What this prompt does
This prompt writes a complete multi-touch B2B outbound sales sequence rather than a single cold email. You set [sequence_length], describe [product_name] and [product_description], name your [target_persona] and [target_company_type], and state the [desired_action]. ChatGPT then writes each email with a distinct job: a cold opener, a value-add, an objection handler, a social-proof touch, and a breakup email, each spaced by your chosen follow-up days.
The variables control tone, timing, and personalization. [subject_char_limit] and [open_rate_target] constrain the subject lines, [personalization_source] tells it where the opening line's personalization comes from, and [social_proof_metric] supplies the proof point for the value-add email. The [followup_day_2] through [followup_day_5] variables set the cadence, and [timezone] informs send-time advice. Because each email is built to earn the next reply with a low-friction ask, the sequence avoids the common mistake of demanding a demo on the first cold touch.
When to use it
- You are launching outbound for a B2B SaaS and need a full sequence written fast.
- Your current cold emails ask for too much too early and you want a low-friction first touch.
- You need objection-handling copy tailored to a specific persona's likely concerns.
- You want A/B variants for subject lines and CTAs without writing them all by hand.
- You are personalizing at scale and want a repeatable structure for the opening line.
- You need a breakup email that actually re-engages rather than just closing the loop.
Example output
The output is a ready-to-load email sequence. You get [sequence_length] emails, each with a subject line under [subject_char_limit] characters, a personalized first line drawing on [personalization_source], body copy matched to that email's purpose, and a CTA. The value-add email includes the [social_proof_metric], the objection email rebuts three persona-specific objections, and the breakup email asks for a referral if you have the wrong person. Each email also comes with A/B variants for the subject and CTA, plus send-time guidance for [timezone].
Pro tips
- Make
[personalization_source]specific and recent — a generic opener is the fastest way to get a cold email ignored. - Keep the first-email CTA genuinely low-friction; the prompt is built to avoid "book a demo," so don't override it with a heavy ask.
- Set
[social_proof_metric]to a real, verifiable outcome — an invented stat damages trust the moment a prospect checks it. - Tune the
[followup_day_2]through[followup_day_5]cadence to your buying cycle; longer gaps suit considered enterprise purchases. - Treat the
[open_rate_target]as a writing constraint for the subject lines, not a promise — actual open rates depend on your list and deliverability. - Generate the sequence, then have a human edit every personalization token, since the model only knows the
[personalization_source]you describe, not the specific prospect.
