Multiple Approaches in Retail Analytics to Augment Revenues

Title

Multiple Approaches in Retail Analytics to Augment Revenues

Creator

Banik H.; Iyer L.S.

Description

Knowledge is power. The retail sector has been revolutionized around the clock by the plentiful product knowledge available to customers. Today, customers can use the knowledge available online at any time to study, compare and purchase products from anywhere. Retail companies can stay ahead of shopper trends by using retail information analytics to discover and analyze online and in-store shopper patterns. A product recommender will suggest products from a wide selection that would otherwise be very difficult to locate for the customer. The algorithm would recommend various products, increase the sales of items that would otherwise be difficult to sell. Market basket analysis is a common use scenario for the search for frequent patterns, which involves analyzing the transactional data of a retail store to decide which items are bought together. To do so data from online resource has been taken, which is analyzed and several conclusions were made. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Source

Lecture Notes in Networks and Systems, Vol-290, pp. 276-284.

Date

2021-01-01

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

Association mining; ECLAT; Product recommender; Skip-gram; word2vec

Coverage

Banik H., Department of School of Business and Management, CHRIST (Deemed to be University), Bangalore, India; Iyer L.S., Department of School of Business and Management, CHRIST (Deemed to be University), Bangalore, India

Rights

Restricted Access

Relation

ISSN: 23673370; ISBN: 978-981164485-6

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-981-16-4486-3_30

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115100335&doi=10.1007%2f978-981-16-4486-3_30&partnerID=40&md5=73912b26f7cf6784862408f169e640f7