Python for Social Media Analytics
What you’ll learn
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Use Python for social media analytics
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Acquire business knowledge and digital marketing skills
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Solve real-world challenges
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Boost digital marketing skills and understanding
01
Course Introduction
Course Introduction
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3:32
Welcome
Learn to transform millions of data points from Facebook into actionable marketing insights by combining data science with social media marketing, using Python for Facebook analytics to drive campaigns.
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1:17
Why is this the right time to learn Python for social media analytics?
Learn to analyze Facebook campaigns with Python, explore the marketing funnel, audience types, and metrics to evaluate campaign performance.
02
Introduction to Social Media Marketing
Introduction to Social Media Marketing
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1:52
Intro to social media marketing
Explore social media analytics for paid ads, covering KPIs like conversion rates, cost per click, and ROAS, and learn to use Facebook ads manager with Python to analyze a campaign.
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3:57
The marketing funnel
Explore how the marketing funnel moves customers from awareness to action, using brand awareness, testimonials, and buy now calls to action, with ongoing engagement to convert interest into purchases.
03
Social Media Marketing Terminology
Social Media Marketing Terminology
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4:24
What is a marketing campaign?
Explore how the Facebook ads manager structures a marketing campaign into campaigns, ad sets, and ads, with awareness, consideration, and conversion objectives guiding key metrics and optimization.
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1:41
What are ad sets?
Explore how a campaign splits into ad sets with assets targeting distinct audiences, using placements on Facebook and Instagram, while budget optimization allocates the overall budget to maximize conversions.
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1:00
What is an ad?
Learn how Facebook campaigns end at the individual ad, with text, creative, headlines, and CTAs, and how AB testing compares video and image ads within ad sets.
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1:55
Core, custom, and lookalike audiences
Explore core, custom, and lookalike audiences on Facebook, from demographics and interests targeting to custom audiences built from email lists, and lookalikes that match your existing users for scalable marketing.
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1:56
Facebook pixel
Explore how the Facebook pixel tracks user actions on your site, identifies visitors, and enables targeted ads with custom and lookalike audiences who initiated checkout but didn't complete.
04
Social Media Marketing Metrics
Social Media Marketing Metrics
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0:47
Intro to social media marketing metrics
Analyze social media campaigns using key metrics and KPIs to measure sales, reach, and engagement on Facebook, and derive data-driven insights to optimize future marketing strategies.
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1:30
Reach & impressions
Explore reach and impressions as top-funnel metrics on Facebook, counting unique users and ad exposures to gauge audience size, campaign visibility, and potential ad fatigue.
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1:11
CTR
Learn how the click-through rate (ctr) measures ad engagement by comparing clicks to impressions on Facebook ads, and how to optimize creative and targeting for better performance.
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0:47
Link clicks
Discover how link clicks represent the subset of total ad clicks that lead users to a destination, such as a website, when users click a call-to-action link.
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2:09
Conversion rate
Conversions track the completion of desired actions in a marketing funnel; monitor drop-offs from slow mobile pages to unfriendly sign-up forms to boost conversions.
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2:11
CPM
Assess ad value by tracking CPM, CPC, and PR to measure return on investment and avoid overspending. CPM indicates cost per thousand impressions, while targeting and campaign type influence it.
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1:04
CPC
The CPC, or cost per link click, measures the cost of each ad click, and Facebook optimizes CPC in engagement campaigns, letting you compare headline or creative in AB tests.
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1:01
CPR
Understand CPR, or cost per result, and its interchangeable terms, and see how spend per conversion determines cost per sale on Facebook, with optimization to reduce costs.
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1:30
ROAS
Learn to calculate ROAS by dividing total ad revenue by ad spend, using 50,000/5,000 as an example; ROAS differs from ROI and may require a three-week assessment window.
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0:41
A message from the instructor
Congratulations on mastering new terminology and metrics in this section. Keep practicing the calculations, and refer to the cheat sheet for formulas like CPM and CTR in the lesson resources.
05
Intro to Facebook Ads Manager
Intro to Facebook Ads Manager
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3:05
Intro to Facebook Ads Manager
Learn to navigate Facebook Ads Manager to create and manage campaigns, understand the interface and ad creation steps, and explore options to set up your own account or follow along.
06
Creating a Facebook Campaign
Creating a Facebook Campaign
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4:53
Creating your first campaign on Ads Manager
Learn to create your first Facebook ads manager campaign by selecting a traffic objective under consideration, naming the campaign, and configuring budget options before moving to an ad set.
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6:08
Creating an ad set
Create an ad set for a campaign, define audience from all countries, females aged 18–34 interested in fitness, maximize landing page views, and configure daily or lifetime budgets.
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6:34
Creating an ad
Create and optimize Facebook ads by configuring an ad, ad set, and multiple ads with distinct content, headlines, and creatives; preview placements, track events, and compare performance to maximize ROI.
07
Analyzing a Facebook Campaign with Python - Overall Campaign Performance
Analyzing a Facebook Campaign with Python - Overall Campaign Performance
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2:29
Examining the dataset
Examine a social media analytics dataset in a Jupyter notebook using pandas to load, preview, and summarize ad set metrics from a May 2022 conversion campaign with a purchase objective.
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4:01
Facebook campaign summary
Analyze Facebook campaign performance by summing reach, impressions, link clicks, landing page views, and results to reveal funnel bottlenecks; highlight 450k reach, 1.1m impressions, 83 conversions, and €4,000 spent.
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2:15
Calculating the CPM
Calculate CPM, the cost per thousand impressions, by dividing total spend by impressions and multiplying by 1000, yielding €6.55 for this campaign.
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3:06
Calculating the CPR
Calculate CPR, the cost per result, by dividing total spent by total results, removing zero-result rows to avoid infinity; the average CPR is €63.8.
08
Analyzing a Facebook Campaign with Python - Ad Set Overview
Analyzing a Facebook Campaign with Python - Ad Set Overview
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0:55
Ad set overview
Explore how the 365 data science team's ad sets use a consistent naming convention to analyze assets by audience segments and Facebook placements with the same purchase objective.
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8:07
Warm, hot, and cold ad sets
Learn to categorize ad sets as hot, warm, or cold based on familiarity, analyze metrics with pandas to compare reach, impressions, click-through rate, conversions, and cost per result across categories.
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10:34
LAL vs Detailed ad sets - Part 1
Explore how to categorize ad sets into lookalike and detailed audiences, compute their performance averages, and visualize differences using pandas, seaborn, and matplotlib.
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1:44
LAL vs Detailed ad sets - Part 2
Compare lookalike audiences with detailed targeting, noting similar clickthrough rates but higher conversions and cost per acquisition for detailed targeting in conversion campaigns, while lookalikes boost reach for brand awareness.
09
Analyzing a Facebook Campaign with Python - Detailed Ad Set Analysis
Analyzing a Facebook Campaign with Python - Detailed Ad Set Analysis
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6:12
Analyzing Hot ad sets - Part 1
Analyze hot ad sets to optimize top of funnel performance by filtering dataframes to hot assets and visualizing reach, impressions, and CPM with seaborn and matplotlib bar charts.
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6:34
Analyzing Hot ad sets - Part 2
Compare hot assets using CPM and reach, then assess engagement and mid and bottom-funnel metrics to guide budget reallocation for higher conversions.
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5:29
Analyzing warm ad sets
Analyze warm wall assets to compare reach and impressions; video ads show higher engagement and more link clicks but a 75% drop-off to landing pages, reducing conversions.
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8:09
Analyzing cold ad sets - Part 1
Compare cold ad sets by asset type to contrast lookalike and detailed targeting, using bar charts of top funnel metrics to reveal performance and cost efficiency.
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5:13
Analyzing cold ad sets - Part 2
Analyze ad set performance by comparing reach, impressions, and CPM across look-alike and detailed targeting assets, identifying cost-effective strategies and engagement drivers.
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3:06
Analyzing Cold ad sets - Part 3
Analyze conversions and cost per result of ad assets, compare lookalike and detailed targeting assets, and assess spend by the 365 data science team to identify cost-efficient reallocations.
