The “Custom GPT” Sales Assistant

Build a custom GPT trained on your company's products, processes, and playbooks to serve as an always-available sales assistant for your team.

Standard Complexity
Owner: Sales Enablement / RevOps
Updated Jan 2025
Workflow overview diagram

Workflow overview

Download diagram

Trigger

Rep asks a question via Slack, chat, or GPT interface

Inputs

Product documentation, sales playbooks, competitive intel, objection handling, pricing

Output

Instant answers, email drafts, objection responses, competitive comparisons

Success Metrics

Questions answered instantly, reduced enablement ticket volume, higher rep confidence

Overview

What It Is

A custom-trained GPT assistant that knows your products, pricing, competitors, processes, and playbooks intimately, enabling sales reps to get instant answers to any question without searching through documentation or waiting for enablement.

Why It Matters

Sales reps spend 30%+ of time on non-selling activities, much of it searching for information. A custom GPT provides instant, accurate answers—reducing time to information from minutes to seconds and ensuring consistency across the team.

Who It's For

  • Sales reps needing quick answers mid-call
  • New reps ramping on product knowledge
  • Sales leaders ensuring consistent messaging
  • Enablement teams scaling their impact

Preconditions

Required Tools

  • OpenAI GPTs (or similar platform)
  • Notion/Confluence (knowledge base)
  • Google Drive (documents)
  • Slack (optional, for integration)

Required Fields/Properties

  • Product documentation
  • Pricing and packaging
  • Competitive intelligence
  • Sales playbooks and methodologies
  • Case studies and proof points

Definitions Required

  • Scope of assistant (what it should/shouldn't answer)
  • Escalation path for unknown questions
  • Confidentiality rules
  • Update frequency for knowledge base

Step-by-Step Workflow

1

Gather and Structure Knowledge Base

Goal: Compile all sales knowledge into assistant-ready format

Actions:

  • Export product documentation
  • Compile competitive battle cards
  • Gather objection handling guides
  • Include pricing and packaging details
  • Add sales process and methodology docs

Implementation Notes: Quality of assistant depends on quality of inputs. Structure documents clearly with headers. Remove outdated content. Mark confidential information.

2

Configure Custom GPT

Goal: Create and configure the GPT with proper instructions

Actions:

  • Create new GPT in OpenAI
  • Upload knowledge base documents
  • Write detailed system instructions
  • Configure conversation style and boundaries

Implementation Notes: System instructions are critical. Be explicit about what assistant should and shouldn't do. Include examples of good responses.

3

Build Common Use Case Prompts

Goal: Create quick-access prompts for frequent scenarios

Actions:

  • Objection handling prompts
  • Competitive comparison prompts
  • Email drafting prompts
  • Call prep prompts
  • Demo customization prompts

Implementation Notes: Provide conversation starters that guide reps to effective queries. Include variables for context (prospect name, competitor, objection).

4

Integrate with Slack

Goal: Enable assistant access without leaving Slack

Actions:

  • Create Slack app/bot
  • Connect to GPT API
  • Set up DM and channel access
  • Configure response formatting for Slack

Implementation Notes: Slack integration makes assistant available in the flow of work. Support both DM (private questions) and channel mentions (team questions).

5

Implement Knowledge Base Updates

Goal: Keep assistant current with latest information

Actions:

  • Set up automated knowledge sync
  • Create update process for new content
  • Build feedback loop for incorrect answers
  • Schedule regular knowledge audits

Implementation Notes: Stale information is worse than no information. Automate syncs from source documents. Have process for reps to flag outdated content.

6

Launch and Train Team

Goal: Roll out assistant and ensure adoption

Actions:

  • Create user guide and quick prompts
  • Run training session with team
  • Set up feedback collection
  • Monitor usage and iterate

Implementation Notes: Adoption requires change management. Show concrete time savings. Celebrate early wins. Iterate based on feedback.

Templates

Sales Assistant User Guide

# Sales Assistant Quick Guide

## How to Access
- **Slack:** DM @SalesAssistant or mention in any channel
- **Web:** chat.company.com/sales-assistant
- **ChatGPT:** Search 'Company Sales Assistant' in GPT store

## Best Practices
1. Be specific with your question
2. Include context (company, industry, competitor)
3. Ask for format you need (bullets, email, table)
4. Follow up if answer doesn't address your need

## Example Prompts
- "How do we compare to Competitor X for enterprise security?"
- "Draft a follow-up email after a demo with a CFO"
- "What case studies do we have for healthcare?"
- "Handle objection: 'Your pricing is too high'"

## What It Can't Do
- Access CRM data (use CRM directly)
- Provide legal/compliance advice
- Share confidential strategy docs
- Make pricing commitments

Feedback Collection Form

**Sales Assistant Feedback**

1. What question did you ask?
_______________

2. Was the answer:
[ ] Accurate and helpful
[ ] Accurate but incomplete
[ ] Inaccurate
[ ] Didn't have the information

3. If inaccurate or incomplete, what was wrong/missing?
_______________

4. Rate usefulness (1-5): ___

5. Additional feedback:
_______________

[Submit to #sales-assistant-feedback]

Weekly Assistant Usage Report

| Metric | This Week | Last Week | Trend |
|--------|-----------|-----------|-------|
| Total Queries | 342 | 298 | +15% |
| Unique Users | 24/30 | 22/30 | +9% |
| Avg Queries/User | 14.3 | 13.5 | +6% |
| Satisfaction Score | 4.3/5 | 4.1/5 | +5% |
| Feedback Submitted | 18 | 12 | +50% |
| Knowledge Gaps Found | 3 | 5 | -40% |

QA + Edge Cases

Test Cases Checklist

  • Verify assistant answers product questions accurately
  • Test competitive comparisons against battle cards
  • Confirm assistant refuses to make up information
  • Validate Slack integration responds correctly
  • Test edge cases (ambiguous questions, out of scope)

Common Failure Modes

  • Hallucination: GPT makes up features or facts. Add explicit instruction to say 'I don't know' and cite sources.
  • Stale information: Knowledge base not updated, answers outdated. Automate sync and add last-updated dates.
  • Low adoption: Team doesn't use it. Run training, share success stories, integrate into daily workflows.

Troubleshooting Tips

  • If answers are too long, add instruction for concise responses
  • For inconsistent answers, improve document structure and reduce ambiguity
  • If reps don't use it, embed in Slack where they already work

KPIs and Reporting

KPIs to Track

  • Daily Active Users: >80% of sales team
  • Queries per User per Week: >10
  • Answer Accuracy: >95% accurate
  • Time Saved per Query: >5 minutes

Suggested Dashboard Widgets

  • Usage Trend: Queries per day over time
  • Top Query Categories: What reps ask most about
  • User Adoption: Active users vs. total team
  • Satisfaction Score: Average rating from feedback

Want This Implemented End-to-End?

If you want this playbook configured in your stack without the learning curve:

  • Timeline: Week 1: Knowledge base prep. Week 2: GPT config + integration. Week 3: Launch + training.
  • Deliverables: Custom GPT, Slack integration, user guide, feedback system
  • Handoff: Enablement owns content updates; RevOps monitors usage; team uses daily
Request Implementation
Jump to Steps Implement