• Sandeep Kamalakar Shelar
• Uma Prashant Gurav

Lead scoring models are widely used by financial organizations to identify prospect customers. These models are developed according to business needs and strategies such as logistic regression, SVM or naïve Bayesian are applied according to data and leads to be focused. Here we are proposing logistic regression model over other models for lead score evaluation when we know exact dependent variables for profile scoring which will be useful to increase customer conversion ratio. Users are having financial plans w.r.t certain goals like Car, House, Children Education, retirement. Users are visiting to sites, but they are not completing registration or investing any amount w.r.t goals. We will collect ratio of prospect customers to actual customer conversion. We will identify such data of users and based on type of goals or amount of invest Mode of invest will suggest benefits plans like direct money points deposited to user wallet, reward system, concession on processing fees, Concession on product price. Based on proposed solution will identify increase in percentage of prospect customers ratio. Also, we can feed online and offline data to for optimal performance.

Keywords -: Lead score, Prospect customer.

"Identify prospects customers using lead score strategies and provide dynamic solution", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 6, page no.d366-d370, June-2022, Available :http://www.jetir.org/papers/JETIR2206347.pdf

"Identify prospects customers using lead score strategies and provide dynamic solution", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 6, page no. ppd366-d370, June-2022, Available at : http://www.jetir.org/papers/JETIR2206347.pdf