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Certification in Marketing Analytics

Name: Certification in Marketing Analytics
Rating: 3.9 (69 reviews)

Learn Marketing Analytics for data representation, processing and creating dashboards for marketing insights

Created byHuman and Emotion: CHRMI

Last updated 8/2024

English

What you'll learn

The course covers marketing analytics, involving data representation and feature engineering, which are crucial for understanding and manipulating marketing d
You will delve into data classification methods, essential for categorizing and organizing marketing patterns.
The course includes advanced topics and practical applications in data visualization, such as interactive dashboards and visual analytics,
You will explore data preprocessing and analysis techniques tailored for marketing data, emphasizing their roles in understanding and manipulating marketing
The course covers creating effective visualizations and crafting compelling narratives with marketing data, along with interactive dashboards and analytics
Learn about marketing analytics techniques tailored for marketing analytics, including methods for creating impactful visual representations of marketing data
Cover data-driven storytelling and dashboard design specific to marketing insights, emphasizing approaches to generate insightful visuals
Explore advanced topics in marketing analytics, including cutting-edge research and applications relevant to marketing analytics.
Explore applications of marketing analytics, examining its role across different industries and investigating the latest advancements
This training will be valuable if your job involves applying marketing analytics techniques in practical scenarios.

Course content

11 sections • 52 lectures • 7h 57m total length

Introduction and Study Plan4:42
Online Marketing Analytics2:53
Introduction to Marketing Analytics4:45
Understanding Marketing Analytics6:49
Understand how marketing analytics gathers data from multiple sources, integrates it into a unified view, applies statistical and machine learning methods, and translates insights into optimized campaigns and KPIs.
Key Components of Marketing Analytics6:47
Discover the key components of marketing analytics, including customer analytics, profiling, segmentation, journey mapping, sentiment analysis, cross-channel evaluation, website analytics, and attribution to optimize ROI.
Benefits of Marketing Analytics5:58
Explore how marketing analytics enable data-driven decision making with evidence-based insights to optimize spend, target with personalization, and enhance customer experience for a competitive edge.
Continuation of Benefits of Marketing Analytics3:46

Data Collection and Sources for Marketing Analytics7:45
Data Collection and Sources for Marketing Analytics210:41
Explore platform analytics and social listening for engagement, reach, and audience insights. Track email campaigns with open rates, click-through rates, bounce rates, and unsubscribe rates to optimize targeting.
Data Collection and Sources for Marketing Analytics35:12
Data Collection and Sources for Marketing Analytics47:00
Data Collection and Sources for Marketing Analytics53:17

Descriptive Analytics for Marketing Insights8:00
Descriptive Analytics for Marketing Insights27:48
Explore demographic analysis and behavioral analysis to segment customers by age, gender, income, and location, and apply RFM, attribution models, and A/B testing to optimize marketing campaigns and channel ROI.
Descriptive Analytics for Marketing Insights36:09
Descriptive Analytics for Marketing Insights411:23
Descriptive Analytics for Marketing Insights55:25

Customer Segmentation and Targeting16:28
Customer Segmentation and Targeting110:29
Explore demographic, psychographic, behavioral, and firmographic segmentation, and apply cluster, factor, and decision-tree analyses (including k-means) for precise marketing targeting.
Customer Segmentation and Targeting211:01
Customer Segmentation and Targeting38:09
Explore how personalization and customization craft segment-specific messages, tailored product offerings, and dynamic content across channels, using ab testing and iterative optimization to boost engagement and conversions.
Customer Segmentation and Targeting46:06

Predictive Analytics for Customer Behavior Forecasting9:26
Predictive Analytics for Customer Behavior Forecasting112:30
Develop data collection, cleaning, and integration across purchases, website behavior, demographics, and social engagement, then perform feature selection and engineering for predictive customer behavior.
Predictive Analytics for Customer Behavior Forecasting214:26
Predictive Analytics for Customer Behavior Forecasting39:07
Forecast future customer behavior with predictive models across short, medium, and long horizons; perform scenario analyses, interpret results, and deploy real-time insights to personalize marketing and optimize campaigns.
Predictive Analytics for Customer Behavior Forecasting410:05

Campaign Analytics and ROI Measurement9:47
Campaign Analytics and ROI Measurement17:49
Apply attribution models, including first click, last click, linear, and time decay, to attribute conversions to campaigns, using UTM parameters, tracking pixels, and conversation tags for ROI insights.
Campaign Analytics and ROI Measurement216:40
Analyze campaign metrics and KPIs across channels to identify top performing campaigns, channels, and creatives, allocate budget efficiently, and maximize ROI via marketing mix modeling, regression analysis, and data-driven segmentation.
Campaign Analytics and ROI Measurement312:37
Campaign Analytics and ROI Measurement415:10

Social media Analytics and Engagement Measurement19:11
Social media Analytics and Engagement Measurement110:35
Social media Analytics and Engagement Measurement214:43
Social media Analytics and Engagement Measurement310:04
Social media Analytics and Engagement Measurement48:21
Create dashboard and report to visualize social media analytics data, train and insight, and share report with stakeholders, decision makers and marketing teams to inform strategy, decision making and optimization.

Customer Journey Mapping and Attribution Modeling9:45
Explore customer journey mapping across touchpoints and channels and apply attribution modeling to allocate credit, optimize the marketing mix, and improve ROI.
Customer Journey Mapping6:45
Collect data from analytics, CRM, sales records, and feedback to map touchpoints across awareness to post-purchase. Create personas and analyze behavior to enable data-driven decisions and improve the journey.
Attribution Modeling8:24
Attribution Modeling110:26
Analyze the customer journey and attribution modeling to identify influential touchpoints, optimize channel mix, and allocate budget for maximum roi through experimentation, including a/b testing, and data-driven strategy.

Requirements

You should have an interest in marketing analytics and its applications.
An interest in data representation and feature engineering for marketing data. Data classification methods for marketing patterns.
Be interested in gaining knowledge of data-driven storytelling and analytics techniques specific to marketing analytics
Have an interest in understanding marketing analytics applications and future trends in marketing analytics

Description

Description

Take the next step in your career as a marketing analytics professional! Whether you’re an up-and-coming marketing analytics specialist, an experienced data analyst focusing on marketing insights, an aspiring data scientist specializing in marketing data analysis, or a budding expert in data-driven insights, this course is an opportunity to sharpen your data processing and analytics capabilities specific to marketing insights, increase your efficiency for professional growth, and make a positive and lasting impact in the field of marketing analytics.

With this course as your guide, you learn how to:

● All the fundamental functions and skills required for marketing analytics.

● Transform knowledge of marketing analytics applications and techniques, data representation and feature engineering for marketing data, data analysis and preprocessing methods tailored to marketing insights, and techniques specific to marketing data narratives.

● Get access to recommended templates and formats for details related to marketing analytics techniques.

● Learn from informative case studies, gaining insights into marketing analytics techniques for various scenarios. Understand how marketing insights impact advancements in data-driven insights, with practical forms and frameworks.

The Frameworks of the Course

Engaging video lectures, case studies, assessments, downloadable resources, and interactive exercises. This course is designed to explore the field of marketing analytics, covering various chapters and units. You'll delve into data representation and feature engineering for marketing data, marketing analytics techniques, interactive dashboards and visual analytics tailored to marketing insights, data preprocessing, marketing data analysis, dashboard design for marketing analytics, advanced topics in marketing analytics, and future trends.

The socio-cultural environment module using marketing analytics techniques delves into sentiment analysis and opinion mining, data-driven analysis, and interactive insights in the context of India's socio-cultural landscape. It also applies marketing analytics to explore data preprocessing and analysis, interactive dashboards, visual analytics, and advanced topics in marketing analytics. You'll gain insight into data-driven analysis of sentiment and opinion mining, interactive insights, and marketing analytics-based insights into applications and future trends, along with a capstone project in marketing analytics.

The course includes multiple global marketing analytics projects, resources like formats, templates, worksheets, reading materials, quizzes, self-assessment, case studies, and assignments to nurture and upgrade your global marketing analytics knowledge in detail.

Course Content:

Part 1

Introduction and Study Plan

● Introduction and know your Instructor

● Study Plan and Structure of the Course

1. Introduction to Marketing Analytics

1.1.1 Introduction to Marketing Analytics

1.1.2 Understanding Marketing Analytics

1.1.3 Key Components of Marketing Analytics

1.1.4 Benefits of Marketing Analytics

1.1.4 Continuation of Benefits of Marketing Analytics

2. Data Collection and Sources for Marketing Analytics

2.1.1 Data Collection and Sources for Marketing Analytics

2.1.1 Continuation of Data Collection and Sources for Marketing Analytics

3. Descriptive Analytics for Marketing Insights

3.1.1 Descriptive Analytics for Marketing Insights

3.1.1 Continuation of Descriptive Analytics for Marketing Insights

3.1.1 Continuation of Descriptive Analytics for Marketing Analytics

4. Customer Segmentation and Targeting

4.1.1 Customer Segmentation and Targeting

4.1.1 Continuation of Customer Segmentation and Targeting

5. Predictive Analytics for Customer Behavior Forecasting

5.1.1 Predictive Analytics for Customer Behavior Forecasting

5.1.1 Continuation of Predictive Analytics for Customer Behavior Forecasting

6. Campaign Analytics and ROI Measurement

6.1.1 Campaign Analytics and ROI Measurement

6.1.1 Continuation of Campaign Analytics and ROI Measurement

6.1.1 Continuation of Analytics and ROI Measurement

7. Social Media Analytics and Engagement Measurement

7.1.1 Social media Analytics and Engagement Measurement

7.1.1 Continuation of Social media Analytics and Engagement Measurement

7.11 Continuation of Social media Analytics and Engagement Measurement

7.1.1 Continuation of Social media Analytics and Engagement Measurement

8. Customer Journey Mapping and Attribution Modeling

8.1.1 Customer Journey Mapping and Attribution Modeling

8.1.2 Customer Journey Mapping

8.1.3 Attribution Modeling

8.1.3 Continuation of Attribution Modeling

9. A/B Testing and Experimentation in Marketing

9.1.1 AB Testing and Experimentation in Marketing

9.1.1 Continuation of AB Testing and Experimentation in Marketing

10. Future Trends in Behavioral Analytics

10.1.1 Case Studies and Real World Applications

10.1.1 Continuation of Case Studies and Real World Applications

10.1.7 Certification

Part 3

Assignments

Who this course is for:

Professionals with a deep understanding of marketing analytics applications, advanced topics in marketing analytics, and a desire to excel in the field of visual data processing and insights specific to marketing data.
New professionals aiming for success in marketing analytics applications and the economic environment of data-driven insights in business.
Existing executive board directors and managing directors who are seeking greater engagement and innovation from their teams and organizations in the realm of marketing analytics and data-driven insights technology.

Certification in Marketing Analytics

What you'll learn

Explore related topics

Course content

1. Introduction to Marketing Analytics7 lectures • 36min

2. Data Collection and Sources for Marketing Analytics5 lectures • 34min

3. Descriptive Analytics for Marketing Insights5 lectures • 39min

4. Customer Segmentation and Targeting5 lectures • 52min

5. Predictive Analytics for Customer Behavior Forecasting5 lectures • 56min

6. Campaign Analytics and ROI Measurement5 lectures • 1hr 2min

7. Social Media Analytics and Engagement Measurement5 lectures • 1hr 3min

8. Customer Journey Mapping and Attribution Modeling4 lectures • 35min

9. A/B Testing and Experimentation in Marketing4 lectures • 53min

10. Future Trends in Behavioral Analytics6 lectures • 46min

Requirements

Description

Who this course is for: