Integrated Salesforce tab for new leads entry automation.
Correction and normalization of over 70% of the processed entries.
Savings in physical marketing campaigns and geographical re-organization of commercial efforts.
The company-client interactions are usually registered in a CRM (customer relationship management). When properly exploited, these data are very valuable as they allow for client targeted offers and improve the sales department performance. The input of new data to CRM in a company with a number of salespersons is decentralized. The lack of a central entity that controls the CRM inputs, speeds up the addition of data by salespersons, but it may also have a negative impact on the quality of these data. Typos, duplicated registers, or a lack of normalization are shortcomings that may complicate or even prevent from the exploitation of these data. The challenge is to design a tailor-made, intelligent algorithm that improves current and future CRM data quality, keeping it a decentralized system.
Together with the Digital Dept. of Simon, we designed and implemented an algorithm that uses similarity measure techniques applied to textual data in order to normalize, clean and disambiguate company’s CRM data. We have also built the web app integrated to the CRM that allows salespersons to benefit from the algorithm results autonomously. The impact of the algorithm-application is an improvement of the commercial data quality, very valuable information both for the Sales department as for the other company departments.