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Pre- and post-launch emotions in new product development: Insights from twitter analytics of three products

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  • Rathore, Ashish Kumar
  • Ilavarasan, P. Vigneswara

Abstract

The paper showcases the possible application of social media analytics in new product development (NPD). It compares users’ emotions before and after the launch of three new products in the market—a pizza, a car and a smart phone—for possible inputs for NPD. The user-generated content offers an alternative to conventional survey data and is cross-cultural in nature, relatively inexpensive and provides real-time information about user behaviour. A total of 302,632 tweets that mentioned the three new products before and after the launch were collected and analysed. Sentiment analysis of the tweets from two time periods was conducted and compared. The users’ responses to the pre- and post-launch of three products vary. The dissatisfaction with the new products represented by negative emotions aligns with the market performance. In the pre-launch period, trust and joy were more common for pizza, joy was more common for the car, and trust was more common for the phone. In the post-launch period, anger and disgust were more common for pizza, joy and trust were more common for the car, and joy was more common for only one aspect of the phone. Further analysis showed that for the car and the phone, firms need to focus on user attitudes towards product attributes, whereas for pizza, firms should concentrate on physiological changes, i.e., changes in product attributes, service and promotional sides. By using the proposed alternative approach, businesses can obtain real-time feedback about the expectations and experiences of the new products. The NPD process can be adjusted accordingly.

Suggested Citation

  • Rathore, Ashish Kumar & Ilavarasan, P. Vigneswara, 2020. "Pre- and post-launch emotions in new product development: Insights from twitter analytics of three products," International Journal of Information Management, Elsevier, vol. 50(C), pages 111-127.
    • Handle: RePEc:eee:ininma:v:50:y:2020:i:c:p:111-127
    DOI: 10.1016/j.ijinfomgt.2019.05.015
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    Cited by:

    1. Xing, Yunfei & Wang, Xiwei & Qiu, Chengcheng & Li, Yueqi & He, Wu, 2022. "Research on opinion polarization by big data analytics capabilities in online social networks," Technology in Society, Elsevier, vol. 68(C).
    2. Qilong Wan & Xiaoqing Zhao & Haibing Liu & Hasan Dinçer & Serhat Yüksel, 2022. "Assessing the New Product Development Process for the Industrial Decarbonization of Sustainable Economies," SAGE Open, , vol. 12(1), pages 21582440211, January.
    3. Geissinger, Andrea & Laurell, Christofer & Öberg, Christina & Sandström, Christian, 2023. "Social media analytics for innovation management research: A systematic literature review and future research agenda," Technovation, Elsevier, vol. 123(C).

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