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Big Data and Brand Creation

With the rapid development of information technology and the Internet, big data is constantly changing the living conditions and development patterns of various industries, and it also profoundly affects the management philosophy, organizational form, and customer service of enterprises. How to summarize the laws from big data and further promote the precision of brand cultivation is a common issue faced by tobacco industrial and commercial enterprises.


The main application directions of big data technology in brand cultivation work are: use big data analysis to achieve precise brand positioning and reasonably meet consumer needs; based on data analysis to extract valuable information from retail customers and consumer feedback to improve products and services, etc.


Specifically, in the era of big data, efforts can be made in the following three aspects to achieve precise brand cultivation:


Use big data to achieve precise market positioning Quickly understanding the real needs of consumers in the target market and potential consumers, accurately segmenting the market, and clarifying market positioning are important ways to promote brand cultivation. First of all, on the premise of ensuring the meticulous, real-time, and comprehensive data collection, use big data algorithms to build a consumer segmentation model, divide multiple dimensions to obtain more effective groups, and ensure that these groups have relative concentrated demand characteristics. At the same time, build a rapid response mechanism for big data algorithms and a fusion mechanism for market research and big data to improve the accuracy of market segmentation. Through the development of big data portraits of different types of markets and consumers, it provides a reference for the precise cultivation of brands. Secondly, tobacco industry companies can combine big data to analyze relevant market needs, and the fit between the market and enterprise development, and develop better products based on consumer needs. In this stage, it is necessary not only to make good use of the company's own data resources, but also to be good at using data and analysis materials from non-industry institutions such as statistical departments, big data centers, think tanks, and consulting companies, to do a good job in multi-dimensional association analysis and data mining.


Use big data to achieve precise brand cultivation strategies. Tobacco industrial and commercial enterprises can formulate strategies such as precise brand cultivation and customer grading services in terms of products and consumers, channels and convenience. In terms of products and consumers, big data marketing tools should be based on a full-brand, full-type platform, and analyze macro factors such as economic policies and market, brand, and consumer data, and then develop new products for industrial enterprises and conduct customer guidance for commercial enterprise marketers for reference. In terms of channels and convenience, we can explore supply chain integration and omni-channel marketing strategies. For example, you can explore the use of electronic tags, barcodes, radio frequency identification and other technologies to realize product tracking and monitoring, grasp brand flow information and logistics node data, and identify the channel ownership of goods in time; relying on terminal information collection systems such as cloud POS systems, Store monitoring systems of retail terminals, etc., use statistical analysis to present store heat maps in real time, providing a reliable basis for retail customers to carry out accurate brand cultivation.


Strengthen safeguards for the use of big data. On the one hand, we should strengthen the training of big data technology talents, establish a professional data analysis team, break through the information and technical barriers between different departments such as marketing and finance, and effectively integrate and use data; on the other hand, we should standardize data collection And use, strictly abide by relevant laws and regulations, formulate corporate and retail customer business information and consumer privacy protection systems, and try to formulate information security risk prevention plans to regulate the scope and use of data acquisition by all parties and links to prevent information security risks .

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