Python for Social Media Analytics

Description

Data science and analytics are revolutionizing every industry, propelling businesses to new heights in today’s data-driven economy. Social media is a powerful tool that 77% of enterprises use as of 2023. It’s reshaping how companies reach their customers and transforming global marketing strategies.

This Python for Social Media Analytics course will teach you the combined skillset of a data scientist and a social media marketer, rendering you invaluable to companies looking to drive business value with data.

Such abilities give you a competitive edge over data science professionals without domain expertise.

Unique features of This Python For Social Media Analytics Course

• Real-World Data: Utilizes real social media data acquired through 365 DataScience's marketing campaigns.

• Practical Problem Solving: Emphasizes a pragmatic, data-driven approach to address real-world business challenges.

• Comprehensive Skillset: Equips you with the in-demand skillset of social media analytics, differentiating you from other data professionals and enhancing your employability.

Typical Data Science Courses

• Dataset Source: Other courses rely on clean, pre-processed Kaggle datasets.

• Focus: Typically emphasize theoretical concepts, often lacking preparation for real-world data science applications.

• Business Relevance: Lacking business or domain-specific knowledge instruction—leading to a skills gap between coursework and practical job requirements.

Topics Covered

· Python

· Social Media Analytics

· Marketing

· Data Analysis

What You’ll Learn

This course prepares you to extract insights from social media data, mainly focusing on Facebook marketing.

The course is structured into five distinct sections:

1. Introduction to Social Media Analytics

The first part of this course is designed to teach you the basics of social media analytics, and how it is used to drive marketing success.

I will also teach you about the marketing funnel, which is a model that illustrates a consumer’s journey with any brand.

By the end of this section, you will be familiar with the fundamentals of social media marketing.

2. Social Media Marketing Terminology

This course segment takes you through the jargon commonly used in digital marketing.

You’ll learn the difference between terms like ads, ad sets, and campaigns, along with data collection mechanisms like the Facebook (Meta) Pixel.

By the end of this section, you’ll have a firm grasp of marketing concepts to work closely with marketing teams and aid in driving organizational success.

3. Social Media Metrics

Social media marketers track various KPIs to measure the success of ad campaigns.

These metrics are then analyzed to improve the performance of future marketing initiatives iteratively.

This is where data analysts come in. Marketing teams work closely with data practitioners to uncover insights from social media performance metrics.

But to deliver data-driven recommendations and improve campaign performance, you must first understand how marketing success is measured.

This section guides you through the metrics tracked in Facebook campaigns and shows how they are calculated with real-world examples.

4. Creating an Ad Campaign on Facebook Ads Manager

This section covers how to use Facebook Ads Manager, which allows you to create and manage your ads on the Facebook platform.

This will give you an understanding of how marketers create social media campaigns, allowing you to work closely with marketing teams and develop an understanding of the strategies employed during the campaign creation process.

By the end of this segment, you’ll understand how social media marketers create, run, and track advertisements on the Facebook platform.

5. Analyzing a Real Marketing Campaign with Python

This is the final part of this course, building on top of all the concepts taught in the previous sections.

Having gained a grasp of various social media metrics and feeling at ease with the Ads Manager platform, you’ll now learn to analyze a Facebook marketing campaign performance using Python.

The dataset we will analyze in this section belongs to a real marketing campaign launched by 365DataScience.

We’ll extract data-driven insights beyond surface-level information to reveal how 365DataScience’s marketing strategies performed.

By the end of this section, you’ll know how to analyze social media data with programming languages like Python.

You’ll also be capable of enhancing a business’s Facebook marketing strategy by delivering quantifiable recommendations backed by data.

So, if all this sounds exciting, click the Buy Now button today. See you inside the course!

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