Wag Linkedin Post

WAG Differentiation:

• NOT a middleman, trading company, or sourcing agent
• Core promise: "Tell me what you need. I get you a free factory quote. If the price works, I take you to see the factory yourself."
• Value layers: Access, Trust, Safety, Logistics, Direct Relationship, Transparent Pricing
• WAG accompanies clients to China, helping them sign contracts directly with factories — WAG is the guide, not the intermediary

Key Market Data:

• 85% of Australian SMBs use Alibaba.com to find overseas suppliers
• China accounts for 62% of all inquiry sources for Australian importers
• Australia-China供应链管理 market: USD 949.4M in 2025, projected USD 2,277.9M by 2034 (CAGR 10.21%)

Service Flow:

• Step 1 (Free): SME describes product needs + current purchase price
• Step 2 (Free): WAG contacts factories for confidential quotes, delivers to client; factory names kept confidential pre-visit
• Step 3 (Paid): WAG coordinates full China trip — flights, hotel, translator, factory appointments; client signs directly with factory

Pricing Model:

• Transparent cost-plus: flights (actual) + hotel (actual) + translator (per day) + coordination service fee
• Estimated total per trip: A$5,300-8,300 for one client; A$3,500-5,000 per client when 2-3 SMEs share

Socratic Question Flow

Before generating any content, guide the user through exactly 5 questions to clarify the post direction. Present questions in Simplified Chinese to match WAG client base, but generate the final LinkedIn post in English.

Question 1 — Topic Discovery: "你的目标读者目前正在面临哪些中国采购挑战？" (What specific China sourcing challenge are your ideal LinkedIn post readers dealing with right now?) [Context: This identifies the core pain point — e.g., factory verification, quality control, communication barriers, minimum order quantities. Reference WAG business model: new brand companies cannot find source factories, cannot trust if factories are real]

Question 2 — Content Structure: "这个问题适合用什么结构来表达——步骤框架（1-2-3步）、案例分析、还是揭露误区？" (What structure works best for this topic — step framework, case study, or myth-busting?) [Context: Based on WAG data, step frameworks (3 steps) outperform all other formats. Prioritize "before doing X, check these 3 things" structure.]

Question 3 — War Story: "你自己或客户有没有经历过这个问题的真实案例？" (Do you have a real story from yourself or a client who experienced this problem?) [Context: Real stories drive engagement. If user has a story, lead with it. If not, create a composite scenario based on WAG experience.]

Question 4 — CTA Design: "读者读完文章后，你希望他们做什么——分享类似经历、联系咨询、还是转发给有需要的人？" (What do you want readers to do after reading — share their experience, reach out for consultation, or forward to someone who needs this?)

Question 5 — Posting Perspective: "这篇文章是以公司主页还是个人账号发布？" (Company Page or Personal Profile?)

[Context: Determines tone, pronouns, and how WAG is positioned in the post. Per 2026 LinkedIn algorithm data, personal profiles outperform company pages by 561% in reach]

RAG Implementation

After gathering the user's answers, retrieve relevant WAG content before generating the post:

1. Glob — Find all blog files:

   Pattern: content/blog/*.mdx
   

2. Grep — Search for content matching the user's topic (use head_limit: 3 to limit matches)

3. Read — Extract content from the top 3 matched files

4. Incorporate — Use sourced statistics, examples, case studies, or insights from the retrieved content in the generated post

Important: Always invoke RAG to retrieve at least 1 WAG blog post before generating. This ensures the post references specific WAG expertise rather than generic content.

LinkedIn Post Templates

Template A: Step-By-Step Framework (ER=33.33%, Highest Performance)

[HOOK - max 210 characters]
Formula: "Before [action], verify [N] things: [promise]"
Example: "Before paying any deposit for your China order, verify three things: factory, not trading company."

[BREAK]

[BODY - 3 numbered steps]

Step 1 — [Tool/Method name, specific action]
[One sentence explaining why this matters]

Step 2 — [Tool/Method name, specific action]
[One sentence explaining the consequence of skipping]

Step 3 — [Tool/Method name, specific action]
[One sentence about Australian legal responsibility]

[BREAK]

[CTA - specific yes/no with reasoning]
"Did you know gsxt.gov.cn is free for anyone to verify a Chinese business license? Were you ever asked to check one before placing an order?"

[HASHTAGS - 6-10 tags, mix broad + niche]
#ChinaSourcing #FactoryVerification #AustraliaChina #SupplyChain #ImportFromChina #AustralianBusiness

Template B: Document Carousel (Best Format for 2026 Algorithm)

For carousel posts, use this structure:

Slide 1 (Title): [Problem statement - curiosity hook]
Slide 2: [Context - why this matters for Australian businesses]
Slide 3: [Step 1 with specific tool/website]
Slide 4: [Step 2 with specific tool/website]
Slide 5: [Step 3 with specific tool/website]
Slide 6 (CTA): [Question that invites comments]

Carousel tip: LinkedIn's 2026 algorithm gives Document Carousels 6.6% average engagement vs 4% for text-only posts.

Template C: Story → Lesson → Framework

[HOOK - 210 chars max]
"A client paid a $12,000 deposit to a supplier in March. By April, the factory had vanished."

[BREAK]

[STORY - 2-3 short paragraphs]
Paragraph 1: What happened (specific details — amounts, platform, timeline)
Paragraph 2: What went wrong (the verification step that was skipped)
Paragraph 3: What we did (how WAG would have prevented this)

[BREAK]

[FRAMEWORK - the 3 things to check]
Before paying any deposit, verify:
1. [Check on gsxt.gov.cn — business license shows "manufacturing"]
2. [Live video of production lines during working hours]
3. [Certification verified directly with issuing body]

[BREAK]

[CTA - experience trigger]
"What verification step would you add to this list? I read every comment."

[HASHTAGS]

Content Format Decision Tree

Before generating, determine format based on topic:

Format priority for WAG topics: Steps > Story+Framework > Carousel > Text > Brand Intro

CTA Frameworks (Data-Proven to Drive Comments)

CRITICAL: WAG's historical CTA "What would you do differently? Share in comments." generated 0 comments across all 3 posts. Replace with specific, experience-based questions.

DO NOT use:

• "What would you do differently?" — too abstract, 0 comments historically
• "Share in comments" alone — passive, no trigger
• "Let's discuss" — vague, no specific angle

Post first-comment-on-LinkedIn rule: After posting, FIRST comment should be the answer to your own CTA question — this seeds the conversation and makes comment section look active.

Hook Formulas (Ranked by WAG Data Performance)

Recommendation: Lead with numbered frameworks. The "3 steps" structure consistently outperformed all other approaches.

WAG LinkedIn Performance Data (2026-03)

Source: LinkedIn Analytics export (03/04 - 03/23/2026), 3 organic posts

Post Performance Ranking

Key Performance Insights

1. Higher impressions do NOT mean higher engagement. The post with most impressions (57) had worst ER (7.02%) and lowest CTR (1.75%). The post with fewest impressions (24) had best ER (33.33%) and highest CTR (20.83%).

2. Step-by-step framework content wins. The 3-step verification framework post (33.33% ER) outperformed the "truth too late" post (7.02% ER) by 4.7x in engagement rate.

3. ZERO comments is the #1 problem. All 3 posts generated 0 comments despite 125 total impressions. The CTA questions are not driving discussion.

4. CTAs must be specific and experience-based to drive comments, not generic questions.

Content Type Preference (Based on Data)

2026 LinkedIn Algorithm Context

Key algorithm changes (2026):

• Shift from "like-driven" to "deep engagement-driven" — NLP analyzes comment quality
• External links in post body = -60% reach penalty
• Engagement pods (互赞群) now detected with 97% accuracy, risk of shadow ban
• Best-performing format: Document Carousel (6.6% engagement), Text-only post (4%), Image/Graphic (4.85%)
• Personal Profile outperforms Company Page by 561% in organic reach
• Best posting time (Australia audience): Tuesday-Thursday, 9-11 AM AEDT
• First 60 minutes after posting: must be online to respond to comments (algorithm boost window)

Optimal hook strategies (data-proven for WAG):

• Framework/Steps: "Before paying any deposit, verify three things..." (ER=33.33%, CTR=20.83%)
• Specific scenario + consequence: "When you source from China as a new Australian brand, one fact matters most..."
• Tactical how-to: "Step 1 — Check the business license on gsxt.gov.cn..."

Fact Check Procedure

After generating the LinkedIn post, verify claims against WAG's existing blog content and, if needed, use web search for real-time data.

Simplified Protocol:

1. Check WAG blog content first — RAG-retrieved content is pre-verified
2. For new claims, use mcp__MiniMax__web_search to verify
3. Flag any claim that cannot be verified with: "[Claim] — unverified, remove or rephrase"
4. Present verification status to user before final approval

Do not use generic industry statistics unless they can be cited from a named source. LinkedIn audiences in B2B respond to specificity, not vague claims.

LinkedIn Post → Blog Article Workflow

When a LinkedIn post should be expanded into a blog article, follow this workflow:

1. Directory Structure

Canonical Storage Path: All generated LinkedIn posts are stored in:

social/linkedin-post/{YYYY-MM-DD-topic}/
├── post.md          # Original LinkedIn post content
├── outline.md       # Image outline/briefing
├── imgs/           # Original AI-generated images
│   ├── 01-factory-reality-check.png
│   └── 02-3step-verification.png
└── prompts/        # AI image generation prompt files
    └── 01-factory-reality-check.md

Published Images (for MDX/blog use): After image generation, copy images to:

public/social/linkedin-post/{YYYY-MM-DD-topic}/imgs/

Archive Path (after publishing): Move completed posts to:

social/linkedin-post/archive/{YYYY-MM}/{YYYY-MM-DD-topic}/

Date format: Use YYYY-MM-DD prefix for unique identification and chronological sorting.

2. Image Naming Convention

Use zero-padded two-digit prefix for ordering:

• 01-fake-factory-reveal.png — First image (appears earlier in article)
• 02-3step-verification.png — Second image (appears later)

3. Blog MDX Frontmatter Template

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