Prompt Details
Model
Chat - (gpt-6-luna)
Token size
410
Example input
[product_or_service]: bookkeeping automation for e-commerce
[ideal_customer_profile]: Shopify brands doing $50k-$500k/mo
[pain_point]: month-end reconciliation eats 20+ hours
[proof_point]: cut month-end close from 3 weeks to 4 days for a 7-figure Shopify brand
[timezone]: US Eastern
Example output
## Email 1 — day 0
Subject: your month-end close
If your Shopify brand is doing $50k–$500k/mo, month-end reconciliation can quietly turn into a 20+ hour job.
We helped a 7-figure Shopify brand cut its month-end close from 3 weeks to 4 days.
Would cutting that reconciliation time be useful for your team?
## Email 2 — day 3
Subject: 3 weeks to 4 days
A 7-figure Shopify brand was spending weeks reconciling month-end transactions.
We automated the bookkeeping workflow around their Shopify data and cut the close from 3 weeks to 4 days.
That gave the team a much faster view of the numbers without the usual month-end scramble.
Worth exploring whether the same approach could cut your close time?
## Email 3 — day 7
Subject: a faster close checklist
Before month-end, check three things:
1. Reconcile Shopify payouts against deposits.
2. Flag unmatched transactions before the close starts.
3. Separate recurring exceptions from one-off errors so they don't get reviewed repeatedly.
Doing those checks earlier can keep reconciliation from becoming a month-end bottleneck.
P.S. Our bookkeeping automation handles much of this workflow automatically.
## Email 4 — day 12
Subject: close the loop
If month-end reconciliation isn't a priority right now, no worries—I’ll leave the door open.
## A/B Subject Variants
**Email 1**
- month-end reconciliation
- your month-end hours
- cutting close time
**Email 2**
- from 3 weeks to 4
- a faster month-end close
- how one brand cut close time
**Email 3**
- a simple close checklist
- before month-end
- three reconciliation checks
**Email 4**
- closing the loop
- leave this open
- should i close this?
## Personalization-Token Guide
**{{firstName}}**
Source from the recipient's first name in the CRM, email signature, or company contact record. Use the person's preferred first name where available.
**{{companyObservation}}**
Source from a specific, verifiable company detail such as its Shopify storefront, product catalog, recent launch, or publicly stated sales channel. Avoid generic observations that could apply to any Shopify brand.
**{{rolePain}}**
Source from the recipient's job responsibilities and publicly stated or internally documented finance workflow. For e-commerce operators, look for signals around month-end reporting, reconciliation, transaction volume, or finance-team workload.
## Best Send Windows — US Eastern
**Tuesday, 9:00–10:30 AM ET** — A common business-email window after the morning rush, when operators are more likely to be actively working through priorities.
**Thursday, 1:30–3:00 PM ET** — Mid-afternoon gives the recipient time to handle operational emails before the end-of-day workload.
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GPT-6-LUNA
'I hope this finds you well' is a spam filter with legs. This builds a 4-touch sequence under the rules that get replies: 120-word bodies, 5-word lowercase subjects, one idea and one soft CTA per email, a value-gift touch, a no-guilt breakup. Six variables; banned-phrase list included. Plus 12 A/B subjects, a token-sourcing guide and send windows for your timezone. For founders, SDRs and agencies stuck at 0.3% reply rates. Paste real proof points — specificity is the engine.
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