Overview

This project analyzes a fictitious B2B sales pipeline dataset from a computer hardware company. The dataset contains information on customer accounts, products, sales teams, agents, and sales opportunities — including deal values, stages, and outcomes. The objective is to uncover insights that help management understand performance trends, improve sales strategies, and identify opportunities for growth.

Business Context

In a competitive B2B environment, understanding how sales teams and products perform is critical for success. A well-analyzed CRM dataset can reveal:

• Which teams or agents are consistently closing deals

• What types of products have the highest win rates

• Seasonal or quarterly performance trends

• Bottlenecks or underperforming areas in the sales pipeline

By using data-driven insights, the company can better allocate resources, train sales staff, and optimize marketing efforts.

Objectives

1. Evaluate Sales Team Performance – Compare total revenue, deals won and win rates across teams.

2. Identify Underperforming Agents – Highlight agents with low conversion rates or revenue performance.

3. Analyze Quarterly Trends – Examine how sales metrics change over time (quarter-over-quarter).

4. Assess Product Win Rates – Identify which products contribute most to successful deals.

5. Provide Recommendations – Suggest data-backed actions to improve overall sales efficiency.

Expected Deliverables

• Cleaned and merged CRM dataset

• Summary statistics and visual dashboards

• Performance comparisons by team, agent, and product

• Quarterly trend analysis

• Final report summarizing findings and strategic recommendations