Tourism marketing strategy is the top priority for all tourist attractions and tourism-related enterprises, and how innovative tourism marketing strategy in the digital era has become the key to improving the competitiveness of attractions and enterprises. This paper uses data mining technology as a basis to study feasible solutions for innovative tourism marketing strategies for scenic spots and enterprises under data-driven. A formalized label representation is used to construct an extended user portrait conceptual model by clustering the tourists' contextual information using K-means. Tourism marketing targets users based on similarity calculation results, and association rules are used to mine the alignment association rules between tourists' contextual features and attractions. Combined with the big data framework system Hadoop technology, we have built a tourism marketing platform that is used to analyze the tourism preferences of different tourists and formulate effective tourism marketing strategies. This paper, based on the data-driven tourism marketing strategy, can significantly improve scenic spot traffic. After marketing the Biluo Tower scenic spot in October, the average value of the traffic is up to 20,384 people, compared with the pre-marketing increase of 56.71%. At the same time, the marketing strategy significantly improves the satisfaction of tourists, and after the implementation of the marketing strategy, the satisfaction of tourists in the scenic area generally improves to more than 0.975. © 2024 Lili Cui, published by Sciendo.