Data-Driven Marketing: Leveraging Big Data for Your Business

Learn how to build a robust data-driven marketing strategy and earn a letter of completion from Cornell University.
Instructed by eCornell
  • Lectures 32
  • Video 2 Hours
  • Skill level beginner level
  • Languages English
  • Includes Lifetime access
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    Available on iOS and Android

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Course Description

Learn about the tools and skills your organization needs to build successful big data-driven marketing campaigns. 

This course, taught by Professor Johannes Gehrke of the Johnson School of Management at Cornell University, introduces you to the world of big data and data scientists. You explore some of the ways that data can inform your marketing strategy and open the door to targeted, customer-aware advertising. Hands-on activities and downloadable templates help you bring the ideas back to your own organization and apply them immediately.

What are the requirements?

  • None

What am I going to get from this course?

  • Over 32 lectures and 1 hour of content!
  • Over 3 hours of activities, practical exercises, and quizzes!
  • Upon completing all modules, you will earn a letter of completion from Cornell University.

What is the target audience?

  • Anyone interested in exploring a career in data-driven marketing
  • Anyone looking to develop data-driven marketing projects and needing to understand the issues and skills needed for success.

Curriculum

Section 1: Course Introduction
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Big Data is revolutionizing business: Companies are using data to drive strategic decisions about product design, marketing, and customer acquisition. In addition, connections through social media are providing a unique insight into the customer base. This course, from the Johnson School of Management at Cornell University, teaches you the language and tools of data-driven marketing research on social media platforms, providing the guidance you need to ask the right questions and put the right people in place to manage your data stream.

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Meet the Cornell faculty member who teaches this course.

Section 2: Drive Your Social Marketing Efforts with Big Data
01:33

Before you can make effective use of big data in your social media marketing, you need to understand what constitutes social media, develop a plan for how you will grow your social media network, engage with your audience, and measure your results.

02:24

Social platforms provide a massive stream of data. Knowing your goals before you begin analyzing that data will help you focus on strategic patterns and behaviors. The major goals of your social media activity fall into two "conversion" categories: engagement and sales. Define the goals carefully and concretely in those two areas and then decide what metrics define success.

01:12

The value of your social media visitors lies in their "connectedness" to others. By introducing you into their networks via "following" or "liking" your content, people influence how others in their network engage with you. By knowing who your connectors are, and nurturing your relationship with them, you can increase the power and reach of your marketing efforts. These social media relationships are also assets for your company. Their lifetime value lies in the long term, as the company recoups initial acquisition costs and retains the income stream over many revenue periods. This sum of their discounted future revenues (derived from the present value of the anticipated future cash flows) is used to calculate the Customer Lifetime Value.

02:20

The large data stream from social media sites allows a company to identify, and calculate both the lifetime and network values, of the connectors in their networks. A careful analysis of the patterns in the data can inform decisions about both marketing campaigns and product development.

01:32

Big data plays a powerful role in marketing strategy because it allows you to test hypotheses about what makes a customer interaction successful. Campaign decisions are informed by measured results instead of guesses.

2 slides

 

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Section 3: Understand How Big Data Works
01:30

Using big data to inform your organization's social marketing efforts will be more effective the more your team understands the basics of data -- what is it, where does it come from, how is it stored, how is it used to provide the team with information for decision-making?

01:16

Most organizations have had "big data" for years, but it has usually been scattered among many databases, often with duplicated or contradictory records. Organizational structures, such as business units or divisions, have led to this partitioning of the organization's data and limited the insights that can be gained from looking at data from across the company.

01:53

Examining longitudinal data -- tracking customers, products etc. over time -- reveals patterns in consumption and needs that marketing departments can respond to strategically. Cumulative data stores require massive data storage and management systems, but allow marketers to leverage nuanced profiles of their target audiences.

04:31

The ability to capture transactions on many types of devices means that large amounts of data are being generated, stored and analyzed every minute. The millions and billions of data points can be analyzed at both micro and macro levels to give you a close understanding of not only your general audience, but of individual customers.

2 slides

 

2 slides

 

Section 4: Learn How Data Scientists Use Testing Data to Support Decision Making
02:15

Because big data comes in varied forms, the role of the data scientist in an organization should be filled by someone with both traditional data analysis skills and creative "hacking" abilities.

02:09

The vast amounts of data available to social marketing teams enables the rapid testing of customer engagement hypotheses. You can implement an idea and then quickly amass response data, allowing you to drop or amend the campaign.

01:56

Transaction data makes up the bulk of big data repositories. Customer purchases, knowledge base queries, file uploads - all of these transactions must be stored and then reflected accurately and immediately in the customer's browser.

01:52

The four asset properties of transactions - atomicity, consistency, isolation, and durability - determine the validity and usefulness of the data.

01:53

The data warehouse that stores the millions and billions of records used for detailed market analysis must be able to handle ad hoc, rapid requests. Traditional records storage and retrieval systems used for transaction processing are not designed to respond to this type of use.

03:14

Market basket analysis can provide deep insights into consumer needs and behaviors. By analyzing what customers purchase together, you can reveal linkages and profile similarities that can be used to inform your targeted marketing campaigns.

03:18

Quality decisions come from quality data. When transactions are created, data may be missing, recorded incorrectly, duplicated, corrupted or have any number of other issues occur. It is vital that the data manager verify the validity and reliability of the data prior to running algorithms against it to uncover patterns and meaningful customer behaviors.

05:00

One of the big challenges in dealing with big data is resolving the data deficiencies in ways that provide you with reliable information. There are a number of approaches that can be taken, incuding the use of artificial intelligence to predictively fill gaps and uncover hidden patterns.

2 slides

 

2 slides

 

Section 5: Introduce Your Marketing Effort to Big Data
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01:31

Gathering data from social media conversations can teach your marketing team what customers really care about, and how they think about your product. Real communications can replace focus groups and reveal new issues and approaches.

01:42

Your organization will need access to high-level, sophisticated tools to make use of the big data available to you. Fortunately, many of those tools are readily available in the cloud and through open source.

01:47

SQL-based databases are powerful when handling structured, tabular data. Unfortunately, big data is often messy and irregular, and therefore difficult to analyze using a structured language like SQL. The last few years have seen the emergence of data processors that, while they lack some of the data rigor of SQL, can handle the ambiguous, amorphous data gathered from social media sources.

2 slides

 

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Course Completion
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Instructor Biography

eCornell is a subsidiary of Cornell University that provides online professional and executive development to students around the world. We offer more than 30 award-winning professional certificate programs in a wide variety of disciplines. eCornell‘s unique approach to online learning combines the most effective elements of an Ivy League classroom with the flexibility of an online learning environment. eCornell courses are all developed by Cornell University faculty, and often include practical insights from other industry experts. All eCornell course content comes from top-rated programs with proven curricula.

Reviews

Average Rating
3.7
Details
  1. 5 Stars
    9
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    • Joel Alcantara

    Well,this class is a must for anyone that is getting into Big Data and it is a nice introduction. The class is very informative and highly suggested for anyone that is new t Big Data.

    http://www.ecornell.com/landing/udemy-data-driven-marketing/?ls=partner&of=LSM55VSU1&poi=Data-Driven%20Marketing

    • Rene Felder

    Bitte geben Sie den Titel Ihrer Bewertung hier ein

    Bitte geben Sie Ihre Bewertung hier ein

    • Meghan Vincent

    Great Intro Into Data-Driven Marketing

    Like other reviews have stated, it would be nice if there were demos of the high-priced programs that are discussed in this course (Hadoop, Oracle SQL, etc). That being said, I think this introductory course lays a good foundation for the value of understanding/utilizing data in marketing efforts.

    • Lalith Prasanth Kode

    Kick start your data-driven marketing

    This course serves as a first step into data-driven marketing world. Data-driven marketing exists from long back I think at least more than 5-10 years. All the advertising pamphlets that we receive in our mail box is the result of data-driven marketing which closely watches customer taste, buying habits, locality etc based on which ads or coupons are customized for that specific customer. Long way to go, to get deep knowledge. Cheers to eCornell!

    • Rick

    Too basic

    Glad I didn't pay full price. Too basic, low on info, too short given the subject. Can get more info for free on Utube.

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