This study assessed whether systematically using finetype data in national surveillance of invasive meningococcal disease serogroup B (IMD-B) in the Netherlands could improve cluster detection in order to prevent further cases through public health actions. We analysed 2005–2023 data, including 1,642 IMD-B cases with complete finetype and municipality information (95%; N = 1729). Using a generalized linear model, we calculated expected baselines for each finetype, including temporal trends. Using SaTScan™, we applied Poisson scan-statistics with a 365-day window to identify spatiotemporal clusters, comparing results to epidemiological and core-genome multi-locus sequence typing (cgMLST) data. Of 453 finetypes, 308 (68%) occurred once; diversity was high (Gini-Simpson index 0.96). We identified 42 spatiotemporal clusters across 37 finetypes, comprising 132 cases (8%), with a median cluster size of two (range 2–21) and duration of 45 days (range 6–356). Between zero and five clusters were detected yearly. Among 18 cases with known epidemiological links, 14 (78%) were within detected spatiotemporal clusters. CgMLST data from eight clusters supported some clusters but rejected others. Systematic cluster detection using finetype could reveal missed epidemiological links, potentially enabling public health action. However, its impact in preventing additional IMD-B cases is likely limited due to small cluster sizes, though meaningful given the severity of IMD-B. Simple finetype mapping may provide a resource-efficient alternative to SaTScan™.