Brand Communities for Fast Moving Consumer Goods

Meister, Sandra

doi:10.1007/978-3-8349-4055-1

Cited by 8 publications

(3 citation statements)

References 81 publications

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“…Today's consumers are more demanding and need to be responded with a more customized treatment [24]. Companies spend significant effort to attract new customers.…”

Section: Substantiality Of Customer Churnmentioning

confidence: 99%

Customer Churn Prediction in FMCG Sector Using Machine Learning Applications

Günesen

Şen

Yıldırım

et al. 2021

IFIP Advances in Information and Communication Technology

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Non-contractual setting and many brands and alternative products make customer retention relatively more difficult in the FMCG market. Besides, there is no absolute customer loyalty, as most buyers split their purchases among several almost equivalent brands. Thereby, this study aims to probe the contribution of various machine learning algorithms to predict churn behaviour of the most valuable part of the existing customers of some FMCG brands (detergent, fabric conditioner, shampoo and carbonated soft drink) based on a real dataset obtained in the Turkish market over the two successive years (2018 and 2019). In this context, exploratory data analysis and feature engineering are carried out mostly to build many predictive models to reach consistent and viable results. Further, RFM analysis and clustering techniques with K-Means clustering are employed to generate meaningful insights for business operations and marketing campaigns. Lastly, revenue contributions of improved customer retention can be achieved, utilising actionable intelligence created by the churn prediction.

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“…Today's consumers are more demanding and need to be responded with a more customized treatment [24]. Companies spend significant effort to attract new customers.…”

Section: Substantiality Of Customer Churnmentioning

confidence: 99%

Customer Churn Prediction in FMCG Sector Using Machine Learning Applications

Günesen

Şen

Yıldırım

et al. 2021

IFIP Advances in Information and Communication Technology

View full text Add to dashboard Cite

show abstract

“…The offered analytic focuses strictly on brand initiated and moderated communities in Facebook (Vitak, 2017), for the sake of consistency in terms of technological platform, mode of interaction, and type of usergenerated comments (b) must have a long-standing presence in Facebook of at least 5 years to ensure a sufficiently large user base, allowing for richness of brand associations against the background of multifarious topics (c) each brand initiated thread must be sufficiently sizeable (i.e., must have garnered at least N = 30 comments), to be amenable to quantitative analysis. Let it be recalled that, as highlighted by Miles and Huberman (1994), the relationship between analytical/ interpretive depth and the sample size is inversely proportionate.…”

Section: Sampling Framementioning

confidence: 99%

Negative brand meaning co‐creation in social media brand communities: A laddering approach using NVivo

Rossolatos

2019

Psychology and Marketing

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Social media brand communities (SMBCs) have been heralded for their co‐creative, participatory potential whereby consumers actively contribute to the proliferation of meaningful brand avenues in a virtuously circular relationship with brands. Elevated loyalty and enhanced brand equity have been posited repeatedly as likely outcomes of a positively engaged community of brand aficionados. However, evidence to the contrary as negative brand co‐creation or brand co‐destruction has been progressively piling up in the extant literature. This paper contributes to the meaning co‐creation in SMBCs literature primarily on two grounds: first, by offering a methodological framework for adapting the laddering research technique in a mixed methods vein to SMBCs data in a thread‐specific context, by leveraging the analytical capabilities of NVivo CAQDAS software; second, by addressing bottlenecks in the applicability of the proposed methodology in light of negative brand co‐creation.

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“…Materials use and consumption patterns in cities are critical to cutting carbon emissions, creating healthy cities, reducing ecological harms from extraction, and living within the resource constraints of the planet [21]. FMCG is the fourth largest sector in the Indian economy, and packaged food sales alone are expected to reach USD 470 billion by 2025, up from USD 263 billion in 2020-2021 [23], a rise that increases alongside the generation of plastic waste.…”

Section: Introductionmentioning

confidence: 99%

Emerging Transformations in Material Use and Waste Practices in the Global South: Plastic-Free and Zero Waste in India

Conlon

2023

Urban Science

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This study uses a qualitative approach to address limitations and blockages to current plastics reduction via semi-structured interviews with zero waste business practitioners in India. Although they are nascent, India is home to a budding zero waste community that is grappling with how to reduce plastics—via trial and error—and these stakeholders hold insights from lived experience on how plastic reduction can actualize in the Indian subcontinent. This research involved interviewing zero waste businesses and consultants and makers of plastic alternatives in India to understand their experiences with plastic reduction strategies. The key stakeholder interviews reveal key insights for moving forward with plastic reduction initiatives, including challenges faced at government, business, and social levels; considerations regarding plastic waste generation; motivations for starting zero waste businesses and organizations; how it will be possible to operationalize plastic bans in India; appropriate actions for plastic waste reduction; elements that would help India shift into a more circular, regenerative economy; and locally appropriate alternatives to plastics. The discussion further delves into caveats with various alternatives to plastic materials, economic considerations, and characteristics of the zero waste network, and provides next steps for action at the government, business, and civil levels for reducing plastic waste generation in India and minimizing plastic pollution.

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Brand Communities for Fast Moving Consumer Goods

Cited by 8 publications

References 81 publications

Customer Churn Prediction in FMCG Sector Using Machine Learning Applications

Customer Churn Prediction in FMCG Sector Using Machine Learning Applications

Negative brand meaning co‐creation in social media brand communities: A laddering approach using NVivo

Emerging Transformations in Material Use and Waste Practices in the Global South: Plastic-Free and Zero Waste in India

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