Relevant criteria are listed and weighted the characteristics of the individual characteristics are evaluated with points. Whitepaper b b new customer acquisition this is how new customer acquisition in the b b area works on the basis of the web scoring analyses 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. Freely based on 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 works prozessgraphik svg v desired customers available. Of course we can relieve you of this step by helping you to determine the urls.

Data enrichment we enrich your database whatsapp mobile number list 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. A positive side effect you also get interesting insights into your existing customers and can identify cross selling 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 the algorithms learn with each new lead 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 but the quality of most crm data often does not allow for complex analyses. The extensive acquisition of data from address dealers is also difficult.