[{"data":1,"prerenderedAt":132},["ShallowReactive",2],{"blog-en-revenue-cluster-analysis-customer-segments":3},{"id":4,"title":5,"body":6,"categories":112,"date":114,"description":12,"draft":115,"excerpt":116,"extension":117,"image":118,"lang":119,"meta":120,"modified":121,"navigation":122,"noindex":115,"path":123,"related":116,"seo":124,"seoDescription":125,"seoTitle":126,"slug":127,"sourcePath":128,"sourceRoute":116,"stem":129,"tags":116,"translated":115,"type":130,"wpId":116,"__hash__":131},"blog\u002Fen\u002Fblog\u002Frevenue-cluster-analysis-customer-segments.md","Revenue cluster analysis: spotting patterns in invoice volume",{"type":7,"value":8,"toc":102},"minimark",[9,13,18,21,25,28,32,35,39,64,68,79,85,88],[10,11,12],"p",{},"Small customers, mid-sized customers, key accounts – most businesses think in categories like these without ever having defined them on the basis of actual figures. To group customers systematically by invoice volume, many resort to a home-made Excel analysis. 1Tool offers a built-in cluster analysis for this that automatically divides customers into groups based on their invoice volume.",[14,15,17],"h2",{"id":16},"how-the-cluster-analysis-works","How the cluster analysis works",[10,19,20],{},"The cluster analysis in 1Tool automatically divides customers into groups based on their invoice volume. Each cluster has a minimum and a maximum threshold and contains the customers whose invoice volume falls within that range. The number of clusters can be configured, so the analysis can be broad – for example three groups – or more finely divided, depending on how detailed you want the segmentation to be.",[14,22,24],{"id":23},"why-automatic-segmentation-saves-time","Why automatic segmentation saves time",[10,26,27],{},"Creating a customer segmentation by hand means, in practice: exporting invoice data, sorting it in a spreadsheet, setting thresholds manually and recalculating the groups every time the data is updated. This is not only laborious but also error-prone as soon as the underlying data changes. The cluster analysis in 1Tool does exactly this work directly on the basis of the invoice data already in the system, without the figures first having to be exported or prepared externally.",[14,29,31],{"id":30},"what-you-can-do-with-the-results","What you can do with the results",[10,33,34],{},"Once customers have been divided into clusters, you can see at a glance how many customers belong to which group and what share of the invoice volume they account for. This creates an objective basis for strategic decisions: should sales focus more on winning new key accounts, or is there untapped potential in developing existing mid-sized customers towards higher revenue? The cluster breakdown also provides a clear, traceable basis for assessing how heavily total revenue depends on a few large customers – without this analysis having to be rebuilt manually first.",[14,36,38],{"id":37},"frequently-asked-questions","Frequently asked questions",[10,40,41,45,48,49,52,54,55,58,60,61],{},[42,43,44],"strong",{},"What criterion is used to form the clusters in 1Tool?",[46,47],"br",{},"\nThe clusters are formed on the basis of customers' invoice volume, with each cluster having a minimum and a maximum threshold.\n",[42,50,51],{},"Can I set the number of clusters myself?",[46,53],{},"\nYes, the number of clusters can be configured, so the segmentation can be adapted to your needs.\n",[42,56,57],{},"Can I also see which specific customers belong to which cluster?",[46,59],{},"\nYes, each cluster contains the customers whose invoice volume falls within the respective range.\n",[42,62,63],{},"Would you like to have your customers segmented automatically by invoice volume?",[14,65,67],{"id":66},"read-more","Read more",[69,70,71],"ul",{},[72,73,74],"li",{},[75,76,78],"a",{"href":77},"\u002Fen\u002Fblog\u002Faccounting-system-not-isolated-tool\u002F","One accounting system, not a set of isolated tools: how the building blocks work together",[10,80,81],{},[75,82,84],{"href":83},"\u002Fen\u002Fappointment-request\u002F","Book a demo",[14,86,67],{"id":87},"read-more-1",[69,89,90,96],{},[72,91,92],{},[75,93,95],{"href":94},"\u002Fen\u002Fblog\u002Fpreliminary-balance-sheet-at-the-push-of-a-button\u002F","The preliminary balance sheet at the push of a button: how it works in 1Tool",[72,97,98],{},[75,99,101],{"href":100},"\u002Fen\u002Fblog\u002Fsepa-payment-files-from-invoices\u002F","Generate SEPA payment files directly from the invoice",{"title":103,"searchDepth":104,"depth":104,"links":105},"",2,[106,107,108,109,110,111],{"id":16,"depth":104,"text":17},{"id":23,"depth":104,"text":24},{"id":30,"depth":104,"text":31},{"id":37,"depth":104,"text":38},{"id":66,"depth":104,"text":67},{"id":87,"depth":104,"text":67},[113],3330,"2026-08-13T09:00:00",false,null,"md","\u002Fmedia\u002F2026\u002F07\u002Fumsatzcluster-analyse-kundengruppen.jpg","en",{},"2026-07-25T08:23:00",true,"\u002Fen\u002Fblog\u002Frevenue-cluster-analysis-customer-segments",{"title":5,"description":12},"Automatic revenue cluster analysis: segment customers by invoice volume without Excel.","Revenue cluster analysis: patterns in invoice volume | 1Tool","revenue-cluster-analysis-customer-segments","\u002Fen\u002Fblog\u002Frevenue-cluster-analysis-customer-segments\u002F","en\u002Fblog\u002Frevenue-cluster-analysis-customer-segments","posts","F1JIY99TloP2DcdLbs5IEHZQiWdm8cLfYJIo6r4V5dY",1791582058683]