Live note taking at the #IIeX conference in atlanta. Any errors or bad jokes are my own.
How the classic fairy tale inspired the mobile ad strategy by Vuk Pavlovic, True Impact (Winner of Best New Speaker at #IIeX Europe)
- What are good guys? Give to others, honest, helpful, kind, polite. What are bad guys? Uninvited, rude, inconsiderate, force their will, vain, self-serving. Which of these reflects your brand?
- Brands need to humanize the customer and not treat them like eyeballs with a screen. The mobile environment is personal, their own social network, with their friends, in their bedroom. We need better relationships with brands that are this close to us.
- Ads need to be seen – attention, be relevant – receptivity, and be chosen.
- They tested ads during games. The ads were presented only when they person actively stopped the game to get help.
- Ads viewed during a more convenient time got more view time, more cognitive engagement
- People ignore pop=up ads but they do pay attention to ads that play at a convenient time. These ads also perform better after the game is finished.
- Ads viewed by choice get a 40 second view compared to 9 seconds for interrupting ads. Heatmaps show people are less likely to be looking for the X Close button
- Annoying ads have more engagement and motivation because they are seeking the X Close button
- Need to consider the person on the other end of the phone. Don’t force them to change the rotation of their phone. If their phone is vertical, then play the ad vertical.
How Home Depot is optimizing the shopper experience by Dan Braker (Brakethrough research) and Brendan Baby (Home Depot)
- Inverted pyramid – customer sits at the top of the pyramid, front line associates, field support, corporate support, CEO
- Use a blend of in store eye tracking, qualitative shop alongs, exit surveys, employee interviews and more to give nagivation behaviours, reasons for behaviours,, experience metrics, operational issues, concept screening
- Asked shoppers on arrival at the store if they would do their shopping trip with eye tracking glasses. Measure area of interest, time in the area of interest, count of shoppers touching or holding a product, time touching or holding a product.
- Path tracking watches the path they walked through the store, where do people spend much more or less time, is it due to interest or confusion
- Can measure pupil dilation for engagement measures, can also measure voice pitch analysis if they talk or ask questions
- Don’t overlook the employees in your research, they know how shoppers navigate, when shoppers need help
- Need to use emerging and raditional approaches to maximize learnings
- Changes to store elements should be thoroughly tested before roll out
Leveraging Artificial Intelligence to do Real-time fan research during NASCAR’s biggest race by Brooks Denton (NASCAR) and Andrew Konya (Remesh)
- Time with friends, cooking and eating, arguments about strategy, social media, ad consumption all together equals the experience
- Asked a set of questions throughout the race, like a live bulletin board, to collect qualitaive data. Choose a few responses that best reflect the full range of responses and match those with segments and demographics
- Build a distribution of opinion for each answer, create a consensus for each answer
- Sometimes they show the live responses to people answering the questions to increase engagement and other times they don’t show the other resposnses to maintain research rigour
- Viewers want split screen commercials, the data proves this and now they can bring that data to the broadcast partners
The automation of behavioural science by Aaron Reid (Sentient Decision Science)
- Some associates are hard wired (attractive person, babies) or learned (police cars, spiders)
- Can you differentiate fear of spiders and spiders using sweat in the hand, do you sweat more for one or the other
- Automation is a major trend in survey design, push button question types and dashboard reporting, full study design is becoming automated, tracking analysis is automated, regression analysis can be automated [I really hope that a person monitors all of these things because humans creating data are not robots]
- STICKY does eye tracking online not in the lab, it may not be great right now but we improve so quickly that it’s worth it to get in early
- We need to automate the science so that cientists can wok on theory, discussion, ideas not button pushing. This gives us time to work on the importat parts. Gives you time to increase empathy for people and brands.
Live note taking at #IIeX in amsterdam. Any errors or bad jokes are my own.
- Our personal lives have blurred, it’s an always on world, a do it yourself mentality prevails
- Expertise still drives world progress, but what is the role of expertise
- There are barriers associated with building expertise in the new digital era
- Even simple analytics are not straightforward
- Human cognitive capacity is inadequate compared to what is required in today’s digital world
- Advances are ushering in a new era of computing, no more punchcards, no more simply programming, now we’re in cognitive systems era
- To error is human but to really mess things up requires a computer, now computers can learn and build expertise
- What is so unique about human intelligence, ability to create a novel idea, ability to differentiate between causality and correlation, ability to combine intuitions with intelligence, ability to ask questions
- The essence of being human is asking questions, not answering questions
- Technology boosts the expertise of intelligence professionals – enhance, scale and accelerate expertise
- computer system confirmed 99% of medical diagnosis but added diagnosis precision to 30% of them
- Think of technology as an enabler, let it cut through the ego and bias of humans
Automation: Robot vs Researcher by Paul Albert (Zappistore) and Tony Costello (RB)
- WHat used to take 6 months is now being done in hours and TV marketing budgets have gone up
- Research budgets are continuing to decline for three years in a row
- In fifteen years, half of Fortune 500 companies have disappeared
- Data and digital requires more research to fuel profit, Netflix and uber have grown immensely but TASI and blockbuster are dying
- We need lower cost and more speed but we also need validated methodologies
- Do you delay until the method os fully validated or launch Asap
- Business that don’t adopt technology are destined to fail, bravery is need to adopt new approaches
- Now they can test many more ads for more brands and chose more effective ads
System 1 Driven Brand Insights by CHristian Ohm (Magda) and Karthik Posnanski (BrainJuicer)
- Mazda has rebounded because of the product line, youngest
- They moved from lower premium and generic to more premium and distinctive, premium experience not high price
- Have a strong product perception but a weak brand image perception, most brands don’t
- Fragmentation leads to a weak brand, in message or tone, sounds like a different brand in different markets
- Took a co-creation approach, more people than marketing need to understand the brand – call Center, dealer, sales person
- People knew the brands and could talk about them but there isn’t a lot of emotion but some people just love driving and are passionate about it, they want to deliver on this experience
- Spirit of Hiroshima – challenger attitude, never give up, we can do it
- Emotional connection is achieved when care and driver are in perfect harmony
- Created a brand book to share with everyone
- Tracking needs to be fast and actionable, cover emotions, simple and engaging, modular and flexible, adapt latest MR thinking, forward focused and predictive, strategic and tactical, more qualitative [excellent advice for research in general]
- Considered fame, feeling, and fluency for brand growth
The nature of consumer emotion by Aaron Reid
- Visceral factors theory – Lowenstein, falling asleep at the wheel – extreme deviation from a desired equilibrium point
- It was a bold man who first ate an oyster – well, maybe a crazy person or simply a very hungry person
- System 1 ans system 2 interact, it can’t be one or the other
- The proportion of emotion model combines emotion and reason in a single predictive algorithm, we are more accurate in predictions if we use both
- You can’t measure racism explicitly, emotion interacts with reason
- We see eye tracking and emotion tracking of the Budweiser immigration ad, can see attention in the right places and emotion being positive or negative at the right moments
- Adding implicit facial coding and implicit impact of ads greatly increases ability to predict virality of an ad
- Need to quantify the emotions from pride, gratitude, and anxiety
- They engaged with startups so they could increase the work with half the cost, half the time and better quality
- Have worked with 800 startups in recent years – the Shark Tank, piloted 200, recruited 30 for research and the new way of doing business
- Want to move away from asking to observing, people forget, they give estimates (not because they’re lying)
- Used google glass technology and advanced video analytics
- Move from asking to sensing, though people struggle to articulate emotions, FMRI, emotion coding, facial coding, they use facial coding on every ad
- Why should we ask at all? Asking reveals needs, combine what people search for on google with what people say on social media to replace traditional research
- Move from studying consumers to building relationships with people
- The technology enables them to string together a more powerful story
- Let’s move to “i have the answer what is your question’
- The pyramid of tomorrow: Input powered by tech, output enabled by tech, outcome delivered by people
- Make the leap from insights to ideas
- They pay their vendors bonuses if they do a job well [fabulous idea, will you do this?]
- Can you buy an ad for a segment?
- Geolocation, attitudinal profiles, likely voters
- Need to use machine learning and targeting to buy thousands of direct targeted ads
- Microsegmentation has its use but you still need to use classic segmentation for higher level needs
- Alternative lenses for segmentation – demographics are targetable in media, behaviors for usage styles of path to purchase, attitudes for believes about category or self, needs for key buying factors, occasion based for needs that vary by occasion
- Right now demographics and behavior segmentation are highly used
- Challenges with segmenting – surveys are too long and phones are too small, we don’t know what we don’t know, self report behavioural data is not very accurate or precise, targeting segments is hard to do in advertising
- Can profile based on quantative data but people are bad with numbers, qualitative research brings richness and texture, plus can add real world behaviours like actual online activities or models propensities
- Audiences are identified and you can message them differently by segment
- The new tools are making classic segmentation more actionable than ever before
Live blogged at the MRS conference in London. ANy errors or bad jokes are my own.
Chair: Elina Halonen. Panel: Colin Strong, Nick Baker, Cat Wiles, Nick Bonney
- Half of people in the room think their jobs won’t be replaced by computers [for me, yes, large parts of my job but definitely not all of it]
- Most professions think technology will disrupt someone else’s profession
- Most #MRX is quite custom, fairly hierachical structure, managed by individuals, this models exists everywhere
- More people will be figuring out how can we streamline our work, how we can streamline our systems, and our research
- Are the innovations so far sustaining innovations or are they genuinely innovate? Balance is more towards sustaining innovations, not disrupting innovations
- Rise of cognitive computing, Google computers win human games [but do they chit chat over coffee? Chuckle with you? Empathize? ]
- Rise of anticipatory computing [do computers kiss booboos on the knees of toddlers?]
- Rise of personality computing, musical tastes, sexual preferences, data trails reveal all. Do we really need to ask questions? [do computer know when an effect size of 0.69 is more meaningful than an effect size of 0.73?]
- Software can now analyze the data and tell the story [can it start with an interesting anecdote about my dad that pulls everyone in and puts them on my side?]
- What used to be a huge multi country study is now simply a Google search
- Qual is at risk also, needs and attitudes based on pictures etc scraped online
- The rise of machines will happen [because people like me demand it]
- There will always need to be a human touch whether through curation or creating
- Creativity is scrappy and raw and joins things that aren’t obvious
- Computers are always programmed and told by people, they lack the cultural framework that people learned
- What is the trade off? Researcher goes through data and pulls out their favorite bits [based on p-values or effect sizes? Yes computers do that, but humans see WHY]
- Maybe junior researchers should be worried about automating taking their jobs
- Will automating give us more time to think except what happens is that everything is just more sped up
- Is our thinking now programmed into how to make a PowerPoint slide out of the info? [this is what I saw all around London this weekend. Everyone has a fancy camera now and it’s turned into “here is a thing that could have a picture taken of it” rather than “oh my god this is amazing, I want to remember it]
- Life would be boring and predictable if it was all automated? Like a Disney movie? [yet more foreshadowing for my presentation!]
- We tend to define ourselves by the research method and tools we use, but those tools are becoming rapidly out of date even though we’re improving them, they are sustaining innovations
- Now you need a black belt in analytics
- Need more diverse teams, journalists, facilitators, designers, analytics all in the research department
- Cadbury’s gorilla would never come out of a computer [nor the old spice dude or the geico commercials!]
- [Brands are all about empathy, can a computer be sufficiently empathetic S when it truly matters?]
Wake Up or Die. Research Automation – The Future of Market Research Corinne Sandler, Fresh Intelligence #NetGain2015 #MRX
Live blogging from the Net Gain 2015 conference in Toronto, Canada. Any errors or bad jokes are my own.
Wake Up or Die. Research Automation – The Future of Market Research
Corinne Sandler, CEO of Fresh Intelligence
- No war in the world has ever been won without intelligence
- we are needed more and more as competition among brands intensifies
- Where is market research on the Montclare SaaS250 list? Salesforce is the closest one.
- We need to think outside the fishbowl
- We play a consultative role, we see a brief that goes from analyst to director and we consult all along the way. What if the brains were integrated into technology.
- We need to move from consulting on research to dispensing research.
- Progress depends on the unreasonable man – George Bernard Shaw
- Intelligence needs to be accessible to the world
- You have only two choices today – you can use a third party or you can do it yourself
- What about combining brains with an automated component, fully automated turn-key platform with consultants
- Buyers of research have specific needs, and automation suits those needs well. Quality is a cost of entry, must believe that is what consumer is truly saying, need to rely on that right data.
- Buyers need to prove value of every dollar they spend. Priorities don’t always allow them to share the wealth among several brands.
- These methods allow you to do all the work without reveal proprietary information
- For instance, what if you told the provider 5 brand names, and the system automatically plugged them into a pre-programmed survey with pre-programmed charts.
- How do you create an app that adds value for toilet paper, because EVERYONE has an app. “Charmin Sit or Squat App” – tells you where the closest washroom is and how clean it is. [My mom would LOVE THIS!]
- 90% of our decisions are based on intuition