An approach to finding customer-value and devising marketing strategies by using data-mining techniques

Title

An approach to finding customer-value and devising marketing strategies by using data-mining techniques

Creator

Dsouza N.; Paulose J.

Description

The digital marketing space is an outcome of the advent of digital age and the booming network technology. The earlier methods of marketing have almost been eclipsed with this digital marketing, which could include any material, information, videos on the internet and social media, etc. The marked distinction between a digital and traditional marketing is that the former uses digital devices in the traditional space. People today consume innumerable products daily and getting to know the customer's interests, their transaction's history, identifying a loyal customer and estimating their lifetime value are all at the very heart of digital marketing. It is here, in this context, that data mining techniques play a key role. This unique blending of data mining techniques with digital marketing will help merchants increase their sales and revenue exponentially. This research paper explores the possibility of finding the frequent item-set generated by a customer while making purchases, tracking their loyalty based on the number of purchases and their frequency and thereafter devising an appropriate marketing strategy for that particular product type. It is the analysis of the product based on the previous marketing experiences of the consumer. This system will boost a merchant's businesses by identifying their loyal customers (customer segmentation), best sold products (product recommendation) and reveal the different marketing strategies that can be adopted by them to reach out to their potential customers and thus increase their sales (Strategy selection/combination). IAEME Publication.

Source

International Journal of Mechanical Engineering and Technology, Vol-9, No. 3, pp. 539-550.

Date

2018-01-01

Publisher

IAEME Publication

Subject

Apriori algorithm; C4.5 algorithm; Data mining; Digital marketing; Lifecycle grids; Marketing strategies; RFM

Coverage

Dsouza N., Department of Computer Science, Christ University, Bengaluru, India; Paulose J., Department of Computer Science, Christ University, Bengaluru, India

Rights

Restricted Access

Relation

ISSN: 9766340

Format

Online

Language

English

Type

Article

Identifier

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85044767835&partnerID=40&md5=1a8c3f82e38b69b27ea1b0f1aea0b2fb