Performance Marketing skill 02 of 13
Media Planning and Budget Allocation SKILL.md
The Media Planning and Budget Allocation skill makes Claude, Codex or another AI agent build media plans from unit economics. It sets the maximum new-customer CAC from margin, lifetime value and payback, baselines each channel with evidence labels, estimates diminishing returns, assigns channel roles, builds conservative, expected and stretch scenarios, plans pacing and reallocation rules and ring-fences a test budget.
media-planning-budgeting/SKILL.md, version 1.0.0, 1,687 words.
By Afeez Adebayo, Marketing, SEO & Growth Expert with 10+ years of experience.
Created 10 October 2026. Updated 10 October 2026. Free to use under CC BY 4.0.
Most media plans are last year's split with a percentage added, or whatever each platform's dashboard says is working best. Both approaches reward channels that are good at claiming credit rather than channels that add customers. A sound plan starts from business goals and unit economics, sets how much the business can pay for a customer, allocates across channels using the best evidence available and keeps budget aside to test.
This skill builds media plans and budget allocations for paid search, shopping, paid social, video, retail media and affiliates, with scenarios, pacing and a test budget.
Operating principles
- Start with economics. Gross margin, lifetime value and payback period set the maximum cost per customer.
- Plan for incremental customers, not platform conversions.
- Respect diminishing returns. The next pound in a channel usually returns less than the last one.
- Fund the full funnel deliberately. Demand creation and demand capture work together; cutting one often hurts the other later.
- Ring-fence testing. Keep 10 to 20% of budget for experiments so the plan improves each quarter.
Unit economics first
| Input | Example | Use |
|---|---|---|
| Average order value or contract value | £85 | Revenue per conversion |
| Gross margin | 55% | Profit before marketing |
| Repeat purchases in 12 months | 1.6 orders | Lifetime value |
| 12-month gross profit per customer | £85 × 1.6 × 55% ≈ £75 | Ceiling for acquisition cost |
| Target payback | 6 months | How much of that value you can spend up front |
| Maximum new-customer CAC | Depends on payback and cash | Sets bids and budgets |
When to use, and when not to
Use it for annual and quarterly planning, launching in a new market, adding a channel, when growth stalls, and when finance asks how much to spend.
Don't use it to run a specific channel (use the channel skills) or to measure incrementality in depth (incrementality-testing, marketing-mix-modelling).
Inputs to ask for, in one message
- Business goals for the period: revenue, new customers, profit, market share.
- Unit economics: order or contract value, margins, repeat rate, LTV, payback target.
- Spend and results by channel for 12 to 24 months, monthly.
- Any incrementality evidence: lift tests, geo tests, MMM.
- Seasonality and planned launches or promotions.
- Constraints: cash, minimum spends, contracts, team capacity.
Raw SKILL.md file
This is the exact file agents read, including the credit header and licence notice. Save it as media-planning-budgeting/SKILL.md.
--- name: media-planning-budgeting description: "Build media plans and budget allocations from unit economics: maximum new-customer CAC from margin, lifetime value and payback, channel baselines labelled by evidence, response curves and diminishing returns, channel roles across search, shopping, social, video, retail media and affiliates, scenarios, pacing, reallocation rules and a ring-fenced test budget. Use whenever someone asks how much to spend on ads, how to split budget across channels, a media plan, marketing budget allocation, CAC targets, payback period, or how to scale paid media profitably." license: CC-BY-4.0 metadata: author: Afeez Adebayo author_url: https://afeezadebayo.com author_linkedin: https://www.linkedin.com/in/afeez-adebayo/ author_x: https://x.com/za_icon source: https://afeezadebayo.com/skills-md/marketing/performance-marketing/media-planning-budgeting/ category: marketing subcategory: performance-marketing version: "1.0.0" created: "2026-10-10" updated: "2026-10-10" --- # Media Planning and Budget Allocation Most media plans are last year's split with a percentage added, or whatever each platform's dashboard says is working best. Both approaches reward channels that are good at claiming credit rather than channels that add customers. A sound plan starts from business goals and unit economics, sets how much the business can pay for a customer, allocates across channels using the best evidence available and keeps budget aside to test. This skill builds media plans and budget allocations for paid search, shopping, paid social, video, retail media and affiliates, with scenarios, pacing and a test budget. ## Operating principles 1. **Start with economics.** Gross margin, lifetime value and payback period set the maximum cost per customer. 2. **Plan for incremental customers,** not platform conversions. 3. **Respect diminishing returns.** The next pound in a channel usually returns less than the last one. 4. **Fund the full funnel deliberately.** Demand creation and demand capture work together; cutting one often hurts the other later. 5. **Ring-fence testing.** Keep 10 to 20% of budget for experiments so the plan improves each quarter. ## Unit economics first | Input | Example | Use | |---|---|---| | Average order value or contract value | £85 | Revenue per conversion | | Gross margin | 55% | Profit before marketing | | Repeat purchases in 12 months | 1.6 orders | Lifetime value | | 12-month gross profit per customer | £85 × 1.6 × 55% ≈ £75 | Ceiling for acquisition cost | | Target payback | 6 months | How much of that value you can spend up front | | Maximum new-customer CAC | Depends on payback and cash | Sets bids and budgets | ## When to use, and when not to Use it for annual and quarterly planning, launching in a new market, adding a channel, when growth stalls, and when finance asks how much to spend. Don't use it to run a specific channel (use the channel skills) or to measure incrementality in depth (`incrementality-testing`, `marketing-mix-modelling`). ## Inputs to ask for, in one message 1. Business goals for the period: revenue, new customers, profit, market share. 2. Unit economics: order or contract value, margins, repeat rate, LTV, payback target. 3. Spend and results by channel for 12 to 24 months, monthly. 4. Any incrementality evidence: lift tests, geo tests, MMM. 5. Seasonality and planned launches or promotions. 6. Constraints: cash, minimum spends, contracts, team capacity. ## Workflow ### Step 1. Set the target Translate goals into the number of new customers or pipeline needed and the maximum CAC the economics allow. ### Step 2. Baseline each channel For each channel: spend, platform results, your own data results (new customers, revenue), and any incremental evidence. Label the confidence of each estimate. ### Step 3. Estimate response curves Use MMM outputs if available; otherwise use past spend changes and tests to estimate how results change with spend. Expect flattening at higher spend. ### Step 4. Allocate Fund proven, efficient channels up to the point where marginal CAC hits the limit; add demand creation channels with test-based evidence; ring-fence a test budget. ### Step 5. Build scenarios Conservative, expected and stretch plans, each with spend, expected new customers, blended CAC and risks. ### Step 6. Plan pacing Monthly or weekly budgets following seasonality and promotions; rules for moving budget between channels based on leading indicators. ### Step 7. Define the test plan Which questions the test budget answers this quarter (new channel, retargeting incrementality, brand search value). ### Step 8. Agree review cadence Weekly pacing checks, monthly allocation reviews, quarterly re-plans with new test results. ## Channel roles | Channel | Typical role | Watch out for | |---|---|---| | Brand search | Capture existing demand | Paying for customers who would come anyway | | Non-brand search | Capture active intent | Rising costs at scale; broad match drift | | Shopping and Performance Max | Capture product demand | Mixing existing customers and brand | | Meta and TikTok prospecting | Create demand, reach new audiences | Over-crediting view-through conversions | | Retargeting | Convert warm audiences | Often low incrementality | | YouTube and CTV | Build awareness and consideration | Hard to measure without lift tests or MMM | | LinkedIn | Reach B2B roles and accounts | High costs; measure pipeline, not clicks | | Retail media (Amazon, others) | Capture marketplace demand | Halo effects on other channels | | Affiliates and partnerships | Pay for performance | Coupon sites taking credit for organic sales | ## Budget plan template ``` | Channel | Role | Q spend | Expected new customers | Marginal CAC | Evidence (label) | Test planned | | Total | | | | Blended CAC | | Test budget % | ``` ## Estimating marginal CAC without an MMM 1. List past periods where a channel's spend changed meaningfully (a step up or down of 20% or more) while other channels stayed steady. 2. Compare new customers (from your own data) before and after each change. 3. Marginal CAC ≈ change in spend ÷ change in new customers. 4. Repeat for several changes to see whether marginal CAC rises with spend. 5. Label the estimate "observational" and plan a test to confirm it. | Channel | Spend change | New customers change | Marginal CAC | Confidence | |---|---|---|---|---| | Meta prospecting | +£20k/month | +210 | £95 | Medium (one clean period) | | Non-brand search | +£15k/month | +90 | £167 | Low (seasonality overlap) | ## Reallocation rules - Move budget weekly only on leading indicators you trust (new customers from your data, qualified leads), not daily platform ROAS. - Cap any single shift at 20% of a channel's budget per fortnight to avoid resetting learning. - If a channel's marginal CAC exceeds the limit for four weeks, reduce it and log the decision. - If a test shows a channel is incremental, scale in steps and re-measure. ## Funnel balance check | Share of spend | Demand creation (prospecting, video, CTV) | Demand capture (search, shopping, retargeting) | |---|---|---| | Warning sign | Under 20% for a growth-stage brand | Over 80% while brand search volume is flat or falling | Flat brand search volume after cutting prospecting is an early sign that capture is eating into future demand. ## Planning calendar - **Annual:** unit economics, targets, big tests, seasonal peaks. - **Quarterly:** reallocation from test results and MMM updates. - **Monthly:** pacing against plan, scenario tracking. - **Weekly:** spend pacing and anomaly checks. ## Edge cases and judgement calls | Situation | What to do | |---|---| | No incrementality evidence anywhere | Start with conservative allocations and run one geo or lift test per quarter | | Cash-constrained startup | Shorter payback targets; favour capture channels; small structured tests for creation | | Strong seasonality | Shift budget ahead of peaks to build audiences; plan for higher costs at peak | | New market entry | Budget for learning; expect higher CAC early; set clear stop-loss rules | | B2B with long cycles | Plan on pipeline and leading indicators; review quarterly, not weekly | ## Handoffs to related skills - Current account health: `paid-media-audit` - Incrementality evidence: `incrementality-testing`, `marketing-mix-modelling` - Channel execution: `google-search-ads`, `performance-max-shopping`, `meta-ads`, `paid-social-tiktok-linkedin` - Reporting against the plan: `paid-media-reporting` ## Worked example A subscription coffee brand planned to grow new customers 30% with a fixed budget increase. Unit economics showed 12-month gross profit per customer of about £70 and a target payback of five months, setting a maximum new-customer CAC. Baselines showed brand search and retargeting claimed many conversions but a past geo test showed retargeting added little. The plan cut retargeting, moved budget to Meta and YouTube prospecting with a geo test to validate it, held brand search at a defensive level, and kept 15% for tests. The expected scenario hit the new-customer target at a blended CAC within the limit, with a stop-loss rule if prospecting CAC exceeded it for four weeks. ## Output format ``` # Media plan: <business>, <period> ## Goals and unit economics (max CAC, payback) ## Channel baselines with evidence labels ## Allocation and scenarios (conservative, expected, stretch) ## Pacing by month ## Test plan and budget ## Review cadence and reallocation rules ``` ## Common mistakes - Allocating by platform ROAS. - Ignoring diminishing returns when scaling. - No test budget, so the plan never improves. - Cutting demand creation because it's hard to measure. - Plans without margin or payback limits. ## Questions to ask before you plan - What can the business afford to pay for a new customer? - Which channels have incrementality evidence? - What cash and capacity constraints apply? ## Self-check before you answer - Is the plan built from unit economics and payback? - Are evidence labels shown for each channel estimate? - Are scenarios, pacing and a test budget included? - Are reallocation rules clear? ## Further reading - Google Meridian (open-source marketing mix model): https://developers.google.com/meridian - Meta Robyn (open-source MMM): https://facebookexperimental.github.io/Robyn/ --- Created by Afeez Adebayo, Marketing, SEO & Growth Expert Website: https://afeezadebayo.com LinkedIn: https://www.linkedin.com/in/afeez-adebayo/ X: https://x.com/za_icon Source: https://afeezadebayo.com/skills-md/marketing/performance-marketing/media-planning-budgeting/ Licence: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). You may copy, share and adapt this skill, including for commercial use, as long as you credit Afeez Adebayo and link to the source URL above. Keep this notice in any copy or adapted version.
Workflow
Step 1. Set the target
Translate goals into the number of new customers or pipeline needed and the maximum CAC the economics allow.
Step 2. Baseline each channel
For each channel: spend, platform results, your own data results (new customers, revenue), and any incremental evidence. Label the confidence of each estimate.
Step 3. Estimate response curves
Use MMM outputs if available; otherwise use past spend changes and tests to estimate how results change with spend. Expect flattening at higher spend.
Step 4. Allocate
Fund proven, efficient channels up to the point where marginal CAC hits the limit; add demand creation channels with test-based evidence; ring-fence a test budget.
Step 5. Build scenarios
Conservative, expected and stretch plans, each with spend, expected new customers, blended CAC and risks.
Step 6. Plan pacing
Monthly or weekly budgets following seasonality and promotions; rules for moving budget between channels based on leading indicators.
Step 7. Define the test plan
Which questions the test budget answers this quarter (new channel, retargeting incrementality, brand search value).
Step 8. Agree review cadence
Weekly pacing checks, monthly allocation reviews, quarterly re-plans with new test results.
Channel roles
| Channel | Typical role | Watch out for |
|---|---|---|
| Brand search | Capture existing demand | Paying for customers who would come anyway |
| Non-brand search | Capture active intent | Rising costs at scale; broad match drift |
| Shopping and Performance Max | Capture product demand | Mixing existing customers and brand |
| Meta and TikTok prospecting | Create demand, reach new audiences | Over-crediting view-through conversions |
| Retargeting | Convert warm audiences | Often low incrementality |
| YouTube and CTV | Build awareness and consideration | Hard to measure without lift tests or MMM |
| Reach B2B roles and accounts | High costs; measure pipeline, not clicks | |
| Retail media (Amazon, others) | Capture marketplace demand | Halo effects on other channels |
| Affiliates and partnerships | Pay for performance | Coupon sites taking credit for organic sales |
Budget plan template
| Channel | Role | Q spend | Expected new customers | Marginal CAC | Evidence (label) | Test planned |
| Total | | | | Blended CAC | | Test budget % |Estimating marginal CAC without an MMM
- List past periods where a channel's spend changed meaningfully (a step up or down of 20% or more) while other channels stayed steady.
- Compare new customers (from your own data) before and after each change.
- Marginal CAC ≈ change in spend ÷ change in new customers.
- Repeat for several changes to see whether marginal CAC rises with spend.
- Label the estimate "observational" and plan a test to confirm it.
| Channel | Spend change | New customers change | Marginal CAC | Confidence |
|---|---|---|---|---|
| Meta prospecting | +£20k/month | +210 | £95 | Medium (one clean period) |
| Non-brand search | +£15k/month | +90 | £167 | Low (seasonality overlap) |
Reallocation rules
- Move budget weekly only on leading indicators you trust (new customers from your data, qualified leads), not daily platform ROAS.
- Cap any single shift at 20% of a channel's budget per fortnight to avoid resetting learning.
- If a channel's marginal CAC exceeds the limit for four weeks, reduce it and log the decision.
- If a test shows a channel is incremental, scale in steps and re-measure.
Funnel balance check
| Share of spend | Demand creation (prospecting, video, CTV) | Demand capture (search, shopping, retargeting) |
|---|---|---|
| Warning sign | Under 20% for a growth-stage brand | Over 80% while brand search volume is flat or falling |
Flat brand search volume after cutting prospecting is an early sign that capture is eating into future demand.
Planning calendar
- Annual: unit economics, targets, big tests, seasonal peaks.
- Quarterly: reallocation from test results and MMM updates.
- Monthly: pacing against plan, scenario tracking.
- Weekly: spend pacing and anomaly checks.
Edge cases and judgement calls
| Situation | What to do |
|---|---|
| No incrementality evidence anywhere | Start with conservative allocations and run one geo or lift test per quarter |
| Cash-constrained startup | Shorter payback targets; favour capture channels; small structured tests for creation |
| Strong seasonality | Shift budget ahead of peaks to build audiences; plan for higher costs at peak |
| New market entry | Budget for learning; expect higher CAC early; set clear stop-loss rules |
| B2B with long cycles | Plan on pipeline and leading indicators; review quarterly, not weekly |
Handoffs to related skills
- Current account health:
paid-media-audit - Incrementality evidence:
incrementality-testing,marketing-mix-modelling - Channel execution:
google-search-ads,performance-max-shopping,meta-ads,paid-social-tiktok-linkedin - Reporting against the plan:
paid-media-reporting
Worked example
A subscription coffee brand planned to grow new customers 30% with a fixed budget increase. Unit economics showed 12-month gross profit per customer of about £70 and a target payback of five months, setting a maximum new-customer CAC. Baselines showed brand search and retargeting claimed many conversions but a past geo test showed retargeting added little. The plan cut retargeting, moved budget to Meta and YouTube prospecting with a geo test to validate it, held brand search at a defensive level, and kept 15% for tests. The expected scenario hit the new-customer target at a blended CAC within the limit, with a stop-loss rule if prospecting CAC exceeded it for four weeks.
Output format
# Media plan: <business>, <period>
## Goals and unit economics (max CAC, payback)
## Channel baselines with evidence labels
## Allocation and scenarios (conservative, expected, stretch)
## Pacing by month
## Test plan and budget
## Review cadence and reallocation rulesCommon mistakes
- Allocating by platform ROAS.
- Ignoring diminishing returns when scaling.
- No test budget, so the plan never improves.
- Cutting demand creation because it's hard to measure.
- Plans without margin or payback limits.
Questions to ask before you plan
- What can the business afford to pay for a new customer?
- Which channels have incrementality evidence?
- What cash and capacity constraints apply?
Self-check before you answer
- Is the plan built from unit economics and payback?
- Are evidence labels shown for each channel estimate?
- Are scenarios, pacing and a test budget included?
- Are reallocation rules clear?
Further reading
- Google Meridian (open-source marketing mix model): https://developers.google.com/meridian
- Meta Robyn (open-source MMM): https://facebookexperimental.github.io/Robyn/
On this page
- When to use this skill, and when not to
- Example prompts
- Example output
- What the agent needs from you
- How this skill hands off to related skills
- How to run Media Planning and Budget Allocation step by step
- Situations this skill handles
- What makes this skill different
- Practical tips from real projects
- Frequently asked questions
- Changelog
When to use this skill, and when not to
Use it for annual and quarterly planning, launching in a new market, adding a channel, when growth stalls and when finance asks how much to spend.
Most plans are last year’s split plus a percentage, or whatever each dashboard says works best. Both reward channels that are good at claiming credit. This skill starts from what a customer is worth and allocates using the best evidence available, from lift tests and MMM to observational estimates, each clearly labelled.
Don’t use it to run a specific channel (use Google Search or Meta) or to measure incrementality in depth (use Incrementality Testing).
Example prompts
- “How should we split next quarter’s budget to grow new customers 30%?”
- “What can we afford to pay for a new customer?”
- “Build conservative, expected and stretch spend scenarios.”
- “Should we move budget from search to YouTube?”
- “Write reallocation rules for weekly budget changes.”
Example output
The skill returns a fixed structure. A shortened example for an imaginary site:
# Media plan: example coffee subscription, Q1 2027 ## Unit economics 12-month gross profit per customer about \u00a370; payback target 5 months -> max new-customer CAC set ## Allocation | Channel | Role | Change | Evidence | | Meta prospecting | Create demand | +35% | Medium (geo test planned) | | Retargeting | Convert warm | -70% | High (geo test: low lift) | | Brand search | Defend | Hold | Low | | Test budget | Experiments | 15% | n/a | ## Stop-loss: cut prospecting if CAC exceeds limit for 4 weeks
Every channel estimate carries an evidence label, so the plan shows where it rests on tests and where on assumptions.
What the agent needs from you
The skill asks for goals for the period, unit economics (order or contract value, margins, repeat rate, lifetime value, payback target), 12 to 24 months of spend and results by channel, any incrementality evidence, seasonality and planned launches, and constraints such as cash, contracts and team capacity.
How this skill hands off to related skills
Planning draws on measurement and feeds execution. Account health comes from the Paid Media Audit, evidence from Incrementality Testing and Marketing Mix Modelling, execution from Google Search, Performance Max, Meta and TikTok and LinkedIn, and tracking against plan from Paid Media Reporting.
How to run Media Planning and Budget Allocation step by step
- Install the skill as
media-planning-budgeting/SKILL.md. - Share goals and unit economics: margins, repeat rate, lifetime value and payback target.
- Export monthly spend and results by channel for 12 to 24 months.
- Add any test or MMM results and planned launches and promotions.
- Review allocation, scenarios, pacing and reallocation rules.
- Run the test plan and re-plan quarterly with new evidence.
Situations this skill handles
Planning questions vary by stage and market. The skill handles these situations:
| Situation | What the skill does |
|---|---|
| No incrementality evidence | Conservative allocation plus one test per quarter |
| Cash-constrained startup | Shorter payback targets and capture-first allocation |
| Strong seasonality | Budget shifts ahead of peaks and higher peak costs planned |
| New market entry | Learning budget, clear stop-loss rules |
| B2B with long cycles | Plans on pipeline and leading indicators |
| Channel claims conflict | Allocates on evidence labels, not platform ROAS |
What makes this skill different
Most media plans allocate by platform ROAS or last year’s split. This skill starts with what a customer is worth, estimates diminishing returns, labels the evidence behind every channel number and keeps a test budget, so each quarter’s plan is better informed than the last.
It also balances the funnel. Cutting demand creation because it is hard to measure often shows up months later as flat brand search and rising acquisition costs.
Practical tips from real projects
- Start from payback, not from last year’s budget.
- Plan for marginal, not average, CAC.
- Ring-fence 10 to 20% for tests.
- Write stop-loss rules before launching new channels.
A worked example: a subscription coffee brand wanted 30% more new customers. Twelve-month gross profit per customer was about £70 and the payback target five months, which set a maximum new-customer CAC. Brand search and retargeting claimed many conversions, but a past geo test showed retargeting added little. The plan cut retargeting, moved budget to Meta and YouTube prospecting with a geo test to validate it, held brand search at a defensive level and kept 15% for tests, with a stop-loss if prospecting CAC exceeded the limit for four weeks.
Channel roles keep the plan balanced. Brand search captures existing demand; non-brand search captures active intent; Shopping and Performance Max capture product demand; Meta and TikTok prospecting create demand; retargeting converts warm audiences, often with low incrementality; YouTube and CTV build awareness; LinkedIn reaches B2B roles; retail media captures marketplace demand; and affiliates pay for performance but can take credit for organic sales.
Without an MMM, marginal CAC can still be estimated from past periods where one channel’s spend changed while others stayed steady, labelled as observational and confirmed with a test. Reallocation rules then cap shifts at about 20% of a channel’s budget per fortnight, so learning isn’t reset.
The planning calendar keeps it alive: annual economics and big tests, quarterly reallocation, monthly pacing and weekly anomaly checks.
Unit economics come first in every plan. Average order or contract value, gross margin and repeat purchases give 12-month gross profit per customer; the payback period the business can afford decides how much of that can be spent up front. A cash-constrained startup might accept only a three-month payback, while a funded subscription business may accept twelve. The plan makes this explicit, so budget debates become discussions about acceptable payback rather than arguments about which platform report to believe.
Frequently asked questions
How much should I spend on ads?
As much as you can while the marginal cost of a new customer stays below what that customer is worth within your payback period, and while cash allows. The skill calculates that limit from your economics.
What is marginal CAC?
The cost of the next new customer from extra spend. It usually rises as spend grows, which is why average CAC can mislead.
How should I split budget between channels?
Fund proven channels up to the point where marginal CAC hits your limit, add demand creation with test evidence, and keep 10 to 20% for experiments.
Why keep a test budget?
Without it, the plan never learns. Tests answer which channels truly add customers and where the next pound should go.
How often should allocation change?
Pacing weekly, allocation monthly and the whole plan quarterly, with new test results and MMM updates.
What if we have no incrementality evidence?
Start with conservative allocations and run one geo or lift test per quarter, labelling estimates as low confidence until then.
Changelog
- 1.0.0, 10 October 2026: first release.
Use, adapt and share this skill under CC BY 4.0: credit Afeez Adebayo and link to this page.
All Performance Marketing skills
- Paid Media Audit
- Conversion Tracking, Consent Mode and Conversions API
- Incrementality Testing: Lift and Geo Experiments
- Marketing Mix Modelling
- Google Search Ads and AI Max
- Performance Max and Shopping
- Meta Ads (Facebook and Instagram)
- TikTok, LinkedIn and Other Paid Social
- Ad Creative Strategy and Testing
- Landing Pages and Conversion Rate Optimisation for Paid Traffic
- Audiences and First-Party Data for Paid Media
- Paid Media Reporting and Attribution
