Consumer Behavior – Understanding It with Big Social Data

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Consumer Behavior – Understanding It with Big Social Data

Social media data can help brands analyze evolving consumer behavior – to serve them better!

With the spike in digitization and the rapid surge of social media usage, customer behaviors are evolving faster than ever before. Today, there is a need to understand the target audience deeply for every industry. More marketers need to go beyond the traditional sales data and shopping behavior and explore the data-informed strategy.

Both of them are vital for brands; however, that need to be merged with big social data – simply, the social media data. It can offer businesses with unique insights into the evolving consumer behavior – enabling them to serve customers better and stand ahead of their peers. Many successful brands have been strategizing big social data to provide people with better experience and value exchange.

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The social media posts are more than valuable for marketers and influencers who are making efforts to break into the high time of the sponsored content. The vast available data can enable marketers to innovate their marketing mix and future-proof their brands. However, for many brands, the social data analysis revolves around the traditional social listening metrics – to measure campaign performance and consumer feedback.

Basically, in times of crisis, brands will need a holistic view of their consumers’ habits – including consuming patterns, product usage, attitude, etc. It is no secret that every industry functions differently and has different areas of focus. With thorough research and analyzing the hefty of consumer conversations, marketers can capture the mentioned terms that are relevant to their domain. This could include branding, products/services, qualities, benefits, and concerns and would be more accessible to explore and act upon.

Undoubtedly, these are the highly structured data – with a blend of automated technology and human intelligence, brands can grasp it effectively. They can create a context in the pool of social data after classifying as per the market verticals, organized by offerings, and then cataloging with qualities and appearance. Furthermore, it will help businesses in developing product trends amid growing consumer concerns. Data context is a vital key for deriving actual insights, and the process of benchmarking data should be a primary function for all enterprises.

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Clearly, social media marketing is not just limited to post content to capture consumers’ attention to generate lead. It is an unrivaled source of an authentic data source. Thus, if it is executed well, contextualized, and analyzed at scale – it can bring in unparalleled insight for brands.