How to Run Product Discovery: Process, Frameworks, and Best Practices

The year is 2001. You wake up, brush your teeth, look out the window.

It's beautiful outside.

"I need to feel the wind in my hair." You whisper to yourself.

You're thinking you want to scoot down the street at about 20mph.

You want your scooter to move only when you lean forward. It's intuitive but also feels like you're falling.

You're excited.

You want it to feel like a scooter, just dorkier.

You want to pay $5,000 for it.

This sounds ridiculous right?

Segway would disagree.

But as we know now, despite much hype and media attention prior to its release in 2001, the Segway failed to meet sales expectations and was widely regarded as a commercial failure.

Some folks might call this unlucky, but us product managers? We call it bad product discovery.

What is product discovery?

Product Discovery is the process of identifying and validating a product idea that solves a real problem for a target audience. It is an essential phase in the product development process, where the team researches and tests various ideas to determine which ones are worth pursuing.

The Product Discovery process typically involves several stages, such as understanding the problem, ideation, prioritization, prototyping, and testing. During these stages, the team conducts user research, collects feedback, generates ideas, and tests prototypes to validate assumptions and refine the product concept.

The goal of Product Discovery is to create a product that meets the needs and desires of the target audience, while also providing a viable business opportunity for the company. By following a structured approach to Product Discovery, companies can reduce the risk of developing products that fail in the market and increase the chances of building successful products that deliver value to users and the business.

Product discovery helps teams build the right thing

The Segway was marketed as a solution to the "last mile" problem, but it didn't solve any real transportation problems. To make matters worse, it's virtually impossible to look cool riding one (I'm still coming to peace with that Segway tour in Savannah, GA).

A more rigorous product discovery process could have helped identify a lower price point and additional features that could have made the Segway more attractive to potential buyers. By investing in product discovery, companies can reduce the risk of developing unsuccessful products and increase the chances of building successful products that deliver value to users and the business.

You can read 10 different posts on product discovery and get 10 different methods. The important piece to understand is your goal: to identify an opportunity to delight customers and validate that your idea is the one to do it.

It's also important to note that product discovery is a continuous process, or continuous discovery. Your goal is to form a deep connection with your users and customers, continuously discover new opportunities, and continuously validate new ideas for your product team.

The Product Discovery Process

At CustomerIQ we've designated 4 main components to product discovery:

1. Learn and understand
2. Identify and decide
3. Brainstorm & prioritize
4. Prototype & test

No matter which product discovery tools or frameworks you choose (we'll discuss a few shortly) these principles will remain the same.

Learn and understand

Before you go about planning anything, you need to be completely immersed in the world of your customer. The goal at this stage is to absorb as much information about your customer's needs, pains, and desires as you can until patterns start to emerge.

To get started, focus on understanding the broader problem or group of problems that your product aims to solve, rather than specific features or ideas. Conduct customer interviews, run surveys, analyze sales call transcripts, and aggregate support tickets. These pieces of feedback contain so much information about your customer. Using CustomerIQ, you can extract valuable insights from these interactions. We'll get into more detail on this further in the post.

The insights you gather through CustomerIQ can help you pinpoint specific pain points to address with your product solutions. This stage may take weeks or months to fully explore manually, we built CustomerIQ to tackle it in seconds.

Identify and decide

First, start by reviewing your company or team's current objectives. Write them down.

Now look at the patterns that emerged from the data you collected.

How do the patterns in the customer data relate to your objectives? This is how you start to narrow down what's most important to solve.

Which of these problems, if solved, moves the needle toward our objective? Craft a simple sentence explaining your hypothesis and proposed solutions. You can use this framework:

By solving [problem] we can improve/reduce [objective]

Now you have an idea of the problem space in which you should build AND how to measure success.

Brainstorm & prioritize

Now it's time for every product manager's favorite part: brainstorming.

Gather key members from your own product management team and other stakeholders if you can. The more diverse experiences you have in the room the better.

Brainstorm different ways to solve the problem you identified in the customer data and prioritized potential solutions based on your objectives. Do your best to explore the entire solution space before settling on a list of potential projects.

Which projects could have the highest impact with the lowest effort? Those are usually good to prioritize. If you want a hand with prioritization frameworks, check out our comprehensive guide to prioritization frameworks here including MoSCoW, Kano, Rice, and Weighted Scoring.

Prototype & test

The final stage of the discovery process is to get user feedback on your idea. Your goal is to develop a prototype, code spike, or other usable example of the solution for your users to give feedback on.

At CustomerIQ, we prototype nearly every new project in Figma and run tests where we watch the customer click through and interact, just like it's real software. This can be a significant time investment during the design phase, but you'd be surprised what you learn, and it's significantly cheaper than building the wrong thing.

With these core principles in mind, let's look at a few popular techniques for conducting product discovery in more detail.

Popular Product Discovery Channels

Every team and every situation will have a few optimal channels and techniques for product discovery. Customer interviews, surveys, recorded calls, support tickets, analytics, and journey maps are staples to high performing teams.

Customer interviews

Customer interviews are an invaluable tool for understanding customer needs, preferences, and experiences. By engaging in direct conversations with users, businesses can uncover pain points, validate assumptions, and discover opportunities for improvement. These insights help drive better product decisions, feature prioritization, and ultimately lead to the development of products that resonate with the target audience, fostering customer satisfaction and loyalty.

However, there are a number of challenges to look out for with conducting customer interviews. Interviewers may struggle with asking open-ended, non-leading questions that elicit insightful responses. Maintaining a neutral tone and avoiding personal biases is essential to prevent influencing the participants' answers. Additionally, effectively managing the conversation to stay focused on the objectives while remaining open to exploring new topics takes practice.

Here are a few key things to remember when conducting customer interviews:

1. Define objectives and select participants: Determine your goals and identify a diverse sample of customers or potential users to interview.
2. Prepare an interview guide: Develop open-ended, non-leading questions that align with your objectives.
3. Build rapport: Follow the interview guide, listen actively, and probe deeper to encourage elaboration.
4. Analyze and synthesize findings: Identify patterns, themes, and insights from the interviews to inform product decisions.
5. Share results and take action: Communicate findings to stakeholders and apply insights to product development or strategy.

Surveys

Surveys are another powerful tool for customer discovery, as they enable businesses to collect quantitative and qualitative data from a large sample of users efficiently. By utilizing surveys, companies can gather information on customer preferences, behaviors, and opinions, which helps identify trends, validate assumptions, and uncover areas for improvement. Surveys can be particularly useful when organizations need to quickly test hypotheses or gather feedback from a broad audience to inform product development, marketing strategies, and other decisions. You can run surveys through email, inside your application, or in some cases, in person.

However, surveys also come with potential pitfalls. Designing unbiased and effective questions can be challenging, as poorly worded or leading questions may result in skewed data. Additionally, low response rates can limit the representativeness of the findings, and self-selection bias might influence the results. Survey fatigue is another concern, as participants may disengage and provide less thoughtful answers when faced with long or repetitive surveys.

A brief guide to getting started with customer discovery surveys:

1. Define objectives: Clearly outline the goals and desired outcomes of the survey, which will help you create relevant and focused questions.
2. Design the survey: Develop clear, unbiased, and concise questions that align with your objectives. Use a mix of question types (e.g., multiple-choice, Likert scale, open-ended) to capture both quantitative and qualitative data.
3. Select your audience: Identify a representative sample of customers or potential users based on factors like demographics, product usage, or behavior. The larger and more diverse the sample, the more reliable the insights.
4. Choose a distribution method: Select the most appropriate channel to reach your target audience (e.g., email, social media, website pop-up, in-app). Consider using survey software to streamline the process and track responses.
5. Test and refine: Pilot your survey with a small group to identify and address any issues with question wording, survey length, or technical problems.
6. Launch and monitor: Distribute your survey to the selected audience and monitor response rates, adjusting your distribution strategy if needed.
7. Analyze and interpret results: Review the collected data, identify patterns and trends, and draw insights to inform product decisions, feature prioritization, or other strategic initiatives.
8. Share findings and take action: Communicate the results to relevant stakeholders and use the insights to drive improvements or new developments in your product or service offerings.

Sales call transcripts

Recorded sales calls can be a treasure trove of insights for customer discovery, as they provide first-hand information on customer pain points, objections, and motivations. By analyzing these conversations, businesses can identify trends, tailor their offerings, and refine their sales strategies to better address customer needs. Additionally, reviewing recorded sales calls allows teams to understand the factors that contribute to successful sales interactions, leading to improved sales performance and stronger customer relationships.

However, there are some challenges associated with using recorded sales calls for customer discovery. Sales conversations might not cover all aspects of the customer experience or product usage, potentially limiting the scope of the insights. Privacy and consent concerns also need to be addressed when recording and analyzing calls. Lastly, processing and extracting valuable information from a large volume of recorded calls can be time-consuming and require considerable analytical skills.

A brief guide to getting started with customer discovery through recorded sales calls:

1. Obtain consent: Ensure that sales representatives inform customers that their calls will be recorded and used for internal purposes, and obtain the necessary consent.
2. Set objectives: Define your goals and desired outcomes for analyzing the recorded calls, such as identifying common objections, customer pain points, or factors that contribute to successful sales interactions.
3. Organize and store recordings: Use a consistent file-naming system and storage solution like CustomerIQ to easily access and retrieve the recorded calls for analysis.
4. Develop an analysis framework: Create a structured approach to review the calls, focusing on specific aspects like customer objections, pain points, or sales techniques. Use a system like CustomerIQ or spreadsheet to categorize and track insights.
5. Sample and analyze calls: Select a representative sample of calls to review, ensuring a mix of successful and unsuccessful sales interactions, as well as diverse customer profiles.
6. Extract insights and patterns: Identify recurring themes, common objections, and customer needs by analyzing the sampled calls. Look for trends and insights that can inform product development or sales strategy.
7. Share findings and implement improvements: Communicate the results to relevant stakeholders, such as product managers and sales teams. Use the insights to refine product offerings, address customer pain points, and improve sales techniques.
8. Continuously learn and iterate: Regularly review and analyze recorded sales calls to stay informed of evolving customer needs and preferences, and adapt your strategies accordingly.

Support tickets

Support tickets offer insights into customer pain points, product issues, and areas for improvement. By analyzing support tickets, a product manager can identify trends, common problems, and opportunities to enhance the customer experience. Reviewing support tickets can also help inform product development, feature prioritization, and customer service strategies, ultimately leading to higher customer satisfaction and reduced support requests.

One major thing to look out for when analyzing support tickets is that the data may be skewed towards negative experiences or specific issues, as customers are more likely to reach out when they encounter problems. Additionally, support tickets may not always accurately represent the broader customer base, as some users may not submit tickets for various reasons.

A brief guide to getting started with customer discovery through support tickets:

1. Set objectives: Define your goals and desired outcomes for analyzing support tickets, such as identifying common issues, customer pain points, or areas for product improvement.
2. Organize and categorize tickets: Use a consistent tagging or categorization system to classify support tickets based on factors like issue type, product feature, or customer segment. In CustomerIQ, we recommend organizing these different categories by folder.
3. Sample and analyze tickets: Select a representative sample of support tickets to review, ensuring a mix of different issue types, product features, and customer profiles.
4. Develop an analysis framework: Create a structured approach to review the tickets, focusing on specific aspects like recurring issues, customer pain points, or suggested improvements. Use a system like CustomerIQ to generate tags automatically.
5. Extract insights and patterns: Identify trends, common problems, and customer needs by analyzing the sampled support tickets. Look for insights that can inform product development or customer service improvements.
6. Share findings and implement improvements: Communicate the results to relevant stakeholders, such as product managers and customer support teams. Use the insights to enhance product offerings, address customer pain points, and refine support processes.
7. Continuously learn and iterate: Regularly review and analyze support tickets to stay informed of evolving customer needs and preferences, and adapt your strategies accordingly.

Analytics

It may seem obvious to include product analytics in this guide, but it's a surprisingly overlooked asset in product discovery. By analyzing user behavior, engagement, and retention metrics, teams can uncover opportunities for growth.

However, analytics are a lagging indicator and best to be used to monitor the success of your solution. Selecting the right metrics to track and analyze can be difficult, and focusing on vanity metrics may lead to misguided decisions. Interpreting the data and translating insights into actionable improvements can be challenging, especially when dealing with large volumes of data.

A brief guide to getting started with product analytics:

1. Set objectives: Define your goals and desired outcomes for using product analytics, such as optimizing user experience, improving engagement, or increasing retention.
2. Identify key metrics: Select the most relevant metrics to track and analyze based on your objectives, such as active users, session duration, feature usage, or conversion rates.
3. Choose an analytics tool: Select a product analytics tool or platform that aligns with your needs and offers the necessary features for tracking and analyzing your chosen metrics.
4. Implement tracking: Properly set up the analytics tool within your product to accurately capture user interactions and data. This may require collaboration with developers and thorough testing to ensure correct implementation.
5. Analyze data and identify trends: Regularly review the collected data, looking for patterns, trends, and insights that align with your objectives. Consider segmenting the data by factors like demographics, user behavior, or acquisition channels to gain deeper insights.
6. Test and iterate: Use the insights from product analytics to inform product improvements, feature prioritization, or marketing strategies. Conduct experiments or A/B tests to validate hypotheses and measure the impact of changes.
7. Share findings and take action: Communicate the results and insights to relevant stakeholders. Use the data to drive informed decision-making and prioritize product enhancements.
8. Continuously monitor and optimize: Regularly review your product analytics data to stay informed of evolving user behavior and preferences. Use the insights to guide ongoing product improvements and adapt your strategies accordingly.

Journey mapping

Customer journey mapping is a valuable technique for visualizing and understanding the entire customer experience, from initial awareness to post-purchase interactions. By creating a visual representation of each touchpoint, teams can take the data they've gathered and visualize pain points, areas for improvement, and opportunities to enhance customer satisfaction. Journey mapping helps align cross-functional teams around a common understanding of customer needs and preferences, leading to better product development, marketing, and support strategies.

However, identifying all relevant touchpoints and ensuring that the map accurately represents the customer perspective can be challenging and is a continuous process. Maintaining and updating the map to reflect evolving customer needs and preferences requires ongoing effort and should be something you revisit regularly.

A brief guide to getting started with customer journey mapping:

1. Set objectives: Define your goals and desired outcomes for the journey mapping exercise, such as identifying pain points, uncovering opportunities for improvement, or aligning cross-functional teams.
2. Research and gather data: Collect data on customer behavior, preferences, and experiences through methods like customer interviews, surveys, support tickets, and analytics.
3. Identify customer personas: Develop representative customer personas based on demographics, behavior, and needs to ensure the map accurately reflects the target audience.
4. Define stages and touchpoints: Break down the customer journey into key stages (e.g., awareness, consideration, purchase, retention) and identify the touchpoints within each stage.
5. Map the journey: Create a visual representation of the customer journey, including touchpoints, actions, emotions, and pain points. Use a format that is easy to understand and share, such as a flowchart, storyboard, or diagram.
6. Analyze and identify insights: Review the journey map to identify patterns, pain points, and opportunities for improvement. Look for areas where the customer experience can be enhanced or streamlined.
7. Share findings and take action: Communicate the journey map and insights to relevant stakeholders. Use the insights to inform product development, marketing, and support strategies, and prioritize improvements.
8. Continuously update and iterate: Regularly review and update the customer journey map to reflect changes in customer needs, preferences, and the competitive landscape. Use the map as a living document to guide ongoing improvements to the customer experience.

The Golden Rules for Effective Product Discovery

We've covered a lot in this guide so far and I'm sure you're ready to put it to use. So we'll give you a few golden rules to remember as you navigate and perfect this remarkable process.

Empathize with your users

By putting themselves in the users' shoes, product teams can create more user-centered solutions that resonate with their target audience, ultimately leading to higher customer satisfaction, increased adoption, and long-term success. Empathy fosters deeper connections with customers, enabling businesses to not only solve existing problems but also anticipate and address future needs.

Involve cross-functional team members

Collaborating with teams such as design, engineering, marketing, and sales helps create a holistic understanding of customer needs and fosters a shared vision for the product. This collaborative approach results in better-informed decision-making, more comprehensive solutions, and a unified effort towards creating a successful product that meets both user and business goals.

Set clear goals and objectives

You may have noticed it repeated in each guide: Setting clear goals and objectives is crucial for a successful product discovery process. By establishing specific, measurable, and achievable targets, product teams can focus their research, prioritize user needs, and evaluate the effectiveness of their efforts. A shared understanding of desired outcomes ensures that all team members, including cross-functional partners, work cohesively towards uncovering valuable customer insights. Clear goals and objectives also provide a solid foundation for data-driven decision-making, enabling product teams to adjust their strategies, optimize resource allocation, and ultimately develop products that effectively address user needs and drive business success.

Data over opinions

Using data to inform decisions in the product discovery process is essential to ensure that product development is grounded in evidence and objective insights. By analyzing quantitative and qualitative data from various sources, such as customer feedback, surveys, and analytics, product teams can accurately identify user needs, preferences, and pain points. Data-driven decision-making helps reduce the influence of subjective opinions and biases, leading to more effective solutions that address real customer problems. Ultimately, relying on data in the full product development journey and discovery process enhances the likelihood of creating successful products that resonate with the target audience and drive business growth.

Iterate and learn from failures

Embracing an iterative mindset and viewing failures as learning opportunities enable product teams to adapt and refine their strategies, ultimately leading to better solutions. By analyzing and understanding the reasons behind unsuccessful attempts, teams can uncover valuable insights, optimize their approach, and pivot more effectively to meet user needs. This continuous learning process not only fosters a culture of innovation and resilience but also drives long-term success by ensuring that the product evolves in response to customer feedback and market demands.

Importance of continuous Product Discovery

Just as solutions change over time, problems change too. Continuous product discovery is vital for maintaining a competitive edge and ensuring that products remain relevant and valuable to users over time. By regularly engaging with customers, gathering feedback, and analyzing data, product teams can stay attuned to evolving user needs, preferences, and market trends. This ongoing process enables businesses to proactively identify and address emerging customer pain points, prioritize product enhancements, and seize new opportunities for growth. By fostering a culture of continuous learning and improvement, companies can adapt to changing circumstances and ensure the sustained success of their products in a dynamic marketplace.

Common Challenges in Product Discovery and How to Overcome Them

Conducting product discovery takes time and resources, both of which can feel hard to come by in certain company cultures. Here are a few challenges you may encounter in implementing an effective product discovery process and how to overcome them.

Lack of buy in from stakeholders

Executives who are not familiar with the product discovery process may initially see it as a waste of time when the team should be building. This is obviously flawed. It's far more cost-effective to do good product discovery, and build the right thing, than to skip it and build the wrong thing. Just ask Segway.

Difficulty prioritizing ideas

By involving cross functional collaboration you're destined to surface many good, competing ideas. Which ones do you work on?

Product teams can effectively prioritize ideas from the product discovery stage by following these condensed strategies:

1. Align with business objectives and customer impact: Focus on ideas that contribute to achieving key performance indicators, drive business growth, and address significant customer pain points or unmet needs.
2. Estimate effort and resources: Balance the potential impact of ideas with the feasibility of execution and the required resources, aiming for the best return on investment.
3. Apply prioritization frameworks and cross-functional input: Use frameworks like RICE or MoSCoW to objectively rank ideas, and involve diverse stakeholders to gain a comprehensive understanding of each idea's feasibility, desirability, and viability.
4. Validate assumptions and reevaluate priorities: Conduct experiments or prototyping to gauge the potential impact of ideas, and regularly reassess the priority list to incorporate new insights, feedback, or market trends, ensuring that the most relevant and impactful ideas remain at the forefront.

Data analysis and synthesis

Data analysis and synthesis in product discovery can be challenging due to the complexity, variety, and volume of data sources. Extracting meaningful insights from this diverse data requires the ability to identify patterns, trends, and correlations, as well as a deep understanding of user needs and preferences. Additionally, managing and synthesizing large volumes of data can be labor-intensive and demand considerable time and resources, making it difficult for product teams to efficiently and effectively derive actionable insights for informed decision-making.

With CustomerIQ, teams can easily consolidate information from various sources such as interviews, surveys, and analytics, enabling a comprehensive view of customer insights. CustomerIQ's AI automatically identifies patterns, trends, and correlations, simplifying the process of extracting meaningful insights from complex data.

Sharing learnings

Once your continuous discovery engine is running, your team will start to identify countless invaluable insights. It's critical that you share these learnings in a place where the entire organization can benefit from them.

Sharing learnings from product discovery is important for several reasons:

1. Alignment and collaboration: Sharing insights fosters a shared understanding of user needs, preferences, and pain points across the organization, enabling cross-functional teams to work collaboratively towards a unified vision of the product.
2. Informed decision-making: Disseminating learnings ensures that product development decisions are grounded in evidence, helping to create more effective, user-centered solutions that resonate with the target audience.
3. Continuous improvement: By sharing insights, teams can identify opportunities for product enhancements, process optimization, and innovation, driving continuous improvement and long-term success.

However, this doesn't always happen due to several factors:

1. Siloed teams: In some organizations, teams work in silos with limited communication, making it difficult to share insights and collaborate effectively.
2. Time constraints: Product teams often face tight deadlines and competing priorities, which can limit the time available for sharing and discussing learnings from product discovery.
3. Lack of structured processes: The absence of a systematic approach to storing, analyzing, and sharing insights can hinder the effective dissemination of learnings.
4. Inadequate tools and resources: Organizations may lack the appropriate tools or platforms to facilitate the easy sharing of information and insights among team members.

By addressing these challenges and fostering a culture of open communication and collaboration, organizations can ensure that learnings from product discovery are effectively shared and leveraged to drive product success.

CustomerIQ fosters collaboration by allowing team members to easily share findings and learnings, ensuring alignment and informed decision-making across the organization. By leveraging CustomerIQ, product teams can focus on driving impactful product improvements based on data-driven insights, ultimately enhancing user satisfaction and business success.

Conclusion

We made it. You're ready to put in place an effective product discovery process. Remember that, while discovery is obviously needed more in certain times, it's best to make this a continuous discovery process. Keep learning, keep exploring, keep iterating and you are sure to win your market.

Our team has been doing continuous discovery for years. We've seen the benefits and we've seen the challenges.

That's why we built CustomerIQ. If you're interested in learning how we automate the organization and synthesis of data uncovered from your product discovery efforts, you can learn more here.