sales-ads-helper

Parse client URLs and requirements to generate ad proposals, ROI estimates, persuasion logic, and CRM-based close probability forecasting for Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, and Shopify Ads services.

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Install skill "sales-ads-helper" with this command: npx skills add danyangliu-sandwichlab/sales-ads-helper

Sales Helper

Purpose

Core mission:

  • Convert customer URL and needs into a launch proposal and ROI estimate.
  • Output persuasion strategy and closing logic.
  • Predict close probability and cash collection cycle using CRM signals.
  • Generate sales daily follow-up and retrospective reports.

When To Trigger

Use this skill when the user asks for:

  • proposal drafting for ads services
  • ROI estimate for prospect conversion
  • close strategy for uncertain deals
  • daily sales report or follow-up summary

High-signal keywords:

  • sales, sell, closer, leads, customers
  • ads, campaign, roi, roas, cpa
  • report, dashboard, revenue, acquire

Input Contract

Required:

  • prospect_url
  • prospect_need_summary
  • proposed_service_scope
  • crm_stage_data

Optional:

  • historical_win_rate
  • contract_terms
  • payment_terms
  • competitor_quote

Output Contract

  1. Proposal Summary (scope + value)
  2. ROI Estimate (assumptions + model)
  3. Persuasion and Objection Strategy
  4. Close Probability and Collection Cycle Forecast
  5. Sales Daily/Follow-up/Retrospective Template

Workflow

  1. Parse URL and infer business model.
  2. Map pain points to ads service package.
  3. Build ROI estimate with explicit assumptions.
  4. Choose persuasion path by decision-maker type.
  5. Score deal probability from CRM stage features.
  6. Output follow-up and close action list.

Decision Rules

  • If prospect urgency is high, prioritize short pilot with rapid proof plan.
  • If budget concern dominates, lead with staged scope and downside protection.
  • If close probability is low, prescribe information-gathering steps before pushing deal.
  • If payment risk is high, optimize term structure before scaling scope.

Platform Notes

Primary scope:

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

Platform behavior guidance:

  • Proposals should tie channel choice to measurable business outcome.
  • Keep ROI model channel-aware, not one blended black-box number.

Constraints And Guardrails

  • Never fabricate past case studies or performance numbers.
  • Keep ROI estimates assumption-driven and auditable.
  • Separate sales narrative from guaranteed delivery claims.

Failure Handling And Escalation

  • If CRM stage data is missing, return low-confidence range and required fields.
  • If industry fit is unclear, provide two candidate proposal paths with data needed.
  • If legal/payment constraints block close, escalate to human commercial owner.

Code Examples

ROI Estimate Payload

{
  "service_fee": 12000,
  "planned_spend": 50000,
  "assumed_roas": 2.4,
  "projected_revenue": 120000,
  "gross_profit_estimate": 36000
}

Close Probability Formula

close_score = stage_weight + urgency_score + budget_fit + stakeholder_alignment
if close_score >= 75: close_probability = "high"

Examples

Example 1: New inbound lead

Input:

  • URL submitted + basic requirement

Output focus:

  • first proposal draft
  • ROI estimate range
  • next follow-up question

Example 2: Stalled opportunity

Input:

  • Deal stuck in negotiation
  • Objection: ROI uncertainty

Output focus:

  • persuasion strategy
  • revised offer structure
  • close plan

Example 3: Sales daily report

Input:

  • CRM updates for 12 opportunities

Output focus:

  • probability movement
  • expected cash collection window
  • rep action priorities

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

Source Transparency

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