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How Recorded Calls Help Product Managers Prioritize the Roadmap

Data is an essential input for product managers when it comes to prioritizing features on a roadmap. A thorough understanding of client pain points can lead to better solutions and higher confidence that new features will deliver the desired impact. This article provides insights on the high-level product manager role and how they can use AI and its data to prioritize the product roadmap.

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By Rob
September 8th, 2021

A product manager will often be the primary decision-maker for a product's direction and the customer it serves. Their role is to ensure that the team is aligned on the most impactful features to solve their clients' pain. Product Managers are responsible for identifying business opportunities, validating ideas, defining new features, and prioritizing the roadmap. In short, they are finding ways to deliver more value and maximize return on investment (ROI). A critical part of a product manager's role is to use data as evidence to increase confidence that a feature will have the desired result of delivering value to the customer. A product manager can leverage a variety of data to gain confidence, but first, let's jump into a definition of the role of a product manager. 

7 Characteristics of a Good Product Manager

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It's not easy to explain the role of a product manager, as it can widely vary depending on the company's stage, size, or product maturity. However, here there are some characteristics that an effective product manager should have:

1. Understanding: A good product manager understands every detail of their product and how it works. Clear and concise language allows them to communicate the product's value, aligning internal stakeholders and external clients.

2. Curiosity: The best product managers are curious about their customers and are passionate about solving their client's pains; having the curiosity to always ask why enables them to dig deep into the customer's mind and what they need for a better buying process. 

3. Strategic: Part of the role of a product manager is to help set the direction for the product and align the team around their vision. This makes it the product manager's responsibility to communicate how each feature fits into the bigger picture while supporting the company's strategy.

4. Relationship Builder: Product managers must be empathetic and good at building relationships with different people, including internal stakeholders, external clients, and internal teams working on the product. By understanding what motivates a team member or an external client, they use this information to communicate efficiently and build relationships.

5. Risk Taker: Being a product manager means not being afraid to try out new things and take risks. Whether they are trying out new technology or developing a new feature, comprehensive data isn't always available. A product manager should weigh the outcome of their solution and embrace risk if it yields a high return. Trying new things is part of the role; remember to have confidence!

6. Storyteller: A product manager is ultimately a storyteller. They should communicate the product vision to different audiences and internal stakeholders so that others can understand. Having the ability to tell simplified stories about the problem they are solving and the people they are serving is what a product manager is all about. This requires the ability to simplify complex topics into simple ideas.

7. Positivity: Be positive! Having a positive attitude motivates a product manager's team and builds the right relationships with internal stakeholders and external clients

Product Manager Activities

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A product manager is responsible for defining the product's strategy and delivering value to its clients. This involves a variety of activities such as:

Data Collection

  • Work with the sales team to gather data on how a product performs and compares to competitors.

  • Listen to client feedback¬†and support the sales team to ensure that clients are happy with the product.¬†

  • Analyze user interactions and click patterns.¬†¬†

Turning data into roadmap features

  • Evaluate the impact of choosing to add new features versus modifying existing ones

  • Look at different users patterns that indicate opportunities to expand the user base

  • Identifying new business opportunities that align with the company's strategy

  • Prioritize the ideation on a roadmap based on the distillation of customer feedback and data.

Execution and follow-through

  • Empower the team to create, develop and launch new features by providing them with resources and direction.

  • Test each version of the feature creation process and iterate on the design. It's unlikely that the first iteration will fully solve the customer pain.¬†¬†

Prioritizing Roadmap Features With AI

Product managers should aim to maximize the ROI. That means delivering value to the product, the company, and its clients. A variety of data sources should be taken into account when developing new features and measuring their impact. 

Quantitative data is more related to business metrics such as revenue growth, profitability, gross margin, churn, user sessions and interactions, and overall engagement with the app or service. 

Qualitative data is more related to qualitative metrics such as client feedback from surveys, client calls, customer service interactions, and interviews. The process of collecting and analyzing this data can be time-consuming and require substantial human resources.

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Artificial Intelligence can help product managers collect qualitative data more accurately and efficiently. AI can reduce the time and effort needed to analyze data by automating specific processes. This allows product managers and client-facing representatives to focus more on the insights and solving the obvious customer pain instead of analytics and data collection. Here are some key insights below:

  • Automate the recording process for you and your team with an AI assistant that joins and captures your calls. For more comprehensive data, get your sales and success teams to record their interactions.¬†

  • Review the moments that matter. An AI can recognize certain words, topics, and key phrases from a recorded call to identify the pain points that the client is experiencing. Tools like Hyperia aggregate customer data into consumable clips for a given topic or tag.¬†

  • Create custom tracking tags. If you're interested in tracking competitor mentions or a specific question, you can set up the AI to tag and clip these events, enabling you to track mentions over time.

  • Cross-reference qualitative data with quantitative data. Comparing what clients are saying on calls vs. the actions that they are taking in the app. A client might express excitement and good intentions towards a feature, but unexpected friction might lower adoption. It's essential to understand how user intentions translate to user actions.¬†¬†

  • Score your feature list. Once you come up with a list of features, you'll need to make them more manageable. Scoring rubrics like RICE can help you turn evidence collected into a weighted number, prioritizing a sortable list.¬†

Summary

In conclusion, product managers need to understand their clients' needs and pain points. It's critical to support new features decisions with data and increase confidence that a feature will have the desired result of delivering value to the customer. 

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