How to Create Effective Product Briefs from Customer Calls

• Why Customer Calls Matter: Direct conversations uncover bugs, inspire features, and reveal unique use cases that surveys or analytics miss.
• Use Product Briefs: These documents turn raw feedback into clear guidance for teams, helping prioritize features, fix issues, and align goals.
• Set Up Call Analysis Systems: Use call recording tools, AI analysis for trends, and structured review processes to capture insights effectively.
• Find Key Insights: Spot recurring issues, track feature requests, and analyze customer emotions to understand their needs.
• Write Better Product Briefs: Focus on clear problem statements, prioritize features using frameworks like RICE, and create actionable user stories.

Pro Tip: Tools like BuildBetter simplify the process by automating call analysis, prioritizing feedback, and generating product briefs seamlessly.

Start using customer calls to create product briefs that align your team and meet real customer needs.

Setting Up Call Analysis Systems

Transforming customer calls into practical insights starts with a well-organized call analysis system. Here's how to set up a system that systematically gathers and processes customer feedback.

Call Recording Tools and Setup

The foundation of effective call analysis is high-quality call recording. Choose software that integrates seamlessly with your current tools and offers clear playback. Will Andrew, Business Transformation Manager at Rezdy, highlights this: "The easy access to call recordings in HubSpot also helps sales and customer care teams review client interactions so we can provide a better service to our customers."

When setting up call recording, keep these points in mind:

• Opt for solutions with automatic backup and search functions.
• Ensure the tool integrates with your CRM.
• Use automatic transcription to simplify reviews.
• Store recordings securely and comply with data protection laws.

Adding AI Analysis Tools

AI tools can analyze calls using natural language processing to detect trends and urgent issues. For example, James Villas, a holiday rental company, reduced their first reply time by 46% by using topic and sentiment analysis to prioritize customer needs. Similarly, Gousto identified damaged food items as their top customer complaint through AI analytics, leading to improvements in their logistics.

Creating Call Review Guidelines

A consistent review process ensures that insights are captured effectively. Your guidelines should include:

• Defined Roles: Assign specific team members to monitor calls and log feedback.
• Quality Benchmarks: Clearly outline what makes a customer interaction successful.
• Regular Reviews: Schedule call analysis at set intervals to ensure consistency.
• Structured Feedback: Use forms for agents and managers to provide organized input.

"A critical aspect of call quality monitoring is asking for agent feedback. Their daily experiences with customers can provide important insights into improving voice practices." – Vocalcom

To enhance your review system, maintain a library of standout calls that demonstrate excellent practices and pinpoint areas needing improvement. This structured approach helps teams uncover the insights necessary for refining products and services.

Finding Key Information in Customer Calls

Once you've set up call analysis, the next step is to dig into the details. Look for patterns, customer requests, and emotional cues that can shape your product decisions. These findings help create product briefs that truly address what customers need.

Identifying Recurring Issues

Recurring problems often point to larger challenges. Post Call Analytics (PCA) uses machine learning models trained on thousands of hours of calls to identify these common issues.

Here’s how to spot recurring problems effectively:

• Leverage AI tools to scan transcripts for recurring themes.
• Track frequency and severity of issues across different customer groups.
• Document specific use cases in the customers’ own words.

"It all really boils down to asking 'why?' and then logging in as much detail as possible, in the customer's own words, the specifics about what they are actually trying to accomplish." - Phil Freo

Tracking Feature Requests

Rather than focusing on isolated feature ideas, aim to understand the core needs behind them.

When logging feature requests, keep these factors in mind:

To organize and prioritize requests, the RICE method (Reach, Impact, Confidence, Effort) is a reliable framework. It ensures your team focuses on features that align with both customer needs and business objectives.

Reading Customer Emotions

Customer sentiment provides important context for decision-making. Tools using Natural Language Processing (NLP) can analyze emotional patterns in customer interactions.

Zonka Feedback, for example, excels in extracting emotional insights by offering features like:

• Opinion mining
• Intent analysis
• Emotion detection

"Sentiment analysis changes that. By uncovering the emotions and tones hidden within feedback, it helps you truly understand what your customers feel, empowering you to address issues and enhance their satisfaction." - Swati Sharma

To get the most out of sentiment analysis:

• Set clear goals for what you want to learn about customer emotions.
• Clean and prepare your data to improve accuracy.
• Combine emotional insights with other metrics for a complete picture.
• Train your team to interpret results and apply them effectively.

Writing Product Briefs from Call Data

Using insights gathered from customer calls, this section focuses on turning raw data into clear, actionable product briefs that align with the needs of product teams and stakeholders.

Writing Problem Statements

Craft problem statements by breaking them into three key components:

"Because big stories have a lot of complexity, they have a lot of risk as well. What if you get 80% or 90% down the path and realize the story was based on erroneous assumptions? Break big stories into smaller stories - representing at most a few days of dev." - Dan Podsedly, VP of Pivotal Labs

Ranking Features by Customer Need

Prioritizing features involves balancing what customers want with what makes sense for the business. The RICE method (Reach, Impact, Confidence, Effort) is a helpful framework for evaluating features objectively.

Key factors to consider when ranking features:

• Business Value Assessment
  Look at how each feature could affect revenue or improve customer retention.
• Implementation Feasibility
  Think about the technical challenges, required resources, and time it will take to build.
• Customer Impact Measurement
  Use tools like the Kano model to determine whether a feature will delight users or just meet their basic needs.

These considerations help prioritize features and guide the creation of effective user stories.

Creating User Stories

Convert customer insights into actionable user stories by focusing on three main components:

"The unit of collaboration in software development is, hopefully, a fine-grained user story." - Dan Podsedly, VP of Pivotal Labs

This structured approach ensures that insights from call data are seamlessly transformed into user stories, paving the way for meaningful product improvements.

Using BuildBetter for Product Briefs

BuildBetter turns customer calls into detailed product briefs using its AI-driven platform. By automating time-consuming tasks, product teams save an average of 6.5 hours each week, freeing up time for more strategic work. This builds upon the call analysis methods discussed earlier.

Quick Call Analysis with BuildBetter

BuildBetter processes recordings and transcripts from platforms like Zoom, MS Teams, and Google Meet automatically. Its "Signals" engine identifies key details within customer conversations, breaking them down into actionable insights:

"It's remarkably reassuring to have BuildBetter monitor meetings." – Tash Keuneman, Head of Design

Turning Feedback into Features

After analyzing call data, BuildBetter uses customer feedback to sharpen feature prioritization. Its AI chat interface uncovers hidden needs by identifying patterns across feedback channels. Sentiment analysis highlights how customers react during demos or pitches, helping teams understand which features resonate most. Feature requests are ranked based on:

• How often they're mentioned
• How critical they are to users

"I'm pulling in a lot of discovery calls over the past several months. It wouldn't be possible to do this at scale without your application." – John Strang, Product Operations

Data-Driven Product Planning

Once priorities are clear, BuildBetter converts insights into structured product plans. It offers ready-to-use templates for PRDs and user stories and integrates smoothly with tools like Jira, Notion, and Slack. The AI chat acts like a virtual product manager, answering questions about customer needs and aligning development priorities by analyzing, organizing, and presenting data effectively.

"Helps me see the forest through the trees." – Ryan Brown, Principal Product Manager

Automated workflows ensure consistency in documentation, making it easier to translate customer feedback into actionable decisions. With pricing starting at $7.99/month for the Starter tier, BuildBetter provides these tools to teams of any size without restricting collaboration through per-seat costs.

Conclusion: Creating Customer-Focused Product Briefs

Product briefs that focus on user needs and clear documentation can make a big difference. Research shows that companies centered on customer feedback are 60% more profitable than those that aren't.

A strong product brief acts as the go-to guide for your team, providing clear direction and cutting down on confusion. The best briefs zero in on user problems without dictating exact solutions. By continuously updating these documents, teams can stay aligned with what customers actually need.

Product briefs should adapt as customer feedback comes in. Tools like BuildBetter's AI-powered platform simplify this by automatically gathering and organizing customer insights, keeping product decisions rooted in real user experiences.

To make product briefs as effective as possible, focus on these three key elements:

• Think like the user: Highlight problems and needs from the customer's point of view, steering clear of overly technical language.
• Set clear goals: Define specific timelines and desired outcomes, while leaving room for creative approaches.
• Use visuals: Add images and diagrams to clarify concepts and show user flows.

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