This project allows you to create a Business Model Canvas with the Mural platform, an online tool for creating professional graphic visuals and working remotely. You will understand the various features of the platform and you will have all the basic skills to create a Business Model Canvas for your project with ease.

This course explores Meta Marketing Analytics Tools. You’ll learn how the advertising platform works and you’ll learn to create ads using Meta Ads Manager. Then, you’ll learn how Meta reports results and how you can customize the reports to match your business goals. You’ll also learn how you can use Meta experiments to evaluate the effectiveness of your advertising campaign. You’ll learn to optimize ads with A/B testing and you will explore how you can integrate data from Meta campaigns in marketing mix modeling. In this course, you’ll also find a summary of Meta’s recommended approach to data analysis. By the end of this course you will be able to: • Describe how an ad is created and delivered in Meta Ads Manager • Evaluate campaign results • Conduct an A/B Test • Evaluate advertising effectiveness with Conversion Lift Tests • Evaluate advertising effectiveness with Brand Lift tests • Choose the best approach to evaluating advertising effectiveness given a scenario • Explain how and when to apply Marketing Mix Modeling • Choose the best approach to optimizing your marketing mix given a scenario • Implement a full analysis process from the formulation of a hypothesis to recommending measurement solutions, performing an analysis, generating insights and presenting results and recommendations This course is for people who want to learn how to use Meta Ads Manager to conduct advertising effectiveness tests and evaluate their campaign results. Learners don't need marketing or data analysis experience, but should have basic internet navigation skills and be eager to participate. Ideally, learners have already completed course 1 (Marketing Analytics Foundation), course 2 (Introduction to Data Analytics), course 3 (Statistics for Marketing), and course 4 (Data Analytics Methods for Marketing) in this program.

In this course, you will learn how to create a successful inbound sales strategy by connecting with and earning the attention of your most promising leads. After learning the basics of inbound sales and the buyer’s journey, you will learn how to develop your buyer persona as well as find and prioritize active buyers. You’ll discover how to reach out to these leads by creating and using an outreach sequence. Next, you will use qualification frameworks to profile and identify the details of your prospects, including their CGP, TCI, and BA. The course will culminate in you applying your new knowledge to design a personalized sales presentation and a multi-step project for developing an inbound sales strategy. By the end of this course you will be able to: • Describe the importance of inbound sales • Develop an inbound sales strategy • Create your ideal customer profile • Identify and prioritize inbound leads • Use social selling • Enrich leads • Connect with inbound leads • Reach out to inbound leads via phone or email • Use trigger events and common connections to connect to leads • Create outreach sequence • Use technology to automate parts of the outreach • Identify a prospect's challenges, goals and plans • Understand a prospect's timeline, consequences and implications • Profile a prospect's budget and authority • Create a personalized sales presentation Throughout the course, you will complete exercises that allow you to apply the skills you have learned in a practical way, such as creating a customer profile, writing emails to prospects, brainstorming a list of questions for a sales call, and creating a sales presentation. You will compile your work and submit it as a project at the end of the course. This course is intended for anyone interested in jumpstarting their career in sales - whether you’re changing careers and looking for an entry-level role, or want to hone your skills in your current role as a sales representative. It does not require any background knowledge or experience to get started.

Pricing is one of the most important but least understood marketing decisions. Learn and practice concepts, techniques, and get to grips with the latest thinking on assessing and formulating pricing strategies. Analyze how firms attempt to capture value, as well as profits, in the revenues they earn. After this course, you will be able to contribute to the process of formulating pricing strategies for your own products and services, or those of your firm. This course has an additional focus on pricing dynamics and the reaction to and by competitors, taking a highly pragmatic approach and one that is directly applicable to your day-to-day professional life. Martin Boehm - IE Professor and Dean of the Business School with over 10 years experience - will guide you through four modules. We begin with the importance of pricing and how it ultimately can affect the bottom line. Then, we move on to methods to help you decide what is the optimal price for your product; and then price discrimination - should all your products follow the same pricing strategy or should you differentiate depending on the customer segment? Finally, we look at pricing psychology and how you can manipulate customers in order to drive the highest possible price for your product.

This is a hands-on, guided project on Predictive Analytics for Business with H2O in R. By the end of this project, you will be able apply machine learning and predictive analytics to solve a business problem, explain and describe automatic machine learning, perform automatic machine learning (AutoML) with H2O in R. We will take a data-driven approach to predict the success of bank telemarketing. H2O's AutoML automates the process of training and tuning a large selection of models, allowing the user to focus on other aspects of the data science and machine learning pipeline such as data pre-processing, feature engineering and model deployment. To successfully complete the project, we recommend that you have prior experience with programming in R, basic machine learning theory, and have trained ML models in R. We will not be exploring how any particular model works nor dive into the math behind them. Instead, we assume you have this foundational knowledge and want to learn to use H2O in R for predictive analytics. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

The world today is all but overwhelmed with internet usage and web pages of all shapes, colors, and designs. Have you ever wondered how to create such a wondrous thing? Creating a visually pleasing webpage, with links attached to certain aspects of the page is a genuine blend of artistic talent, and computer science. Here, you will learn to utilize a touch of both to create and save an image sliced and configured for use on the web!

In this project, you will learn how to make selections in GIMP using various selection tools. You will understand how selections can be used. You will learn how to make selections based on geometrical shapes, how to make selections using freehand tools, and how to make selections based on color. You will learn how to use up to six different tools and when to use each one. As you learn how to use these tools, you will create a digital poster displaying your selections. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

AI is everywhere! By harnessing the power of Artificial Intelligence, businesses and marketers have amazing growth potential, and the opportunities to enhance marketing with AI are always expanding. But how can businesses use AI tools to drive their success and gain sustainable competitive advantages? What are the challenges faced by businesses as they implement AI into their marketing strategies? In this course, developed at the Darden School of Business at the University of Virginia, and delivered by Professor of Business Administration Raj Venkatesan, you will explore an important frontier of digital transformation in marketing. You will examine three key forces that enable AI in marketing strategies - Algorithms, Networks, and Data - and gain a deeper understanding of how businesses in a wide variety of industries can get the most out of this exciting technology. You will see real world examples of successful companies like Ford, Netflix, and the Washington Post using AI to take on the competition in new and creative ways, and hear from experts about how AI is shaping the present and the future in their respective industries. You can learn more about Raj by following his posts on Twitter (@rajkumarvenk) and on LinkedIn: https://www.linkedin.com/in/education-marketing.

In the world of business managing projects well is essential. Tableau is a powerful data visualization tool that has many applications in a variety of business scenarios. One frequently used tool to visualize time and movement through projects is something called a Gantt Chart. Using Tableau to create a Gantt chart has the added benefit of easy connection with other data sets being collected by this tool. Learning how to take advantage of this powerful business tool to display time-sensitive data is a high-demand skill. In this project, learners will learn how to start accounts in Tableau, how to prepare data to be used in a Gantt Chart, and how to modify Gantt charts to answer business questions. Learners will also learn how to present their findings for a variety of business scenarios. This course will enable users at all levels of business to answer business questions with powerful data visualizations.