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Research Project………………………………………………….………  \nSupervis ……………………Qurrat Ul Ain …………………………………………………………….……… or:  \nSubmissi  \non Due   01-02-2023   Date:  \nProject ……Identifying Factors Contributing to Lead Conversion Using Machine Learning to Gain  \nTitle: Business Insights……………………………………………………………………………….……… Word  \nCount: ……7691……………………………Page Count……………………20…………………….……..  \nI hereby certify that the information contained in this (my submission) is information pertaining to research I conducted for this project. All information other than my own contribution will be fully referenced and listed in the relevant bibliography section at the rear of the project.  \nALL internet material must be referenced in the bibliography section. Students are required to use the Referencing Standard specified in the report template. To use other author's written or electronic work is illegal (plagiarism) and may result in disciplinary action.  \nSignature: ……………………………………Mansi Sharma………………………………  \nDate:   29-01-2023    \nPLEASE READ THE FOLLOWING INSTRUCTIONS AND CHECKLIST  \n\n| Attach a completed copy of this sheet to each project (including multiple copies) | □ |\n| --- | --- |\n| Attach a Moodle submission receipt of the online project submission, to each project (including multiple copies) . | □ |\n| You must ensure that you retain a HARD COPY of the project, both for your own reference and in case a project is lost or mislaid. It is not sufficient to keep a copy on computer. | □ |\n\nAssignments that are submitted to the Programme Coordinator Office must be placed into the assignment box located outside the office.  \n\n| Office Use Only |  |\n| --- | --- |\n| Signature: |  |\n| Date: |  |\n| Penalty Applied (if applicable): |  |\n\nIdentifying Factors Contributing to Lead Conversion Using Machine Learning to Gain Business Insights  \nMansi Sharma  \nx21143315  \nAbstract  \nDigital marketing has become a major factor contributing to a company ’s revenue.  \nSince, the people invest most of their time online, it is important do promotions online in order to run a business. Companies promote their products online in a lot of ways such as showing advertisements, sending newsletters and so on. This makes people get interested in their products and are called leads. Since not every lead will turn into customer, it is beneficial to identify those leads who have the potential and nurture them in becoming customers. There are a number of factors which contribute in converting a lead to a customer. The goal of this research is to predict the lead conversion with the help of machine learning and determine the most contributing factors in this process. The study uses 5 different machine learning algorithms, namely, Logistic Regression, Decision Tree, Random Forest, CatBoost and XGBoost in predicting the lead conversion. It also aims to visualise the results so that it is easily understandable to thenon-technical stakeholders and thus, to help sales and marketing teams in planning to target leads. Among the best performing models, importance of all the variables are calculated from Logistic Regression, Random Forest and CatBoost and the most contributing ones are selected. These variables are then used to create visualizations in Tableau that will help businesses in making marketing and sales strategies.  \nKeywords: Lead Conversion, Binary Classification, Feature Importance, Tableau  \n1 Introduction  \n1.1 Background  \nMarketing is","cbCaifNN0YYNO7Ws","https://ap.wps.com/l/cbCaifNN0YYNO7Ws","pdf",1320735,22,"English","# Abstract\n# 1 Introduction\n## 1.1 Background","[{\"question\":\"What is the main goal of the research project?\",\"answer\":\"To predict lead conversion using machine learning and determine the key factors that contribute to converting leads into customers.\"},{\"question\":\"Which machine learning algorithms are used in the study?\",\"answer\":\"Logistic Regression, Decision Tree, Random Forest, CatBoost, and XGBoost are used to predict lead conversion.\"},{\"question\":\"How are the results intended to support business teams?\",\"answer\":\"Feature importance findings from strong models are visualized in Tableau to help non-technical stakeholders and guide sales and marketing lead targeting strategies.\"}]","Identifying Factors Contributing to Lead Conversion Using Machine Learning to Gain Business Insights - MSc Research Project | PDF",55]