# Paid media strategy Human Guide ## What This Is For A discipline for running paid media that does not light money on fire. It gives the agent a clearer input/output frame for paid media: what context to ask for, what decisions to make, and what usable artifact to return. Use this as a human-readable version of the Paid media strategy agent skill. It is meant for marketers, operators, founders, and other non-coders who want the workflow without reading agent-specific implementation instructions. ## When To Use This - Use this when you need a repeatable process for paid media strategy. - Use this when the task needs judgment, examples, constraints, or a clear output format rather than a one-off prompt. - Use this when you want to hand an AI assistant enough context to produce a usable marketing artifact. ## When Not To Use This - Do not use this when you only need a quick factual answer. - Do not use this when the work depends on private data you cannot share with the assistant. - Do not use this as a replacement for legal, compliance, financial, or medical review. ## What You Need Before Starting - The goal or business outcome you want. - The audience, customer segment, or market context. - Any source material the assistant should respect, such as notes, briefs, examples, URLs, or brand guidance. - Constraints such as tone, length, channel, deadline, region, or approval requirements. - A clear definition of what a good final answer should look like. ## Step-By-Step Workflow 1. State the job clearly: "Use the Paid media strategy guide to help me with..." 2. Add context: audience, goal, offer, channel, source material, and constraints. 3. Ask the assistant to identify missing inputs before producing the final output. 4. Have the assistant follow the skill-specific guidance below. 5. Review the result against the final checklist and ask for revisions where needed. ## Skill-Specific Guidance - **Display network without targeting.** Broad display drives garbage traffic. Use only for retargeting unless you have specific contextual targeting. - **Geographic markets you do not serve.** Sounds obvious, fails 30% of accounts. Audit geo targeting quarterly. - **Hours you cannot service.** For service businesses (legal, B2B, medical). Pause off-hours unless lead form clearly converts asynchronously. - **Devices that do not convert.** If mobile converts at 1% and desktop at 5% with the same CPC, bid down mobile aggressively. - **Audiences who never convert.** Pull last 90 days of converters, build exclusion lists for everyone else who repeatedly clicks but never converts. - **Creative that is tired.** Frequency above 4 with declining CTR means refresh. Refusing to refresh because "it still works ok" is incremental loss. - "We are scaling but CAC went up." Saturation on the primary audience. Expand the audience or diversify the channel mix. - "Conversions look fine in the platform, terrible in revenue." Attribution mismatch plus customer quality, not just count. The platform is selecting low-LTV converters because they are easier to find. - "We A/B tested and one wins, but only by 5%." Within margin of platform noise. Not a real signal. - "We turned off the underperforming campaign and conversions dropped overall." View-through or assist conversions you were not counting. Test with hold-out, not flat off. - "Frequency hit 8 last week." Refresh creative. Do not blame the audience. - "We are trying to scale Meta to $100K per day from $20K per day." That is not scaling, that is a 5x jump. Expect efficiency drop; phase the increase. ## Decision Points And Nuance The original skill emphasizes: What this skill is for, Hypothesis discipline for paid spend, Channel selection: when to use which platform, Budget allocation: brand vs performance, baseline vs test, Audience targeting: prospecting vs retargeting vs exclusion, Bid strategy: when each fits, Campaign types, What NOT to spend on, Creative testing: within campaign vs across campaign, Frequency capping. Use these questions to steer the work: - What is the intended audience or buyer? - What source material must be preserved? - What should the assistant optimize for: clarity, persuasion, accuracy, speed, creativity, or conversion? - What examples represent the desired quality bar? - What should the assistant avoid? ## Common Mistakes - **Retargeting.** People who engaged but did not convert. Smaller audience size, higher CTR, lower CAC. Do not bid too aggressively or you train the platform to charge a premium for users who would have converted anyway. - **Manual CPC or CPM.** Full control, slow to scale. Useful for diagnostics and very early campaigns where you do not trust the platform's machine learning yet. - **Geographic markets you do not serve.** Sounds obvious, fails 30% of accounts. Audit geo targeting quarterly. - **Devices that do not convert.** If mobile converts at 1% and desktop at 5% with the same CPC, bid down mobile aggressively. - **Audiences who never convert.** Pull last 90 days of converters, build exclusion lists for everyone else who repeatedly clicks but never converts. - The "winning creative is the floor" principle. Do not kill winners to test new ideas. Test alongside. The downside of running the proven winner is small; the downside of killing it for an unproven concept is large. - "Frequency hit 8 last week." Refresh creative. Do not blame the audience. - **What not to spend on.** Branded beyond defensive, untargeted display, wrong geos, off-hours, low-converting devices, never-convert audiences, tired creative. ## Copy-And-Paste Prompt ```text Use the Paid media strategy human guide. My goal: [Describe the business outcome] Audience: [Describe who this is for] Context and source material: [Paste notes, examples, links, or existing copy] Constraints: [Tone, length, channel, timeline, must-include items, must-avoid items] Before producing the final output, ask me for any missing information that would materially improve the result. ``` ## Final Checklist - [ ] The output matches the original goal. - [ ] The audience and context are reflected in the answer. - [ ] Important constraints and source material were preserved. - [ ] The assistant made the relevant decisions explicit. - [ ] The final artifact is ready to use, review, or hand to the next person. ## Source This guide was generated from the rampstackco/claude-skills skill entry for `paid-media-strategy`. ## Source Skill Notes These notes preserve the nuance from the original skill. Use them as supporting reference when the workflow above feels too generic. # Paid Media Strategy A senior performance marketer's playbook for running paid media that produces real outcomes. The default state of paid media is wasted spend. Most accounts have campaigns running because they always have, audiences targeting because the rep suggested it, bid strategies on auto because manual is hard, creative not refreshed because there is no system. The cost compounds. A 20% efficiency gain on a $500K-per-year account is $100K back to the business. A 50% gain on a $5M-per-year account is $2.5M. This skill is the discipline that produces those gains. It assumes you have a paid media platform (Google Ads, Meta, LinkedIn, TikTok, or aggregators like Synter) connected. It assumes you have working analytics and conversion tracking. The hard part is the strategic discipline behind the spend, and that is what is here. When to use this skill: any time you are designing a paid media plan, evaluating whether to scale or kill a campaign, allocating budget across channels, or auditing an existing account. --- ## What this skill is for This skill spans paid media strategy and operations. It does not cover ad creative production (use `ads-creative-development`), result interpretation in depth (use `ads-performance-analytics`), or platform-specific MCP tooling (consult each ad platform's official documentation for current MCP setup, auth, and example prompts). The audience is a performance marketer (in-house or agency), a growth lead allocating spend across channels, or a founder making early paid budget decisions. The voice is tactical. There is no "evaluate every option yourself with no opinion." Paid media decisions have shape, and a senior practitioner can map a situation to a defensible plan in an afternoon. --- ## Hypothesis discipline for paid spend Most paid media failures start with a vague reason for spending. A real spend hypothesis has five parts: audience, offer, channel, outcome metric, and magnitude. Missing any of them and the campaign cannot be evaluated honestly. A bad reason: "We need to scale Google Ads spend." No audience, no outcome metric, no magnitude. Nothing is falsifiable. A good hypothesis: "Top-of-funnel SaaS prospects searching for project management tools convert from a free-trial CTA at 3.2% CAC under $80. Increasing Search budget from $40K to $80K per month should hold CAC under $80 and add roughly 500 trial signups based on Q3 search volume." That hypothesis names the audience (top-of-funnel SaaS prospects on PM-tool keywords), the offer (free trial), the channel (Google Search), the outcome metric (CAC, trial signups), and the magnitude (500 signups, CAC under $80). It is falsifiable: if CAC blows past $80 or signups come in below 250, the hypothesis is wrong and you pull back. Pre-commit the falsification rule. Decide before scale: at what CAC do we hold? At what CAC do we pull back? At what trial-signup count do we kill? Without pre-commit, every result becomes a debate. With pre-commit, the decision is mechanical. Primary metric is the one you are optimizing for (CAC, ROAS, CPL). Guardrails are the metrics you do not want to break (LTV, retention, brand search lift). Scaling the primary metric while breaking a guardrail is a Pyrrhic win. --- ## Channel selection: when to use which platform Pick the channel where intent matches your offer. Run the wrong channel and your CAC reads as a channel problem when it is actually a fit problem. **Google Search.** High-intent demand capture. Best when you have a real product people search for and the query volume justifies the floor. Worst when category awareness is low and no one is searching. Predictable, expensive at scale, the highest floor of any channel. **Google Performance Max.** Automated multi-channel within the Google ecosystem. Best when you have a strong product feed (e-commerce) or want to lean into Google's automation. Worst when you need control over placements; PMax is a black box and disagreements with the algorithm cost money. **Meta (Facebook plus Instagram).** Broad-targeting demand creation. Best for visual products, lifestyle brands, B2C scale, and direct response with strong creative. Worst when targeting is too narrow (audiences saturate fast) or when the offer is high-consideration B2B. **TikTok.** Discovery-mode advertising. Best for native-feeling video creative, younger audiences, and brand awareness. Worst for direct response with high consideration cycles. Spark Ads (boosting organic posts) outperform pure paid creative. **LinkedIn.** B2B targeting precision. Best for high-LTV B2B with clear job-title targeting. Worst for low-AOV products; the floor is too high to be efficient. **Reddit, Pinterest, Snapchat, X.** Niche or supplementary. Best as scale-out channels after primary channels are working. Worst as starting points; spreading thin across niches before you have proven any channel is the most common waste pattern. **YouTube (Google).** Video at scale. Best for awareness or for B2C consideration. Underrated for B2B SaaS in some categories where the buyer-research path includes long-form video. The decision rule. Start with the channel where intent matches your offer. Search for high-intent demand capture. Meta or TikTok for demand creation. LinkedIn for B2B precision. Do not run all of them at once until you have proven any of them. Detail in [`references/channel-decision-matrix.md`](references/channel-decision-matrix.md). --- ## Budget allocation: brand vs performance, baseline vs test Four splits operate at the same time. Get them all right and the budget compounds. **Brand vs performance.** Brand keeps the demand pipeline filled (long term); performance captures it (short term). 70-30 to 80-20 performance-heavy is typical for most B2C. Brand-heavy splits fit high-consideration B2B where the buying cycle is months long and pipeline visibility matters more than week-over-week conversions. **Baseline vs test.** 70 to 80% of budget to channels, campaigns, and audiences that are working. 20 to 30% to systematic testing of new channels, new audiences, new creative. Without test budget, you stagnate. Without baseline budget, you have nothing to scale. **Primary vs secondary channel.** One channel does the heavy lifting (60 to 70% of budget). Others scale supplementally. Resist the equal-split temptation; spreading across channels before any one is proven is the most expensive way to learn nothing. **Daily vs lifetime budgets.** Daily for ongoing campaigns where you want a stable spend floor. Lifetime for finite tests where the platform should pace itself across the test window. Lifetime budgets prevent runaway spend during testing. Budget pacing matters too. Front-load some weeks to test creative aggressively. Back-load others to capture seasonality (holiday, end-of-quarter, category-specific moments). Do not run flat; flat budgets miss the demand peaks. Detail and templates in [`references/budget-allocation-templates.md`](references/budget-allocation-templates.md). --- ## Audience targeting: prospecting vs retargeting vs exclusion Three audience types. Treat them as separate strategies.