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Course

Analyzing Marketing Campaigns with pandas

Beginner

4.7+

Updated 05/2025

Build up your pandas skills and answer marketing questions by merging, slicing, visualizing, and more!

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PythonExploratory Data Analysis4 hours14 videos53 Exercises4,500 XP28,916Statement of Accomplishment

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Course Description

One of the biggest challenges when studying data science technical skills is understanding how those skills and concepts translate into real jobs. Whether you're looking to level up in your marketing job by incorporating Python and pandas or you're trying to get a handle on what kinds of work a data scientist in a marketing organization might do, this course is a great match for you. We'll practice translating common business questions into measurable outcomes, including "How did this campaign perform?", "Which channel is referring the most subscribers?", "Why is a particular channel underperforming?" and more using a fake marketing dataset based on the data of an online subscription business. This course will build on Python and pandas fundamentals, such as merging/slicing datasets, groupby(), correcting data types and visualizing results using matplotlib.

Prerequisites

Intermediate Python

1

Pandas

Introduction to pandas for marketing

Importing the dataset

Examining the data

Data types and data merging

Updating the data type of a column

Adding new columns

Date columns

Initial exploratory analysis

Daily marketing reach by channel

Visualizing daily marketing reach

2

Exploratory Analysis & Summary Statistics

Introduction to common marketing metrics

Calculating conversion rate

Calculating retention rate

Customer segmentation

Comparing language conversion rate (I)

Comparing language conversion rate (II)

Aggregating by date

Plotting campaign results (I)

Visualize conversion rate by language

Creating daily conversion rate DataFrame

Setting up our data to visualize daily conversion

Visualize daily conversion rate

Plotting campaign results (II)

Marketing channels across age groups

Grouping and counting by multiple columns

Analyzing retention rates for the campaign

3

Conversion Attribution

Building functions to automate analysis

Building a conversion function

Test and visualize conversion function

Plotting function

Putting it all together

Identifying inconsistencies

House ads conversion rate

Analyzing House ads conversion rate

House ads conversion by language

Creating a DataFrame for house ads

Confirming house ads error

Resolving inconsistencies

Setting up conversion indexes

Analyzing user preferences

Creating a DataFrame based on indexes

Assessing bug impact

4

Personalization A/B Test

A/B testing for marketing

Determining key metrics

Test allocation

Comparing conversion rates

Calculating lift & significance testing

Creating a lift function

Evaluating statistical significance

A/B testing & segmentation

Building an A/B test segmenting function

Using your segmentation function

Analyzing Marketing Campaigns with pandas

Course
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Included withPremium or Teams

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*4.7

from 72 reviews

79%

18%

1%

0%

1%

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Most recent
Top reviews

Abdelrahman

1 day

Isai

2 days

Joshua

4 days

Anil

4 days

Lipsa

about 18 hours

Amber

about 20 hours

Most of the information and questions were very helpful and learning more about how to use pandas in Python. There were a few questions that were misleading and showed graphs with non-legible writing that made it hard to answer questions about the graphs. It was longer than needed but informational still.

Abdelrahman

Isai

Joshua

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