57-next-ads-plan

Generates a data-driven advertising plan for the next period from prior campaign performance reports.

569|224|Updated Apr 15, 2026
One-click install
npx skills add https://github.com/minhnv0807/ai-business-skills --skill 57-next-ads-plan
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: 57-next-ads-plan
Source: https://github.com/minhnv0807/ai-business-skills/tree/main/skills/vi/57-next-ads-plan
Command: npx skills add https://github.com/minhnv0807/ai-business-skills --skill 57-next-ads-plan

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Planning next month's ad campaigns without data leads to guesswork and wasted budget. This Skill turns last period's performance report into a structured plan: scale winners, stop or fix losers, test new hypotheses, and allocate budget across three scenarios.

Core Features & Use Cases

  • Winner/Loser Review: Classifies creatives, audiences, and channels into keep, stop/fix, and untested buckets with supporting metrics like CPL, ROAS, CTR, and frequency.
  • Budget Allocation with 3 Scenarios: Splits budget across scaling (50%), testing (30%), retargeting (15%), and lookalike (5%), then models bad, baseline, and good scenarios with predefined actions.
  • Hypothesis Testing & Weekly Schedule: Limits new tests to 2-3 hypotheses with defined variables, KPIs, and timelines, plus a 4-week calendar with cumulative KPI checkpoints at 20/45/70/100%.
  • Use Case: At month end, feed last month's marketing report into this Skill to produce a next-month ads plan file with scaling decisions, loser logs, creative pipeline, and scenario-based budgets.

Quick Start

Use the next ads plan skill to build next month's advertising plan from last month's performance report, including winner scaling, loser decisions, new test hypotheses, and a three-scenario budget.

Frequently Asked Questions about 57-next-ads-plan

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create a next month ads plan from campaign data?

Start with last period's performance report covering spend, CPL, ROAS, and leads by channel and creative. Then classify winners to scale by 20-30%, stop or fix losers with logged reasons, define 2-3 new test hypotheses, and allocate budget across scaling, testing, retargeting, and lookalike segments.

What data do I need before planning next period's ads?

You need the prior period's performance report with spend, CPL, ROAS, and lead metrics per campaign and creative, plus any audit findings if performance had issues. You also need the new period's KPI targets, total budget, and any new offers or products to launch.

How much budget should go to testing new ad hypotheses?

Allocate roughly 30% of budget to testing new hypotheses, 50% to scaling proven winners, 15% to retargeting, and 5% to lookalike audiences. Limit new hypotheses to 2-3 per period so each test gathers enough data for a valid conclusion.

When should I stop an underperforming ad set versus fix it?

Stop an ad set when CPL exceeds 2x target for three consecutive days. Fix it instead when CTR drops below 0.5% by changing creative or hook while keeping the audience, or when frequency exceeds 3.5 with declining CTR by refreshing creative and expanding the audience.

When should I use a full media plan instead of a next-period ads plan?

Use a full media plan when starting advertising for the first time without historical data, or when the new period involves major changes like new channels or new offers. The next-period ads plan is designed for iterating on existing campaigns with available performance data.