This document discusses how companies can create "perfect customers" through advanced analytics and experiential engagement. It suggests that companies will increasingly use customer data and behavioral insights to actively modify customer behaviors and mold them into preferred personas. This level of influence aims to ensure customers will buy what they have been influenced to buy. The document also notes that the most successful analytics companies in the future will help businesses carry out continuous behavior modifications to create perfect customers and maximize lifetime value.

1. THE FUTURE OF CUSTOMER ENGAGEMENT :
CREATING THE PERFECT CUSTOMER
THROUGH ADVANCED ANALYTICS AND
EXPERIENTIAL IMPRESSION
Edmas Neo

2. 4,000

6. A I D AAttention Interest Desire Action

8. MULTIPLE CHANNELS FOR MARKETING
Physical Location
Social Media
Radio
TV
Email
Direct Mail
Paid Search
Catalog
Website

9. A I D AAttention Interest Desire Action

11. Alibaba sets new Singles Day record
with more than $30.8 billion in sales
in 24 hours

12. 360 DEGREE CUSTOMER PROFILE
Who are you?
Where are you?
What have you purchased?
What content do you prefer?
Who do you know?
What can you afford?
What is your value to the
business?
How / why have you contacted
us?

13. A I D AAnalyse Introduce
(Recommend)
Desire Action
AJUSTED AIDA Framework by Edmas Neo, 2019

14. 360 DEGREE CUSTOMER PROFILE
Travelling
twice a
year
Cell phone
Luxury car
Loyalty Point
Fashion Jewellery
Store visit
Followers on
Twitter
Buys insurance
Friends on
Facebook
Bought a TV
and iPad
Had searched for
insurance but
did not buy
Returned
a Sofa
Socioeconomic
Status
Shopping
Behavior
Social
Activity
Shopping
History
View of
Customers

15. Organizations that leverage customer behavior data
to generate behavioural insights outperform peers
by 85 percent in sales growth and more than 25
percent in gross margin.
https://www.pointillist.com/blog/customer-behavior-data/

16. 75% of Netflix viewer activity is driven by
recommendation
Netflix’s recommendation system saves the company an estimated
$1 Billion per year through reduced churn
35% of Amazon’s sales are generated through
their recommendation engine
built their entire respective empires around a nucleus of customer behavior data and analytics
https://www.pointillist.com/blog/customer-behavior-data/

17. Why should business care about ?
Predict Customer value
Content optimization
https://www.business2community.com/marketing/state-marketing-2018-reach-todays-omnichannel-consumers-02025354
Customer Analysis

19. Level of Action Based Analytics & Influence
Multi Source
Raw Data,
Standard
Reports,
OLAP,
Visualisation,
Relationships
Analysis
Live Data
Streams,
Real-time
Analytics,
Targeted
Campaign,
Personalisation
Real-time Decision
Tracking and Predictive
Intervention,
Direct and Subliminal
Influences
LevelofBusinessValue/PositiveDisruption
ANALYSIS
& SEGMENTATION
MONITORING
& INFLUENCING
PREDICTIVE MODELLING,
CUSTOMER PROFILE
& PERSONAS MODELLING
CUSTOMER
PROFILE & BEHAVIOR
MODICATION, &
DEMAND CREATION
REPORTING
Profiles & Personas
Modelling,
Predictive Modelling,
Behaviour
Modification
Simulations,
Influence Algorithm
Development
Framework by Edmas Neo / 4 July 2014
The Next Stage of Customer Analytics
Knowing What Customer has
Bought?
Understanding Why Customer
Buy?
Knowing What Customer is
Buying Now & Influence
Customer’s Decision
Predicting What Each Customer
Will Buy
Creating the Perfect Customer &
Ensuring the Customer Will Buy
What They have been Moulded
to Buy

20. Consumer Buying Behaviour
1. Internal or Psychological factors
2. Social factors
3. Cultural factors
4. Economic factors
5. Personal factors.
N Ramya and Dr. SA Mohamed Ali
https://www.researchgate.net/publication/316429866_Factors_affecting_consumer_buying_behavior

21. Community & Experience

23. “Give me a child until he is 7
and I will show you the man.”

24. Today’s businesses make use of analytics to make
sense of their data, and understand their customers
to provide personalised services, up-sell, cross-sell
and optimise their business operations to meet the
customers’ needs.
Tomorrow ‘s winning businesses make use of
analytics to mould their customers into the
preferred customer personas, carry out individual
and precise early age influencing, and continuously
modify their behaviour to create the demand for
what the businesses want them to buy.
The Future of Customer Analytics
Concept by Edmas Neo / 4 July 2014

25. Level of Action Based Analytics & Influence
Multi Source
Raw Data,
Standard
Reports,
OLAP,
Visualisation,
Relationships
Analysis
Live Data
Streams,
Real-time
Analytics,
Targeted
Campaign,
Personalisation
Real-time Decision
Tracking and Predictive
Intervention,
Direct and Subliminal
Influences
LevelofBusinessValue/PositiveDisruption
ANALYSIS
& SEGMENTATION
MONITORING
& INFLUENCING
PREDICTIVE MODELLING,
CUSTOMER PROFILE
& PERSONAS MODELLING
CUSTOMER
PROFILE & BEHAVIOR
MODICATION, &
DEMAND CREATION
REPORTING
Profiles & Personas
Modelling,
Predictive Modelling,
Behaviour
Modification
Simulations,
Influence Algorithm
Development
Framework by Edmas Neo / 4 July 2014
The Next Stage of Customer Analytics
Knowing What Customer has
Bought?
Understanding Why Customer
Buy?
Knowing What Customer is
Buying Now & Influence
Customer’s Decision
Predicting What Each Customer
Will Buy
Creating the Perfect Customer &
Ensuring the Customer Will Buy
What They have been Moulded
to Buy
In future, we do not analyse data
only to meet customer’s needs
but to actively create the perfect
customer through Behaviour
Modifications

26. Types of Companies/ Competencies
Value
ANALYSIS
& SEGMENTATION
MONITORING
& INFLUENCING
PREDICTIVE MODELLING,
CUSTOMER PROFILE
& PERSONAS MODELLING
CUSTOMER
PROFILE & BEHAVIOR
MODICATION, &
DEMAND CREATION
REPORTING
Framework by Edmas Neo / 4 July 2014
Value of Customer Analytics Companies
The most successful analytics
companies will be those that can
help businesses carry out
continuous behaviour
modifications, to create the
Perfect Customers.
Analytics Companies
Data Scientists
Behaviour Modification Companies
AIML & Behaviour Learning
Companies Technologies
Neuro Technologists/ psychologist
Reactive
Value
Creation
Active
Value
Creation

27. What We See & What We Hear
Will Influence
What we Buy, What We Use &
What We Eat, What We Like
In Turn, This Will Influence
Our Networks & Experience &
How Our Life Will Turn Out to Be
Most Importantly, It will Determine
What Type of Customers We Will Become
&
Our Customer Life Time Value to Businesses
Concept by Edmas Neo / 4 July 2014

28. Possible Results of Early Age Influence and Personas / Behaviour Modifications
What We See, What We Hear, What We Eat and What We Use Make Us Who We Are
Concept by Edmas Neo / 4 July 2014
Photos based on fair use and royalty free photos for non-commercial use
http://www.publicdomainpictures.net/view-image.php?image=65440&picture=man-and-cigarette
https://pixabay.com/en/boy-portrait-people-happy-person-992080/
https://static.pexels.com/photos/25733/pexels-photo.jpg
There is no right or wrong customer through influencing and modifications, but only whose customer will this boy grow up to be.
By early influencing and behaviour modifications, multi-brands organisations will have a high chance of creating their perfect customers.

29. Loftus, E., & Pickrell, J. (1995). The Formation of False Memories. Psychiatric Annals, 25(12),
720-725. doi: 10.3928/0048-5713-19951201-07

30. Still shopping in stores even if they’re
comfortable making purchases online
U.S. Census data
Prefer to spend money on a desirable
experience or event over a desirable
object.
Harris Poll Eventbrite, 2014
90%
78%

31. Dutch supermarket Albert Heijn has created the
Help Yourself herb garden

34.  Can we influence the influencers?
 Can we hack people’s preferences and mould them into
our customers and/or supporters?
Experiment

35.  Personal Preference is Hackable
 Community and Experiential Engagement can be a
tool to Hack Personal Preferences
Hypothesis

38. 400% increased in conversion and followers

39. I D E A LIntelligence Direct
Influence
Emotional
Engagement
Association Long Term
Attachment
Marketing Framework by Edmas Neo, 2019

41. This slide deck, unique frameworks and presentation concept developed by Edmas Neo belongs to Edmas Neo.
This deck is not for further distributions without the Author’s permission.
The Author does not claim rights to the Models, Frameworks that belong to other authors, and the rights remains with the other authors.
Photos and graphics used are from public domain for education purposes only. The rights belongs to the respective owners.