Shopping Marketplace Analysis Based On Customer Insights Using Social Media Analytics

It provides dynamic insights into the changing factors of societal trends and technological advancement. (oleh Santi Anisa Cahyani )

In the era of industry 4.0, business companies that want to develop must understand the customer perspective. Social media platforms have changed digital marketing, by facilitating a space for customers to share information with each other and supported by media, this makes social media a promising source of data for consumers.

Data analysis is useful for making information clearer and easier to access. The methods used for research on distribution channel strategies on consumer behavior are surveys and quantitative analysis. This research focuses on supplier interactions and various distribution strategies through expert evaluation and analytical synthesis.

Sentiment analysis (opinion mining) is a computational technique that involves analyzing textual data to determine sentiment as positive, negative or neutral. In the context of product development, sentiment analysis plays an important role in understanding consumer feedback and opinions about a product or service. This analysis includes several stages, including preprocessing, data, extraction, features, model training, and sentiment labeling.

Ethnic stores focus on providing products that are authentic to the cultural community, whereas chain stores have a wider range of standard goods with an emphasis on convenience and cost effectiveness and focus on mass market goods. Customers who visit local stores or chain stores to buy their products eventually become social media users and share their shopping experiences. Marketing departments can leverage this data to gain deeper insights into customer sentiment and preferences. This analysis allows the company to understand customer satisfaction levels with various stores, including local ethnic stores and large chain stores.

With the application of digital twin technology, the marketing department creates a virtual representation of the real market, where the behavior of social media users is simulated in real-time. This approach provides a comprehensive understanding of customer trends that can be used as a reference for potential market targets. To broaden the base longitudinal analysis can be conducted to track the evolution of customer experiences and preferences over a long period of time. It provides dynamic insights into the changing factors of societal trends and technological advancement. (oleh Santi Anisa Cahyani )