feat: Tier B operator scaffolding — bundle, copy SoT, posts, emails

Pick up and finish yesterday's cut-off Tier B pass.

- build/: PyInstaller scaffold (datatools.spec + launcher.py +
  hook-streamlit.py + README) — folder-mode bundle, locked
  127.0.0.1, per-OS recipe
- marketing/COPY.md: single source of truth for every customer-facing
  string — landing H1/sub/CTAs, demo CTAs, email subjects, Gumroad
  listing, banned phrases
- marketing/community-posts/: 9 drafts (3 posts × 3 niches:
  bookkeeper, revops, shopify-pet) — story / tip / soft-offer
- marketing/emails/: 18 drafts (Gumroad delivery + 5-touch
  onboarding × 3 niches), per-niche segmentation guidance
- docs/NEXT-STEPS.md: flip 2.2 / 2.4 / 3.1 / 3.4 to done with
  pointers to the new assets; add Phase 0 inventory rows
- .gitignore: narrow `build/` ignore so PyInstaller spec + launcher
  + hooks get tracked, only generated artifacts (build/build/,
  build/__pycache__/, build/dist/) stay ignored

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

marketing/community-posts/bookkeeper/01-story.md

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+# Bookkeeper · Post 1 — Story
+
+**Where to post:** r/Bookkeeping, r/QuickBooks, AAT forums, ICB
+member groups, Bookkeeping Slacks/Discords.
+
+**Format:** longish post, ~400 words. Subject line / title goes
+first; everything below is the body.
+
+**Tone:** "fellow bookkeeper venting + sharing what worked" — not
+salesy, not preachy.
+
+---
+
+## Title
+
+How I cut my month-end bank reconciliation from 4 hours to 30 minutes (the boring 3-step version)
+
+## Body
+
+I've been doing month-end reconciliation for {{your-client-count}} clients for {{your-years}} years and the part I hated most was the bank export cleanup. Not the reconciliation itself — the *cleanup before* the reconciliation.
+
+You know the drill: client sends you a CSV from their bank. Half the dates are `MM/DD/YYYY`, the other half `DD-MM-YY`. The merchant column has trailing whitespace, weird unicode hyphens, and the same vendor spelled four ways ("Amzn Mktp", "AMAZON MARKETPLACE", "Amazon.com*1A2B3", "AMZN Mktplace"). QuickBooks chokes on the import, so you fix it by hand. Every. Single. Month.
+
+Last quarter I sat down and wrote out the steps I do every single time. There were 11. I automated the 8 that were deterministic. Here are the 3 that matter most — you can do these with built-in tools, no purchase required:
+
+**1. Normalize dates first, before anything else.**
+Excel's `TEXT(DATEVALUE(A2), "yyyy-mm-dd")` works for ~80% of bank exports. The other 20% have at least one row with a value Excel parses wrong (it'll silently swap day/month). Sort by date afterwards and *visually scan* for any row that's now in the wrong year — that's your tell.
+
+**2. Standardize merchant names with a fuzzy match, not a regex.**
+A regex won't catch "Amzn Mktp" → "Amazon". A fuzzy-match function (Excel doesn't have one natively; Google Sheets has `=FUZZYMATCH` via add-ons) will. The threshold I use is 0.85 — high enough to avoid false positives, low enough to catch the spelling drift.
+
+**3. Keep an audit trail of every change.**
+This is the one most bookkeepers skip and then regret 6 months later when the client asks "wait, why did you re-classify that?". Add a sidecar CSV: `original_value, new_value, rule_applied, timestamp`. Five columns, append-only, never delete.
+
+Doing those three turned a 4-hour job into roughly 30 minutes for me. The rest I eventually wrapped into a desktop tool I built called DataTools (the audit trail thing was the bit I needed and couldn't find anywhere — figured other bookkeepers might want it too). It's $49 if you want to skip the spreadsheet wrangling, but the 3 steps above will get you most of the way without it.
+
+Happy to share the audit-trail CSV template if anyone wants it — just reply.
+
+— {{your-name}}

marketing/community-posts/bookkeeper/02-tip.md

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+# Bookkeeper · Post 2 — Tip
+
+**Where to post:** LinkedIn (your own feed), AAT/ICB Facebook
+groups, accountancy newsletters' "tip submission" inboxes.
+
+**Format:** short, ~150 words. Practical. Reads as "thing I learned"
+not "thing I'm selling".
+
+---
+
+## Title
+
+The 30-second check that catches 90% of bank-export errors before they hit QuickBooks
+
+## Body
+
+If you do client bank reconciliations, do this once before every import:
+
+Open the export. Sort by amount. Scroll to the bottom. Look at the totals row.
+
+Most banks add a totals row at the bottom of the CSV that *isn't* a transaction. If you import it, QuickBooks treats it as a real entry and your books are off by exactly the value of the totals row — usually a five-figure number that takes you 40 minutes to track down.
+
+Same trick catches blank rows the bank inserts as section breaks (especially Wells Fargo, Chase, and most UK challenger banks). One sort, one scroll, two seconds of looking — saves the rest of your evening.
+
+If you're doing this for 20+ clients a month and want to automate the whole pre-import scrub (this trick + ~10 others), I built a $49 desktop tool called DataTools that does it: datatools.gumroad.com. No subscription, runs locally so client data stays on your machine.
+
+— {{your-name}}

marketing/community-posts/bookkeeper/03-soft-offer.md

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+# Bookkeeper · Post 3 — Soft offer
+
+**Where to post:** IndieHackers "show what you're working on", r/SideProject,
+r/Bookkeeping (only in monthly "self-promo" threads — read each
+sub's rules), bookkeeping newsletter "tools" sections.
+
+**Format:** ~250 words. Pitches the product but leads with the
+problem and is honest about the scope.
+
+---
+
+## Title
+
+I built a desktop CSV cleanup tool for bookkeepers who hate the bank-export reconciliation grind
+
+## Body
+
+Quick context: I do {{your-context — e.g., "books for 12 small clients" or "side-bookkeeping for a few non-profits"}} and the part I dreaded most every month was cleaning bank exports before importing them to QuickBooks. Different bank, different format, every time.
+
+I built **DataTools** — a desktop app (Mac/Win/Linux) that runs the same six cleanup steps every export needs:
+
+- Normalizes dates, currencies, account-number formats
+- Fuzzy-matches merchant-name variants ("Amzn Mktp" = "Amazon")
+- Flags duplicate transactions across re-exported date ranges
+- Strips trailing whitespace, hidden chars, BOM markers — the stuff QuickBooks chokes on silently
+- Generates a per-file audit trail your client can open in Excel: every change, every rule that fired, timestamped
+- Splits oversized exports for tools with row limits
+
+It runs **locally** — your client's bank data never goes to a server. (This was the whole reason I built it instead of using one of the cloud "data cleaning" SaaS tools.)
+
+It's **$49 one-time**, no subscription, no per-client license. v1.x updates included.
+
+If you want to try before you buy: there's a hosted demo with sample bank exports at the link below. The demo is identical to the desktop app — same UI, same six tools, just running in your browser on synthetic data.
+
+→ datatools.gumroad.com (or the bookkeeper landing page: datatools.app/bookkeeper)
+
+Happy to answer questions in the thread.
+
+— {{your-name}}