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>
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Shopify-pet · Day 7 — Run it before every Klaviyo sync
Subject: Run it before every Klaviyo sync Send: Day 7 Goal: reframe from one-off tool to per-sync workflow
Hi {{first_name}},
A week in. By now you've probably run DataTools on a real customer export once or twice and seen the cleanup catch things you'd been losing in Klaviyo for months.
The thing that turns DataTools into a recurring win instead of a one-off purchase: run it before every sync, not just the first time.
The pattern that works for most stores:
1. Pick a cadence. Most stores I talk to do this monthly; high-volume stores do it weekly. The cadence should match your "I'm planning a campaign" rhythm.
2. The Sunday-morning ritual:
- Pull a fresh customer export from Shopify (Customers > Export > "All customers")
- Drop into DataTools
- Run the pipeline (analyzer → format → text-clean → dedupe → gate)
- Review the gate quarantine file (typically 0.5-2% of rows)
- Push the cleaned CSV to Klaviyo (their CSV import or via their API)
3. Save your settings as a preset. The "Save settings" button writes a .datatools-preset.json. Keep it in your store's Drive / Notion / wherever your shop docs live. Next month, load preset, run pipeline, done in 4 minutes.
4. After 3 months, retune the preset. Look at your manual-review queue across the 3 runs. If you're consistently approving 0.86-confidence merges, drop the auto-merge threshold to 0.85. If you're rejecting 0.92 merges, raise it to 0.94. The preset improves with use.
The store owners doing this monthly tell me their open rates go up 8-15% in the first 90 days — not from new content, just from the email actually reaching the inbox.
If you want, reply with a sanitized export and I'll suggest a starting preset for your store — happy to do this for the first 50 buyers.
— Michael {{support_email}}