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Machine Learning Approach for Targeting and Recommending a Product for Project Management

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  • Hasmat Malik

    (BEARS, NUS Campus, University Town, Singapore 138602, Singapore
    Faculty of Business and Management, Universiti Sultan Zainal Abidin (UniSZA), Gong Badak, Kuala Terengganu 21300, Terengganu, Malaysia)

  • Asyraf Afthanorhan

    (Faculty of Business and Management, Universiti Sultan Zainal Abidin (UniSZA), Gong Badak, Kuala Terengganu 21300, Terengganu, Malaysia)

  • Noor Aina Amirah

    (Faculty of Business and Management, Universiti Sultan Zainal Abidin (UniSZA), Gong Badak, Kuala Terengganu 21300, Terengganu, Malaysia)

  • Nuzhat Fatema

    (Faculty of Business and Management, Universiti Sultan Zainal Abidin (UniSZA), Gong Badak, Kuala Terengganu 21300, Terengganu, Malaysia
    Intelligent Prognostic Private Limited, Delhi 110093, India)

Abstract

Conventionally, a market research and strategy for a product depends on the interviews and an explicit cluster/society to identify the customer’s needs. Customer-created information (CCI), such as call-center data, online reviews, and social media posts, provides an opportunity to recognize the customer’s needs more efficiently. Moreover, developed conventional approaches are not compatible with large CCI datasets because most of the CCI-contents are repetitive and uninformative. In this paper, a machine learning approach for identifying the customer needs from the CCI dataset is proposed and its performance is evaluated for targeting and recommending a new product for project management. After the identification of the needs of the customer, information can be used to develop a market strategy, new product launching, brand positioning and much more long/short term planning.

Suggested Citation

  • Hasmat Malik & Asyraf Afthanorhan & Noor Aina Amirah & Nuzhat Fatema, 2021. "Machine Learning Approach for Targeting and Recommending a Product for Project Management," Mathematics, MDPI, vol. 9(16), pages 1-29, August.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:16:p:1958-:d:615470
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    References listed on IDEAS

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