Specifically, the following challenges still exist in the crude data insights:
01 On-line and off-line customer experience touchpoints are numerous, fragmented information is scattered in various departments of the enterprise, and it is not possible to utilize the integrated data to quickly understand the consumer demand and customer experience, and to empower the management decision-making.
02 Traditional research has a small sample size, a long implementation cycle, and the statistical results often lag behind consumer trends, making it difficult to transform them into actionable insights to empower product innovation and marketing growth.
03 Market intelligence data sources are thin, making it difficult to cope with the rapidly evolving competitive landscape, and there is a lack of unified tools for benchmarking competitors, making it impossible to know one's enemy and know oneself.
A refined data operation based on real-time big data and machine learning algorithms is an effective solution for true "consumer-centric" insights. Consumer experience insights can help companies quickly collect and understand consumer demand, product reputation, competitor dynamics, new product trends, and consumer hotspots, and then drive professionals in marketing, R&D, customer experience, retail operations, and other functions to capitalize on business opportunities and respond to the fast-changing consumer market with agility.