CoachPulse

Turn every sales call into a coaching plan.

CoachPulse is an AI-powered sales coaching tool for sales managers and RevOps teams. It ingests call transcripts from tools like Gong, Zoom, and Chorus, scores rep performance against a playbook, and generates a concrete improvement plan with next actions, talking points, and coaching priorities. It helps managers coach faster, more consistently, and with better evidence.

Business Goals

  • Increase weekly manager coaching capacity by 30% within 90 days by reducing manual transcript review time.
  • Achieve a 25% conversion rate from trial to paid within 60 days for team-based buyers.
  • Drive 40% of accounts to connect at least one call source and generate three improvement plans in the first week.
  • Reach 90% logo retention at 6 months by making coaching plans part of the team workflow.
  • Reduce time from call completion to actionable coaching plan to under 5 minutes for 95% of processed transcripts.

User Goals

  • Let managers upload or sync a transcript and get a clear rep improvement plan quickly.
  • Show exactly what the rep did well, where they missed opportunities, and what to coach next.
  • Align feedback to the team’s sales methodology so coaching is consistent.
  • Make it easy to share a plan with a rep before the next 1:1.
  • Track whether a rep improved on the next calls after coaching.

Non-Goals

  • Not a full sales CRM or opportunity management system.
  • Not a call recording or transcription engine; it consumes transcripts from other tools.
  • Not a performance review system for HR or compensation decisions.
  • Not real-time live call coaching in the MVP.

Sales Manager Priya, 38 - Priya manages a team of eight SDRs and AEs. She listens to a few calls each week but cannot review every transcript in detail, so she needs fast, evidence-based coaching.

Sales Manager Priya, 38

  • As a sales manager, I want to upload a call transcript and get a prioritized coaching plan, so that I can prepare for my 1:1 in minutes.
  • As a sales manager, I want to see transcript evidence tied to each coaching point, so that my feedback feels credible and specific.
  • As a sales manager, I want to compare a rep’s recent calls against our playbook, so that I can coach to the same standard across the team.

Revenue Ops Lead Daniel, 44 - Daniel owns sales process quality and adoption of the team’s methodology. He needs consistent scoring, analytics, and integration with existing call tools.

Revenue Ops Lead Daniel, 44

  • As a RevOps lead, I want to configure scoring criteria for our methodology, so that the output matches our sales process.
  • As a RevOps lead, I want usage and coaching trend dashboards, so that I can prove the tool is improving manager effectiveness.
  • As a RevOps lead, I want to sync transcripts automatically from our call stack, so that adoption does not depend on manual upload.

Sales Rep Amina, 29 - Amina wants practical feedback after each call, not vague criticism. She needs clear next steps she can act on before her next conversation.

Sales Rep Amina, 29

  • As a sales rep, I want a simple explanation of what I should improve, so that I can change my approach immediately.
  • As a sales rep, I want suggested talk tracks and questions, so that I can practice better discovery and objection handling.
  • As a sales rep, I want to see progress over time, so that I know whether coaching is helping me improve.

Transcript Intake and Sync · High priority

  • Ingest transcripts from manual upload and supported call platforms, then normalize them into a standard analysis format.
  • Accept plain text, .txt, .docx, and pasted transcript input in the MVP.
  • Support OAuth-based sync from Gong and Zoom recordings, with Chorus as a phase 2 integration.
  • Detect speaker turns, timestamps when available, and transcript language before analysis.
  • Reject empty, corrupted, or extremely short transcripts with a clear error message.
  • Store the raw source transcript separately from the normalized analysis copy for traceability.

Coaching Analysis Engine · High priority

  • Analyze the transcript against configurable sales coaching criteria and generate a ranked improvement plan.
  • Score the call on categories such as discovery, objection handling, next-step clarity, talk-to-listen balance, and closing.
  • Generate 3 to 5 prioritized coaching recommendations based on the biggest missed opportunities.
  • Quote transcript excerpts for every recommendation to show evidence.
  • Support multiple playbooks such as MEDDICC and BANT, with a default generic sales rubric.
  • Flag low-confidence outputs and show a warning when transcript quality is poor or missing context.

Improvement Plan Builder · High priority

  • Convert analysis into a structured, shareable plan with goals, actions, and practice prompts.
  • Create an action plan with strengths, gaps, next steps, and recommended practice exercises.
  • Allow managers to edit, reorder, or remove AI-generated recommendations before sharing.
  • Generate a rep-facing summary in plain language and a manager-facing coaching version with more detail.
  • Include specific questions the manager can ask in the next 1:1.
  • Let users export the plan as PDF or share via a private link.

Team Configuration and Scoring Rules · Medium priority

  • Let admins define how calls are scored and what good looks like for the team.
  • Provide a rubric editor for categories, weights, and custom coaching tags.
  • Allow per-team templates for SDR, AE, and enterprise account management roles.
  • Support mandatory review criteria such as mention of next steps or business pain discovery.
  • Version scoring templates so historical plans retain the rubric used at the time.
  • Allow role-based permissions for admins, managers, and reps.

Reporting and Feedback Loop · Medium priority

  • Track usage and coaching outcomes so teams can measure adoption and improvement.
  • Show dashboards for call volume analyzed, plan completion, and review status.
  • Track repeated gaps by rep and by team to identify training themes.
  • Capture rep feedback on whether the coaching plan was useful.
  • Display trend lines for each rubric dimension across the last 30, 60, and 90 days.
  • Allow CSV export for RevOps analysis.

Fast First Analysis

  • Sign in with Google or Microsoft, or start with a demo transcript.
  • Connect Gong or Zoom, or paste a transcript manually.
  • Choose a team playbook such as MEDDICC or use the default rubric.
  • Submit the transcript and see a processing status with a 2 minute target for first-time value.
  • Review the generated coaching plan, edit it if needed, and share it with the rep.
  • Save the plan to the team workspace for later review and trend tracking.

1. Ingest Transcript

  • The user provides a transcript through upload, paste, or sync from a connected source.
  • Validate file type, transcript length, and basic speaker structure before analysis.
  • Show clear retry guidance if the transcript is too short or unreadable.
  • Preserve the original transcript for auditability and later reprocessing.

2. Analyze Call Quality

  • The system evaluates the transcript against the chosen rubric and identifies evidence-backed coaching opportunities.
  • Surface a score summary and the top three problem areas first.
  • Highlight exact transcript snippets supporting each finding.
  • If the model confidence is low, flag uncertain recommendations instead of overstating them.

3. Generate Improvement Plan

  • The system turns analysis into an actionable coaching plan for the rep and manager.
  • Include strengths, gaps, next actions, and practice prompts.
  • Allow the user to adjust emphasis, for example focusing on objection handling over discovery.
  • Keep the plan concise enough for a 1:1, with an expandable detail view.

4. Review and Edit

  • The manager can refine the output before sharing it with the rep.
  • Support inline editing of any recommendation or title.
  • Show change tracking so the user can see what came from the AI versus manual edits.
  • Prevent sharing if the manager deletes all coaching actions by prompting for at least one next step.

5. Share and Track

  • The plan is shared and then monitored for completion and improvement over time.
  • Generate a private share link and optional email summary.
  • Record whether the rep viewed the plan and whether the manager marked it complete.
  • Link follow-up calls to the original plan to measure improvement.

Power Features and Edge Cases

  • Bulk transcript import for weekly coaching reviews.
  • Team-level benchmark comparisons by role, region, or manager.
  • Custom coaching tags for objections, competitor mentions, and next-step quality.
  • Language detection and support for non-English transcripts in a later phase.
  • Fallback manual scoring mode for transcripts that cannot be parsed cleanly.
  • Anonymization controls for sensitive customer names in shared summaries.

Clear, Coach-Friendly Interface

  • Use a three-panel layout with transcript, score summary, and coaching plan for easy review.
  • Highlight evidence in context with clickable transcript quotes and timestamps.
  • Keep the plan readable on desktop and mobile for pre-meeting review.
  • Use high-contrast status colors and accessible text sizes for managers in fast-paced environments.
  • Render analysis quickly with skeleton states and progressive loading so users see value before all details finish.

Priya manages a team of SDRs and used to spend Sunday evenings skimming transcripts and writing coaching notes by hand. She often ended up coaching the same missed discovery questions repeatedly, but the feedback was inconsistent because it depended on how much time she had that week.

With CoachPulse, she connects Gong, selects the team playbook, and gets a transcript-based improvement plan in minutes. The plan shows the exact moments where the rep missed an opportunity, suggests better questions to ask, and turns the 1:1 into a focused coaching session instead of a vague review.

Over time, Priya sees the same coaching gaps across the team and uses the dashboard to target training. Her reps get faster, more specific feedback, managers save hours every week, and leadership gets proof that coaching quality is improving.

User-Centric Metrics

  • 90% of generated plans are opened by the assigned rep within 7 days.
  • At least 70% of plans receive a manager edit or approval before sharing.
  • Average time to first usable coaching plan is under 5 minutes.
  • At least 60% of users rate the plan as helpful or very helpful.
  • Rep follow-up completion rate reaches 50% within 14 days of plan creation.

Business Metrics

  • Trial to paid conversion reaches 25% within 60 days.
  • Monthly active team retention stays above 85% after 3 months.
  • Net revenue retention reaches 110% within 12 months through team expansion.
  • At least 40% of customers add a second team or manager within 6 months.
  • Reduce customer churn attributed to low adoption below 10% annually.

Technical Metrics

  • System uptime stays above 99.9%.
  • P95 transcript analysis latency stays under 90 seconds for transcripts under 30 minutes.
  • Authentication and data access are fully audited with zero critical security findings per quarter.
  • Failed transcript processing rate stays below 1% excluding bad input files.

Tracking Plan

  • track transcript_ingested with source, file type, and transcript length.
  • track analysis_started with playbook type and team id.
  • track analysis_completed with latency, confidence, and score summary.
  • track coaching_plan_generated with recommendation count and category breakdown.
  • track coaching_plan_edited with fields changed and time to edit.
  • track coaching_plan_shared with channel and recipient role.
  • track rep_feedback_submitted with usefulness rating and comment length.

Technical Needs

  • Frontend in Next.js with TypeScript for a fast SaaS interface.
  • Backend API in Node.js with NestJS or Express for transcript ingestion and orchestration.
  • AI analysis layer using OpenAI or Anthropic APIs with a structured JSON output schema.
  • PostgreSQL for core app data, plans, users, and rubric configuration.
  • Object storage such as AWS S3 for raw transcript files and exported PDFs.
  • Background jobs using BullMQ or Temporal for long-running transcript processing.
  • Observability with OpenTelemetry, Datadog, or Sentry for tracing and error monitoring.

Integration Points

  • Google OAuth and Microsoft OAuth for user sign-in.
  • Gong API for transcript and call metadata sync.
  • Zoom API for transcript and recording ingestion.
  • Slack for optional coaching plan notifications.
  • SendGrid or Postmark for email sharing and plan delivery.

Data Storage & Privacy

  • Encrypt transcript content and generated plans at rest and in transit.
  • Separate tenant data by organization with strict row-level authorization.
  • Provide data retention controls so admins can delete transcripts and derived plans.
  • Support GDPR and CCPA deletion requests for personal data in transcripts and metadata.
  • Mask or redact sensitive fields in shared summaries when configured by an admin.

Scalability & Performance

  • Use asynchronous processing so transcript uploads do not block the UI.
  • Cache rubric templates and recent plans to keep dashboard loads under 2 seconds.
  • Scale workers horizontally for analysis spikes after batch imports.
  • Set size limits and chunking for very long transcripts to avoid model and memory failures.

Potential Challenges

  • Transcript quality may be poor or incomplete; mitigate with validation, confidence scoring, and user warnings.
  • AI recommendations may feel generic; mitigate with customizable rubrics and evidence-linked outputs.
  • Privacy concerns around call content; mitigate with strong access control, encryption, and deletion tools.
  • Integration failures with call platforms; mitigate with retries, webhook monitoring, and manual upload fallback.
  • Managers may not adopt the workflow; mitigate with fast time-to-value, editable plans, and lightweight sharing.

Team & resourcing - Small team - 2 engineers, 1 product designer, 1 AI/ML engineer shared part-time, part-time PM.

Phase 1: MVP Transcript-to-Plan · Weeks 1-4

  • Manual transcript paste and file upload
  • Single default sales rubric
  • AI-generated coaching summary with evidence quotes
  • Editable improvement plan view
  • Basic auth and organization workspace

Phase 2: Sync and Sharing · Weeks 5-8

  • Gong and Zoom integrations
  • Private share links and email export
  • PDF export
  • Manager/reps role permissions
  • Usage analytics and event tracking

Phase 3: Team Configuration · Weeks 9-12

  • Rubric editor and scoring weights
  • Playbook templates for SDR and AE teams
  • Rep feedback capture
  • Trend dashboards by manager and team
  • CSV export for RevOps

Phase 4: Scale and Reliability · Weeks 13-16

  • BullMQ or Temporal job orchestration
  • Improved confidence scoring and error handling
  • Performance tuning for long transcripts
  • Retention and deletion controls
  • Expanded monitoring and alerting

Paste this into Cursor, Bolt, Lovable, or v0 to start building.

Build a SaaS web app called CoachPulse that turns sales call transcripts into actionable improvement plans for sales managers and RevOps teams.

Core product:
Users can sign in, upload or paste a transcript, or sync call transcripts from Gong and Zoom. The app analyzes the transcript against a configurable sales coaching rubric, highlights evidence-backed issues and strengths, and generates a shareable improvement plan for the rep and manager.

Primary screens/flows:
1. Auth and org setup
2. Transcript intake page with paste/upload/sync options
3. Analysis progress state with job status
4. Results page with transcript evidence, scores, and AI recommendations
5. Editable improvement plan page with share/export actions
6. Team settings page for rubric configuration and roles
7. Simple dashboard for recent plans, usage, and rep feedback

Data model:
Organization, User, Role, Team, TranscriptSource, Transcript, AnalysisJob, RubricTemplate, RubricCategory, CoachingPlan, PlanItem, EvidenceSnippet, ShareLink, RepFeedback, AuditLog.
Each transcript belongs to one org and optionally one team. Each analysis job produces one coaching plan with multiple plan items and evidence snippets. Rubrics are versioned.

Requirements:
Use Next.js + TypeScript for the frontend and API routes, PostgreSQL with Prisma for persistence, S3 for raw transcript files and exports, and a job queue such as BullMQ or Temporal for background analysis. Use OpenAI or Anthropic to generate structured JSON output from the transcript and rubric. Add Google and Microsoft OAuth, role-based access control, secure file handling, audit logs, and responsive UI.

UX details:
Make the transcript-to-plan workflow feel fast, with a clear progress indicator and a target of under 5 minutes to first useful output. Show transcript quotes next to each recommendation. Support empty/invalid transcript validation, low-confidence warnings, editable AI output, private share links, PDF export, and team dashboards.

Implementation notes:
Create clean, production-ready components and a polished B2B UI. Include sensible seed data, a default sales rubric, and mocked integration adapters for Gong and Zoom if real API keys are unavailable. Focus on a working MVP first, but structure the code so integrations, custom rubrics, and analytics can be expanded later.

Business Idea

Rate your sales people turn a transcript into an improvement plan

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