Relevant criteria are listed and weighted the characteristics of the individual characteristics are evaluated with points. Whitepaper b b new customer acquisition how to acquire new customers in the b b area based on the web scoring analysis a model is developed to identify statistical twins of your existing customers from more than million german language company websites. You receive a scoring of your own customers and prospects and can expand your lead list with companies with a high score I.E. A high probability of closing. True to the principle “if these are your customers these companies should also be your customers. “ the smart way to acquire new customers in b b – this is how it works prozessgraphik svg.
Your database you simply provide us with up to urls of your whatsapp mobile number list existing or desired customers. Of course we can relieve you of this step by helping you to determine the urls..Data enrichment we enrich your database with up to date information from publicly accessible sources such as the customer's website..Customer analysis a data mining algorithm identifies the characteristics that your existing customers have in common in the external presentation on the website and that distinguishes them from non customers. For example the presentation of certifications the use of technical terms or the description of your own quality requirements allow conclusions to be drawn about your customers. Positive side effect you will also receive interesting insights into your existing customers and may be able to identify cross and up selling potential.
Search for new customers you will receive a graphic representation of your customer dna in the form of a tag cloud and up to of the most similar company websites. Your sales work you can start acquiring new customers with the potential leads we have provided. Model extension with each new lead the algorithms learn and become more and more accurate in the customer analysis. Optimal use of scarce sales resources criteria such as company size industry and turnover are standard in many companies when selecting potential business contacts. The demand for meaningful criteria and big data is increasing however the quality of most crm data often does not allow for complex analyses.