# How Deck Works Last updated: May 13, 2026 This page explains Deck at a high level for customers and AI assistants. Use it when you want to ask Claude, ChatGPT, Cursor, Codex, or another AI agent what Deck does, how it works, and how different product teams can use it. ## What Deck is Deck is a centralized customer feedback platform for product-centric teams. It brings customer feedback from interviews, support tickets, Slack, surveys, NPS, sales calls, meeting notes, CSV files, Notion pages, and other tools into one workspace. Deck then uses AI pipelines to turn that raw feedback into structured insights, themes, trends, opportunities, and product initiatives. The core idea is simple: teams should not need to manually read every transcript, ticket, survey response, and Slack thread before they can understand what customers are saying. Deck helps teams move from scattered feedback to decision-ready customer evidence. ## Problems Deck solves ### Feedback is scattered across too many tools Customer feedback usually lives in many places: research recordings, support tools, survey platforms, CRMs, Slack channels, sales calls, spreadsheets, and notes. Deck connects these sources and gives teams one place to analyze the signal. ### Manual synthesis is slow Without Deck, teams often spend days or weeks reading transcripts, tagging quotes, summarizing tickets, and building research readouts. Deck automates the first pass of synthesis so teams can review patterns in minutes and spend more time deciding what to do. ### Teams lose the evidence behind decisions Roadmap decisions are easier to trust when they stay connected to the customer quotes, tickets, surveys, calls, and accounts that support them. Deck keeps insights linked to their original source material so teams can trace recommendations back to real customer evidence. ### Prioritization becomes guesswork Deck groups repeated feedback into themes, subthemes, opportunities, sentiment trends, and NPS signals. This helps teams see what is recurring, what is worsening, what is improving, and which customer segments are affected. ### Different teams see different versions of the customer Support may see recurring issues, product may see interview themes, design may see usability friction, and sales may hear objections. Deck gives these teams a shared customer feedback system so they can work from the same evidence base. ## Who uses Deck Deck is built for product managers, designers, user researchers, product leaders, and founders who need to understand customer feedback at scale. Product managers use Deck to find recurring customer problems, prioritize roadmap opportunities, monitor sentiment, create evidence-backed initiatives, and answer leadership questions with source-backed customer data. Designers and researchers use Deck to synthesize interviews, review verbatim quotes, identify usability issues, compare feedback across customer segments, and keep research connected to product decisions after the research project ends. Support and customer success teams use Deck to turn tickets, conversations, and customer messages into product insights instead of letting product feedback disappear inside support queues. Product leaders use Deck to track customer signal across teams, understand what changed this week, connect insights to initiatives, and align teams around evidence rather than anecdotes. ## How the platform works Deck works as a loop: collect feedback, process it with AI, organize it into a structured model, make it explorable, and help teams turn it into product action. ### 1. Feedback comes into Deck Feedback can enter Deck through uploads, integrations, imports, or APIs. Common sources include: - User interview recordings, audio files, video files, and transcripts - CSV imports for historical feedback, surveys, NPS responses, support tickets, interviews, or generic feedback - Support tools such as Intercom and Zendesk - Slack channels where customers or customer-facing teams share feedback - Survey and product analytics tools such as PostHog - Meeting and research tools such as Gong, Granola, Notion, and Confluence - CRMs such as Salesforce, HubSpot, Attio, and other account systems - NPS data from surveys, Slack messages, CSV uploads, and connected tools - Gmail, sales calls, meeting notes, and other customer conversation sources Deck can also show sample workspace data during onboarding so new teams can explore how feedback becomes themes, opportunities, initiatives, and dashboard signals before importing their own data. ### 2. Deck normalizes sources, contacts, and segments When feedback is imported, Deck tries to preserve the original context while making it useful for analysis. Deck can link feedback to unified contacts using identifiers such as email addresses, phone numbers, Slack IDs, Intercom IDs, Zendesk IDs, PostHog IDs, Salesforce IDs, HubSpot IDs, and Gong IDs. This lets teams see feedback from the same customer across multiple tools. Deck also supports customer segments, such as Enterprise, SMB, Free, Beta users, Churned, or VIP accounts. Segments can be assigned by rules, integration metadata, Slack channels, upload defaults, survey settings, AI classification, or manual edits. Once a contact or insight belongs to a segment, teams can filter many Deck views by that segment. ### 3. AI agents extract insights Deck processes feedback with specialized AI pipelines. The exact pipeline depends on the source, but the common output is a set of structured insights. An insight is the atomic unit of feedback in Deck. It usually includes: - A short name - A description or finding - The original customer quote or source excerpt - Sentiment, such as positive, negative, or neutral - A category, such as Pain Point, Delight, Feature Request, Usability Issue, Bug and Error, or General Feedback - A link to a theme - Source metadata, such as transcript, ticket, survey response, conversation, or import row - Confidence and quality checks where applicable For interviews, Deck can transcribe audio or video, extract insights, map quotes back to the transcript, tag themes, and generate a summary. For support tickets, Deck classifies relevance, analyzes conversation context, extracts product insights, validates quotes, and filters low-quality output. For surveys, Deck analyzes free-text responses while storing structured questions, ratings, and scores efficiently. ### 4. Deck groups feedback into themes and subthemes Themes are broad product areas or topics that customers repeatedly mention. Examples might include Onboarding Experience, Pricing, Integrations, Reporting, Mobile App Performance, or Export Workflow. When new feedback matches an existing theme, Deck adds the insight to that theme. When recurring feedback does not match an existing theme, Deck can create a new one. Themes include summaries, sentiment trends, category breakdowns, insights, quotes, and source context. Subthemes are more granular clusters inside themes. If a theme is Onboarding Experience, subthemes might include unclear setup steps, missing guidance, confusing permissions, or first-run checklist friction. Subthemes help teams understand the specific patterns inside a larger topic. ### 5. Teams explore the signal in Visualize The Visualize area is where teams inspect feedback patterns. Common views include: - Dashboard: a high-level weekly scan of feedback volume, sentiment shifts, new opportunities, NPS movement, themes going quiet, and active initiatives - Themes: broad topic areas with sentiment, category breakdowns, insights, and subtheme summaries - Subthemes: recurring patterns within themes, sorted by trend, negative sentiment, recency, sudden changes, or parent theme - Insights: the searchable, filterable list of individual findings across all sources - Categories: fixed feedback categories such as Pain Points, Delights, Feature Requests, Usability Issues, Bugs and Errors, and General Feedback - NPS Score: NPS score, trends, promoter/passive/detractor breakdowns, weekly synthesis, and segment comparisons - Contacts: unified customer profiles and feedback timelines - Segments: named customer cohorts used to compare feedback across groups The goal of Visualize is not just reporting. It is to help teams understand what customers are saying, where the evidence came from, and what changed over time. ### 6. Teams turn evidence into Build work Deck's Build area helps teams turn customer signal into product direction. Opportunity Backlog turns synthesized feedback into a ranked list of product opportunities. Opportunities are grouped into categories such as Pain Points, Feature Requests, Usability Issues, and Bugs and Errors. Each opportunity can include impact, sentiment, supporting insights, linked contacts, trend data, and source evidence. Initiatives help teams turn opportunities or product questions into structured plans. A team can create an initiative manually or generate one with AI. During generation, Deck searches across relevant insights, themes, subthemes, NPS feedback, tickets, and segments, then writes initiative content with supporting evidence. Initiatives can include a goal, overview, evidence, status, and links back to related opportunities. This closes the loop from raw feedback to product strategy. ### 7. Teams ask questions with AI Deck supports AI-assisted exploration in two ways. Deck Intelligence is the in-app chat assistant. It lets users ask plain-English questions about their feedback, such as "What are enterprise customers complaining about?" or "Which onboarding issues are getting worse?" Responses include citations back to the underlying feedback. Deck also supports MCP, the Model Context Protocol, so external AI assistants and code editors can connect to a Deck organization. Supported clients include Claude Desktop, Claude Code, ChatGPT, Cursor, VS Code, Windsurf, Zed, Codex, and v0 by Vercel. Through MCP, an AI assistant can use Deck tools to explore themes, subthemes, insights, transcripts, sources, NPS, opportunities, and initiatives. Some MCP tools can perform narrow Build actions when the user explicitly asks, such as creating or updating an initiative. ## Main Deck features ### Manage Manage is where teams bring feedback into Deck. This includes interview uploads, transcript uploads, CSV imports, PostHog surveys, Slack sync, support integrations, Notion imports, and other connected tools. ### Visualize Visualize is where teams understand customer feedback. It includes dashboards, themes, subthemes, insights, categories, NPS, contacts, and segment-filtered analysis. ### Build Build is where teams convert feedback into product opportunities and initiatives. It helps teams move from "customers are saying this" to "here is the product work we should consider." ### Deck Intelligence Deck Intelligence is an AI chat assistant inside Deck. It answers questions about an organization's feedback data with citations. ### MCP access MCP access lets external AI assistants use Deck as a customer feedback context source. This is useful when a team wants to ask Claude, ChatGPT, Cursor, Codex, or another assistant to reason from live Deck data. ### Integrations Deck connects with tools where customer feedback already lives, including support platforms, CRMs, Slack, survey tools, meeting tools, Notion, and imports. ### Settings, privacy, billing, and organization controls Deck includes workspace setup, billing, team management, integrations, company context, API access, MCP access, security settings, privacy controls, and NPS configuration. ## Use cases for product managers - Find the top recurring customer pain points before roadmap planning - Compare what different customer segments are asking for - See whether a theme is growing, shrinking, or becoming more negative - Track NPS trends and understand what promoters, passives, and detractors are saying - Convert a high-signal opportunity into an initiative - Generate an initiative brief from customer evidence - Answer stakeholder questions with quotes and citations - Monitor whether recent launches changed customer sentiment - Connect support, research, sales, and survey feedback into one prioritization view Example PM prompts: - "What are the top three product opportunities in Deck right now?" - "Which themes are most negative among enterprise customers?" - "What customer evidence supports improving onboarding?" - "Which opportunities are linked to active initiatives?" - "Summarize the most common feature requests from support tickets." - "What changed in customer feedback this week?" ## Use cases for designers and researchers - Upload interview recordings, audio, video, or transcripts for synthesis - Extract and review insights from interviews without manually tagging every quote - Trace insights back to transcript passages or source conversations - Identify usability issues and repeated experience problems - Compare feedback across segments, such as new users, enterprise accounts, or churned customers - Find representative quotes for research readouts or design reviews - Track whether design changes improve sentiment over time - Keep research findings connected to roadmap opportunities and initiatives Example design and research prompts: - "What usability issues appear most often in recent interviews?" - "Show me quotes about onboarding confusion." - "Which subthemes exist inside the Onboarding Experience theme?" - "What are detractors saying about the setup flow?" - "What evidence should I review before redesigning the dashboard?" - "How do enterprise users describe this workflow compared with SMB users?" ## Use cases for support, success, and sales teams - Turn support tickets into product insights - Find repeated product gaps mentioned by customers - Identify bugs and usability issues that create support demand - Understand customer sentiment by account, segment, or source - Link conversations back to unified contacts and CRM accounts - Surface sales-call objections and product requests - Share evidence with product teams without writing manual summaries Example customer-facing team prompts: - "What support issues are creating repeated frustration?" - "Which customer accounts are connected to this opportunity?" - "What feature requests are coming from sales calls?" - "Which Zendesk or Intercom conversations support this theme?" - "What are churn-risk customers complaining about?" ## What makes Deck useful for AI agents Deck is designed to keep customer feedback structured, source-backed, and queryable. That makes it useful for AI agents because the agent can reason from organized customer evidence instead of loose notes. Important concepts for AI agents: - Insights are the smallest structured feedback unit. - Themes group related insights into larger product topics. - Subthemes break themes into more specific recurring patterns. - Categories classify the type of feedback. - Sentiment shows the tone of a feedback item or group. - Contacts connect feedback to people. - Segments let teams compare different customer cohorts. - Opportunities represent possible product work backed by customer evidence. - Initiatives represent planned or active product work with supporting evidence. - Citations and source links matter. Deck is most valuable when answers stay connected to the original customer voice. When connected through MCP, an AI assistant should usually start with an overview, then explore themes, insights, subthemes, NPS, sources, opportunities, or initiatives depending on the question. ## Trust, privacy, and limits Deck data is scoped to an organization. AI features and MCP access are designed to operate within the connected organization's data, not across unrelated workspaces. Deck Intelligence is read-only inside the app. MCP exposes read tools and a small set of bounded Build mutation tools. Mutation tools are intentionally narrow and should only be used when the user explicitly asks for an action. AI-generated synthesis should be treated as a decision aid, not a replacement for product judgment. Teams should review important insights, source quotes, and supporting evidence before making major roadmap decisions. Some features depend on plan level, workspace configuration, credits, enabled integrations, and whether enough feedback has been imported. For example, subthemes and NPS analysis may require particular plans or sufficient data. ## A simple mental model Deck turns this: ```text Interviews + tickets + surveys + Slack + NPS + calls + notes + CSVs ``` into this: ```text Sources -> contacts -> insights -> themes -> subthemes -> opportunities -> initiatives ``` and makes it explorable through: ```text Dashboard + Visualize pages + Build pages + Deck Intelligence + MCP for AI agents ``` ## Good questions to ask an AI agent using this page - "Explain Deck to a new product manager." - "How does Deck turn raw customer feedback into product opportunities?" - "What should a designer use Deck for during a redesign project?" - "What is the difference between insights, themes, subthemes, opportunities, and initiatives?" - "What data sources can Deck analyze?" - "How should a team use Deck during weekly product planning?" - "How can Deck help us connect NPS, support tickets, and interviews?" - "What Deck features should I use to understand enterprise customer pain points?" - "How does Deck keep AI answers tied to customer evidence?" - "How can Claude or ChatGPT use Deck through MCP?" ## Short summary Deck is a customer feedback intelligence platform. It centralizes feedback, uses AI to extract insights and organize them into themes, helps teams analyze customer signal across segments and sources, and turns that evidence into product opportunities and initiatives. Product managers use it to prioritize and plan, designers and researchers use it to synthesize and validate, and customer-facing teams use it to make support, sales, and success conversations visible to product strategy.