the scarcity principle - "only X left in stock" - to create a sense of urgency, really works
- UK is culturally difficult to US, need to soften the hard sell -
- Tweet to unlock benefits seems to work well
- Humans focus on contrast, and on concrete stuff - eg money management website example "I will teach you to be rich" is succinct and to the point.
- Framing in terms of loss raher than gain is better, as Humans are more loss averse
- 10% of a population = tipping point, when people start to follow without thinking (Interesting, I've seen memetic algoritms that calculate that when say when cheating gets to about 5% of the population it then starts to spread rapidly)
- This is an emerging new field - cognitive economics
- Talked about improving profit via the "rule of 3" - Typically with 2 choices get a 70/30 split, 70% cheapest.
- Insert an expensive 3rd choice - 3 choices split 60/35/5 - fastest way to improve profit
- Concept of "anchoring" - set expectations of higher price first, people will choose next cheaper option
- Human brain treats spending money siilarly to pain, so give people something or offer a later payment
- If you make price complicated, befuddles customer, reduces ability to discern (I tried to ask Leigh why mobile Co's, Energy Co's etc do this, despete stromg evidence it puts off customers but ran out of question time)
- You must Price differentiate for different customer segments to maximise profits, but be prepared to lose some sales
- People will value what you price
- Old models (persuasion) only lead to accidental success as 95% of decisions are instinctive, not rational/ logical
- People don't like change/new ideas, so try to rationalise to their past knowledge, and it seems to work "well enough" as new approaches haven't really had major impact yet
- New approaches are still complicated to use, no rules of thumb, no benchmarks
- Rapid Change, new "New things" every 6 months - overwhelming amount of data coming out and overwashing last new new thing
- "Institute of Decision Making" set up, linking Research to actual Application of these ideas
- People buy things to achieve goals, they do not have a "relationship" with brands as such. And their real goals are the implicit goals, eg buy Mercedes to feel powerful
- 3 main implicit driver axes
(ii) excitement (drives dopamine)
(iii) autonomy (drives testosterone)
- Intersections between the above 3 exist - then adventure, discipline, enjoyment (see my diagram at to of page)
- So move proposition to answer explicit and implicit goal. E.g. Oreo - explicit goal, treat child. Implicit goal - passing on your experience, childhood
- technology is not the issue in Innovation
- people need to see the benefits,
- also must sort wheat from chaff
- need to put culture in place to force innovation
- Idea management is about process of generating, selecting and executing ideas, not about the 1 big idea
- Only about 5% of ideas will get executed
- Its roots were in music roots so they started look at interconnections there
- looked at what energy drinkers like, by age, sex, etc etc on FB, and clustered the data into 200 like groups with interlinks,
- Saw that Relentless drinkers unique in Top Man U, Bad Diets, Classic heavy metal. So th
- Built Matrix of Energy drinks vs like groups, with probabilities on intersect.
- Overlay like groups with demography, and created a new new psychological profile layer above the "correlation" layer
- Relentless users are impulsive, neurotic etc, create narratives to fit
- Found that Music choice is a good proxy for personality index overall, so you can see eg Aerosmith and Journey hit different people
- Now working on Numerical score of musical affinity
- built Unruly Sharerank algorithm by testing large no of hypotheses of what drives sharing vs actual sharing
- Myth #1 you can't predict sharing - you can, and quite accurately
- Myth #2 content must be funny - but you can do warmth or excitement as Main vector for eg
- 2 Video examples predicted - "3"s Pony doing a Fleetwood Mac Dance = funny and happy and warm; and Pepsi's Camaro = funny and nervous and excitement
- Camaro did as their aglorithms expected, Pony did much better - mainly due to an unpredicted factor, the horsemeat scandal at teh time
- Viral peak is usually day 2, on avearge 25% of all shares on 1st 3 days
- optimal time of video = c 3 min (We found the same for video clips when testing in 2007)
- The only people who were shocked by behavioural economics were economists (rational man)
- $35bn Market prediction industry, only 2% modern tools - why?
- traditional tools are not that broken
- New methods are not that simple to use, and hard to transfer from specific project
- emotion is not everything, most people have very little resonance with most brands most of the time
- New methods give very different results but case law does not exist to calibarte them - very little published success.
- Also they are hard to understand
- Most useful method they have found is facial response, map facial
happiness as Ad plays. Integrated with survey data from same people
- Shows key impacts across different cultures, and what people react to vs what they say they do
Can also check reactions at 2nd view etc.
- Online Behavioural Psych is more Nudge than Revolution
- using mobile technology to improve productivity
- if you get 5 hours sleep a night you are no better than being drunk
- only a decade into ubiquitous connectivity, 3 years into smartphones, so started to look at what can be done
- use Design thinking to structure workflows, design Prototype Days to test what works/doesn't work, timeline a bad day, see what you can learn.
- Also looked at older ideas that neuroscience backs up
- Thinking is expensive, glucose is measurable - habit is lowest energy levels
- work day doesn't match how our brain works. We only have 3 - 4 hours a day at peak performance, yet we often waste it on doing emails and meetings
- Benjamin Franklin was a major designer of his day
- Need to close off little worries
- Know when to switch off, scheduling time for email and Twitter etc - McKinsey report showed multitasking is less efficient on all tasks
- Use technology to remind you to do something different that is good for you, force behavioural flexibility
- people tend to use some behaviours too much, drives personality (locked in habits)
- brains like to save energy, repetition drives strong pathways. But this default is not always right way in every situation. Success can over- embed behaviours.
- If there is a gap between our behaviours and what is needed, it drives stress, eg: strong extrovert may not have introversion capability, creates stress
- Most effective way of changing people is not change what they know but change what they do, as otherwise they flip back to what they know how to do
- People develop by doing new things, trying to do same stuff in new ways
- how to use technology to change larger groups - uses social data to drive changes in organisations
- Amount of data in businesses has grown hugely, used to have data scarcity, now glut in flow and storage
- Unstructured data is the major challenge, we now store it and work out how to structure it later (I agree with Benjamin here, this is the major issue wiyh a lot of Corporate data)
- Old way of marketing - ask people, but they tend to give acceptable answers - different Co cultures drive different mindsets - measure attitudes, not behaviours
- New way - scrape social media behavioural data - tells are not only what people say, do - but how they do it eg how long they take - aim is to predict behaviours
- A lot of social network data is not behavioural, it's managed attitudinally
- In businesses using social media proxy data, main lesson is the shape of the graph
- Language used is an interesting tell, in the business social media, you can tell a lot of things from it, eg Sentiment
- Look at where people use common language, shows the social influence graph
- But can wind up with "beautiful mind" syndrome, seeing many many potential patterns
- Also need to factor out correlation, to only get causation - its very hard
- People also follow biases when given Big Data, anchor on the 1st thing they see, confirmation bias and bandwagon effect can take over
- Chris Anderson saying sheer volume would obviate theory - wrong. Nate Silver book better
- Game mechanics is using psychology to influence behaviours
- Rory Sutherland started behavioural economic arm, heavy usage of outside academics. Case study was that people are stopping buying newspapers, so how do we sell them again. Approaches were
- 3 option choice architecture with dummy option (like Economist used)
- differentiate between tablet, PC and smartphone offerings
- Nudge 1 choice sleight of hand in use of deals (see Economist above)
- Nudge 2 choice overload
- Nudge 3 superiority bias - "ultimate" pack
- Nudge 4 - create easy to choose default
- Piloting: trying out the New new thing in some areas of the business, somethimes structurally, often though by "Intrapreneurs" who do it locally out of passion, or seeking promotion etc.
- Pressure: A company realises it will not succeed doing "Business as Usual", and has to do "Business as Different". Recessions are for this reason more likely times to see new ideas implemented
- Politics - needing to be seen to be "with it", intra-divisional rivalry etc - all these can drive early day projects
(i) Replace the modus operandi of most businesses. Social Media is essentially a communications medium, like telephony or IT. Telephony made a major difference to the cost of selling retail insurance for example, but it did not replace insurance. Web sales has restructured the book industry, for example - but not replaced it.
(ii) Replace existing operating techniques - marketing and sales techniques, service techniques, working practices etc - or not straight away, anyway. This is for 2 reasons. Firstly, existing techniques exist because they still work a lot of the time, and Social Media is not an appropriate complete replacement, but is an adjunct to improve them in most cases. Now it may come to pass that eventually Social Media might replace, say, telephone call centres - it's plausiblee - but than a bunch of other things need to change too so it will more likely be a phased change, not a big bang. Secondly, history tells us that any new enabling technique actually doesn't replace the old, it usually just slowly supercedes it in the pecking order. The revolution will (in the main) be evolutionary.
(iii) Massively replace employees with other peoples' brain cycles - "crowd -X'ing" is overblown, because most businesses do not win the day on one-off surge efforts, but on day to day execution over many cycles, and to do that you need well trained and motivated teams, not an ever-shifting cast of part-time volunteers. Adhocracy is a great way of getting Ad hoc one-offs done, and we are all for it in its place - but its not a great way of delivering reliable, predictable products and services day in day out.
(iv) Be the Silver Bullet that saves the day. It will need to integrate into a number of other existing systems in any enterprise. Social Media is a new layer of enabling communication technology, that makes existing practices and processes more productive, or effective, or both. The degree of just what, where and how it is apporopriate will vary by company and industry.
(v) Ensure that This Time Things Will Be Different, save the Planet, bring Universal peace and Love, etc etc. Humans are humans, with the same foibles as they have ever had. Social media is not going to bring about a Business Utopia, where people give warm personal service all the time, all goods are maximum quality at minimum price, and cheaters never prosper - but because it lowers transaction costs, all those things will become a bit easier to police - and thus new ways of cheating, skiving and flogging lemons will emerge.
- Leaky Ships: Sensitive information will leak more easily, so there does need to be more attention paid to keeping things tight where required. This is of course in direct opposition to the need to be open, and finessing the systems that handle commercially important data is still an emerging area and in our view is still a limit to Social Media reaching its theoretical potential.
- The Viral Faux Pas: The inappropriate and inopportune tweet that goes viral and pours opprobrium on the company is a frequent enough occurrence to be a Social Media standard trope. Apart from blaming it on the Intern, companies do need to be careful and have checks on their output, and damage limitation measures in place
1. Are typically a very early entrant, integrating a variety of existing systems in a hitherto poorly served early adopter sector with promise, to create an easy-to-use product.
2. Use great design to create a demand for a high margin product. In recent years they have also become "cuter" at doing software as well as hardware after being caught out by the MS-DOS ecosystem
3. As that market matures, retreat to the highest profit quartile. Follow the money, not the volume.