IEEE Access,
Год журнала:
2024,
Номер
12, С. 111468 - 111480
Опубликована: Янв. 1, 2024
Customer
segmentation
is
an
important
aspect
in
aiding
businesses
to
comprehensively
understand
their
customer
base
and
tailor
marketing
strategies
for
optimal
effectiveness.
Traditional
approaches
have
predominantly
concentrated
on
demographic
factors
observable
characteristics.
However,
these
limitations
that
prevent
them
from
capturing
the
intricate
user
journeys
of
each
identified
segment.
Hence,
this
paper
proposes
approach
using
clustering
algorithms,
specifically
K-Means,
BIRCH,
Gaussian
Mixture
Model
dataset
derived
Wi-Fi
advertising
system,
with
a
focus
tracking
progression
through
stages
AIDA
(Attention,
Interest,
Desire,
Action)
Model.
This
not
only
presents
AIDA-based
metric
designed
data,
it
also
strives
measure
different
journey
analysis.
Through
combination
main
objective
gain
nuanced
understanding
distinct
characterizing
within
further
incorporates
dynamic-characteristics
range
table
delineate
weak
strongly
engaged
behavioral
traits,
thereby
demonstrating
efficacy
combining
algorithms
unraveling
insights
into
behavior
across
diverse
segmented
group.
Based
detailed
levels
segment,
suggests
actionable
enhance
by
identifying
which
emphasize,
ultimately
leading
improved
campaign
effectiveness
satisfaction.
Electronics,
Год журнала:
2024,
Номер
13(2), С. 288 - 288
Опубликована: Янв. 8, 2024
Ensuring
the
safety
of
autonomous
vehicles
is
becoming
increasingly
important
with
ongoing
technological
advancements.
In
this
paper,
we
suggest
a
machine
learning-based
approach
for
detecting
and
responding
to
various
abnormal
behaviors
within
V2X
system,
system
that
mirrors
real-world
road
conditions.
Our
including
RSU,
designed
identify
exhibiting
driving.
Abnormal
driving
can
arise
from
causes,
such
as
communication
delays,
sensor
errors,
navigation
malfunctions,
environmental
challenges,
cybersecurity
threats.
We
simulated
exploring
three
primary
scenarios
driving:
overlapping
vehicles,
counterflow
The
applicability
learning
algorithms
these
anomalies
was
evaluated.
Minisom
algorithm,
in
particular,
demonstrated
high
accuracy,
recall,
precision
identifying
vehicle
overlaps,
situations.
Notably,
changes
vehicle’s
direction
its
characteristics
proved
be
significant
indicators
Basic
Safety
Messages
(BSM).
propose
adding
new
element
called
linePosition
BSM
Part
2,
enhancing
our
ability
promptly
detect
address
abnormalities.
This
addition
underpins
technical
capabilities
RSU
systems
equipped
edge
computing,
enabling
real-time
analysis
data
appropriate
responsive
measures.
emphasize
effectiveness
behavior
offering
ways
enhance
facilitate
smoother
traffic
flow.
International Journal of Management and Administration,
Год журнала:
2024,
Номер
8(15), С. 1 - 19
Опубликована: Фев. 17, 2024
This
research
offers
a
rich
narrative
explaining
this
multifaceted
relationship
by
exploring
the
transformative
impact
of
Artificial
Intelligence
(AI)
on
marketing
adopting
qualitative
descriptive
approach
for
in-depth
exploration.
The
findings
reveal
profound
implications
customer
engagement,
market
strategy,
and
ethical
considerations.
integration
AI
into
enables
personalization
increases
brand
loyalty.
Predictive
analytics
enable
businesses
to
develop
proactive
strategies
aligned
with
future
dynamics.
Despite
its
advantages,
considerations
surrounding
data
privacy
consumer
consent
require
be
used
responsibly
transparently.
Integrated
augmented
reality,
virtual
predictive
journeys,
Internet
Things
that
transform
dynamics
must
harnessed
balance
concerns.
A
comprehensive
resource
academic
researchers
industry
professionals,
work
provides
clear
roadmap
organizations
effectively
leverage
in
their
operations
an
environment
increasing
reliance
digital
platforms
expanding
availability.
Heliyon,
Год журнала:
2024,
Номер
10(16), С. e36392 - e36392
Опубликована: Авг. 1, 2024
The
recent
advances
in
machine
learning
and
deep
algorithms,
along
with
the
advent
of
generative
AI,
have
led
AI
to
become
"new
normal"
organizations.
This
trend
has
extended
CRM,
resulting
development
AI-enabled
CRM
systems,
or
AI-CRM.
Despite
growing
adoption
as
part
competitive
strategies,
many
firms
report
minimal
no
positive
effect
on
performance.
study
addresses
research
questions:
"What
are
critical
features
AI-CRM
systems?"
"How
do
these
impact
organizational
advantage?"
To
explore
this,
we
aim
identify
key
characteristics
assess
their
In
Study
1,
utilize
BERTopic
topic
modeling
extract
from
user
reviews.
2
employs
PLS-SEM
examine
how
influence
advantage.
1
reveals
four
main
(general,
marketing,
sales,
service/support),
each
comprising
distinct
features.
shows
that
differentially
capability,
significantly
affecting
performance
findings
offer
valuable
insights
for
both
theory
practice
regarding
effective
use
Machine
learning
(ML)
has
transformed
the
financial
industry
by
enabling
advanced
applications
such
as
credit
scoring,
fraud
detection,
and
market
forecasting.
At
core
of
this
transformation
is
deep
(DL),
a
subset
ML
that
robust
in
processing
analyzing
complex
large
datasets.
This
paper
provides
comprehensive
overview
key
models,
including
Convolutional
Neural
Networks
(CNNs),
Long
Short-Term
Memory
networks
(LSTMs),
Deep
Belief
(DBNs),
Transformers,
Generative
Adversarial
(GANs),
Reinforcement
Learning
(Deep
RL).
Beyond
summarizing
their
mathematical
foundations
processes,
study
offers
new
insights
into
how
these
models
are
applied
real-world
contexts,
highlighting
specific
advantages
limitations
tasks
algorithmic
trading,
risk
management,
portfolio
optimization.
It
also
examines
recent
advances
emerging
trends
alongside
critical
challenges
data
quality,
model
interpretability,
computational
complexity.
These
can
guide
future
research
directions
toward
developing
more
efficient,
robust,
explainable
address
evolving
needs
sector.
PLoS ONE,
Год журнала:
2025,
Номер
20(2), С. e0318519 - e0318519
Опубликована: Фев. 7, 2025
Effective
and
well-structured
customer
segmentation
enables
organizations
to
accurately
identify
comprehend
the
distinct
characteristics
needs
of
various
groups,
thereby
facilitating
development
more
targeted
marketing
strategies.
Contemporary
artificial
intelligence
technologies
have
emerged
as
predominant
tools
for
segmentation,
owing
their
robust
capabilities
in
analyzing
complex
datasets
extracting
profound
insights.
This
paper
proposes
a
framework
within
realm
digital
marketing,
which
integrates
reinforcement
learning-based
differential
evolution
algorithm
with
K
-means
clustering
using
dimensionality
reduction
techniques
address
challenges
process.
Initially,
correlation
matrix
is
used
redundant
noise
multicollinear
features
feature
Principal
Component
Analysis
applied
denoising
enhance
ability
model
potential
features.
Subsequently,
parameter
adaptive
adjustment
method
based
on
Q
-learning
proposed,
significantly
augments
performance
-means.
Ultimately,
effectiveness
proposed
validated
Kaggle
dataset,
elbow
employed
ascertain
optimal
number
clusters.
Based
cluster
category
centers,
typical
different
types
are
analyzed.
Furthermore,
four
widely
recognized
machine
learning
methods
classify
results,
achieving
over
95%
classification
accuracy
test
set.
The
experimental
results
demonstrate
that
exhibits
high
degree
characteristic
identification
not
only
enhances
efficiency
satisfaction
but
also
fosters
corporate
profit
growth
through
strategic
formulation
initiatives.
International Journal for Research in Applied Science and Engineering Technology,
Год журнала:
2024,
Номер
12(1), С. 1586 - 1591
Опубликована: Янв. 31, 2024
Abstract:
Effective
marketing
involves
targeting
specific
customer
groups
with
personalized
products,
services,
and
campaigns,
making
segmentation
a
crucial
strategy
in
modern
business.
This
paper
introduces
pioneering
method
that
utilizes
machine
learning
techniques
to
accurately
efficiently
segment
customers
based
on
their
behaviors,
demographics,
transaction
history.
By
combining
transfer
learning,
Rfm
(recency,
frequency,
monetary)
modeling,
clustering
algorithms
like
K-means,
our
approach
generates
meaningful
segments,
offering
valuable
insights
for
improved
experiences.
We
showcase
the
positive
impact
of
real-world
dataset,
displaying
noteworthy
enhancements
effectiveness
satisfaction.
Innovative Marketing,
Год журнала:
2024,
Номер
20(2), С. 1 - 14
Опубликована: Апрель 1, 2024
This
bibliometric
analysis
aims
to
delineate
the
progression
of
research
in
domain
digital
marketing
by
examining
513
English-language
articles
published
Scopus
during
period
2003–2024.
An
examination
scholarly
productivity
indicates
an
upward
trend,
as
evidenced
increase
publications
from
one
2003
115
2022
and
citations
79
1131
2021,
determined
keyword,
citation,
authorship
analyses.
A
review
citation
patterns
reveals
that
with
significant
impact
are
primarily
found
prestigious
academic
journals,
such
Industrial
Marketing
Management
International
Journal
Research
Marketing.
Prominent
contributors
hail
Jordan,
Finland,
Spain,
United
Arab
Emirates,
Saudi
Arabia;
among
other
regions
–
States,
Middle
East,
Europe,
Asia.
Keyword
revealed
emphasis
on
emerging
technologies
artificial
intelligence
traditional
techniques
(e.g.,
social
media,
content
marketing,
internet
marketing).
Co-occurrence
theme
highlighted
strategy,
audiences,
transformation
business
acceleration
adoption
a
result
COVID-19.
Further
areas
investigation
encompass
optimizing
utilization
emergent
media
platforms,
implementing
virtual
augmented
reality
enhance
customer
experience,
capitalizing
potential
machine
learning
augment
efficacy
marketing.
By
utilizing
data-driven
insights,
this
study
offers
guidance
for
curricular
enhancements,
agendas,
practice.
AcknowledgmentThe
author
thanks
everyone
who
helped
make
possible,
but
especially
those
at
Ho
Chi
Minh
University
Banking,
Vietnam.
International Journal of Business Law and Education,
Год журнала:
2024,
Номер
5(1), С. 1270 - 1283
Опубликована: Апрель 17, 2024
This
research
aims
to
find
out
in
depth
about
digital
marketing
strategies,
namely
segmentation,
targeting,
positioning
and
differentiation
using
methods
favorite
announcing
thing
(Preferred
Reporting
Items)
andmeta
examinations
(meta
analysis)
or
commonly
called
the
PRISMA
method.
4
(four)
journal
websites,
Google
Scholar,
Sciencedirect,
Emerald,
Taylor
&
Francis.
The
results
of
this
show
that
segmentation
a
brand
will
have
sustainable
competitive
advantage.
A
product
advantage
if
is
considered
important
unique
by
customers.
Targeting
process
evaluating
each
segment's
attractiveness
then
selecting
one
more
characteristics
serve.
discusses
issue
how
select,
select
reach
market.