Emotion Mining in Brief - Master 06.2016

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Transcript of Emotion Mining in Brief - Master 06.2016

Emotion Mining™What Really Moves Us?

C H I C A G O • D E T R O I T • F R A N K F U R T • S H A N G H A I • B E I J I N G

Agenda Understanding Emotions

The Tool

The Results

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Understanding Emotions

Turning Starbucks Around With EmotionsHoward Schultz re-appointed as Starbucks CEO.

◦ Commits to laser focus on customer experiences‒ New espresso machines are too tall, automated

‒ Coffee aroma lost by bagging and burnt sandwiches

‒ Merchandizing is sterile and boring

Customers’ emotional experiences drove the turnaround strategy.

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Great CEOs Empathize With Customers

Steve Wynn on the resort business: All of the razzmatazz and jazz we hear about facilities and everything else doesn't amount to a hill of beans.

It's customer experience that determines the longevity and endurance of these enterprises.

Steve Jobs on how technology fits into Apple products: The hardest thing is: how does that fit in to a cohesive, larger vision, that’s going to allow you to sell $8B, $10B of product a year?

And, one of the things I’ve always found is that you’ve got to start with the customer experience and work backwards to technology.

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Great Products Reflect Empathy

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Emotions Drive Our ExperiencesThe brain has two systems of thinking.

◦ System 1: Fast, automatic, frequent, emotional, stereotypic, subconscious

◦ System 2: Slow, effortful, infrequent, logical, calculating, conscious

Most customer experience is in System 1.◦ Experts say 95% of cognitive activity is subconscious

◦ Walking into a Wynn casino or Starbucks

◦ Paying the premium for an Apple product

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The Big Prize: Understanding EmotionsCan a market research firm supplement C-suite intuition?

◦ Can customer emotions be quantified? ‒ Can the emotional response to a Blackberry be compared to an iPhone?‒ Could Shultz’s insights be derived using quantitative methods?

◦ Could such quantitative insights be relied upon?

◦ If so, what would be the value of such a solution? ‒ Invest in what customers love‒ Eliminate what they don’t

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The Tool

Emotions Are Expressed With Words

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We acquire language at an early age.◦ Capable of verbalizing feelings by the age of 4

Emotion Mining™ discovers the emotions hidden in words.

◦ The Emotion Mining dictionary maps 4K+ emotion words to 32 channels

Cloud-based Survey

Unique Emotion Mining™ web-based tool drills down into how respondents “feel”

Three Sources of Words

Existing Data

Text from previous research, company reports and/or news can be used

Web Scraping

Content from online sources is scraped and analyzed

Active Passive

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Start with a Simple Topic“How does ______ make you feel?”

◦ Tons of options for how a <topic> makes you feel: brand, product feature, market trend, competitor, problem, etc.

Stimulus can provide context before the respondent starts the exercise.

Follow-up (and screening) questions get closer to the right insights – enable rich segmentation.

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Respondents complete an online survey to uncover emotions.

Unique Survey Process

Respondents provide emotions (words) related to stated topic/questions – “How do you feel?”

Respondents elaborate on the meaning of emotional responses – attempts to rationalize emotions.

Each emotional response is measured for current ambient “temperament” or mood (apart from the topic).

Free Association Exercise

Ambient Mood & Subconscious Intensity

Emotion Clarity

Conscious Intensity

Each emotional response is measured for baseline intensity relevant to topic.

Conscious Emotion Mapping

Conscious and Subconscious Emotion Mining

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Algorithms Map Words to 32 ChannelsEach channel represents a type of emotion – based on a combination of 4 channel properties.

◦ Enjoyment◦ Interest◦ Commitment◦ Passion

Separates conscious from subconscious emotions.

LoyaltyKindnessAcceptance

Interest

JoyPride

ConfidenceEnergy

DreadDismay

FearHesitation

SorrowEmbarrassment

AcceptanceInterest

AmazementAdmiration

AttractionTrust

SerenityWorth

ContentmentSecurity

ContemptAnger

RejectionDisinterest

DiscomfortDisreputeDiscontent

Insecurity

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Property #1: EnjoymentPleasant Unpleasant

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Offerings should be pleasant. Problems typically are unpleasant.◦ Per Michael Skok’s Value Proposition

Framework, a good offering must have…‒ High gain => Unpleasant problem‒ Low pain* => Pleasant offering

*Refers to pain of adoption, which could be a topic in itself Pleasant in green. Unpleasant in red.

Property #1: Enjoyment

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Property #2: InterestInward Outward

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Inward in red. Outward in green.

Property #2: Interest

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Inward emotions relate the topic to internal things.

Outward emotions relate the topic to external things.

◦ Inward offerings are valuable, ubiquitous and internalized by the customer

◦ Outward offerings should be luxurious, exclusive and in need of customer loyalty‒ How does <product feature> make you feel?‒ How does <trend/competitor> make you feel?

Property #3: CommitmentActive Passive

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Property #3: CommitmentActive emotions indicate a need to control.

Passive emotions indicate a consent or coercion to give up control.

◦ Passive offerings should be habit forming and easy to use

◦ Active offerings should be feature-rich and customizable

◦ Active problems are blatant needs, and passive problems could be latent ‒ Relates to Michael Skok’s BLAC analysis

Mild Intense

Active

Passive

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Property #4: PassionMild

(Mundane < Common)Intense

(Extreme < Sublime)

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Property #4: PassionPassion ranks the emotional intensity within a channel group.

◦ There are 4 levels of intensity for each channel group

◦ Intensity is good within “ideal” channel groups for specific topics

◦ Similarly, a mild level of passion is a good thing in “non-ideal” channel groups‒ e.g., the Insecurity channel ranks fourth as the

mildest level of passion, which is far better (less intense) than Discomfort

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Results

◦ Analysts chart the ideal channel groups that will benefit the client and work to get inside the mind of the respondent

◦ This exercise helps reduce hindsight bias and forces analysts to seek the reasons why results mismatch expectations

Find the IdealFind the ideal channel groups before beginning analysis.

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Bar chart showing conscious and subconscious responses by channel

Dials showing ◦ Enjoyment◦ Interest◦ Commitment◦ Passion

Word cloud based upon verbatims entered by respondents

Database linking verbatims to specific emotional channels

Core Reports

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Emotion Analysis

Filter by segments

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Subconscious intensity in gold (above 0)

Conscious intensity in grey (below 0)

Engagement Metrics◦ Average CI % across four

channel properties‒ Enjoyment = Pleasant/Unpleasant‒ Interest = Inward/Outward‒ Commitment = Active/Passive‒ Passion = Mild/Intense

◦ Filter by segments◦ Filter by conscious or

subconscious

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Word Cloud◦ Word cloud of words in verbatims◦ Filter by segments◦ Filter by conscious or

subconscious◦ Filter by emotional channel

properties

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Verbatim Data◦ Searchable◦ Filter by

segments◦ Sorted by

intensity◦ Filter by C/SC &

channel properties

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Compare Apples-to-Apples

Can compare a topic across time with similar respondents. ◦ Check the pulse of the topic, such as “driving a Volkswagen”◦ Understand the impact of events, such as the emissions scandal

Can also compare two topics within the same category.◦ Apple iPhone 6+ vs. Nexus 6P◦ American auto industry vs. American retail industry◦ Gas powered vs. electric

Compare results across time and within the same category.

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• Non-linguistic measures• Additional dimensions• Crowd-sourced dictionary• Synonyms and variants• Transcript analysis

• Result validity• Probabilistic methods• Correlation detection• Dictionary reliability• Study reliability

• Pulse tracking• Emotion repository• Respondent pools• Visualization techniques• Best practices on topics

Three Pillars to Trust the Results

Emotional measurement

Law of Large Numbers

Wisdom of Crowds

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Jim DurkinPartner/PresidentDirect: 312-606-9672jim.durkin@martecgroup.com

Chuck BeanPartner/CMODirect: 248-327-8005chuck.bean@martecgroup.comQuestions?