---
type: method
slug: objection-handling-playbook
title: "Build an objection-handling playbook"
category: "Sales"
subcategory: "Running the deal"
level: starter
source: https://deepstoryresearch.com/method/objection-handling-playbook
publisher: Deepstory Research
---

> **How to use this file:** attach it to ChatGPT, Claude, Gemini or Copilot (or paste the prompt section), replace every [PLACEHOLDER] with your details, and add any data or Deepstory evidence files the method needs.

## When to use this method
- Deals stall on the same objections.
- Onboarding new sellers.

## Prompt

# Build an objection-handling playbook
Method by Deepstory Research: deepstoryresearch.com/method/objection-handling-playbook

You are a sales enablement lead. Follow the method below step by step. Goal: The top objections with root cause, response framework, proof and follow-up questions.

## My inputs
- Product and price: [PRODUCT_AND_PRICE]  (example: $20k/year analytics platform)
- Common objections: [COMMON_OBJECTIONS]  (example: too expensive, we built it in-house, not now)
- Proof assets: [PROOF_ASSETS]  (example: case studies, ROI data)

Before you start: if any input above is still in [BRACKETS] or missing, ask me for it in one short numbered list and wait. Do not guess. If I attached files (data, briefs, Deepstory evidence files), treat them as the primary source.

## Steps to follow
1. List 8–12 objections, grouped (price, timing, trust, need, competitor).
2. For each: what is really being said, a response (acknowledge, clarify, respond, confirm), proof and a question back.
3. Add a talk track for competitor comparisons.

## Deliver the output in this structure
- Objection table
- Talk tracks
- Proof library mapping

## Quality rules
- Responses must be honest; never disparage competitors with unverified claims.
- Label every number as FACT (with source and date), ESTIMATE (show the calculation) or ASSUMPTION.
- If a Deepstory evidence file is attached, use its figures as the reference values and cite its source references; tag claims that are not from it as [UNVERIFIED].
- End with: the 3 assumptions that matter most, what would change the answer, and the single best next step.

## Evidence you can attach
- E-Commerce Share of US Retail: https://deepstoryresearch.com/data/us-ecommerce-share (AI context file: https://deepstoryresearch.com/context/us-ecommerce-share.md)
- Six-Economy Macro Baseline: https://deepstoryresearch.com/data/global-macro-baseline (AI context file: https://deepstoryresearch.com/context/global-macro-baseline.md)
- UPI vs Visa & Mastercard: India’s Payments Rewiring: https://deepstoryresearch.com/data/upi-vs-cards (AI context file: https://deepstoryresearch.com/context/upi-vs-cards.md)

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Deepstory methods are process guidance for AI tools. Review AI output before relying on it; legal, tax, medical and investment matters need a qualified professional.