NEXT
BEST ACTION MARKETING IN THE DEVELOPMENT OF EMONEY PT.XYZ INDONESIA USING
DESCRIPTIVE ANALYTICS
Eristiar Syah
Permana Tarigan S.T 1
12 Master of Management, Telkom University
Indonesia
ABSTRACT
The development of information
technology has caused companies in the Information Technology Industry sector
to innovate and develop products in accordance with customer needs. PT. XYZ is
a company that innovates due to government regulations and customer needs.
After a change in the methodology of the company PT. XYZ has decreased
purchases in the application so it requires the right marketing methods for
customers. Next Best Action (NBA) Marketing is the best marketing action centered
on customers by considering customer actions (customer action) during
interaction (customer interaction) so that it can recommend the best for
certain customers (specific customers). In this company will be using Next Best
Action Marketing in developing PT. XYZ Indonesia uses Descriptive Analystics.
Keywords: Next Best Action, Marketing, Descriptive Analytics
I.
INTRODUCTION
1.1
Background
PT. XYZ Indonesia is a company engaged in the
Information Technology Industry. The company was founded with the goal of
facilitating and assisting people in conducting transactions meeting their
daily needs. PT. XYZ
shade a software application that is used for routine bill payments, electronic
credit purchases, and travel tickets. With the existence of an emoney license, PT. XYZ's
business model changes are currently divided into 2 models, namely the sharing
margin model for emoney applications and the multi-level marketing system
application model. Emoney application, it uses sharing method of sharing
margins and bus topology
It
can be seen from the bus topology above that the company has begun to determine
the business model to be able to add new users and is expected to increase
sales.
1.2 Purpose and Objectives
This
research was conducted with the goals to answer the research questions that
have been raised previously, namely:
1. Knowing which
variables are the most important (Important variables) for segmenting customer
applications PT. XYZ.
2. Knowing the
optimal number of customer segmentation PT XYZ applications.
3. Knowing the
characteristics of the targeted segment (highly prospect).
4. Knowing what is
the next best action marketing that is recommended in order to increase sales
in the application PT.XYZ.
According to (Armstrong & Kotler, 2015) marketing
is a process of a company in creating value for customers and building stronger
relationships with customers to get value back from customers. In the midst of
business competition today, companies must be able to understand consumer needs
so that they can provide more value to consumers. The more consumers or customers
obtained and the higher the transaction, the more it will contribute to the
company's revenue. The purpose of marketing is to attract new customers by
providing more value or benefits to customers and retain existing customers
while maintaining customer satisfaction.
The concept of marketing starts with the fulfillment
of human needs which then grows into human desires. According to (AMA, 2013),
Marketing is an activity, a series of institutions, and the process of
creating, communicating, delivering, and exchanging offers of value to
customers, clients, partners and the general public. Meanwhile, according to
(Kotler P., 2003), marketing is a human activity that is directed to meet the
needs and desires through the exchange process. This theory is corroborated by
opinions (Kotler & Keller, Marketing Management 15e, 2016), which states
that “marketing is a societal process by which individuals and groups obtain
what they need and want through creating, offering, and freely exchanging
products and services of value with others”.
Next Best Action (NBA) Marketing is the best
marketing action centered on customers by considering customer actions
(customer action) during interaction (customer interaction) so that it can
recommend the best for certain customers (specific customers). This strategic
method relies on the scope of marketing and building collaboration between
marketing and sales.
III.
Research
Methods
3.1 Framework for Mind
In this study, the
author refers to the concept of segmentation which goals to group customers
with the same characteristics. Consumer segmentation can be done based on
geographic, demographic, psychographic, and behavioral factors (Armstrong &
Kotler, 2015).
For this study
customer segmentation will use the factors of Recency, Amount and Transactional
Frequency. Thus the framework of thought in research.
Gambar
1
Kerangka Pikiran
After
finding the most important variable (Important Variable), segmentation optimization
is performed so that the five most influential variables on purchases (Amount
and Frequency) are found so that the characteristics of high prospect users are
known and can be done Next best action marketing.
3.2
Research
stages
In this study, the
authors study at the stage of the data mining process based on CRISP-DM
(Cross-Industry Standard Process for Data Mining) in which the sequence is not
rigid and the results of one stage will be input for the next stage. According
to (Chapman, et al., 2000) that the process in data mining consists of 6 stages
as follows:
Sumber : Chapman,
P., Clinton, J., Kerber, R., Khabaza, T., Reinartz, T., Shearer, C., &
Wirth, R.
From the picture
above it can be seen that the outer ring of CRISP-DM (The Cross-Industry
Standard Process for Data Mining) is not broken & continuously iterated to
perfect the results to be achieved in order to answer business challenges by
taking lessons from previous iterations..
(2000). CRISP-DM
1.0 Step-by-step data mining guide. SPSS Inc. Dipetik 2018
Brooks,
C., & Thompson, C. (2017). Preditive Modelling in Teaching & Learning.
Handbook of learning Analytics, 61-62.
Collica, R. (2018). Customer Segmentation and Clustering Using SAS
Enterprise Miner. USA: SAS Institute
Inc
Collin
Priest, Delivering Next Best Action with artificial Inteligence. Datarobot, 10
April 2018. https://blog.datarobot.com/delivering-next-best-action-with-artificial-intelligence
Grottrup
Soren, W. T. (2016). Data Mining with SPSS Theory, Exercises and Solutions.
Berlin, Germany: Springer International Publishing Switzerland.
doi:10.1007/978-3-319-28709-6
REFERENCE
Agrawal,
D. (2014). Analytics based decision making. Journal of Indian Business
Research, 6(4), 332-340. doi:10.1108/JIBR-09-2014-0062
Angela
Stringfellow, What is
Next Best Action Marketing? Benefits, Challenges, Best Practices, and More.
NgData, 6 Novembe
Indrawati,
P. (2015). Metode Penelitian Manajemen dan Bisnis Konvergensi Teknologi
Komunikasi dan Informasi. (D. Sumayyah, Penyunt.) Bandung, Jawa Barat, Indonesia:
PT Refika Aditama.
Keith
J. Tuckwell, M. J. (2016). Think Marketing. Canada: Pearson Canada Inc.
Kerin,
R., & Peterson, R. (2015). Pemasaran Strategis: Kasus dan Komentar.
Jakarta: Indeks.
Kotler,
P., & Keller, K. (2018). Marketing Management.
Jakarta: Indeks.
Kotler,
P., & Lane Keller, K. (2016). Marketing Management (Global Edition ed.).
USA: Pearson Education Limited. doi:ISBN 978-0-13-385646-0
Kotu,
V., & Desphande, B. P. (2015). Predictive Analytics and Data Mining.
Waltham, USA: Elsevier Inc.
Larose,
D., & Larose, C. (2015). Data Mining and Predictive Analytics (second ed.).
New Jersey, Canada: John Wiley & Sons.
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