Miro Insights

Miro Insights, formerly known as Cardinal (YC W23), is a sophisticated AI-powered platform designed to revolutionize product management. Acquired by Miro, it is now integrated into the Miro Innovation Workspace, empowering product teams to move from idea to outcome with greater speed and confidence. The platform addresses the common challenges of product management—scattered data, conflicting opinions, and a disconnect between customer feedback and development priorities. By centralizing and analyzing customer interactions, Miro Insights provides a single source of truth, enabling teams to make data-driven decisions and build products that truly resonate with their users.

The core mission of Miro Insights is to transform real customer insights into actionable recommendations for your product backlog. It leverages advanced AI to sift through vast amounts of unstructured feedback from various channels, identifying feature requests, pain points, and emerging trends. This allows product managers to prioritize what matters most, backed by quantifiable data like potential revenue impact, ensuring that development efforts are always aligned with business objectives and customer needs.

How to use Miro Insights

Getting started with Miro Insights is designed to be a seamless process that integrates into your existing workflows. The typical user journey involves several key steps:

1. Connect Your Data Sources: The first step is to integrate all your feedback channels. Miro Insights supports a wide range of integrations, including CRMs (Salesforce, Hubspot), customer conversation platforms (Gong, Zoom, Chorus.ai), support systems (Zendesk, Intercom, Jira Service Management), and task management tools (Jira, Linear, Notion). This creates a unified data stream for analysis.

2. Let AI Synthesize Insights: Once connected, the platform's AI gets to work. It automatically analyzes transcripts from calls, support tickets, and messages to identify and categorize feature requests, customer needs, and sentiment. It extracts who wants what, when, and how important it is for them.

3. Align with Product Strategy: The extracted insights are not just a list of requests. You can map each feature to your broader product strategy, grouping them into initiatives and key impact areas. This provides a clear strategic context for every potential development item.

4. Prioritize with Revenue Data: A key differentiator is the ability to connect feedback to financial data. By syncing with your CRM, Miro Insights can calculate and forecast the revenue value (new, retained, or churned ARR) associated with each feature request, enabling you to prioritize high-impact work.

5. Collaborate and Build: With a prioritized backlog, you can align your Product, Engineering, and Go-to-Market teams. The platform provides visibility into feature status, development progress (synced from Jira/Linear), and business impact, ensuring everyone is on the same page.

6. Query Your Data: Use the 'Ask Insights' feature to ask natural language questions about your data. For example, you can ask, "What are the top feature requests from enterprise customers in Q3?" or "Show me all feedback related to security concerns," and receive structured, actionable answers.

Core Features of Miro Insights

• AI-Powered Feedback Synthesis: Automatically analyzes customer feedback from calls, tickets, and messages to identify feature requests, needs, and blockers.
• Centralized Feedback Hub: Aggregates customer data from dozens of integrations into a single, searchable, and analyzable view.
• Revenue-Driven Prioritization: Connects feature requests to CRM data to quantify their potential impact on ARR, helping teams prioritize features that drive business growth.
• Strategic Roadmapping: Allows teams to group features into initiatives, align them with strategic goals, and visualize the product roadmap.
• Seamless Integrations: Offers extensive integrations with leading tools across CRM, Customer Support, Call Recording, and Project Management categories like Salesforce, Gong, Zendesk, and Jira.
• Cross-Functional Alignment: Acts as a single source of truth that keeps Product, Engineering, GTM, and leadership teams aligned on priorities and progress.
• Ask Insights (AI Assistant): A conversational AI that allows users to freely query their customer data and receive intelligent, structured answers to complex questions.

Use Cases for Miro Insights

Miro Insights is valuable for various roles and teams within a product-led organization:

• Product Managers: To automate feedback analysis, build data-backed roadmaps, and confidently justify prioritization decisions to stakeholders.
• Product Teams: To achieve a deep, shared understanding of customer needs and collaborate effectively on building the right features.
• UX Researchers: To quickly identify patterns and themes in user feedback to inform design and product improvements.
• Sales & Customer Success Teams: To track customer requests, understand their impact on deals and renewals, and have visibility into the product's future direction.
• Executive Leadership: To gain a high-level overview of the product strategy and its direct impact on revenue and key business metrics.

Advantages of Miro Insights

The primary advantage of Miro Insights is its ability to create a direct, data-rich link between customer feedback and product development. It replaces intuition with evidence, automates manual work, and fosters company-wide alignment. By focusing on revenue impact, it ensures that product decisions are also smart business decisions. Its integration within the broader Miro ecosystem further enhances collaboration, allowing teams to seamlessly move from insight to ideation and execution on a single platform.

Pricing and Plans

Miro Insights is positioned as an enterprise-grade solution. Specific pricing information is not publicly available on the website. To get details on plans and pricing, prospective customers are encouraged to schedule a demo with their sales team. This approach suggests that pricing is customized based on the organization's size, needs, and the specific integrations required.