CRM for a Show HN Launch: Tracking Your First Wave of Users

DenchClaw launched on Hacker News with a Show HN post and got 147 points and 124 comments. It was exactly as chaotic as you'd expect — and having a CRM running in the background made a real difference.

I'm writing this to share the playbook we used, because I think every founder with a Show HN-caliber product should have something like this set up before they post.

The Nature of Show HN#

Show HN is different from Product Hunt. The HN audience is:

• More technical (lots of engineers, fewer marketers)
• More skeptical (they'll find the real weaknesses)
• More vocal (they'll say it bluntly in comments)
• More likely to try it immediately (if the setup friction is low)

The ideal Show HN response is:

1. Answer technical questions thoughtfully
2. Acknowledge real criticisms honestly
3. Engage with the people who clearly tried it
4. Don't get defensive about negative feedback
5. Turn engaged commenters into contributors or customers

A CRM helps you do all of this systematically, especially when the comments are coming in faster than you can track them.

Pre-Launch Setup#

The HN Response Tracker#

Objects:
- hn_comments: username, comment_text, type (technical_question/criticism/praise/bug_report/feature_request), priority, responded, my_response, lead_potential (high/medium/low)
- hn_users: username, email (if they DM'd), project (GitHub, portfolio), assessment, follow_up_status

Tell the agent:

"Set up a Show HN tracker for me: I need to track all HN comments and any users who reach out directly. The key things I care about: have I responded? Is this person a potential user/contributor? What category of feedback is it?"

The Feedback Taxonomy#

Before the post goes live, tell the agent:

"I'm about to post a Show HN. The main concerns people will have about DenchClaw are: (1) complexity of setup, (2) data privacy/local storage tradeoffs, (3) how it compares to existing CRMs. Pre-draft thoughtful responses to each of these that I can adapt."

You'll use these as the basis for your HN comments. Adapting a good draft is 5x faster than writing from scratch when comments are flooding in.

During the Launch (First 6 Hours)#

The Comments Triage Flow#

Every 15 minutes:

1. Scan new comments
2. Log anything with substance to hn_comments
3. Flag high-priority responses (top-level comments, influential users, sharp criticisms)
4. Draft/adapt responses

Tell the agent as things come in:

"Log HN comment from 'throwaway1234': 'DuckDB is an interesting choice but I worry about corruption on unexpected shutdowns. How do you handle this?' Type: technical_question, priority: high. They seem knowledgeable."

"Agent, draft a response to the DuckDB corruption question — cover WAL protection, backup recommendations, and our own experience with it."

"Log comment from 'pg' (note: this is Paul Graham): 'Congrats on the launch' — type: praise, priority: high, lead_potential: low (obviously)."

Tracking Who Tries It#

Some HN commenters will try your product within hours of posting. Track them:

"User 'hakobapollo' commented that they installed DenchClaw and it worked. Add them to hn_users, they're a real user. Follow up with them in a few days to check in."

These are your first evangelists. Personal follow-up from a founder when they're still excited converts them to advocates.

The Technical Deep-Dives#

HN loves technical depth. If someone asks a hard technical question — DuckDB internals, your EAV schema choice, the agent architecture — log it and give it your best answer. These often get upvoted and become the most-read comment thread.

"Draft a detailed technical response explaining why we chose EAV over a traditional schema — cover the dynamic field creation, the PIVOT view pattern, and the tradeoffs. Make it honest about the downsides too."

After the Post Settles (Day 2-3)#

The Feedback Synthesis#

"Synthesize all the HN feedback from the launch. Categorize it by type and identify the top 3 actionable insights. What should we build or change first based on this feedback?"

The agent reads through all your logged comments and returns:

"Top themes from 47 substantive comments:

1. Setup complexity: 15 comments mentioned friction in the first-run experience
2. Team features: 12 comments asking about multi-user support
3. Linux support: 8 comments asking about Linux compatibility Most urgent: the setup friction feedback, as it correlates with users saying they couldn't complete installation."

This goes directly into your product roadmap prioritization.

The Follow-Up Queue#

"Who from the HN launch should I follow up with personally? Identify the 10 most engaged commenters who showed real interest in using the product."

The agent surfaces:

• People who tried it and commented publicly
• People who DMed or emailed after the post
• Critical-but-constructive commenters (often your best future contributors)

Personal follow-up from a founder days after the launch, when they've had a chance to try it, is often incredibly well-received. Most founders don't do this.

Converting HN Users to Email List#

"For everyone who interacted with our HN post and left an email or GitHub handle, add them to my contacts with source='Show HN' and send them a personal follow-up email — not a template, but something that references their specific comment or interaction."

The agent drafts individualized emails for each person, using the context from their comments. You review and send.

Longer-Term Tracking#

The HN cohort is worth tracking as a cohort. Add them all as contacts with a tag or source field, then:

Month 1 check-in:

"It's been a month since our Show HN. Which users from the HN cohort are still active? Who churned? What's the conversion rate from HN commenter to active user compared to our Product Hunt cohort?"

Contributor identification:

"Which HN commenters have since contributed to the GitHub repo or written about DenchClaw? Update their records with this context."

What We Learned from Our Launch#

The DenchClaw Show HN had 124 comments and 147 upvotes. Key things we tracked that proved useful:

1. The most engaged commenters (10-15 people) became our initial Discord community core
2. The top criticism (setup complexity) led to a major onboarding improvement
3. One commenter's technical question about DuckDB led to a conversation that became a contributor relationship
4. We tracked all GitHub star spikes back to specific comment threads — useful for understanding what language resonates

All of this context lived in DenchClaw, searchable months later.

Frequently Asked Questions#

How do I handle hostile comments on HN?#

Log them, note the specific criticism, and respond professionally with substance. Don't argue. The audience watching is more important than the person you're replying to. Ask the agent to help draft measured, thoughtful responses.

Should I track anonymous HN accounts?#

Track the substantive commenters regardless of whether they're anonymous. The comment content matters more than the identity.

What if my launch doesn't go well?#

A "failed" HN launch (front page but low engagement) is still valuable data. Log what feedback you got. Ask the agent to identify what questions your post failed to answer.

How is Show HN different from Ask HN or standard HN?#

Show HN is specifically for projects you've built. The community expects something to try, not just read about. Make sure your post has a direct link to the product and clear installation instructions.

Ready to try DenchClaw? Install in one command: npx denchclaw. Full setup guide →