Next Content Plan (Global)

SkillDev tools

Use when the next period content plan must be built from last period DATA — keep and replicate winners, cut losers, at most two new hypotheses, a 70/20/10 mix, a four-week overview, and an owner per slot. Trigger on 'next content plan', 'content plan for next month', 'plan from the audit', 'what should we post next quarter', 'scale what worked', 'plan content using the numbers'. Also use when a report just landed and the user asks what to do with it. Not for — auditing the past period first, see `39-content-audit-global`; turning the plan into a dated calendar, see `01-content-calendar-global`; the next period ADS plan, see `57-next-ads-plan-global`.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Next Content Plan (Global) skill

What this skill tells your AI

The instructions your AI receives, as published by minhnv0807/ai-business-skills in skills/en/40-next-content-plan-global/SKILL.md and read by ahel’s review.

A plan without last period's data is a guess. The order is fixed: read the data, replicate the winners, test a small number of new hypotheses, then schedule. Do not change everything at once — a team that rebuilds from scratch every period never learns what works.

Information gathering — always read the old data first

Before writing a single line of plan, you need:

  1. The prior period's content audit (from 39-content-audit-global). If it does not exist, run that skill first. Do not plan around it.
  2. The prior period's report (from 07-marketing-report-global) if available.
  3. KPI targets for the new period — what changes versus last period.
  4. Known variables in the new period: upcoming campaign, launch, event, seasonality; changes in budget, headcount, or capacity.

If the user cannot supply at least an audit or a post list with metrics, stop and recommend running 39-content-audit-global first.

Principles

  1. Data first, plan second. Every change in the plan must trace back to a specific line of prior-period data.
  2. Replicate winners before chasing new ideas. A winner has already proved itself. Reproduce it with small variations before betting on an untested concept.
  3. The 70/20/10 split:
    • 70 percent of output is proven format plus proven angle — the winner's formula, held constant.
    • 20 percent is optimization of a winner — change the hook, the channel, or the length while keeping what worked.
    • 10 percent is genuinely new — the test hypotheses.
  4. Maximum 2 new hypotheses per period. More than that and no single test accumulates enough data to conclude anything.
  5. Losers are not automatically deleted. Separate a loser caused by a wrong angle (retire it) from a loser caused by weak execution (fix the execution, try once more).
  6. Plan at the week level here. Day-level detail belongs to 01-content-calendar-global.
  7. Account for seasonality in paid amplification. Q4 media costs run well above Q1 globally; if a proven post type is normally boosted, the same plan costs more in November than in January (see references/benchmarks-global.md).

Workflow

1. Review the prior period

From the audit (39-content-audit-global) and report (07-marketing-report-global), fill three columns:

Worked (KEEP)Did not work (STOP)Not yet tried (TEST)
[format / angle / channel + the numbers that prove it][+ the data reason][idea from a pattern or a new insight]

2. Set the direction for the new period

PeriodPrimary objectivePriority KPIAttached campaignMajor change

Exactly one primary objective — reach, lead generation, conversion, or retention. The priority KPI is the metric this period will actually be judged on.

3. Build the content mix at 70/20/10

GroupShareContent
Proven (70%)~70% of postsWinner formula held constant — only the subject changes
Optimized (20%)~20% of postsVariations on winners: different hook, channel, or length
Experimental (10%)~10% of postsNew hypotheses (maximum 2)

Then adjust the funnel and format ratios, with a data reason for each change:

DimensionPrior period ratioNew period ratioReason (from data)
TOFU / MOFU / BOFU
Video vs static vs text
Channel split

4. Plan the winner replication

Original winnerResult (metric)Replicate intoWhat changesChannel / timing

Each winner becomes 2-3 variations. Hold the hook structure and format constant; change the subject, the angle of the shot, or the person on camera.

5. Define the new hypotheses (maximum 2)

HypothesisFormatChannelMetricTest durationDecision rule

Write each one so it can be falsified: "If we [change X], then [metric Y] will [rise or fall by Z percent]." For test design and sample sizing, hand off to 19-ab-test-setup-global.

6. Build the overview calendar and assign ownership

WeekThemePriority channelPostsHighlights (replicated winner / hypothesis)
Week 1
Week 2
Week 3
Week 4
OwnerResponsibilityPosts per weekPrimary channel

Day-level detail (publish time, hook, CTA, status) goes to 01-content-calendar-global. Per-piece briefs go to 36-content-brief-global.

Output structure

File name: next-content-plan-[brand]-[YYYYMMDD].md

# Next Content Plan — [Period] — [Brand]

## I. Prior period review
| Worked (keep) | Did not work (stop) | Not yet tried (test) |
|---------------|---------------------|----------------------|
| | | |

## II. Direction for the new period
| Period | Primary objective | Priority KPI | Attached campaign | Major change |
|--------|-------------------|--------------|-------------------|--------------|
| | | | | |

## III. Content mix — 70/20/10
| Group | Share | Posts | Content |
|-------|-------|-------|---------|
| Proven (70%) | | | |
| Optimized (20%) | | | |
| Experimental (10%) | | | |

| Dimension | Prior ratio | New ratio | Reason (from data) |
|-----------|-------------|-----------|--------------------|
| TOFU / MOFU / BOFU | | | |
| Video vs static vs text | | | |
| Channel split | | | |

## IV. Winner replication
| Original winner | Result | Replicate into | What changes | Channel / timing |
|-----------------|--------|----------------|--------------|------------------|
| | | | | |

## V. New hypotheses (max 2)
| Hypothesis | Format | Channel | Metric | Test duration | Decision rule |
|------------|--------|---------|--------|---------------|---------------|
| | | | | | |

## VI. Overview calendar
| Week | Theme | Priority channel | Posts | Highlights |
|------|-------|------------------|-------|------------|
| | | | | |

## VII. Ownership
| Owner | Responsibility | Posts per week | Primary channel |
|-------|----------------|----------------|-----------------|
| | | | |

Related skills

  • 39-content-audit-global: required input — run it first. No audit means no plan.
  • 07-marketing-report-global: the prior period's report adds the full-funnel KPI view.
  • 01-content-calendar-global: takes this plan and produces the day-by-day schedule.
  • 36-content-brief-global: briefs each individual piece inside the plan.
  • 19-ab-test-setup-global: designs the tests for the 2 hypotheses.
  • 13-data-analysis-global: supporting analysis when the data needs a deeper look.

Quality checklist

  • Prior period data present as the basis (audit from 39 or report from 07) — nothing planned on instinct.
  • Every change in the plan traces back to a specific line of data.
  • Content mix follows 70/20/10 and the shares total 100 percent.
  • Each winner has a concrete replication plan (2-3 variations each).
  • No more than 2 new hypotheses, each falsifiable and each with a decision rule.
  • Losers separated into wrong angle (retire) versus weak execution (fix and retry once).
  • Funnel and format ratio changes each carry a data reason — nothing changed arbitrarily.
  • Overview calendar covers all 4 weeks with named owners.
  • Seasonality accounted for where the plan depends on paid amplification.
  • Handoffs stated: 01-content-calendar-global for the detailed schedule, 19-ab-test-setup-global for the hypotheses.

Signals

GitHub stars
574
Forks
226
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
x-40-next-content-plan-global
Source
github.com/minhnv0807/ai-business-skills