/directory-submissions — 13-tier launch + listing playbook

Plan and execute systematic product listings across directories, review platforms, and AI-citation surfaces with the right sequence and positioning per tier. Closes the launch loop alongside /product-launch and /aeo-content.

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When to invoke

• A product is launching (new or major refresh) and needs a directory rollout plan.
• A client's directory presence is sparse and a structured audit + sequenced fill-in is needed.
• A Product Hunt launch is on the calendar and the 3-week warm-up needs scoping.
• G2 / Capterra reviews are absent or stalled and the 10-in-30 protocol needs deploying.

Do NOT invoke when:

• The destination pages aren't ready (comparison pages, alternative pages, ROI calculator) — get foundations in place first.
• The product hasn't hit its first 100 users — directory submissions before product-market signal wastes the launch window.

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The 3 hard rules

1. Foundation before submission. Destination pages (comparison, alternative, "vs.", ROI calculator, case studies) must exist before directories link to them. Otherwise link equity flows to a generic homepage that doesn't convert.
2. Destination pages before directories. Build the page the directory links to first; submit second. Reversed order leaves directory traffic landing on stub pages.
3. Positioning varies by directory type. What sells on Product Hunt (founder story + visual demo) does not sell on G2 (peer validation + feature depth) or on AI-engine citation pages (factual + comparison-honest). One positioning copy doesn't fit all.

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The 13-tier submission taxonomy

Submit in tier order. Each tier has different audience, mechanics, and positioning needs.

Tier	Examples	Audience	Positioning angle
1 — Flagship launch	Product Hunt, BetaList	Early adopters, makers	Founder story + 60-sec demo + community-relevant hook
2 — General SaaS directories	SaaSHub, AlternativeTo, GetApp	Tool researchers	Feature-by-feature comparison + screenshots
3 — Review platforms	G2, Capterra, TrustRadius, Software Advice	Buyers in evaluation	Peer reviews-first; 10-in-30 protocol applies
4 — Comparison hubs	AlternativeTo, Slant, StackShare	Buyers comparing options	"How we differ from X" angles
5 — Investor / startup databases	Crunchbase, F6S, AngelList	Investors, partner-seekers	Traction + funding-friendly positioning
6 — Tech newsletter directories	TLDR, Indie Hackers, Hacker News listings	Niche operators	Founder voice + community participation
7 — AI-engine citation surfaces	Perplexity-cited domains, ChatGPT-cited resources	AI-search audience	Honest comparison + structured data + GEO-optimized content
8 — Industry-specific directories	(e.g., FinTech: Finovate, FintechWeekly; AdTech: AdAge tool lists)	Vertical operators	Industry-specific use case + integrations
9 — Geographic directories	LocalBusiness directories, country-specific (e.g., StartupBlink UK, France Digitale)	Local market entrants	Local language + regulatory compliance
10 — Maker / no-code platforms	Bubble showcase, Webflow showcase, Notion templates	Builder community	Behind-the-scenes build + remix angle
11 — Integration ecosystem	Zapier App Directory, Make Integromat, Slack App Directory	Workflow-builders	Integration value + use case
12 — Conference / event directories	Sponsorship logos, attendee directories	In-person network	Event-relevant offer
13 — Niche vertical directories	Targeted to client niche (e.g., for FinTech: AdviserTech directories like AdviserSoftware.com)	Niche buyers	Niche-specific value prop

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Sharp numbers (cite-verified from source, MIT)

Metric	Number
Product Hunt: video uplift vs. no-video posts	2.7× more upvotes
Product Hunt: optimal launch window	12:01 AM Pacific Tuesday–Thursday only
Comparison / alternative page conversion rate	5–15% vs. 0.5–2% generic content
AI-referred traffic conversion uplift vs. traditional search	6–27× higher
Template-gallery LTV potential (e.g., Typeform)	Up to $3M/year
G2 / Capterra reviews protocol target	10 reviews from 20 asks in 30 days post-launch

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Product Hunt 3-week warm-up timeline

Week –3 (3 weeks before launch)

• Identify and contact hunter (someone with 100+ followers + history of launching credibly).
• Build email list of ~200 "launch supporters" — opt-in commitments to upvote on day-of.
• Prepare assets: 240×240 logo, 4–6 product screenshots, 60-sec demo video (with captions).
• Draft 4 angle variants for the launch tagline; A/B-test internally.

Week –2

• Brief launch supporters via email (no early sharing of the link — Product Hunt penalizes).
• Build the comments-pack: 6–10 thoughtful, on-topic responses to expected questions.
• Schedule social posts for launch day (LinkedIn, X, internal Slack-share with team).
• Test the demo video on mobile + desktop; fix any rendering bugs.

Week –1

• Final hunter call — confirm timing, agree on the post title.
• Get 3 advance "first commenters" lined up (founders, advisors, customers) for the first hour.
• Schedule the launch post draft for 11:50 PM Pacific the night before.

Day 0 — Launch day

• 12:01 AM Pacific (Tue–Thu only). Hunter posts the product.
• 12:05 AM — first commenter posts the lead comment.
• 12:10 AM — share to email list + Slack + Twitter + LinkedIn.
• 1:00 AM – 4:00 AM PT — respond to every comment within 15 minutes.
• 7:00 AM – 11:00 AM PT — follow-up wave to email list ("we're at #X — final push").
• 11:59 PM PT — post a thank-you comment on the listing.

Day +1 / +2 — Post-launch

• DM new followers (genuine, not template).
• Convert top commenters to G2 / Capterra reviewers (start the 10-in-30 protocol).
• Repurpose launch content into LinkedIn carousel + newsletter.

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The 10-in-30 reviews framework

Goal: 10 published reviews within 30 days of launch from 20 review-asks.

Mechanics:

1. Identify 20 customers. Tenure ≥ 60 days, NPS ≥ 8, recent positive interaction. Mix sizes/segments.
2. One-week cadence. 5 asks/week × 4 weeks. Don't bulk-ask.
3. Personal ask format. Founder or CS owner messages 1:1 (email or LinkedIn). Template ≠ personal — write each.
4. Include the link. Pre-filled review URL (G2 supports direct review URLs).
5. Offer reciprocity. Small thank-you (swag, Amazon gift card under $25 — within G2 policy).
6. Follow up at day 4. One nudge max.

Expected conversion: 50% asks → reviews (10/20). If under 5/20 after week 1, the ask copy is wrong — rewrite.

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GEO / AI-citation optimization (Tier 7)

AI engines (Perplexity, ChatGPT, Claude, Google AI Overviews) cite domains they find authoritative and structurally rich. To improve citation eligibility:

• Single <h1> per page (matches /schema-markup rule).
• FAQ schema on every product / comparison / pricing page (per /schema-markup).
• Comparison tables in markdown / HTML format (parseable, not screenshots).
• Honest "Who it's for" sections on comparison pages (the /aeo-content pattern absorbed from I11).
• Track AI-engine citations weekly via Brand Radar / Profound / AirOps (per /aeo-strategy).

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{Product / Client} directory submissions — phase 1

Readiness check

• Destination pages: ✅ / ⚠️ / ❌ (which gaps to fill first)
• Product-market signal: ✅ / ⚠️ (≥100 users / not yet)
• Positioning + messaging locked: ✅ / ⚠️

Tier selection

• Tier 1 (flagship): Product Hunt, BetaList — yes/no, with reasoning
• Tier 2–13: per-tier yes/no with rationale

Phased schedule (weekly)

• Week 1: {tiers, with deadlines}
• Week 2: …
• Week N: …

Per-tier positioning variants

• Product Hunt: {60-word pitch}
• G2: {feature-anchored description}
• AlternativeTo: {comparison angle}
• AI-citation surfaces: {honest-comparison pattern}

Product Hunt prep (if Tier 1)

• 3-week timeline checklist (as above)
• Asset list with status

Reviews protocol (if Tier 3)

• 20-customer asks list
• Weekly cadence + ask template

KPIs

• Launch-day target: top-N of day on PH
• 30-day target: 10 G2/Capterra reviews
• 90-day target: N AI-engine citations (via Brand Radar tracking)

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## Integration with other skills

- **Upstream:** `/positioning` + `/product-messaging` provide the per-tier positioning variants; `/aeo-content` provides destination pages (comparison, "vs.", alternative); `/schema-markup` ensures structured-data eligibility for Tier 7.
- **Downstream:** Feeds `/product-launch` orchestration; reviews protocol feeds `/lifecycle-marketing` (the customer-reviewer relationship continues post-review).
- **Companion:** `/aeo-strategy` plans which citation surfaces to target; this skill executes against them.

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## Anti-patterns

- ❌ Submit before destination pages exist.
- ❌ Same positioning copy across all 13 tiers.
- ❌ Product Hunt launch with no warm-up — typical result: <50 upvotes, lost launch window.
- ❌ Bulk-ask 20 customers for G2 reviews on the same day. Reads as a campaign; conversion tanks.
- ❌ Hidden / paid reviews. G2 and Capterra enforce. Manual-action territory.
- ❌ Submit to every tier on day 1 — exhaust attention budget; later tiers get half-prepped submissions.

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## Attribution

This skill adapts patterns from [`coreyhaines31/marketingskills/directory-submissions/SKILL.md`](https://github.com/coreyhaines31/marketingskills/blob/main/skills/directory-submissions/SKILL.md) (MIT license, © Corey Haines / Conversion Factory). Adapted to Genesys operator voice and integrated with our existing launch chain.

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## Final ship gate

Run `/premortem --output` before ship. See [`/premortem` skill](../../../../meta/orchestration/premortem/SKILL.md) for the 5 execution domains (will-it-resonate / will-it-convert / will-it-stay-on-brand / will-stakeholder-push-back / will-it-degrade-over-time) and output template.

Trivial-case escape: `## Premortem\nNo failure modes — trivial change` satisfies the contract for genuinely trivial outputs.

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## Persuasion & stickiness pass

Output complies with [persuasion-and-stickiness.md](../../../../../rules/persuasion-and-stickiness.md) — Cialdini's 7 persuasion levers + Heath's SUCCESs. Deploy the 1-2 Cialdini levers that fit the reader's barrier (never all seven; every lever must be TRUE), run the SUCCESs diagnostic (Simple / Unexpected / Concrete / Credible / Emotional / Stories) over the near-final draft, then the rule's pre-ship gate.

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