It has been an honor and a pleasure to be your instructor this semester. I want to thank you for your hard work and attention. Each of you has taught me something about being a better teacher, and you’ve inspired me to continue improving this course for future students. In this post, I share some reflections on the past 13 weeks and some suggestions and words of encouragement for your professional pursuits.
What Have You Learned?
If someone asked you, during a job interview or random conversation, what you learned in this course, what would you say? Here are some ways to answer that question:
- You learned to apply experimental methods and statistical tools to marketing challenges across web, mobile app, email and direct mail channels.
- You learned that great companies aren’t guided by intuition or genius alone – in fact, they rely heavily on experimentation to understand their customers and maximize revenue.
- You learned that companies like Netflix, LinkedIn, Google and Microsoft (among many others) put a great deal of time and resources into creating experiments that produce robust, statistically sound results.
- You learned that marketing experimentation requires deep thinking and skillful analysis. For example:
- At LinkedIn, a team of marketers, statisticians and mathematicians have worked hard to identify selection bias and network effects in their experimental results. They have also created quasi-experiments in their mobile app using the Staged Rollout feature in Google Android.
- At Netflix, the experimentation team has also developed quasi-experimentation methods for situations where A/B testing is just not possible. They use techniques like clustering, among others, to create test conditions similar those in A/B testing.
- At Google and Microsoft, hundreds of tests are occurring at any given moment to help these organizations maximize revenue from their search engines, and an elaborate experimental architecture is part of the culture of those companies.
- At an educational institution in Europe, experimenters have used fractional factorial experimental design (a form of multivariate testing) to determine which variables had the largest effect on email click-through rates, and to understand the interactions between variables.
- You learned to evaluate A/B test results using hypothesis testing and to create linear regression models to explain the relationship between a success metric and an independent variable.
- You learned the relationship between customer retention, marketing spending and revenue through the Customer Lifetime Value equation, and you’ve seen how CLV can guide decisions about success metrics.
Did I miss anything? 😉
I recognize that many of the skills taught in this class are forgotten if they are not used and applied regularly. You can always refer to the notes or slides from this class to refresh your memory. I would also recommend the following blogs:
- MARKETING: Loyalty 360, Occam’s Razor, Optimizely (to name just a few)
- STATISTICS: XL Stat tutorials, Minitab blog
- DATA SCIENCE: Check out this list.
If you do intend on pursuing a career in marketing, I would invite you to reflect on how this course has helped you determine what kind of marketer you want to be. There are so many avenues to explore: branding, content, product development, channel optimization, data science, or overall program management…to name just a few.
But maybe you’re not sure what you want to do yet, and this course has not helped you figure that out. If that is the case, then here is a suggestion: Think about a business problem that you can help solve.
How do you do this? Start by looking at your own experiences. In your daily life, you probably encounter potential business opportunities without recognizing them as such. Any time you experience some inconvenience or annoyance, you can think about it in business terms. Do this by filling in the blanks in the following sentences with business-oriented answers:
- It would be so much more efficient/less wasteful if ________________.
- ____________ would be so much easier/better if _________________.
- My life would be easier if _________________.
Here are some examples based on real-life companies that solved an ordinary problem with an innovative idea:
- It would be so much more efficient if people could rent empty homes for short trips, instead of staying at big, expensive hotels. (Airbnb)
- Getting around would be so much easier if I could have a car pick me up anywhere, anytime. (Uber)
- My life would be easier if I could just rent clothes, rather than buy them. (Rent the Runway)
See how powerful this can be? Once you’ve filled in those blanks, your next step is to consider how marketing can help solve the problems you care about. What do you, as a marketer or business person, bring to the table?
Seeking Your Feedback…
Finally, I would like to ask a favor of you: I am developing a course that helps students “design” their careers using the principles of innovation and value creation. If you are interested, please read the syllabus, and if you think this course would be valuable, send me an email at [email protected], post a comment in Forums, or leave a comment on Slideshare here. Something as simple as “I would be interested in taking a course like this” would be helpful.
I will use your feedback to show why the class is worth teaching as a non-credit offering. The syllabus can be found at www.sandranoonan.com/syllabus-designing-innovation-centered-career.
I am always happy to hear from former students, and I’d love to know where you end up after graduation.
Feel free to keep in touch via the following channels:
Email: sandramarienoonan [at] gmail [dot] com
To your success,