Michael
e1f364f010
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>
2.7 KiB
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}}