Marketing Campaign Analysis

On This Page

• C10.1  Project Overview
• C10.2  Business Problem
• C10.3  Dataset Description
• C10.4  Objectives
• C10.5  Step-by-Step Solution
• C10.6  Complete Python Code
• C10.7  Expected Output
• C10.8  Visualizations
• C10.9  Key Insights
• C10.10  Business Recommendations

Capstone Project 10: Marketing Campaign Analysis

C10.1  Project Overview

This project analyzes marketing spend and returns across multiple advertising channels to determine which platforms deliver the best ROI — directly relevant to Samantus's own digital marketing agency work.

C10.2  Business Problem

A marketing team is spreading budget across 5 channels and wants data-backed clarity on which channels actually deliver the best return, to reallocate spend more effectively.

C10.3  Dataset Description

Sample scope: 10 campaigns across 5 channels over one quarter.

C10.4  Objectives

• Calculate ROI for each marketing channel
• Analyze the relationship between ad spend and conversions
• Identify the best and worst performing channels
• Recommend a revised budget allocation strategy

C10.5  Step-by-Step Solution

• Step 1: Load the campaign performance CSV into Pandas
• Step 2: Calculate ROI % for each campaign: (revenue - spend) / spend * 100
• Step 3: Calculate average ROI per channel
• Step 4: Visualize spend vs conversions using a scatter plot
• Step 5: Rank channels from best to worst ROI
• Step 6: Summarize budget-reallocation recommendations

C10.6  Complete Python Code

import pandas as pd
import matplotlib.pyplot as plt

df = pd.read_csv("campaign_data.csv")

df['roi_pct'] = (df['revenue'] - df['spend']) / df['spend'] * 100

channel_roi = df.groupby('channel')['roi_pct'].mean().sort_values(ascending=False)
print("Average ROI % by Channel:\n", channel_roi.round(1))

best_channel = channel_roi.idxmax()
worst_channel = channel_roi.idxmin()
print("Best Channel:", best_channel)
print("Worst Channel:", worst_channel)

plt.scatter(df["spend"], df["conversions"])
plt.title("Spend vs Conversions")
plt.savefig("spend_scatter.png")

C10.7  Expected Output

C10.8  Visualizations

C10.9  Key Insights

• Instagram delivers the highest average ROI (185%), meaningfully ahead of Google Ads (110%) and Facebook (95%, the weakest performer).
• Spend and conversions show a strong, roughly linear positive relationship — suggesting the channels analyzed aren't yet hitting diminishing returns at current budget levels.
• Email marketing (140% ROI) punches well above its typical budget share, suggesting it's currently under-invested relative to its efficiency.

C10.10  Business Recommendations

• Shift 15-20% of Facebook's current budget toward Instagram and Email, based on their clearly superior ROI performance.
• Since spend and conversions haven't plateaued, consider testing a modest overall budget increase on the top 2 channels to capture more scale before returns diminish.
• Re-run this exact ROI analysis quarterly to catch channel performance shifts early, rather than relying on outdated assumptions about which platforms work best.