Data analytics

Data Analytics Projects

Full case studies — from raw data to interactive dashboards to sales and business recommendations. As I complete new analyses, they'll appear here automatically.

X Education Lead Scoring Analysis

X Education is an online education company that generates leads through multiple digital marketing channels, including landing pages, Google Search, referrals, and direct traffic. However, not every lead becomes a customer, making it difficult for the sales team to prioritize prospects with the highest likelihood of conversion.

The objective of this project was to analyze historical lead data to identify the characteristics of high-converting leads, evaluate the performance of acquisition channels, and uncover behavioral patterns that distinguish "hot leads." The insights can help improve sales prioritization, marketing effectiveness, and overall conversion performance.

Business Objectives

  • Which customer segments generate the most conversions?
  • Which lead sources generate the most leads and the highest conversion rates?
  • Where do most of the leads come from (demographics)?
  • Which customer behaviors are associated with successful conversions?
  • What recommendations can improve lead quality and conversion performance?

Dataset

The X Education Lead Scoring dataset contains historical information on prospective customers and their interactions with the company's marketing channels.

Lead demographicsOccupation and specializationGeographic locationLead source and lead originWebsite engagementEmail and marketing interactionsConversion status (target variable)

Data Preparation

  1. 1Reviewed the data dictionary to understand the purpose and meaning of each variable, and identified variables relevant to the business objectives.
  2. 2Assessed data quality — examining missing values, empty records, incorrect formatting, inconsistent data types, and irregular values.
  3. 3Cleaned the dataset: removed empty cells where appropriate, converted variables to correct data types and formats, trimmed unnecessary whitespace, and standardized categorical variables.

Exploratory Data Analysis

Before building the dashboard, exploratory analysis was performed using pivot tables to identify trends, high-performing customer segments, lead acquisition channels, and behavioral differences between converted and non-converted leads. These findings directly informed the design of the Tableau dashboard.

Dashboard Overview

The Tableau dashboard provides an interactive overview of lead generation and conversion performance.

  • Executive KPI cards — Total Leads, Total Conversions, Overall Conversion Rate
  • Lead Source Performance
  • Customer Segment Analysis
  • Geographic Distribution of Leads
  • Behavioral Indicators of Hot Leads
View Interactive Dashboard

Key Insights

Customer Segment Performance

Marketing Management professionals generated the highest number of converted leads, while the Services Excellence segment produced the fewest conversions.

Business insight: Marketing-related professionals appear to have a stronger need for X Education's offerings and should be a priority audience for future campaigns.

Lead Source Performance

Direct Traffic and Google generated the highest number of leads, making them the company's primary acquisition channels. However, although References generated only 13 leads, every one of those leads converted — a 100% conversion rate.

Business insight: Referral-based leads exhibit exceptionally high purchase intent, suggesting that increasing referral volume could significantly improve conversion efficiency.

Geographic Distribution

The majority of leads originated from India, with 1,554 recorded leads. Several other countries generated only a single lead each.

Business insight: India represents the company's strongest market and should remain a strategic focus, while international expansion decisions should be supported by further market research.

Behavioral Indicators of Hot Leads

Converted leads interacted with the website more frequently (5.1 vs. 4.5 average visits) and spent more than twice as long on the site (990s vs. 447s average time).

Business insight: Website engagement, particularly time spent on-site, is a strong indicator of conversion likelihood and can be incorporated into lead qualification strategies.

Average website visits by outcome

Converted leads5.1 visits
Non-converted leads4.5 visits

Recommendations

  1. 1

    Expand referral marketing: referral leads achieved a 100% conversion rate. Referral incentives and stronger partnership programs could increase the volume of high-quality leads.

  2. 2

    Continue investing in high-performing acquisition channels: Direct Traffic and Google consistently generated the highest lead volumes.

  3. 3

    Prioritize highly engaged leads: leads that spend more time on the website and visit more frequently show a greater likelihood of conversion.

  4. 4

    Focus marketing on high-converting customer segments: tailored campaigns targeting Marketing Management professionals may further improve conversion outcomes.

Tools Used

  • Google Spreadsheet — Data Cleaning, EDA, Pivot Tables
  • Tableau — Interactive Dashboard, Data Visualization, KPI Reporting

Skills Demonstrated

Business Problem FramingData Cleaning & PreparationExploratory Data AnalysisData VisualizationBusiness IntelligenceBusiness Analytics & StorytellingLead Scoring AnalysisData-Driven Decision Making

What's Next

In Progress

  • Marketing Campaign Analysis

Next Up

  • Sales Performance Dashboard
  • Customer Segmentation Analysis
  • CRM Sales Funnel Analysis

Tools

Google Sheets · Tableau · Power BI

Languages

SQL · Python

Focus Areas

Business Analysis · Business Intelligence · Sales Analytics · Customer Insights