Sales Analytics for Increased Conversion Rate of Leads

Project Summary: Developed a lead insights dashboard to help sales representatives work more efficiently and increase the conversion rate of their leads. The dashboard combined data from diverse data sources and provided insights by machine learning models.

Project Duration: 2 years and 2 months

Team Size: 1 team member

Industry: IT

Customer

US public corporation developing mission critical enterprise software products.

Business Case

The company’s products are well known in the IT industry and they generate a very large number of leads on a daily basis. The leads are generated through multiple channels and are stored in different data collection systems.

The sales representatives need to prioritize the leads in order to use their time efficiently. They also need to customize their approach for each lead in order to increase the likelihood of conversion.

In order to optimize their work, the sales reps need to augment their knowledge about the leads using insights from data that is scattered across different systems. They need the insights to be easily understandable and accessible in the software tools that they already use on a daily basis.

Solution

Lead insights dashboard visualizing information about each lead. The dashboard presents summarized information collected from multiple systems (website traffic, CRM, marketing automation system, customer support platform, and others). It augments the knowledge that the sales rep already has from the CRM record about the lead.

In addition to that, the dashboard provides a lead score representing the likelihood that the lead will convert. This score is calculated by a machine learning model trained on a large set of historical data.

Moreover, the score is accompanied by a set of explainability factors that provide insight on why the model has assigned a particular score to the lead. The lead score and insights are also integrated for convenience directly into the CRM system that the sales reps use on a daily basis.

Tools & Technologies

  • Python
  • Microsoft SQL Server
  • Google Cloud BigQuery
  • Salesforce CRM
  • Oracle Eloqua
  • Other internally developed business systems

My Role & Responsibilities

I was the single developer and analyst for this project, being supported by my manager, the data warehouse team, and the CRM team. My responsibilities were:

  • Defining and discussing business requirements with stakeholders
  • Gathering data from various data systems
  • Applying data analysis to understand data and the facts that it represents
  • Data cleaning and wrangling
  • Researching and testing possible solutions for prediction problems based on the available data
  • Building machine learning models and evaluating their performance
  • Building scalable infrastructure for providing live predictions to users
  • Integration of the developed predictive solutions into internal business processes
  • Maintenance and continuous improvement of the prediction models and infrastructure

Results

The lead insights dashboard and the lead score were integrated into the sales reps’ daily workflow. The dashboard helped the sales reps to work more efficiently and increase the conversion rate of their leads.