Your One Page For Data Science in Product Management

A Guide to How Product Managers & Data Scientists Can Collaborate

Author

Joy Chatterjee
September 21, 2023

This Thursday. One Page.

  • Who is this one-pager for?

  • How can Data Science & Product Management collaborate?

  • Case Studies

    • AirBnB

    • Uber

    • Duolingo

  • How can you learn more?

  • Quote of the week!

READ TIME → 8 minutes

Welcome back to another edition of our newsletter!

As promised, here is your one-pager.

If you've ever wondered how a Product Manager and a Data Scientist can collaborate to create amazing products, today’s post is for you!

In a world where terms like “data-driven” and “data-informed” are becoming party lines, understanding how to actually adopt these practices can be a foggy truth.

So today we share how this “collaboration” between Product Managers (PMs) and Data Scientists looks like, including real-life case studies explaining how we can work together to achieve a common goal - product growth.

Who is this one-pager for?

🌟 Product Managers, Product Owners: Learn how data science can help you make more informed decisions, iterate on your product faster, and achieve that elusive product-market fit.

🧠 Data Scientists: Understand how your skillset can be a crucial asset in the product development lifecycle, enabling the creation of features that truly resonate with users.

📈 Business Development & Sales: You often serve as the gateway to external parties and clients. Get a grip on how the data science outputs feed into product features, helping you understand your product / service offering and driving more sales!

💡Entrepreneurs and Start-up Founders: Acquire insights into how a strong synergy between product management and data science can set your business up for monumental success.

Think you know someone who might be in this list, but has not seen this one-pager? Well, you’re one click away from sharing it with them!

How can Data Science and Product Management collaborate?

🤝 The collaboration between Product Managers (PMs) and Data Scientists often involves a series of interrelated steps that integrate both technical and business perspectives.

Below is a deeper dive into how they work in tandem:

Ideation and Goal Setting

  • Product Managers: Identify the problem space or an opportunity for a new feature based on market research and user feedback.

  • Data Scientists: Discuss the feasibility of solving this problem through data-driven methods, sometimes proposing initial hypotheses.

Data Collection and Preliminary Analysis

  • Data Scientists: Outline the data requirements and start collecting the data, often collaborating with Data Engineers.

  • Product Managers: Assist by providing context, such as which user interactions could be most relevant or which market metrics matter the most.

Model Development

  • Data Scientists: Begin to build, train, and test models based on the initial hypotheses. This could involve machine learning algorithms, statistical models, or A/B testing frameworks.

  • Product Managers: Monitor these developments closely to ensure that the models align with the business objectives and user needs.

Model Interpretation

  • Data Scientists: Once the model is built, they interpret the results in technical terms.

  • Product Managers: Translate these technical outcomes into actionable business insights. PMs use their ability to communicate complex ideas simply to bridge the gap between technical and non-technical stakeholders.

Implementation

  • Product Managers: Define the requirements for implementing the model into a live product environment.

  • Data Scientists: Work with developers and engineers to deploy the model, often also creating APIs for real-time analysis.

Monitoring and Iteration

  • Data Scientists: Once the feature is live, monitor its performance, and gather new data for ongoing optimization.

  • Product Managers: Evaluate whether the feature achieves the initial objectives and decide on next steps, which could be further refinement, scaling, or sometimes even rollback.

By having a common language, iterative feedback loops, and aligned goals, Product Managers and Data Scientists create a synergy that is increasingly becoming the backbone of successful, data-driven companies.

Case Studies

The best way to learn and understand any concept is to look at real-life examples. This helps us relate to how it was formed and how it adds value to our lives today.

So here we go!

AIRBNB’s DYNAMIC PRICING MODEL

Role of Product Management: Product wanted to help hosts price their listings competitively and increase their chances of getting booked.

Role of Data Science: Data Scientists developed a dynamic pricing model based on multiple factors like location, amenities, seasonality, and competitor pricing. Hosts now had a "suggested price," which improved booking rates by up to 13%.

Next, let’s look at a feature every one is probably using quite often.

UBER’S RIDE ETA PREDICTIONS

Role of Product Management: One of the key value propositions of Uber is its ability to accurately predict how long it will take for a ride to arrive.

Role of Data Science: Data Scientists used historical data, real-time traffic, and other variables to predict accurate ETAs for rides. This increased customer satisfaction and optimized driver routes

And finally, ¿hablas español?

DUOLINGO’s LEARNING PATH

Role of Product Management: Product wanted to offer personalized learning experiences to keep users engaged and facilitate faster language acquisition.

Role of Data Science: By using machine learning models to assess the performance of each user on various exercises, Duolingo could adapt the curriculum in real-time, offering a more customized and efficient learning path.

How can you learn more?

Hungry for more? If you're interested in diving deeper into how your data scientists and product managers can get together, here are some resources that could be of interest:

  1. Books:

  2. Articles:

  3. Online Courses:

❝

Your most unhappy customers are
your greatest source of learning.

Bill Gates

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