Install
openclaw skills install @leooooooow/aes-competitor-radarAnalyze competitor product listings, pricing strategies, and promotional tactics to identify gaps and opportunities.
openclaw skills install @leooooooow/aes-competitor-radarAnalyze competitor product listings, pricing strategies, and promotional tactics to identify gaps and opportunities — structured for ecommerce operators who need actionable intelligence, not just data.
| Decision | Guidance |
|---|---|
| Mode selection | Mode A (Single Competitor Deep-Dive) for detailed analysis of one rival. Mode B (Landscape Scan) for comparing 3-10 competitors side by side. |
| Platform focus | Amazon, Shopee, TikTok Shop, Lazada, Shopify, or platform-agnostic. Specify upfront — analysis categories shift per platform. |
| Analysis depth | Quick scan (~15 min): listing audit + pricing snapshot. Full radar (~45 min): all 6 analysis categories with strategic recommendations. |
| Data freshness | All analysis reflects the moment of observation. Flag any data older than 7 days. Never fabricate historical trends. |
| Output format | Use references/output-template.md for structure. Include the Competitive Positioning Map in every full radar. |
This skill exists because ecommerce sellers need structured competitor intelligence but typically default to ad-hoc browsing. Without a framework, critical signals get missed — a competitor's coupon strategy, their review volume trajectory, or a gap in their keyword coverage that represents an opportunity. This skill turns scattered observations into a prioritized action plan.
Analyze one competitor in depth across all 6 categories. Best when you have identified a specific rival threatening your position or a new entrant you need to assess quickly.
When to use:
Compare 3-10 competitors across standardized dimensions. Best for quarterly reviews, market entry research, or identifying where you stand in the competitive field.
When to use:
Transform raw competitor observations into a structured competitive intelligence report with a prioritized list of strategic recommendations ranked by impact and effort.
Your product or store URL — Link to your product listing or storefront so the skill can establish your current competitive baseline and market position.
Competitor URLs or names — Links to 3-10 competitor product listings or store names you want to analyze. The more competitors provided, the richer the landscape analysis. For Mode A, provide 1 competitor with deep detail.
Product category — The specific product category or niche you are competing in, e.g., "portable blenders" or "organic dog treats." This anchors the analysis and determines relevant benchmarks.
Analysis focus — Specify whether you want deeper analysis on pricing, listing optimization, promotional tactics, or review sentiment. Defaults to a balanced overview of all areas.
Time period — Historical timeframe for trend analysis such as last 30 days, last quarter, or year-over-year comparison.
Your margin floor — Minimum acceptable margin percentage. If provided, all pricing recommendations will respect this constraint.
Priority metrics — Which KPIs matter most to you: BSR, review velocity, conversion rate, traffic share. Helps weight the recommendations.
Before analyzing the competitor, document your own listing's current state across the 6 analysis categories. This creates the comparison anchor. Record:
Analyze the competitor's product listing element by element:
Title analysis:
Visual content:
Bullet points and description:
Backend indicators:
Map the competitor's pricing approach:
Analyze the competitor's review profile:
Document the competitor's promotional playbook:
Assess the competitor's search positioning:
Compile findings into the Competitive Positioning Map and generate prioritized recommendations:
Identify and categorize competitors:
For each competitor, collect a consistent data set using the Competitor Snapshot Card format (see references/output-template.md). Ensure every field is populated for apples-to-apples comparison.
Build comparison matrices across:
Create the Competitive Landscape Map showing:
Deliver:
The 6 core analysis categories, applied consistently across all competitor assessments:
| # | Category | Key Questions |
|---|---|---|
| 1 | Listing Quality | How well-optimized is the competitor's product listing? Title, images, bullets, A+ content, variations. |
| 2 | Pricing Strategy | How is the competitor positioned on price? What's their promotion cadence? Per-unit economics? |
| 3 | Review Profile | What's the review volume, rating, velocity, and sentiment? Where are the complaints? |
| 4 | Promotional Tactics | What promotions, coupons, campaigns, and partnerships is the competitor running? |
| 5 | Search Visibility | What keywords is the competitor targeting? Where do they rank? What gaps exist? |
| 6 | Brand & Positioning | How does the competitor position themselves? Premium vs value? What's their brand story? |
State evidence strength explicitly. Every claim must be tagged: "observed" (you saw it), "inferred" (logical deduction from available data), or "estimated" (rough approximation). Never present estimates as facts.
No fabricated data. Never invent BSR numbers, sales velocity, conversion rates, or price history. If data is unavailable, say so and explain what could be observed instead.
Normalize before comparing. Multi-packs to per-unit. Different currencies to one standard. Different sizes to per-gram or per-ounce. Shipping costs included in landed price.
Separate new from used/refurbished. Never mix condition types in price comparisons. Flag when competitor listings include refurbished or open-box inventory.
Flag temporary conditions. If a competitor is running a Lightning Deal or seasonal promotion, note it as temporary. Don't set strategy based on a flash sale price.
Timestamp everything. Every data point gets a collection date. Analysis based on old data (>7 days) gets a freshness warning.
Acknowledge platform limitations. You cannot access private analytics, internal conversion data, or exact ad spend. Recommendations must be based on publicly observable signals only.
Competitor names are facts, not judgments. Report what competitors do. Avoid characterizing their decisions as "wrong" or "stupid" — they may have information you don't.
Recommendations must be specific and actionable. "Monitor the market" is not a recommendation. "Reduce your price by 8% to match Competitor B's effective per-unit cost while maintaining a 22% margin" is.
Every recommendation respects the margin floor. If the user provided a minimum margin, no pricing recommendation should breach it without an explicit warning and justification.
Scenario: You sell a portable blender on Amazon US at $29.99. A new competitor launched 3 months ago at $24.99 and has accumulated 800 reviews with a 4.6 rating. You want to understand their strategy and respond.
Input provided:
Key findings (abbreviated):
Listing Quality: Competitor uses 7 images (you have 5) including a size-comparison infographic and a 30-second video. Their title is keyword-optimized with "Portable Blender" in position 1-2. Their bullet points lead with benefits and include specific measurements. A+ content with comparison chart showing advantages over 3 unnamed competitors.
Pricing: Competitor's effective price is $22.49 after a persistent 10% coupon. At your COGS of $9.50, matching this price would give you a 58% margin — well above your floor. However, their lower price is driving volume: estimated 500+ units/month based on review velocity.
Review Intelligence: 800 reviews in 3 months = ~267/month velocity (likely vine + early reviewer program + insert cards). Rating distribution: 72% 5-star, 15% 4-star, 8% 3-star, 3% 2-star, 2% 1-star. Top complaint (23 mentions): "Lid leaks when blending thick smoothies." Your product doesn't have this issue — this is an exploitable gap.
Recommendation #1 (Impact: High, Effort: Low, Urgency: Act now): Add a bullet point and A+ module specifically addressing leak-proof design. Target the search term "leak proof portable blender" which the competitor is not optimizing for but their negative reviews are generating demand for.
Recommendation #2 (Impact: High, Effort: Medium, Urgency: This quarter): Reduce price to $26.99 (10% reduction) and add a 5% coupon for an effective price of $25.64. This narrows the gap to $3.15 while maintaining a 73% margin. Pair with increased PPC spend on "portable blender leak proof."
Scenario: You sell organic dog treats on Shopee Malaysia and want to map the competitive landscape before expanding your product line.
Input provided:
Key findings (abbreviated):
Market Map: The organic dog treats category clusters into 3 tiers: Budget (RM 8-15/pack, 4 competitors), Mid-range (RM 18-28/pack, you + 2 competitors), Premium (RM 35-55/pack, 1 competitor). No competitor owns the "premium organic + locally sourced" positioning — whitespace identified.
Cross-Competitor Pricing Matrix:
| Competitor | Price/pack | Price/gram | Free shipping? | Voucher active? |
|---|---|---|---|---|
| Competitor A | RM 12.90 | RM 0.13 | Above RM 40 | 15% off, min RM 25 |
| Competitor B | RM 14.50 | RM 0.15 | Above RM 30 | Free shipping voucher |
| You | RM 22.90 | RM 0.19 | Above RM 50 | None |
| Competitor C | RM 25.00 | RM 0.21 | Free | 10% new customer |
| Competitor D | RM 38.00 | RM 0.25 | Free | Bundle: buy 3 get 1 |
Strategic Synthesis: You are positioned in mid-range with the highest per-gram price in your tier and no active promotions. Lower your free shipping threshold to RM 35 (matching Competitor B's approach) and introduce a "subscribe monthly" bundle at 15% off. This addresses the key competitive gap without a direct price cut.
Treating a flash sale price as the regular price. A competitor running a Lightning Deal at 40% off is not "permanently cheaper." Check whether the discount is temporary before adjusting your strategy.
Comparing multi-packs to single units. A 3-pack at $15 ($5/unit) is cheaper than a single unit at $7, but the comparison must be per-unit. Always normalize.
Equating review count with quality. A competitor with 5,000 reviews and a 3.8 rating is not necessarily in a stronger position than you with 200 reviews and a 4.7 rating. Weight velocity and sentiment, not just volume.
Ignoring fulfillment method differences. FBA vs FBM pricing comparisons are apples to oranges. FBA listings include fulfillment in the price; FBM may have separate shipping. Account for landed cost.
Assuming static competitor behavior. Competitors react to your moves. A price cut that works today may trigger a price war tomorrow. Factor likely competitive response into recommendations.
Over-indexing on a single competitor. Unless Mode A was specifically requested, don't build your strategy around one rival. Market dynamics involve the full competitive set.
Fabricating historical trends. If you only have today's data, you have a snapshot, not a trend. Say "current price as of [date]" not "prices have been declining."
Recommending below the margin floor. If the user set a 35% minimum margin, every pricing suggestion must respect that constraint — or explicitly flag the exception with justification.
Confusing organic rank with sponsored placement. A competitor appearing in position 1 for a search term may be paying for that placement. Note whether rankings are organic or sponsored.
Presenting competitor data without context. "Competitor has 1,000 reviews" means nothing without knowing the category average, the competitor's time in market, and the review velocity trend.
| File | Purpose |
|---|---|
references/output-template.md | Structured templates for Mode A and Mode B deliverables |
references/analysis-frameworks.md | Detailed frameworks for each of the 6 analysis categories |
references/platform-specifics.md | Platform-specific data points and benchmarks for Amazon, Shopee, TikTok Shop, Lazada, Shopify |
assets/quality-checklist.md | Pre-delivery quality checklist (45 items) |