Keynote: Why Social Media “Likes” Say More Than You Might Think by Dr. Jennifer Golbeck, Human-Computer Interaction Lab, University of Maryland #ISC2015 #MRX
Live blogged from the 2015 MRA Insights & Strategies Conference, June 3-5, 2015 in San Diego. Any errors or bad jokes are my own.
- how much do two strangers online trust each other? you need to know about the people themselves first.
- social media data can give you accurate data, even when used in a simple way
- can predict introversion, political leaning, procrastination, personal health habits from your posts
- likes on facebook are always public, can use this to predict many things
- top four likes most indicative of high intelligence include science, thunderstorms, colbert report, and liking the page for curly fries. For low intelligence, the like was for the page “i love being a mom” But these don’t truly relate to intelligence.
- homopholy – we are friends with people who are like us, our traits are more common among friends than among random people.
you just need one smart person to like a page and then it spreads like a virus to all your friends
- we’re really good at predicting sexual orientation, even in places where being gay could get you executed
- how does a store like Target figure out you’re pregnant, not from pregnancy tests, – an extra bottle of vitamins, a bigger purse, brightly coloured rugs together are a statistical connection
- how can you know what these statistical combinations are?
- can your social media network figure out which friend is your spouse? you know which friends are friends with each other and nothing else. Often it is the person with the most friends in common. But look at social dispersion instead, eg., your sports friends, your school friends, your family friends, your work friends. Dispersion is who is connected to the most of your groups – that is the spouse about 75% of the time. the other 25% is a good indicator that youre going to break up your relationship
- can predict postpartum depression from social media content.
- how easy is it to get data?
- takethislollipop.com – makes a video out of your social media accounts, try it if you think all your settings are private
- we leak a lot of data, we don’t realize how much data apps are pulling
- it’s not all bad – apps recommend products you might like, google uses it to make the web easier to interact with
- we don’t have control over it – don’t know who has data or what they’re doing with it
- even though the algorithms are smart, we still don’t buy whatever the algorithm says we might like. but they tell us things we would never think about but we actually want
- treat your business algorithms as useful but realize some are wrong or shouldn’t be acted on, it’s one more piece of advice
- [jen needs no slides, she changes every 5 or 10 minutes just for the heck of it, impressive]
- how do you figure out which people like the targeting or don’t like the targeting
- you don’t want to be the creepy facebook stalker guy, it needs to be handled with care
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Ten Emerging Privacy Challenges for Marketing Research & How to Navigate Them by Howard Fienberg and Stuart Pardau #ISC2015 #MRX
Live blogged from the 2015 MRA Insights & Strategies Conference, June 3-5, 2015 in San Diego. Any errors or bad jokes are my own.
- This is not legal advice 🙂 [and along those lines, please assume my notes are completely wrong. do the research properly and that doesn’t mean perusing this blog post.]
- There are federal and state laws, then more laws segmented by the vertical, and by modality of how you collect information
a data breach can cost millions, if one data breach is $200, then thousands or millions of breaches is huge money
- be transparent about what you do and don’t do, accurately describe what you do
- data security breaches
- playstation, sony cyber attack, target, home depot, anthem all lost millions of records; most states have data breach notification laws, when a breach occurs, you must report it
- states have different definitions of PII, different time frames, safe harbour for encryption so advisable to encrypt, build your policy for the most restrictive policy
- must have a conspicuous descriptive privacy policy
- Do Not Track requests – you need to specify whether you honour these request though you aren’t required to honour them [wow, did not know that]
- Eraser Law – minors have a right to be forgotten, if you know they are minors or your site appeals to minors it applies to you
- 2 beacons and mobile tracking
- tracking in around between brick and mortor without cash register receipts
- where is data going and where is it being shared, can you opt out, how identifiable is the data
- are consumers notified when they’re being tracked, if you don’t like it you can turn off your device [that makes me uncomfortable – IIII have to change my device as opposed to you buggering off?]
- Nomi tracking – say what you do and do what you say, they didn’t let people opt out because people didn’t know they were being tracked
- emerging area with great potential but must be very careful
- Spokeo case – firm does deep web crawls and aggregates it into reports, you can look up yourself or your friends
- must it be concrete harm to bring forward a case? if information is wrong and you can’t prove it, do you have a case; this case could open floodgates. in this case, the information seemed to be better than reality. [better is in the eye of the beholder]
- international data transfer – if you focus on US domestic you’re generally ok, but if one project is outside, then it matters
- if you work with EU, make sure you know the data principles; you can self-certify but then you must adhere to those principles, must renew it every year; requirements for regular privacy assessments; need a privacy officer if you have 250 or more employees
- MR is a data broker, FTC won’t rule our MR
- policy makers are concerned with brokering data for marketing purposes, and verification of respondents
- need option to be able to delete all the information they have about you, this is because we are sometimes lumped in with creepy businesses
- Internet of things – hypothetical security risks right now, unauthorized use of PII, attacks on systems, personal safety
- focus on privacy by design, select providers carefully, control access and monitor constantly
- how do you deliver notifications on a device with no readout
- American community survey – gets response rates around 95%, because government survey and because its mandatory, but mandatory upsets people, voluntary would cut repsonse rates to 50% and we wouldn’t get data from about 40% of the country
- BYOD – bring your own device
- employees can access sensitive company data on their own device – HR, health, financial, trade secrets, client lists, confidential information, or, employees use company devices at home
- if its your own device, you can control it or lock it, otherwise you have no control
- still must notify if data is breached even though its not your device
- Employers could say you’re not allowed to use your own device but this is not realistic, its better to have a policy
- Policy – onboarding documentation, agreements to keep data secure, remote data deletion and limits on apps, data retention, termination process, be clear on who pays for what
- Federal Trade Commission – deceptive and unfair trade practices, polices data privacy and data security
- LabMD/Wyndham hotels cases – failed to institute reasonable and appropriate security measures, case is under appeal and suspect FTC will be allowed to police data privacy
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Keynote: Demographic Shifts Are Moving Your Markets by Joel Kotkin #ISC2015 #MRX
Live blogged from the 2015 MRA Insights & Strategies Conference, June 3-5, 2015 in San Diego. Any errors or bad jokes are my own.
- Future drivers of growth: rise of opportunity city, persistent of suburbia, critical importance of housing affordability particularly for families, canaries in the coalmine like seniors millennials and immigrants
- we’re no longer in an era where income correlates with housing prices, housing prices are 6 times the income not 3 times
- recently biggest growth has been Houston, dallas, Denver, san fran, Miami
Fastest for STEM jobs has been Detroit, Houston, San Fran, Seattle, Denver, Dallas
- NY can’t compare to silicon valley at all, their area is media
- Two success approaches – opportunity vs luxury – economic diversity, reduction of poverty, affordable housing, middle class job opportunities are things the luxury cities don’t have
- net migration is highest for dallas, Houston, Denver, Seattle; lowest for new york, Chicago, LA, Detroit
- Affordability is worst in san fran, LA, new york, Miami, Boston, Seattle; san fran ratio will hit a ratio of 10 very soon where it’s normally 3 (house price to income ratio)
- wealthy classes go to certain cities because they can afford to
- consumer housing preferences are 80% for a detached house, 8% want an apartment, 3% want a mobile home
- suburbs continue to grow out much faster
- 25% of people want to live in rural areas, 50% want suburbs
- millennials have high student debt, plunging home ownership, millennials are moving to suburbs
- population is growing fastest in Miami, Detroit, Houston, Denver, they are hidden millennials
- 80% of millennials also want to own a home
millennials might have not had the exposure to small town life like previous generations
- millennials aren’t as different as we like to think
- but, they do have less money to spend so it will take them 5 to 10 years long to get things also they will also live 5 to 10 years longer than previous generations
- word has gotten out that you can’t afford to live in certain cities so millennials arent going there
- millennials are not perpetually 20 years old
- in 2018, millennials will be more likely over age 28
- 70% want to get married, 74% want to have kids
- couples need 2.1 kids to maintain a population. many places are now at 1.3 which means declining populations in those areas
- opportunity cities have more children
- seniors are a prime target for marketers – the young old as opposed to the old old
- young old are over 60 but active, maybe work, drive
household growth will be largest among 65+ households and the vast majority of wealth belongs to these people
- most retirees don’t plan to move or they plan to stay in their community
- people move to be closer to family, to reduce expenses, or because of a change in health
- immigrants are more likely to start a business than native born, they know where the best bargain is
- don’t believe what you read in the newspaper, check the statistics
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Branded Entertainment? We’ve Got a Stat For That! by Dr. Raymond Pettit, Rentrak, Inc. #ISC2015 #MRX
Live blogged from the 2015 MRA Insights & Strategies Conference, June 3-5, 2015 in San Diego. Any errors or bad jokes are my own.
- recall the Seinfeld episode where george’s parents stayed at a hotel and they thought everything was free – the hotel complained after the episode because hotel guests started to ask for macadamia nuts when the hotel didn’t offer those
smart brands turn to the content to integrate branding moments
it’s broad from passive placement like coke on american idol, organic integration like Seinfeld where the brand is part of the story as in the junior mints episode
- brands plan across platforms – movie TV and online
- the mere exposure effect – mere repetition leads to a change in underlying attitudes and responses, proven over and over again, the more familiar we are with something the more we like it
- implicit processing – 80% of what influences and drives us is not consciously apparent
- expert systems – technology supports and drives massive changes in measurement possibilities
- characteristics of branded entertainment – subtle, nuanced, and embedded, it is processed differently than commercials, try to make it part of the character
- how the brain processes images and sound – seeing and hearing a brand has a multiplicative impact on perceptions and memory
- celebrities and brand advocates – you can respond to a character, or the actor as a person, the person as an advocate for a brand
- narrative storyline aesthetics and information theory – compact powerful and efficient way to communicate
emotion and meaning – constantly interact
- predictive analytics – are woefully inadequate, people use surveys in general but branding moments are implicitly processed, people can’t self report because they aren’t really conscious of it
- branded entertainment and TV audience measurement
- case studies
- monster.com and pivot cable – used monster colours on the set, brand name was mentioned, ads on either side of the show; recorded shows with a time stamp, did biometric testing, eye tracking, facial movement, heart rate, skin conducting, also a short survey; branding segments were stronger than the ads, emotional response was higher, and survey showed a pre post difference
NBCuniversal and Frozen movie – NBC wanted to measure all the peripheral stuff, not the ads; there were 84 custom content elements to discover total audience reached was 362 million people and $4 million in media value
- Ellen show – wanted to measure cultural relevance of show, celebrity in the show, the show itself, brands in the show, audience in the theatre, the celebrity host; used implicit association, got 75% return on investment
- branding moments are important, measurable, and can be optimized
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Big Data and the Dawn of Algorithms in Everything by Dr. Morten Middelfart, Social Quant, Inc. #ISC2015 #MRX
Live blogged from the 2015 MRA Insights & Strategies Conference, June 3-5, 2015 in San Diego. Any errors or bad jokes are my own.
- has been a professional programmer since the age of 14
- Wrote “Calm – computer aided leadership and management”
- Level 1 – access to information; Level 2 – speed; LEvel 3 – autonomy of removing human from equation
- Maersk is the biggest container shipping company in the world, they could tell their client exactly where their container was to the millisecond in the 90s. Then they wanted to tell you where an item within the container is but there was too much data to go through and easily process.
built software that used menu driven programming in 2002
- level 2 was speed from 2005 to 2014 – access to data is now a commodity
- what is excellence in management and leadership and how can we apply computing to do more and better like that
- John Boyd is the father at the Top Gun school – concept called OODA loop – loop of observation, orientation, decision, action. Found a way to make planes a lot faster.
- what tools can we used in each of these areas, how do we communicate each of these
- orientation is analytics, simulation, data mining
- observation is dashboards, reporting, agents
- action is storyboard, communication, workflow
- decision is search for additional knowledge
- is there data we don’t’ want to analyze? why are you collecting data if you aren’t analyzing it
- analytics and reporting must be completely integrated
- each team in an organization must cycle these loops
- OODA loop includes strategic, tactical and operational levels
- the stealth bomber can’t be run by people because it is far too fast, if the computer breaks, the plane crashes, you get manoeuvrability that is impossible with a human pilot, it is essentially invisible. Human decision making isn’t fast enough
if you shut down your power for two months, which organizations would survive? we can’t go back to pen and paper anymore. We are already in the seat of the stealth bomber.
- [i always think, in ten years from now we’ll look back at our innovative technologies and think they’re hilariously old]
- now we have a lot of external data that is free, 90% of world’s data has been created in the last 2 years. any small percentage of the data is garbage, but the amount of relevant data is outside your company. What is its availability, quality?
- if you clean garbage data, its still garbage data.
- Kevin Slavin – How algorithms shape our world, a TED talk – talks about locations of stock companies so that they are physically closer to the cables to save milliseconds of processing time
- why do you need a dashboard? let the computer tell you if when something is wrong [hell yeah!]
- if you aren’t using algorithms, assume all of your competitors are. it’s not scifi. it is mainstream media.
- how can you use computing to accelerate ourselves, not replacing, doing it differently.
- SocialQuant startup – don’t ask what you want, have computer tell you what you want,
- Eli Pariser: beware online filter bubbles – TED talk, there’s a risk that whenever you ask a computer to show you something, it will always give you junk food, maybe it needs to show you things that aren’t what you want
- do you trust technology so much you’d bet your life on it – cars, planes, trains – can you trust google to show you the world? are ten results the truth? we generally believe it
- do we trust facebook to take what is relevant about all our friends and put it into one stream
- only 1 in 4 people are helped by cancer drugs, only 25% get a life prolonging effect, chemo by default is not a good choice
- when its a confined game, rules are set, computer will win every time
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Keynote: Innovation, Technology and the Future of Marketing Research by Ashish Soni, USC Viterbi Engineering Startup Garage #ISC2015 #MRX
Live blogged from the 2015 MRA Insights & Strategies Conference, June 3-5, 2015 in San Diego. Any errors or bad jokes are my own.
- Give support and mentorship programs, look for disruptive innovation, companies you cannot clone in a week
- Deep insight versus deep technology vs big product
- the best way to predict the future is to create it = peter drucker
- when you get the urge to predict the future, better lie down until the feeling goes away – forbes magazine
- technology fuelled disruption – exponential improvement in core technology
- cost of computing and storage will soon be less than pennies per gb/mbps
- democratizes computing, information, and knowledge, now anyone can access processing power, storage on their own device
- digital products are disrupting all industries
- 30 000 startups launched in 2015 and will grow exponentially – we’re at a Cambrian moment
- kickstarter campaigns have had 1.8 billion pledged
- besides sleep, we are digital creatures – learning, shopping, dating
- SMACS – social, mobile, analytics, cloud, sensors
- software is eating the world – marc andreesen
- SMACS will eat market research
- Most companies already have big data, now they need big computing, the next is applications – simple tools that put power of insights in the hands of the users
- it lets us do things differently and do different things
Tilofy – worlds first universal offline analytics platform – looks at demographics, tag clouds, influencers, heatmaps
- io – leading video intelligence platform – know what video reviews are saying about your brand
- Muko – next generation mood driven music discovery – ingests music reviews, aggregates meaning and emotion, can apply to any product
- machine intelligence – can system anticipate what i want before i want it, this is already coming
think about microsofts how-old.net program works
- deep learning is AI, used to recognize objects and translate speech in real life – machines can now understand a photo
- affective computing – system understands who we are,
- virtual humans – can be used for training, therapy, training in the lab and in real life, can interpret human cues, just needs a camera
- Neurovigil – a small headband records EEG as long as you wear it and sends it to drug company doing pharmaceutical collection, don’t need the patient to come in and hook up or do anything
a computer should not ask anything it should know, sensors profoundly change what a computer can know, every new sensor creates a new business
- the future is seamless and pervasive intelligence, reusable, automated
- technology facilitate new ways to capture, understand and predict human behaviour
- the web sees, understands, and forgets nothing
- text comes from NLP, analytics; images comes from deep learning, vision; audio comes from AI, deep learning; video comes from deep learning, vision
- intelligent ethnography – can be 24/7 with cameras and audio video
- mobile sensors, passively behind the scenes, just based on your phone data, can tell your age and gender, without installing any application
- data aggregation is the next area for MR – GNIP, twitter, RescueTIme, DataSift
- next market research is dynamic 24/7, contextual, passive and active, digital and analogue, what i DO, real time, future/predictive
- AIO robotics case – identified top five complaints about the product and made these their main goals
- Does WHY matter – with enough data, the numbers speak for themselves
- What makes a sticky user – someone who adds 30 friends in the first week of using a social network, think about facebook vs myspace growth and development
- today is market research, the future is computational social science
- book – the mind in context – by batja mesquita – thoughts feelings are not driven by a single cause but multiple transactive processes
- what will my company do when everyone has great processing power on their own
- technology will be the core of the future, need generalist technologists to keep them informed about the edges of technology
- be prepared to kill your first born [not for real!]
- you can’t know it all so partner with other companies
- prepare to become a computational social scientist [LEARN R!!!!]
- learn how to manage, clean, process data – R; stay on top of new applications; partner with a company that does manage data
- two sales people go to africa to see if their is a market for their product. one returns and says there is no opportunity there, no one wears shoes. The second returns and says there is fantastic opportunity there, no one wears shoes.
- @StartUpMind is his twitter name
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Keynote: “Good Enough” – The Myth of 70% Emotive Accuracy by Dan Hill, CEO, SensoryLogic #ISC2015 #MRX
Live blogged from the 2015 MRA Insights & Strategies Conference, June 3-5, 2015 in San Diego. Any errors or bad jokes are my own.
- Self-report has its limitations
- In the New York Times, men report 1.6 billion condom uses per year but only 400 million are sold annually
- 95% of mental activity is subconscious
- It’s not just lying, it’s what people can’t tell you
- Self-reported information can be lip service, filtered input
- Emotional metrics include recall, call to action, preference, satisfaction, loyalty
- We have a sensory brain, emotional brain, and rational brain
Emotional brain is 10 times more active , emotional responses have 5 times more quickly than cognitive responses
- Consumers are well informed but not rational well informed
- 20% of adults in the western world are functionally illiterate and have no real command of the English language. [and yet we write the longest most complicated surveys and expect everyone to answer them perfectly]
- Dial data – there is a time delay, do we assume that if someone doesn’t move the dial it is the same affect as the last time the dial was moved – “padding” the data
- Once dial data gets to a certain level, it doesn’t change even though people might be really bored
- It’s difficult to get someone to understand something when his salary depends on not understanding it – think TV ratings
- The last five seconds of a tv spot is tough territory because people know they’re getting a sales pitch at that point. It needs a really clever hook.
- Facial coding vs self-report correlated 12% for cognitively filtered feelings
- Athletes show a lot of fear, they remember the fear of losing. Do guys self-report fear? Very rarely, I’m tough, I’m a road warrior.
- EEG measures cognitive load, attention, and arousal. Correlates highly with IQ.
- [so conclusion, every research method has flaws.]
- Recall the TV show “Lie to me” – scientist could tell when people were lying even if they didn’t speak
- Charles Darwin new that emotions were universal, spontaneous, abundant – blind people emote the same way as everyone else, it is hardwired. Social display rules vary – expressions may be shorter or longer. Otherwise same by gender, religion, culture, etc.
- Dan wrote “Emotionomics” – for the business investor
- Automated coding is still probably only 34% accurate. Automation over reports because of random noise
- Unless they’re faking it, full emoting of happiness doesn’t last longer than 4 seconds.
- Software can’t pick up micro-expressions – like when you’re bored with someone but you’re still smiling
- Tilting your head can change the automated scoring completely unrelated to the emotion
- When the mouth moves as you talk, reliability of software declines
- 70% is perceived as commercially viable since 90% sounds like a lie and 60% sounds bad. But the software just isn’t there yet.
- Linking verbatims to emotions provides solid insights – you might say something but not really mean it – reasons aren’t causes
- There is no ‘lying’ muscle in the face J
- Could not code Michael Jackson because of too much surgery [sounds like a way to get around facial coding!]
- Automation is prevalent now but it is buyer beware
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Branded Memory vs. Branded Experience by Samantha Moore, Ralph Blessing, Ameritest #ISC2015 #MRX
Live blogged from the 2015 MRA Insights & Strategies Conference, June 3-5, 2015 in San Diego. Any errors or bad jokes are my own.
- Experienced self vs remember self and research techniques for each
- System 1 thinking is fast thinking, operates automatically and unconsciously, no sense of voluntary control, instincts that we share with other animals
- System 2 thinking is slow thinking, controlled processes, requires focused, effortful attention, involves choice
- System 2 makes the final decisions but is heavily influenced by system 1
- System draws upon memories created by experiences when making suggestions
- When someone disturbs you during a movie, you might not like the movie. It was the experience that ruined the movie, not the movie.
- You don’t remember every meal during a holiday, you remember the holiday overall
- Research techniques can measure experience or memories, and consider system 1 and system 2
- Experience system 1 – eye tracking, facial response, brains waves, heart rate
- Experience system 2 – dial meter, channel switching
- Remembered system 1 – picture sort, copy sorts, flash test/t-scope [wow, does anyone still use a tachistoscope?]
- Remembered system 2 – brand linage, purchase intent, liking, rating, open ends
- In an ad, the most remembered part is the outcome. Hopefully that’s the brand queue. But the most remembered part is the one with the most emotion.
- Watch Eleanor Maguire from University College London on YouTube – what in the brain controls memory
- Important to use visuals to access memories
- Great brands deposit into all three long term memory banks – procedural memories (know how), semantic memories (knowledge), episodic memories (recollections)
- Procedural memory is when you just grab the box of tide because you always grab that one – all the time you spend changing your package might not be recognized by your loyals
- You know a brand even when the brand name is not shown
- Do – is seeing a lime in a beer bottle, think is seeing the brand name Corona, Feel is seeing two people on a beach (remember that commercial now?)
- Now consider Target – data theft, opening and closing in Canada, adding grocery to the store
- Target found the “shopping with your girl friends” was the best in store feeling, the key in moment feeling. Also tapped into the “do” component. Must recapture the fun of shopping with friends and using technology to enable it. This positioning increased store traffic by 23%
- Make communications easy to get
- Don’t rely on measuring immediate experience only, look for long-term branded memories,
- Memories are largely created by visuals and so are best retried visually
- Build all three types of long-term branded memories
- Insights that 90% of people agree with are just vanilla – find your unique target, consider letting go of some consumers to build up your brand.
- Assign pictures to the key strategic words that define your brand.
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Opening Keynote: Better and Faster by Jeremy Gutsche, CEO, TrendHunter.com #ISC2015 #MRX
Live blogged from the 2015 MRA Insights & Strategies Conference, June 3-5, 2015 in San Diego. Any errors or bad jokes are my own.
- [Start with a burst of rowdiness and free books for the noisy ones J ]
- We’re experience the highest rate of change and yet our brains are still 10 000 years old
- How do you reinvent faster and better
- [If you have seizures, do not watch this presentation!]
- Lifespan of a fortune 500 in the 50s was 75 years, now it’s 15
- Companies aren’t inherently structure to adapt
- You need to understand how chaos works
- [really getting tired of the yelling, really feels like theatre not learning]
- Almost all innovation happens by making connections between fields that people don’t realize
- We need to use patterns and technology to accelerate our work
- Profit comes from overlooked opportunities and this is what researchers are always looking for
- Opportunity is a riddle that you’re trying to solve
We are prewired to do whatever led to the last success – this is how humans have successfully grown wheat for thousands of years
- Block Buster was a big data company that personalized movies by region, failed due to a bad decision to not go digital
- Blackberry, Smith Corona, Blockbuster, Kodak and Microsoft chose to focus on their main product instead of seeking out innovation and that is why they failed
- Step 1: Awaken, 2: Hunt, 3: Capture
- Awaken – 3 traps of a farmer – when we become successful we become complacent, we become repetitive, we become protective. Difficult to convince us out of it.
- Daily task is self-improvement and the search for opportunity. Be perpetually looking. Be insatiable, curious, willing to destroy.
- You only need 10% of your brand to be innovation.
- How often do you experiment with ideas and strategies that might not work?
- How much time do you spend each week hunting opportunities to do things differently?
- Do you let your new ideas die? How many of them?
- How much simpler would your business be if you started from scratch?
- Hunt
- Acceleration, cyclicality, convergence, reduction, reductions, divergence
- Facebook is a huge success – but if you want a business version, you want twitter. If you don’t want your photos saved, that snapchat. If you like food pictures that’s Pinterest.
- Rethink what people want – we don’t want to say that we came 2000 in a marathon, we want to say that we FINISHED. And now there are marathons that don’t time you. You just do amazing tasks with your friends.
- To see patterns, you need to step back from your role in your industry. Don’t dismiss them. Act on them first.
- You increase your odds of winning by aligning with multiple trends
- What services can be combined with your offering?
- Be irresistible for a specific group of people
- What parts of your business do consumers actually care about? If you split your companies into 5 companies, which one would be more valuable?
- Don’t fight an unstoppable force, rechannel to your own advantage.
- Where could you over-deliver to delight consumers?
- What do people hate about your industry? How can you be more customized from the mainstream.
- Opposing the mainstream fuels success
- http://www.Trendhunter.com/secret/MRA