A hot topic in Product Management for a long time has been data science. Why should a Product Manager pay attention to it and what is important to know about data?
For one thing, understanding analytics will help you work better with the data scientists on your team, much like having a bit of tech knowledge will help you communicate with engineers. But, what else do you need it for?
Data Scientist on Supply Growth at Airbnb
Dr. Theresa Johnson is a data scientist on Supply Growth at Airbnb, a two-sided marketplace for travel. She also stepped into product management for her team and recently shipped Paid Photography globally. Dr. Johnson came to data science with a Ph.D. in Aeronautics and Astronautics from Stanford University.
She currently serves as a founding board member of Street Code Academy, a non-profit dedicated to connecting culture, community, and technology in East Palo Alto. She also serves on the special panel on data science interviewing and is a co-founding member of Stddev (Standard Deviation), Airbnb’s employee resource group for Underrepresented Minorities in technical fields.
Theresa is passionate about extending technology access for everyone and finding mission-driven companies that can have an outsized impact on the world.
Intro to Data Science
Understanding how to access and interpret data is critical for the modern Product Manager. In this session, a data scientist at Airbnb taught the basics in data-informed thinking as well as resources and tools for SQL, Python, and R. She discussed how you can up-level your skills in interpreting A/B tests, incrementally, and when and why to use Machine Learning techniques.
- Data science means “taking sets of information from your customer and product channels online and offline and organizing it in a way that gives insight into the business.”
- Expect a data scientist to have technical as well as business skills.
- Data is about people, not numbers. “Data is the voice of your customer.”
- “They say you should only optimize what you can measure. The truth is your only measure what you can log.”
- Data doesn’t solve everything!
- Challenges that Product Managers face with Data Scientists: Who are they? What to do with them? How can I do this myself? How do I use the information they give me to guide the product?
- At the beginning of a company’s life, data scientists work more like as consultants.
- Data scientists work with cross-functional teams; engineers, designers, the user experience research team, other data scientists, etc.
- “Data scientists are only as impactful as the context they have for the set of problems they’re meant to solve.”
- Airbnb uses machine learning at nearly every stage of the user experience process; search, pricing, booking, risk, etc.
- Airbnb has hundreds of metrics to follow constantly and hundreds of experiments running at the same time.
Data scientists can bring tons of useful information to the Product Manager, and the Product Manager needs to know how to use that information to benefit the product. You’re making products for customers, and therefore listening to them, and gathering information about them is how you can fulfill their needs the best.