A founder you're tracking just posted about raising their Series B. Your competitor's CEO shared their product roadmap publicly. An industry analyst published a take that's getting 2,000 comments from decision makers in your target market.
Professional posts on LinkedIn contain intelligence that doesn't exist anywhere else. Not in CRM data. Not in news articles. Not in earnings calls. The people running companies are publishing their thoughts, announcing their moves, and engaging with their audience in real time.
The problem is accessing this data programmatically. Copy-pasting from a browser doesn't scale. Building your own extraction system means months of engineering time and constant maintenance. And manually monitoring feeds is a full-time job that nobody wants.
We built a Post Data API that returns structured data from any public post: the full text, author details, engagement metrics, timestamps, and media attachments. One API call, clean JSON response, ready for your pipeline.
This guide covers how to extract and analyze post data for competitive intelligence, content research, market analysis, and sales prospecting.
Why Post Data Matters for B2B
Posts are unfiltered signals. When an executive writes a post, they're sharing something they want the world to know. Unlike press releases filtered through PR teams or earnings calls scripted by lawyers, posts reveal how people actually think.
That's valuable information for anyone paying attention.
The Information Advantage
Consider what happens when a Chief Product Officer at your competitor posts about their upcoming feature release. That information is public, but it's buried in a feed that most people will never see. By the time it shows up in industry news or your competitor monitoring tool, weeks have passed.
Now consider having an automated system that captures every post from every competitor executive the moment it's published. You see the announcement in real time. Your product team knows what's coming. Your sales team can address competitive objections before prospects even raise them.
That's the difference between reactive and proactive intelligence.
The Scale Problem
The challenge isn't that this information is hidden. It's that there's too much of it to process manually.
A mid-sized company might have 50 competitors worth tracking. Each competitor has 5 to 10 executives who post regularly. That's 500 potential sources of intelligence, each posting multiple times per week.
No human can monitor that volume consistently. But an API can capture it all, structure it, and surface what matters.
Competitive Intelligence
Your competitors post about product launches before the press release goes out. They share hiring milestones that signal growth. They respond to industry news in ways that reveal their positioning. They celebrate customer wins that tell you who they're selling to.
Tracking competitor posts systematically means you see these signals as they happen, not weeks later when they show up in a news aggregator.
What Competitor Posts Reveal
Product direction: When a VP of Product shares thoughts on industry trends, they're telegraphing where their roadmap is headed. When they post about a new feature, you learn about it before their marketing site is updated.
Hiring velocity: Posts celebrating new hires or team growth signal which departments are expanding. A flurry of engineering hire announcements means they're building something. Sales team growth means they're pushing for revenue.
Customer wins: Companies love posting about landing big customers. These posts tell you exactly who they're winning and in which segments. That's intelligence for your competitive positioning.
Strategic shifts: When messaging changes across multiple posts, something strategic is happening. Maybe they're repositioning, maybe they're entering a new market, maybe they're responding to competitive pressure. Posts reveal these shifts early.
Culture and values: How leadership talks about their company tells you about their culture. This matters for competitive hiring, partnership discussions, and understanding how they make decisions.
Building a Competitor Monitoring System
The workflow is straightforward:
- Identify the key people at each competitor (CEO, CTO, VP Product, VP Marketing, VP Sales)
- Get their profile URNs using our API
- Pull their posts weekly or daily using
/api/v1/posts/all - Store the data and analyze trends over time
- Set up alerts for posts mentioning specific keywords (your company, your product category, key topics)
This gives you a living intelligence feed that updates automatically. Your team starts each week knowing exactly what competitors said publicly.
Buying Intent Signals
When a VP of Engineering posts about "evaluating new CI/CD solutions" or a Head of Sales complains about "CRM limitations," they're broadcasting buying intent. These signals are gold for sales teams.
The challenge is finding them at scale. Manually scrolling through feeds isn't a strategy. An API that lets you search posts by keyword, author title, or industry turns this into a systematic process.
Types of Intent Signals in Posts
Direct evaluation signals: Posts explicitly mentioning they're "looking for," "evaluating," "considering," or "researching" solutions. These people are actively in a buying process.
Pain point signals: Posts complaining about current tools, processes, or vendors. These people have problems you might solve, even if they're not actively shopping yet.
Trigger event signals: Posts about company changes that often precede buying: new funding, rapid hiring, new leadership, market expansion. These events create budget and urgency.
Social proof seeking: Posts asking "anyone use X?" or "recommendations for Y?" are people looking for validation before making a decision. They're deep in the buying process.
The Math on Intent-Based Outreach
Cold outreach to someone who never expressed interest: 1-2% response rate.
Warm outreach to someone who just posted about evaluating solutions in your category: 15-25% response rate.
That's not a marginal improvement. It's the difference between a sustainable sales motion and burning through your TAM with spam.
Finding Intent Signals at Scale
Use post search with strategic keywords and filters:
Keywords to search:
- "evaluating"
- "looking for recommendations"
- "anyone use"
- "switching from"
- "frustrated with"
- "need a better"
- Your product category terms
Author filters:
- Filter by job title to focus on decision makers
- Filter by industry to stay in your ICP
- Filter by date to get fresh signals
Each matching post is a potential opportunity. The author already raised their hand publicly. Your job is to show up with a relevant solution.
Content Research and Strategy
What topics resonate with your audience? Which formats get engagement? What are industry leaders talking about this week versus last quarter?
Post data answers these questions with actual numbers instead of intuition. Likes, comments, shares, and reposts are measurable signals of what content works.
Analyzing What Works
Pull posts from thought leaders in your space. Look at engagement metrics across different topics, formats, and posting times. Patterns emerge quickly.
You might find that posts about industry trends get likes, but posts about personal stories get comments. That's useful information for your content strategy. Comments indicate deeper engagement than likes.
You might find that posts with images outperform text-only posts by 3x. Or that posts published Tuesday morning get more engagement than Friday afternoon. The data tells you.
Benchmarking Your Performance
How does your content perform compared to peers? Pull engagement data for accounts similar to yours and compare.
If industry average engagement is 2% and you're at 0.5%, you have a content problem. If you're at 5%, you're doing something right worth doubling down on.
Benchmarking also helps set realistic goals. "We want more engagement" isn't actionable. "We want to match the 3% engagement rate of our top competitor" gives your team a target.
Identifying Content Gaps
What are competitors posting about that you're not? What topics are getting high engagement in your industry that you haven't covered?
Analyzing competitor post content and engagement reveals gaps in your own strategy. Maybe they're winning attention on a topic you haven't addressed. That's an opportunity.
Influencer and Partnership Discovery
Who drives conversation in your industry? Which voices have audience attention? Posts with high engagement reveal the people worth building relationships with.
Engagement data helps you prioritize outreach. Someone with 50,000 followers who gets 20 likes per post is less influential than someone with 5,000 followers who gets 500 comments.
Metrics That Matter
Engagement rate: Engagement (likes + comments + shares) divided by follower count. This shows how much of their audience actually pays attention.
Comment depth: Are people leaving thoughtful comments or just emoji reactions? Deep comments indicate real influence on thinking.
Share velocity: Posts that get reshared spread beyond the original audience. High share rates mean the content resonates enough that people want to associate with it.
Consistency: Does this person get engagement on every post, or was one post a fluke? Consistent engagement indicates real audience attention.
Building an Influencer Database
Systematic process for finding influencers in your space:
- Search posts for your industry keywords
- Identify posts with high engagement
- Pull author data for those posts
- Calculate engagement rates over their recent posts
- Rank by consistent engagement, not one-time viral hits
- Segment by audience type (practitioners, executives, analysts)
This gives you a prioritized list for partnership outreach, guest content, podcast invitations, or co-marketing opportunities.
Market Sentiment Tracking
Track how your brand or product is mentioned across professional posts. Search for posts mentioning your company and analyze sentiment over time.
This works for tracking competitor mentions too. When people publicly praise or criticize a competitor, that's intelligence you can act on.
Brand Monitoring
Search for posts mentioning your company name, product names, or key executives. Categorize by sentiment: positive, negative, neutral.
Positive mentions are testimonials you might feature. Negative mentions are problems to address. Neutral mentions are opportunities to engage.
Track volume over time. Are mentions increasing or decreasing? Does sentiment shift after product launches or PR events?
Competitive Sentiment
The same approach works for competitors. When people praise a competitor publicly, understand why. When they criticize, understand the pain points.
This intelligence feeds into competitive positioning. If people consistently complain about competitor X's pricing, that's a message to emphasize in your own positioning.
Industry Trend Detection
What topics are gaining attention? Search for posts containing industry keywords and track volume over time.
Rising volume on a topic means it's becoming more important to your audience. Declining volume means attention is shifting elsewhere.
This early signal helps you stay ahead of trends instead of reacting to them.
What Data You Can Extract
Our API returns structured data for every public post. Here's what you get:
Post Content
The complete text of the post, including hashtags, mentions, and formatting. No truncation. No "see more" links to click through. The full content exactly as published.
This includes any text formatting the author used: line breaks, bullet points, emoji. You get the post as it appears, not a stripped-down version.
Author Information
Full details on who wrote the post:
- Full name: The author's display name
- Headline: Their current title and company
- Profile URN: For further enrichment if needed
- Profile picture URL: Useful for display in your applications
- Follower count: Indicates reach
- Creator status: Whether they're in LinkedIn's creator program
- Premium status: Whether they have a premium account
This means you don't need a separate API call to enrich the author. The post data includes everything you need to understand who's behind it.
Engagement Metrics
Complete engagement breakdown:
- Total likes: Overall reaction count
- Reaction breakdown: Likes, celebrates, supports, insightful, funny, love
- Comments count: Number of comments on the post
- Shares count: How many times it was reshared
- Reposts count: Reposts with and without commentary
These metrics update in real time. When you fetch a post, you get current numbers, not cached data from hours ago.
Timestamps
When the post was published. Essential for:
- Tracking velocity of engagement (how fast did it take off?)
- Identifying trending content early
- Analyzing optimal posting times
- Building chronological feeds
Media Attachments
URLs for any content attached to the post:
- Images (all sizes available)
- Videos (including video posts and native video)
- Documents (PDFs, slides shared natively)
- Article links (with preview data)
- Poll data (for posts with polls)
Useful for content analysis, archiving, and understanding what formats the author uses.
Our Post Endpoints
Get Post Details
Endpoint: /api/v1/posts/info
Returns complete information about a single post given its URN.
| Parameter | Type | Required |
|---|---|---|
urn | string | Yes |
Returns: text, author details, postedAt, likesCount, commentsCount, sharesCount, mediaURL, and reaction breakdown.
Use this when you have a specific post URN and need full details.
Get All Posts by a Profile
Endpoint: /api/v1/posts/all
Returns all posts published by a specific person, paginated. First request returns up to 100 posts; subsequent pages return 20 each.
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| Parameter | Type | Required |
|---|---|---|
urn | string | Yes |
cursor | string | No |
start | integer | No |
Use this for building profile-based content feeds or analyzing someone's posting history.
Get Featured Posts
Endpoint: /api/v1/posts/featured
