Mô tả

In this big data age, knowing how to organize, synthesize, and analyze large quantities of marketing data is no longer an "good-to-have" skill. It is absolutely essential! Are you a student looking to set yourself apart from your peers? Are you looking to break into social media marketing? Do you want to become an expert in marketing analytics? If so, then this course is for you! 

In this course, we'll teach you everything you need to know to become an expert in marketing analytics. No prior experience in social media marketing, statistics, or marketing required!

Our course is based on the hands-on, case-study method to learning. In other words, we'll learn by analyzing the data in a real-life scenario. The course begins with an introduction to big data, data analytics, and marketing analytics. This will allow you to feel comfortable with these terms.

Afterwards, we move on to learning the most important web, social media, digital advertising, customer, and revenue metrics in marketing. As we learn each new metric, we'll immediately apply it to the real-life case study.

We cap off the course by teaching you how to properly model out a new marketing initiative. This model will project out a campaign's revenue and expenses for 2 years and will be complete with scenario and sensitivity analyses. We then conclude by summarizing our data in a beautiful, dynamic dashboard.

We are excited to have you join us on this journey and look forward to seeing you in the course!

Bạn sẽ học được gì

Learn the most important marketing metrics and how to apply them to your data

Analyze a company's PPC marketing campaign using key metrics

Know how to ask the right questions from your data

Build a marketing initiative forecast model from the ground up

Build a dynamic dashboard to summarize your analysis

Yêu cầu

  • You should have a beginner/intermediate knowledge of Excel including SUMIFS and COUNTIFS
  • NO background in statistics required

Nội dung khoá học

7 sections

Introduction

2 lectures
Download the Files
00:11
Introduction to the case study
04:50

Web, Social Media, & Digital Advertising Analytics

11 lectures
Web Analytics: Traffic sources
04:15
Web Analytics: Time spent on site
03:00
Web Analytics: Bounce/Abandonment rate
04:33
Introducing the case study data
03:02
Social Media Analytics: Followers/Likes
02:36
Social Media Analytics: Engagement
03:41
Social Media Analytics: Key takeaways
03:15
Digital Ad Analytics: Impressions and reach
04:22
Digital Ad Analytics: Click-through-rate (CTR)
02:18
Digital Ad Analytics: Cost-per-click (CPC)
03:06
Digital Ad Analytics:Cost-per-lead & Key takeaways
05:39

Applying our Analytics

6 lectures
Campaign Cost & # of Impressions
05:23
Calculating CPC & Lead conversion
04:23
Asking more questions of our data
05:17
Analyzing our data by ad pt. I
06:11
Analyzing our data by ad pt. II
03:03
Calculating Cost-per-lead
08:58

Customer Analytics

5 lectures
Customer Analytics: Customer acquisition cost
03:50
Customer Analytics: Customer lifetime value
05:46
Customer Analytics: Customer lifetime value example
02:43
Customer Analytics: Net promoter score
04:57
Customer Analytics: Key takeaways
02:53

Applying our Analytics pt. II

14 lectures
Introduction to our new data
06:19
Calculating the # of new customers
05:54
Calculating average customer age & Days to convert
08:09
Calculating customer acquisition cost & Average purchases
03:57
Adding fields to our data
07:01
Calculating touch points & Lead conversion
03:47
Building a PivotChart with Slicers
08:57
Analyzing age demographics
07:26
Creating a PivotTable with a calculated field
06:47
Calculating net promoter score
04:21
First contact with customer
08:50
Customer satisfaction
06:21
Understanding customer engagement
03:51
Calculating customer lifetime value
06:06

Modeling Out a New Marketing Initiative

17 lectures
Our Recommendation
04:57
Introduction to modeling
04:18
Evaluating new ad channels
05:21
Calculating customer lifetime value
05:25
Modeling tips and best practices
05:00
Inputting our assumptions pt. I
04:44
Inputting our assumptions pt. II
05:44
Inputting our assumptions pt. III
05:00
Projecting ad revenue pt. I
04:19
Projecting ad revenue pt. II
08:07
Projecting organic follower revenue
04:51
Projecting expenses
05:46
Calculating net profit and breakeven
02:26
Understanding ROI
04:51
Calculating our returns
04:38
Creating a single-variable sensitivity table
05:11
Creating a multi-variable sensitivity table
06:22

Introduction to Dynamic Dashboards

4 lectures
Presenting key performance indicators (KPIs)
06:12
Creating spin buttons
06:15
Making our dashboard dynamic
05:35
Creating various charts and graphs
05:39

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