Building data-driven personas
Customer personas can really drive your business forward - if you base them on data, not fluff and subjective ideation.
This course will teach you to combine qualitative research with quantitative methods to build truly representative personas in a research-based method that is both fast and rigorous.
In just 8 sessions, you'll be able to...
- Build truly representative and effective personas based on research.
- Quantitatively segment your customer or user base.
- Conduct successful interviews to integrate qualitative data into your personas.
Learn how to build strong personas and actually put them to use.
In this course you'll learn to identify elements of good personas, and provide you with actionable ways to incorporate them in your organization.
The course will also outline the difference between two different approaches in building personas—data-driven vs. hypothesis-driven. You will learn the advantages and disadvantages of each approach and understand which circumstances make one method more appropriate than the other. You'll also learn to optimally combine qualitative research with quantitative data.
Lastly, you will learn how to package and market your personas in your organization.
This course is right for you if you...
- You're involved in any customer or user centric effort in a medium to large organization.
- You own a startup of any kind, with or without existing customer or user base.
- You're a UX designer or UX researcher looking to step up their strategy game.
This course is NOT for you if...
- You're the user of your product (hint: this is an extremely rare circumstance).
- You already have your bullet-proof method to create personas.
- Your company's monetization strategy exclusively depends on technology advancement.
Skills you should have before taking this course:
- Domain expertise on your specific industry (e.g., Marketing, UX Design, etc.)
- Basic knowledge on how to use an electronic spreadsheet (i.e., data handling and graphs).
- Basic statistics understanding (probability, descriptive statistics such as mean and mode, data summary and visualization)is ideal, but not completely necessary.
About your instructor:
Stefania is a UX Data Scientist, Strategist & Evangelist. She is director of user experience at Pearson. Before then, she was Sr. Quantitative UX Researcher at Express Scripts and Vice President of Research at Vast, a medium size startup that raised $14 million last year. Previously, she worked as a Statistician and Human Factors Engineer at the Federal Aviation Administration and as a researcher at University of Illinois at Urbana-Champaign. She also served as a consultant for Fortune 500 companies, including Southwest Airlines, USAA and Google.
She obtained a doctorate degree in Cognitive Psychology from Sapienza University of Rome in Italy. She loves teaching, spending time with her family, cooking delicious Italian food and playing board games. She also loves music. Fun fact: her graduate school job was at a record store specialized in rare vinyl. She was also a freelance contributor of an Italian music magazine.
Classes are self-paced and entirely online
Building data-driven personas
This introductory lecture will guide the user through some general, but important considerations about the use of personas in an organization, and will present a few real world use cases. What are they? How do you build them? And why?
Elements of good user personas
The lecture will explain what elements need to be included in personas, how to make personas actionable, and how to maximize personas effectiveness by adapting their elements to the context in which they'll be used.
Hypothesis-driven vs data-driven personas
The third lecture will present two approaches in the creation of user personas, and will rationalize advantages and disadvantages of each approach.
Quantitative, data driven user segmentation
This lecture will introduce you to the data-driven, quantitative method of creating personas.
Qualitative validation of user segments
This lecture will introduce you to the process of creating personas through qualitative techniques.
Examples of personas for different industries
This lecture will follow up on Class 2, by presenting realistic use cases of personas for different industries. The lecture will explain which elements and data point are most useful for three different types of personas: customer personas, user personas, and marketing personas.
Put it together and sell it
The process of packaging the persona is important to ensure that personas will be used in the organization. I'll show how to package the personas to ensure effectiveness in the evangelization process.
Practical examples and wrap-up
We'll examine several examples of student submitted data, and try to imagine what kind of personas the data could generate.
You will also get introductory
In addition to classes, you’ll get access to snack-sized video lessons to bring you up to speed before you begin the course.
The Fast & Rigorous framework consists of three steps: collect quantitative data, statistical clustering, build archetypes. This lesson serves as on overview of what each step entails, and explains what skills and data are necessary to bring it to execution.
The first step in Eric & Stefania’s approach is to begin collecting quantitative data. In this lesson, you’ll learn how to write valuable survey questions as well as a few presentation strategies to minimize confusion.
Learn to construct a survey in Google Forms and setup your results for smooth interpretation in Steps 2 & 3.
Learn to setup a task on M Turk so you can recruit respondents. In this lesson, Stefania will walk you through setup and also give a few tips for verifying that your participants are attentive.
Learn a few tips for ensuring your data is trustworthy and and get a preview of the second half of the course, which will focus on analyzing the data and building archetypes.
You’ve collected your quantitative data, and now it’s time to simplify your data set. This is done by highlighting a few underlying issues or factors which influence respondents in discernible patterns.
By simplifying your data into a few key factors, you will understand the theoretical relationship between questions, and also discern how individual respondents assigned weight to different factors.
Now that you’ve identified factors and determined how much weight different respondents have assigned each one, it’s time to identify clusters of like-minded users. In this lesson you will learn the general theory behind clustering.
Now that you understand the theory behind drawing clusters from factors, Eric will talk you through the procedure, recommend some packages, and explain best practices when preparing your data for the analyst.
Now that you’ve surveyed your users, identified factors of importance, and calculated clusters it’s time to pull it all together. In this lesson Stefania will show examples from the car buying survey to illustrate different methods for visualizing your data into a persona that different departments can share.
Visualizing quantitative data is a powerful tool to use when creating the living document that represents your personas. In this lesson, you’ll learn how to nail this important last step.
How long can you expect to refer to these personas? How should you archive your data, performance of the personas, and ideas for future iterations? This lesson will answer these questions theoretically.
Show Off Your New Skills: Get a Certificate of Completion
Once you have completed the course, pass a test to earn a CXL certification.
Add it to your resume, your LinkedIn profile or just get that well-earned raise you’ve been waiting for.
- 8 in-depth classes with Stefania
- 50 min of introductory videos to get you up to speed before you start the course
- Additional resources to further your learning
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Teams of 2 and more get a 25% discount during checkout.
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