
Landing Optimizer
FreeEnhance landing pages for influencer traffic conversion.
Free · Opens the source repo
What Landing Optimizer does
The Landing Optimizer skill is designed to help marketers and developers create and refine landing pages specifically for traffic generated by influencer campaigns. When users seek to optimize their landing pages for conversions from influencer-driven traffic, this skill provides a structured approach to audit and improve the user experience. It focuses on aligning the landing page with the influencer's messaging, ensuring that visitors have a seamless transition from the influencer's content to the landing page.
This skill operates by collecting key information from the user, including the landing page URL, current conversion rates, and details about the influencer's message and audience demographics. It then performs a comprehensive message-match audit, assessing how well the landing page reflects the influencer's key messages and offers. The output includes prioritized recommendations for page structure, social proof integration, and conversion optimization strategies, tailored to the specific context of influencer marketing.
In addition to providing actionable insights, the Landing Optimizer skill outlines a roadmap for A/B testing, allowing users to systematically test changes and measure their impact on conversion rates. By focusing on elements like call-to-action (CTA) placement, promo code experiences, and mobile optimization, this skill equips users with the tools needed to enhance their landing pages effectively.
This skill is particularly useful for marketers and web developers who are working on campaigns that leverage influencer partnerships. It streamlines the process of optimizing landing pages, ensuring that they are not only visually appealing but also functionally effective in converting visitors into customers.
When to use it
Use this skill when you need to optimize landing pages specifically for traffic coming from influencer marketing efforts.
When not to use it
This skill is not suitable for measuring the performance of campaigns after they have launched; use the performance-analyzer for that purpose.
What you can build with it
Improving a Low-Converting Page
When a user reports a low conversion rate from an influencer campaign, the skill provides a detailed audit and actionable recommendations to enhance the landing page.
Aligning Messaging for New Influencer Campaigns
For a new campaign, the skill helps ensure that the landing page reflects the influencer's messaging, improving user trust and conversion potential.
Creating A/B Testing Plans
The skill outlines a structured A/B testing roadmap, allowing users to systematically test changes and measure their impact on conversion rates.
How to install Landing Optimizer
View source1. Install with the skills CLI
npx skills add aaron-he-zhu/aaron-marketing-skills/landing-optimizer --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by aaron-he-zhuLanding Optimizer
This skill helps you create and optimize landing pages specifically for influencer marketing traffic. When users click from an influencer's post, the landing experience should feel connected and optimized for conversion.
Cross-discipline (paid ads): this is also the paid-ads post-click skill — the page half of the ROAS Offer message-match (it pairs with ad-creative-builder, which owns the ad half). The same diagnose-and-fix flow applies to paid landing pages; save paid runs under
memory/ad/landing-optimizer/. On paid runs, message-match the page against the offer-claims-registry ledger when present: offer terms, promo codes, and dates againstmemory/claims/offers.md, and claim wording against the approved variants inmemory/claims/claims-ledger.md.
Quick Start
Shortest invocation:
Optimize our landing page for traffic from [influencer campaign]
Common scenario — diagnose and fix a low-converting creator page:
Our influencer landing page has [X%] conversion rate. How can we improve it?
Skill Contract
- Reads: landing page URL and current state, conversion rate and goal, traffic source (influencer handles, platforms, content type), the influencer's key message/quote, promo code, audience demographics. Inputs come from the user when no tool is connected.
- Writes: optimization plan saved to
memory/influencer/landing-optimizer/YYYY-MM-DD-<topic>.md(message-match audit, structure and social-proof recommendations, conversion/CTA plan, A/B test roadmap). - Promotes: durable facts — active campaign name, page URL, baseline conversion rate, promo code, primary creator — to
memory/hot-cache.md. - Done when:
- Message-match score and named fixes are produced for the page.
- A prioritized conversion plan (CTA, promo-code experience, friction, mobile) exists with expected impact.
- An A/B test roadmap with at least one hypothesis and success metric is written.
- Primary next skill: performance-analyzer — measure whether the optimizations moved conversion.
Handoff Summary
Emit the standard shape from skill-contract.md §Handoff Summary Format.
Data Sources
This family needs no live integrations (Tier 1). The skill works by asking the user for the page URL, current conversion rate, the influencer's message, and the promo code, then producing the audit and plan from those inputs.
Optional connectors that can deepen the analysis when available:
~~analytics— pull live conversion rate, bounce rate, scroll depth, and add-to-cart events instead of asking.~~A/B testing platform— read past test results and feed sample-size/duration estimates.~~CMS / landing page builder— inspect current page structure and copy directly.~~social platform analytics— confirm the creator's actual messaging and audience.
See CONNECTORS.md for the verified free/keyless recipe per category. Every step degrades gracefully to user-supplied inputs.
Instructions
When a user requests landing page help, work through these steps. Each step's fill-in template, ASCII layout, and HTML snippet live in references/templates.md — keyed by the same step numbers.
- Assess current state — capture campaign, URL, traffic source, current conversion rate, goal, and the traffic context (influencers, platforms, content type, key message, promo code, audience).
- Evaluate message match — compare what the influencer says against what the page shows across message, value prop, offer, product, and tone; produce a Message Match Score (X/10) and named fixes. Mismatch causes confusion and abandonment. For paid runs, also verify the page's offer/promo terms against
memory/claims/offers.mdwhen the ledger exists — an ad's "50% off" promise is only true while the offer row is live. - Page structure — recommend the influencer-traffic layout (hero → social proof → product → more proof → FAQ → final CTA) and give section-by-section hero/social-proof/product fixes.
- Social proof integration — place the driving creator most prominently, then the proof hierarchy: other influencers → customer reviews → trust indicators.
- Conversion optimization — tune CTA copy/placement, design the promo-code experience (auto-apply via URL param, prominent display, confirmation), cut friction, and check mobile (load speed, thumb-friendly CTA, scroll depth).
- A/B testing plan — rank tests by impact/effort, then write at least one hypothesis with variants, sample size, duration, and success metric.
- Influencer-specific pages — decide whether a dedicated
/creator-namepage is warranted and what to personalize. - Performance tracking — set targets for load time, bounce, CR, add-to-cart, AOV; define UTM params and events for attribution.
Save the finished plan to memory/influencer/landing-optimizer/YYYY-MM-DD-<topic>.md (paid runs to memory/ad/landing-optimizer/) and promote durable facts to memory/hot-cache.md.
Example
User: "Our landing page for @fitnessanna's protein powder campaign has a 1.2% conversion rate. How can we improve it?"
Output (abridged — full version in references/templates.md):
- Diagnosis: 1.2% CR, below the 2-3% benchmark for influencer traffic.
- Issues: message mismatch (Anna says "smooth texture", page leads with "high protein"); Anna's content not featured; code
ANNA20not auto-applied; mobile CTA below the fold. - Priority fixes: Anna's video in hero (+0.5%), auto-apply promo (+0.3%), headline match (+0.3%), CTA above fold on mobile (+0.2%) → combined 1.2% → 2.5% CR.
- Test plan: wk1 hero changes, wk2 headline A/B, wk3 CTA copy.
Reference Materials
-
templates.md — all step fill-in templates, ASCII layouts, HTML snippets, the full worked example, and tips.
-
skill-contract.md — shared contract and Handoff Summary format.
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state-model.md — memory tiers and save-path conventions.
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CONNECTORS.md — free/keyless data recipes per connector category.
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conversion-quality.md — advisory conversion rubric (non-veto) to sanity-check the optimization plan.
-
Sibling skills in the influencer-marketing family:
- content-amplifier — source creator content for landing pages and drive traffic to them.
- brief-generator — align creator content with landing goals.
Next Best Skill
Primary: performance-analyzer — measure whether the optimizations actually moved conversion, AOV, and attribution.
Alternates (same Report family):
- content-amplifier — when the audit shows the page needs more creator content to feature.
- roi-calculator — when the page's conversion is validated and you want to translate it into ROI and payback math.
Termination note: Maintain a visited-set this session. If a recommended skill has already been invoked, stop and report the chain as complete rather than re-running it. Hard stop at chain depth 3 to avoid loops.
Frequently asked questions about Landing Optimizer
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