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 !