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Transcript of Real-Time measurementsamra.co.za/wp-content/uploads/2013/05/Noeth_Real-time...Knows the past and...
Real-Time
measurement -
Functional
methodology, fact or fallacy
Andries
Noeth
Section 7
Section 6
Section 2
Section 3
Section 4
Section 5
What is real-time?
Section 1
Section 7
Section 6
Section 1
Section 3
Section 4
Section 5
Traditional measurement
vs.
Real-time
Section 2
Section 7
Section 6
Section 1
Section 2
Section 4
Section 5
4 Important
differences
Section 3
Section 7
Section 6
Section 1
Section 2
Section 3
Section 5
Customers’ psychological
jourr journey
Section 4
Section 7
Section 6
Section 1
Section 2
Section 3
Section 4
Remembering self
vs.
Experiencing self
Section 5
Section 7
Section 5
Section 1
Section 2
Section 3
Section 4 Integrating
Section 6 Systems
2
Section 6
Section 5
Section 1
Section 2
Section 3
Section 4
What does the
future hold
?
Section 7
Course Title |This is the slide title Objectives
Get a better understanding of what real-time measurement is How does real-time measures differ from traditional research methods Look at the differences between the two measures The psychological experience of the customer and how it relates to the different measures How they can be integrated to provide a more robust measurement
Section 7
Section 6
Section 2
Section 3
Section 4
Section 5
What is real-time?
Section 1
Course Title |This is the slide title What is real-time
Definition: “A system in which input data is processed within milliseconds so that it is available virtually immediately”
Rreal-time typically come from the engineering, telecommunications and computer industry where certain computerised processes or machines give instantaneous feedback while the event occurs. The graphics in a action game are rendered in real-time by the computer's video card. This means the graphics are updated so quickly, there is no noticeable delay experienced by the user.
In the past it could take months to collect a couple of hundred face to face interviews using traditional research techniques.
With new technologies you literally have millions of megabytes of data with the push of a button in real-time.
Course Title |This is the slide title Real-time vs. Near real-time
Market research
In the market research industry this real-time relay of data, i.e. instantaneous processing of the event during the event itself, is still in its infancy. Technology like eye tracking, biometrics and portable MRI scanners are only recently being used as reliable and effective ways of collecting consumer data. Most “real-time” data is collected using SMS, online of telephonic surveys
Interaction with call center agent
Event Measure
event Capturing
data Reporting
SMS, online or
telephonic evaluation
Transfer data to system server
Results displayed
on a dashboard
Time delay = “Near real-time” No time delay = Real-time
Section 7
Section 6
Section 1
Section 3
Section 4
Section 5
Traditional measurement
vs.
Real-time
Section 2
Course Title |This is the slide title Real time vs. Traditional
Lets look at the major differences between these two measures:
Near real-time research Traditional research
Time delay Measurement happens in the event
or very close to the event Measurement happens at a later stage
after the event
Questionnaire length
Usually short; 1-5 questions Usually longer; 10-60 minutes
Data volumes Large amounts of data
(1000-5000 interviews per wave) Limited data points
(usually less than 1000 per project)
Reporting Immediate reporting Time delay to reporting
Metric Transactional measure Strategic measure
Data depth Feedback Insight
Frequency Measures very frequently, daily and weekly data collection
Measures less frequently, maybe once or twice a year
Measures Measures the very short term, the momentary experience
Measures the long term or the memory of the experience
Deals with Experiencing self Remembering self
Section 7
Section 6
Section 1
Section 2
Section 4
Section 5
4 Important
differences
Section 3
Course Title |This is the slide title Operational vs. Strategic 1
Adapted from: Gartner Report in J Kirkby, J. Wecksell, W. Janowski, T. Berg – March 2003 - The Value of Customer Experience Management
Vision & goals
Customer relationship
management strategy
Operational customer
experience management
Balanced
Scorecard
Customer value
proposition metrics
Number of Metrics / Volume of Data
Effectiveness
reporting
Action
reporting
Vision & goals
Customer relationship
management strategy
Operational customer
experience management
Vision & goals
Customer relationship
management strategy
Contact with the
customer
Operational customer
experience management
Vision & goals
Customer relationship
management strategy
METRICS • Brand Image • Market Position
• Customer acquisition • Value (share of wallet & loyalty) • Retention • Strength of relationship
• Brand experience dimensions • Key attributes of brand image • Key attributes of product & service • Key service levels • Satisfaction • Complaints
• Individual service levels • Resolution of problems
Strategic
reporting
Volumes and type of data 2
Tien, J. M., (2006). Data mining requirements for customization. International Journal of Information Technology and Decision Making.
Basic transactions
captured during
operations Processed data;
derivations,
groupings, patterns,
etc.
Processed
information together
with experiences,
belief, values, culture Processed knowledge
together with insights,
theories, models,
context
Data Information Knowledge Wisdom
Real Time
Traditional
Feedback vs. Insight 3
PEOPLE
Real Time Traditional
Time delay between measures
IN 24hrs 2 weeks 1 month 3 months
4
Emotion
Memory
More
Less
Time of measurement
Effect
Perception vs. Reality
Section 7
Section 6
Section 1
Section 2
Section 3
Section 5
Customers’ psychological
jourr journey
Section 4
Customers psychological journey
Association with the
experience
Value in use &
Subconscious value
This is the functional
outcome of dealing
with the organisation
and the
subconsciously
perceived value
Pre experience
Expectations of an experience
Interacting with the experience
Memory of the experience
Learning
• The psychological baggage consumers bring
with them to an experience
• These affect the customers expectations they
have
• What consumers seek from an experience.
• What they expect influences how they judge
the experience.
• How consumers interact with an experience
psychologically and physically
• What companies actually do has an impact
here
• Experience is remembered and socialized
• Integrated into current beliefs, values,
context
• Ultimately what is remembered is what is real
• Socialisation and rationalisation turns
memory into learning.
• This learning is what stays with us and is
used to influence future decisions
Association affect the
pre-experience
Section 7
Section 6
Section 1
Section 2
Section 3
Section 4
Remembering self
vs.
Experiencing self
Section 5
Measuring what?
Pre experience
Expectations of an experience
Interacting with the experience
Memory of the experience
Learning
Experiencing
self
Remembering
self
Measured in
real-time
Measured
traditionally
Experiencing self vs. Remembering self
Lives in the moment
Lives in the moment
Experiences the now
Lives in the moment
Knows and cares about the present
Lives in the moment
Reacts emotionally
Lives in the moment
Experience 600 million time slices
Lives in the moment
ENJOYS EVERY MOMENT
Lives in the moment
Live from memory
Rationalizes and socializes experience
Knows the past and cares about the future
Reacts sensibly
Forgets most time slices, remembers
significant ones
TRACKS AND MAINTAINS THE
STORY OF YOUR LIFE
Experiencing
self
Remembering
self
Experiencing self vs.
Remembering self
Experiencing self
Remembering self
Feeling YOU Thinking YOU
Rational, moral,
logical
Irrational passions
and appetites
Section 7
Section 5
Section 1
Section 2
Section 3
Section 4 Integrating
Section 6 Systems
2
Difference in process
Traditional CEM Real-time
Strategic vision
Detailed measure
Cultural changes
Behaviour changes
Operational changes
Improved customer experience
Strategic changes
Daily / weekly feedback
Identify immediate issues
Behavioral changes
Improved customer
experience
Cultural changes
Operational changes
Integrating measures
Strategic vision
Strategic CEM
measure
Identify strategic changes
Implement strategic changes
Change behaviour
Improved experience
Real time measure
Identify problems
Operational changes
How to create memorable
experiences
Feeling
YOU
Thinking
YOU
Experiencing
self
Remembering
self
Emotions Moments
Feelings Sensations Memories
Pinnacles
Dri
ven
lon
g te
rm v
alu
e
Dri
ven
sh
ort
te
rm s
pe
nd
Creating memorable experiences (A)
Advocacy
cluster
Recommendation
cluster
Attention cluster
Destroying cluster
Happy, Pleased
Trusting, Valued,
Focused, Safe, Cared for
Interesting, Energetic,
Exploratory, Indulgent,
Stimulated
Irritated, Hurried, Neglected, Unhappy,
Unsatisfied, Stressed, Disappointed,
Frustrated
Shaw (2010) Customer experience; future trend and insights.
Creating memorable experiences (B)
Positive
Feelings
Negative
Feelings
PEAK PEAK
PEAK PEAK
Time Neutral
What have we seen
IN 24hrs 2 weeks 1 month 3 months
Time of measurement
Experiencing
self
Remembering
self
Section 6
Section 5
Section 1
Section 2
Section 3
Section 4
What does the
future hold
?
Section 7
Course Title |This is the slide title GRIT report 2013
Clients prefer short term insights to deep understanding of consumer markets
I believe that traditional quantitative research is too slow and expensive to meet the needs of
clients
Clients see traditional primary research as an old fashioned luxury
GRIT report 2013
Clients prefer short term insights to deep understanding of consumer markets
I believe that traditional quantitative research is too slow and expensive to meet the needs of
clients
Clients see traditional primary research as an old fashioned luxury
Huge possibilities
big data
biometrics
eye tracking
biofeedback
real-time
mobile
internet
social media analytics
blogs
discussion forums
CATI
face to face
CAPI
ethnography
web-ethnography
personal interviews
focus groups
communities
text analytics
webcams visualization analytics
apps based research
mobile ethnography
virtual environments social networks
gamification crowd sourcing
facial analytics
neuro-marketing GPS tracking
MRI scanning WAP-based research
Market researchers should form part
of the knowledge community and not
the data community.
Data Rich, Information Poor
DRIP
Create knowledge
"Every day, three times per second, we produce the equivalent of the
amount of data that the Library of Congress has in its entire print
collection. Most of it is irrelevant noise. So unless you have good
techniques for filtering and processing the information, you're going to get
into trouble”
“Traditional research is being redefined
before our very eyes. The game has
changed, and the pace of change is only
accelerating” – GRIT 2013
Data explosion
Transformation
Don’t lose sight of who
we are and what our
purpose is
Purpose
Thank You !