As data practitioners and product managers strive to gain actionable insights with the data at hand, it’s important for both roles to work together.
The latest webinar featured Nick Kadochnikov, Head of Data Science at ShipBob, and Peter Bradford, Pragmatic Institute’s Director of Enterprise Transformation, as they discuss the relationship between data science and product management. They also discuss how cross-functional team collaboration can help organizations stay ahead of the competition.
In this webinar hosted by Pragmatic’s Director of Community Georgina Donahue, discover:
- The intersection between data science and product management
- How data can be better integrated into the product development cycle
- Decision making models based on insights from data practitioners
- How to create strong partnerships between data practitioners and product managers
Below are the key takeaways from the conversation, or listen to the full webinar.
Cross-functional team collaboration is important for organizations to move forward and drive data-driven decisions. Business leaders from different organizations are applying the data insights to consumer behavior for a more tailored approach.
Here are three different examples of well-known companies driven by the application of data science:
- USAA SafePilot is one of the many insurance programs that offer users insurance premium rebates for safe driving, as determined by mobile telematics.
- Netflix’s recommendation engine filters thousands of titles using recommendation clusters based on user preferences. 80% of Netflix viewer activity is driven by personalized recommendations, contributing to a 93% retention rate. Amazon Prime Video uses similar technologies.
- Airbnb leverages A/B testing image recognition and natural language processing to determine which photos work best, to test ranking algorithms and understand user’s feelings behind reviews.
Data science can play a critical part in decision making and can be used in service of product management activities to produce more effective strategies.
Additionally, dashboards and effective visualization are required to deliver actionable insights to business users and leaders.
Applying Data Science to Product Development
Product managers and data scientists are birds with different feathers, but clearly there’s a lot of value in the collaboration. Data science can influence businesses in many ways, so why isn’t it more often part of the innovation process?
Product leaders continue to use insights to improve designs, delivery and adoption, but they could do more. Here are some examples of how product managers can better integrate data science:
- Develop deeper insights into the user journey
- Improve the design and identify where users get stuck
- Drive engagement and adoption, especially when integrated with digital software
Leveraging Data Science for Business Decisions
Business leaders normally use data science to reduce risks and wastes with products. Business functions at all levels are using data science in their roles.
Below are a few examples of how different team members can leverage data science.
There’s a new path to improve product innovations, however, it requires movement from data practitioners and product managers to function correctly and improve. Therefore, product managers should become data fluent, as well as data scientists should improve their business sense.
In addition, data can be so rich and driven by market needs, it can help business leaders make decisions. Moreover, it can help organizations collect consumer data to get a better understanding of the users’ pain points. Inviting data scientists to the next product meeting will help them understand and capture better insights into what the business is trying to solve.
Resources to Continue Learning
Data Science for Business Leaders
The world of data is moving fast. This course will show you how to partner with data professionals to uncover business value, make informed decisions and solve problems.
Business-Driven Data Analysis
Deliver critical insights that power business strategy. This course teaches a proven and repeatable approach you can leverage across data projects to deliver timely analysis with actionable insights.
