Fast Lane Keyword Study: 6,993 long-tail queries with keyword metrics, SERP signals and Fast Lane Scores (dataset and code)

Data and code for: Pereira, P. (2026). The Fast Lane Keyword Methodology: A Structural Framework for Identifying and Prioritizing Zero-Data Long-Tail Keywords in Competitive Digital Markets. Journal of Digital Marketing and Communication, 6(2), forthcoming. https://doi.org/10.53623/jdmc.v6i2.1433 Google autocomplete suggestions were collected for 29 seed keywords in three verticals (SEO and digital marketing tools, small-business consulting, e-commerce) in the United States on 21 October 2026, giving 6,993 relevant long-tail queries. Search volume, keyword difficulty and CPC were retrieved for every query from DataForSEO; 2,459 queries (35.2%) returned none of the three. Live SERPs were collected for every zero-data query and scored with the four Fast Lane signals. Files: queries.csv (the scored dataset, one row per query); fastlane-keyword-study.zip (the full package: data, summary and results files with every figure reported in the paper, the collection, scoring and analysis code, Figures 1 to 4, and README). Raw API responses are not included. Data: CC BY 4.0. Code: MIT. Funding: none; data collection was paid for by the author.