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@article{197859,
        author = {Pragati Rajendra Meshram and Prof. Abhijeet Gajbhiye and Prof. Nitin Prakash},
        title = {Sales Forecasting and Consumer Behaviour Analysis Using Social Media Analytics: A Case Study of Haldiram’s Nagpur},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {7977-7982},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=197859},
        abstract = {The spread of social media sites has radically redefined the consumer interaction and corporate intelligence in the modern online economy. This paper will critically analyse how social media analytics can be of use in improving the quality of sales forecasting and understanding consumer behaviour of a particular location with reference to Haldiram Nagpur. The study explores how the online reviews, measures of engagement, sentiment, and content interaction (user-generated data) can be analysed systematically to provide actionable information to predict demand and make strategic decisions.
The paper will follow a descriptive and analytical research design incorporating primary information gathered by using structured questionnaires and secondary information obtained via scholarly literature and online sources of analytics. There are sophisticated analytical methods used to determine the connection between indicators of the digital engagement and consumer buying intentions such as the trend analysis and qualitative sentiment interpretation methods. The results indicate that there is a high level of correlation between the activity on social media and the consumption patterns thus suggesting that the level of engagement has a great impact on the brand perception, customer loyalty, and buying behaviour.
Moreover, the research paper indicates the predictive nature of social media analytics when it comes to detecting seasonal changes in demand, new consumer trends, and product performance trends. It also highlights how strategic real-time data can be used to improve the real-time marketing and inventory planning. The study concludes that, in addition to enhancing the accuracy of sales forecasting models, the incorporation of social media analytics in sales forecasting models can ensure organizations are in a proactive and customer-focused mode in an environment that is very competitive in the sale of the FMCG. The research has useful implication to managers that indicate that they need to consider using data-driven marketing strategies and sophisticated analysis tools to maintain long-term growth and competitive advantage.},
        keywords = {Social Media Analytics, Sentiment Analysis, Sales Forecasting, Consumer Behaviour Analysis, FMCG Marketing, Predictive Modeling, Customer Engagement, Brand Loyalty, Demand Forecasting, Haldiram Nagpur.},
        month = {April},
        }