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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
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'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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Added 1 week ago
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