Introducing the Product Discovery Certification Course

If you’re a product manager, designer, engineer, or leader of one of these teams, you know that one of the most important—and challenging—parts of the job is deciding what to build.

This is because product teams are no longer only responsible for building functionality that meets users’ needs. They also have to deliver products and features that drive business outcomes—which all starts with effective product discovery.

Getting product discovery right is one of the best ways to drive outcomes like reducing risk in the development process, lowering support and R&D costs, and increasing revenue. But what does this look like in practice? Pendo and Mind the Product created the Product Discovery Certification Course to answer this exact question. 

The course dives deep into the fundamentals of product discovery, how to leverage data and AI at each stage, and why product discovery is key to product—and business—success. It’s also full of proven frameworks, best practices, and real-world examples that you can apply to your own strategy. Once you take the course and pass the exam, you’ll earn a “Product Discovery Certified” digital badge that you can add to your LinkedIn profile.

Ready to get started with the Product Discovery Certification Course? Sign up for free here.

What does effective product discovery look like?

The Product Discovery Certification Course is centered around a six-part framework for product discovery. Here’s a quick overview:

Part one is to define the outcome. Determining the business goal you’re looking to impact is key to driving meaningful product discovery. When possible, teams should try to identify this outcome from the onset.

Part two is to understand users’ problems. This is when you’ll shift into the mindset of your customers and spend time getting to know your users—and more specifically, their pain points.

Part three is to identify the problem to solve. Use the inputs you’ve collected to identify the most pressing problem that when solved, will impact the outcome you identified at the beginning of the process.

Part four is to explore possible solutions. Come together as a team to ideate on different ways to solve the problem with your product. This is where you get really creative and use innovation exercises like team brainstorming, mind mapping, and storyboarding.

Part five is to test and validate solutions. The goal of this step is to come away with the solution that will move on to development. And the best way to do this is to test different solutions with your customers and get their feedback directly. 

And part six is to close the loop. It might seem like deciding what to build and moving on to development is the final step, but it’s crucial that you close the loop—both with your customers and internal stakeholders.

The power of data-driven discovery

Another central theme throughout the course is the importance of data. When it comes to product discovery, quantitative and qualitative data not only helps you uncover users’ problems, it allows you to deeply understand those problems, determine which one to solve, and project—and measure—the impact of the solution.

In the course, we focus on four primary types of data that can be used for discovery: research, customer feedback, product analytics, and testing.

Product teams can (and should) also use AI to collect and analyze data more efficiently and on a larger scale. Here are three ways AI can help optimize the product discovery process:

1. AI can help accelerate product discovery
2. AI allows teams to include more inputs
3. AI makes product discovery more continuous

Let’s walk through an example of data- and AI-driven product discovery for each of the four types of data above.

Research: If you’re working to improve a certain feature, you can administer an in-app survey and only target users who have engaged with the feature in the last three months.

Customer feedback: Teams can leverage AI to analyze large amounts of feedback submissions and extract common pain points and themes—helping to speed up the process and enable faster decision making during discovery.

Product analytics: Use Funnels to measure how users move through a defined series of steps and identify where there is dropoff—signaling a user problem that needs to be addressed.

Testing: Leverage generative AI by providing prompts informed by customer and other data to quickly create a prototype that’s ready to validate.

Get a sneak peek of the course

Want to see what the Product Discovery Certification Course is like? Here’s a clip from Module 2, where Nichole Mace (SVP of Product and User Experience at Pendo) explores how discovery has evolved with the product development process and the rise of AI.

Here’s what else you can expect from the course:

• • 5 modules covering product discovery frameworks and strategies
  • 1.5 hours of engaging, instructor-led videos
  • Curriculum developed by product management and UX experts
  • Downloadable product discovery resources
  • Optional exam to check your knowledge and earn a badge

Ready to get certified? Sign up for the Product Discovery Certification Course for free here.