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Objective: A company aims to evaluate its CRM data and sales pipeline for leads registered over the last five months. The task is to build a comprehensive analytical report that provides insights into lead distribution across countries, industries, and organization sizes. The report will assess the health of the sales pipeline, and compare sales agent performance.
The report needs to provide solutions for ad-hoc requests:
Who are the top-performing sales agents?
What are the conversion rates from leads to paying customers in different countries?
How does sales performance vary across different industries?
How healthy is the sales pipeline month-over-month, considering the number of leads at each stage of the sales funnel?
What is the average time taken by sales agents to respond to new leads, and how does it impact conversion rates?
What are the trends in average deal values? Are there noticeable fluctuations?
Does the size of the organization affect the sales cycle duration and deal value?
How effective are sales strategies for different products offered (e.g., SAAS vs. other product types)? Compare the deal closure rates and values between products.
Assess the time taken from lead acquisition to deal closure. Which factors (country, industry, agent) influence the duration of the sales cycle?
Investigate the common characteristics of lost opportunities. What are the primary reasons for deals not closing, and how do these reasons vary by industry or country?
Process:
Before diving into analysis, it's essential to establish boundaries.
Assumptions: Assuming monthly performance discussions occur in the first week, focusing on metric review.
Limitations: Due to limited information, I decided to prioritize a few requirements and skip forecasting. Therefore, my focus was on recent pipeline performance.
I concentrated on two key issues: Closed deals and Churned customers.
After completing data modeling and exploratory data analysis (EDA), I found that most metrics have underperformed in recent weeks.
I curated the MTD Performance report based on KPIs, This approach helps us understand selected metrics at a granular level, enabling each team to focus effectively.
Taking inspiration from the recent SQL BI 3-30-300 rule video (big shout out to Kurt Buhler), and incorporating insights from various YouTube resources (Thanks to Injae Park and Bas Dohmen for their awesome PBI content).
My analysis revolves around these metrics.
Metrics:
The Report contains 3 pages:
Overview Page:
MTD Deals Page:
Details Page:
Finally Suggestions: