Launch Plan: Ledgerly Auto-Categorize

There was no product marketing context file, so I planned from what you told me. I assumed Ledgerly is an existing SaaS and Auto-Categorize is a major feature on it. Timeline and team size are guesses and are flagged in the open questions at the end.

Positioning and channel strategy

• Core promise: "Your bank transactions, sorted into tax categories automatically. Tax time takes minutes, not weekends."
• Audience reality: You have 2,300 customers, 9,000 emails and a small LinkedIn following. Your owned channels (email and in-app) are your strongest asset. Use them first.
• ORB split:
  • Owned (primary): email list, in-app messaging, blog and changelog.
  • Rented (support): LinkedIn only. Use it to point people to email signups. Product Hunt is optional (see below).
  • Borrowed (high leverage): accountants, bookkeepers, and freelancer or small-business newsletters and communities. Their audience is exactly who needs tax categories, and one good partner can beat Product Hunt.

Readiness gate (SLC check)

Pass all three before Phase 1.

• Simple: it does one job, which is assigning a tax category to each transaction.
• Lovable: accuracy is the whole product. Set a bar before launch, for example 90% or more correct on beta users' real data, with a one-click correction that teaches the model. Users who have to fix every third row will not love it.
• Complete: it needs these five things.
  • Review and approve flow
  • Bulk edit
  • Undo
  • Export to the formats your users already file with
  • A clear "what happens to my existing categories" answer
• Stop rule: if you are adding things such as multi-country tax regimes, you are in "Just One More Feature" territory. Cut scope and ship the one tax regime you serve best.

Also add a visible disclaimer that this is categorization assistance, not tax advice. Trust is the main risk for a finance product.

Phased plan

Timeline is about 8 weeks, with Week 0 as the start.

Phase 1: Internal launch (Weeks 0–1)

• Run it on your own team's books and on 10–15 friendly customers, recruited one-on-one. Accountants and power users are best.
• Measure categorization accuracy, correction rate and time saved.
• Exit criteria: the accuracy bar is hit and there are no data-trust or privacy blockers.

Phase 2: Alpha (Weeks 2–3)

• Publish a landing page with a waitlist form and a "Get early access" button inside the app.
• Send a short email to your most engaged customers, such as active users in the last 30 days and anyone who filed taxes through Ledgerly.
• Invite about 100 customers individually.
• Collect before and after examples with permission, such as "Q3: 412 transactions categorized in 3 minutes."
• Goal: the first quotes, plus a list of the categories it gets wrong.

Phase 3: Beta (Weeks 4–5)

• Add a "Beta" badge in the dashboard and an early-access toggle in settings.
• Open to about 10% of customers (about 230) in batches, then to the full waitlist.
• Start teaser content on LinkedIn and email about the problem: "Tax season shouldn't start with a CSV."
• Recruit 3–5 accountants or bookkeepers as testers and potential co-promoters.
• Build the launch assets: a 60–90 second demo video, GIFs, screenshots and the landing page.
• Goal: broader feedback, case studies, and a confirmed accuracy number you can publish.

Phase 4: Early access (Week 6)

• Invite all 2,300 customers, labeled "early access" (Option B), since the base is small enough.
• Run a short survey: "How would you feel if you could no longer use this?"
• Offer a credit or incentive for a user-research call to your 10–15 most engaged users.
• Leak screenshots and the demo to the 9,000-person list.
• Decide Product Hunt go or no-go (see below).
• Goal: quantitative usage data, a polished onboarding flow, and a final messaging check.

Phase 5: Full launch (Week 7, Tuesday–Thursday)

• Remove the beta label and add a "New" badge.
• Run the full launch-day checklist below.
• Open the feature to new signups.

Post-launch (Weeks 8+)

• Onboarding email sequence for new users of the feature.
• Include it in the next roundup email for people who missed it.
• Publish a case study and a comparison page, such as "Auto-categorize vs. manual spreadsheet categorization".
• Build an interactive demo, since people can try categorization without connecting a bank.
• Ask accountants about a referral or partner program.
• Plan the next launch moment, such as new categories or regions.

Product Hunt: recommendation

Do it as a secondary channel, not the centerpiece. Be realistic about the fit.

• Why it's a weak fit: Product Hunt skews to tech early adopters, while your buyers are small businesses and freelancers filing taxes. With a small LinkedIn following and no existing PH network, ranking well is hard.
• Why it's still worth it: it gives backlinks, some credibility, and a place to collect feedback from a different audience.
• Go criteria (decide in Phase 4):
  • You have a team member who can respond to comments all day.
  • You have at least 20–30 real supporters ready to leave genuine comments, not just upvotes.
  • The demo video and listing are polished.
• If you launch:
  • Treat it as a feature-led listing, which is fine for a new feature.
  • Start building your PH presence 2–3 weeks beforehand by commenting on other launches.
  • Send PH visitors to a landing page with an email capture or free trial.
  • Don't ask for upvotes in mass emails, since PH discourages it. Ask people to "check it out and share feedback."
• If you skip it: put the same effort into accountant partnerships and a webinar. That is likely the better return for your audience.

Launch-day checklist

Night before

• [ ] Final QA on the feature with real bank data, including edge cases (refunds, transfers, split transactions)
• [ ] Support and monitoring ready: error alerts, a support macro for "why was this categorized wrong?", and a status page
• [ ] All emails, posts and the blog post scheduled and proofread
• [ ] Landing page, demo video and screenshots uploaded and links tested
• [ ] Analytics and conversion events verified (feature activation, first approved batch)
• [ ] Rollout flag ready, with a rollback plan if accuracy or load problems appear

Morning

• [ ] Publish the blog post and update the website with a banner linking to it
• [ ] Send the announcement email to the full 9,000-person list. Send a more specific version to current customers: "Auto-Categorize is now live in your dashboard."
• [ ] Turn on in-app announcement: modal or banner, and the "New" badge
• [ ] Post on LinkedIn from the company page and from founders and team, with the demo GIF
• [ ] Send direct notes to accountants, partners and beta users with a ready-to-share post
• [ ] If using Product Hunt: listing goes live at 12:01 AM PT. Post the maker comment first, then notify supporters

During the day

• [ ] Reply to every comment, email reply and support question quickly, especially on Product Hunt and LinkedIn
• [ ] Watch error rates, categorization accuracy and support tickets. Be ready to roll back.
• [ ] Share social proof as it comes in, such as a customer quote or a time-saved screenshot
• [ ] Check signup and activation numbers at midday and again in the evening

End of day

• [ ] Send a thank-you reply to everyone who engaged
• [ ] Log feedback and bugs
• [ ] Review the numbers: email open and click rates, feature activations, signups, PH rank if applicable
• [ ] Schedule a 48-hour follow-up email to people who opened but didn't activate

Metrics to track

Set targets for these after the beta, once you know your baseline.

Open questions

These would change the plan.

1. Is the 8-week timeline realistic, or is there a fixed date such as tax season or a filing deadline?
2. Is Auto-Categorize free for existing plans, a paid add-on, or tiered? That changes how you run the pricing announcement.
3. Which tax regime and countries does it cover at launch?
4. How many people can work on launch day?