sales-proposal-simulator（销售提案模拟器）

Ads Sales Proposal

Purpose

Core mission:

• proposal architecture, objection handling, closing path

This skill is specialized for advertising workflows and should output actionable plans rather than generic advice.

When To Trigger

Use this skill when the user asks for:

• ad execution guidance tied to business outcomes
• growth decisions involving revenue, roas, cpa, or budget efficiency
• platform-level actions for: Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, Shopify Ads
• this specific capability: proposal architecture, objection handling, closing path

High-signal keywords:

• ads, advertising, campaign, growth, revenue, profit
• roas, cpa, roi, budget, bidding, traffic, conversion, funnel
• meta, googleads, tiktokads, youtubeads, amazonads, shopifyads, dsp

Input Contract

Required:

• client_request: what the client wants to achieve
• business_context: product, margin, seasonality
• offer_scope: service package or campaign scope

Optional:

• objections
• competitor_reference
• contract_constraints
• expected_start_date

Output Contract

1. Proposal Positioning
2. Scope and Deliverables
3. ROI Logic and KPI Commitment Range
4. Objection Handling Script
5. Close Plan with next steps

Workflow

1. Summarize client objective and urgency.
2. Translate objective into measurable ad outcomes.
3. Build value argument and risk controls.
4. Prepare objection responses and confidence proof.
5. Output a close-ready proposal structure.

Decision Rules

• If goal is vague, anchor on one north-star KPI first.
• If budget is low, propose phased pilot with strict milestone gates.
• If trust is low, lead with transparent assumptions and reporting cadence.

Platform Notes

Primary scope:

• Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, Shopify Ads

Platform behavior guidance:

• Keep recommendations channel-aware; do not collapse all channels into one generic plan.
• For Meta and TikTok Ads, prioritize creative testing cadence.
• For Google Ads and Amazon Ads, prioritize demand-capture and query/listing intent.
• For DSP/programmatic, prioritize audience control and frequency governance.

Constraints And Guardrails

• Never fabricate metrics or policy outcomes.
• Separate observed facts from assumptions.
• Use measurable language for each proposed action.
• Include at least one rollback or stop-loss condition when spend risk exists.

Failure Handling And Escalation

• If critical inputs are missing, ask for only the minimum required fields.
• If platform constraints conflict, show trade-offs and a safe default.
• If confidence is low, mark it explicitly and provide a validation checklist.
• If high-risk issues appear (policy, billing, tracking breakage), escalate with a structured handoff payload.

Code Examples

Proposal Skeleton

section: Objective section: Channel Plan section: Budget and KPI Range section: Risks and Mitigation section: Next-step Commitment

Objection Response Map

objection: "CPA too high" response: "Pilot 14 days with capped budget and clear stop-loss"

Examples

Example 1: Performance growth proposal

Input:

• Client wants lower CPA in 30 days
• Current channels: Meta + Google Ads

Output focus:

• pilot scope
• KPI promise range
• close checklist

Example 2: New product launch proposal

Input:

• Client has no baseline data
• Wants global ads rollout

Output focus:

• phased contract scope
• risk clauses
• reporting cadence

Example 3: Renewal negotiation proposal

Input:

• Existing client doubts ROI
• Needs proof before extension

Output focus:

• retrospective evidence summary
• revised operating model
• signed next-step plan

Quality Checklist

• [ ] Required sections are complete and non-empty
• [ ] Trigger keywords include at least 3 registry terms
• [ ] Input and output contracts are operationally testable
• [ ] Workflow and decision rules are capability-specific
• [ ] Platform references are explicit and concrete
• [ ] At least 3 practical examples are included