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Cold outreach and follow-ups

Cold outreach fails the same way everywhere: the email is about the seller, not the prospect; the personalization is a first-name token; the ask is a 45-minute meeting from a stranger. The reply rate is the market's honest review.

These prompts each take one narrow outreach job and your real material — the actual prospect research, the actual product, the actual thread — and produce something a self-respecting person could send. None of them will invent case studies, fabricate familiarity, or promise reply rates. Deliverability and honesty beat cleverness.

Curated

Answer a brush-off without arguing

The prospect replied with a brush-off. Write a response that takes the brush-off at face value (never argue with it or 'just checking' around it), extracts the one legitimate signal inside it, and either gracefully closes or reframes with genuinely new information — choose based on what the brush-off actually says, and state your choice in one labeled line ('Read:') before the email. Never claim other customers 'said the same thing before buying'. Use only the facts provided. Brush-off: {{reply}} Thread: {{thread}} Facts we have: {{facts}}

Fill in: Their brush-off verbatim, the thread, and any real facts that could honestly reframe (pricing, integrations, results).

Known limits: Some brush-offs are final. Treating 'no' as an objection to handle instead of an answer to respect costs the future deal too.

Run evidence

Sandbox run 2026-08-19 · openai/gpt-5-nano

Input fixture
BRUSH-OFF: "We already use Intercom's triage features, not looking to add
tools."

THREAD: Cold email offering Relay's Zendesk ticket triage to a mid-market e-commerce
support team. (Their public careers page and help center clearly run Zendesk, not
Intercom — the reply likely confuses us with a different vendor's pitch, or they use
Intercom for chat only.)

FACTS: Relay is Zendesk-native (no Intercom integration exists); it handles email/form
tickets, not live chat; a 14-day pilot runs on historical tickets without touching the
live queue.

Model output (unedited)

Read: Reframe with a no-risk, Zendesk-native 14-day pilot on historical tickets that runs without touching the live queue; demonstrates Relay's Zendesk ticket triage independent of Intercom usage.

Hi [Name],

Thanks for the quick reply. Since you’re not looking to add tools, I’ll keep this focused on your current setup. Relay is Zendesk-native (no Intercom integration) and handles ticket triage for email/form tickets—not live chat. We can offer a no-risk 14-day pilot that runs on historical Zendesk tickets and does not touch your live queue. This lets you evaluate whether Relay’s approach to ticket triage could fit your Zendesk workflow without altering your Intercom usage or live operations.

If you’d like to explore, I can share a brief setup plan and what we’d need to get started. A quick 15-minute call to confirm the pilot details works if that’s easiest.

Best regards,
[Your Name]
[Relay]

Editorial review (independent AI agents)

  • Accuracy — pass (editorial-accuracy/google/gemini-2.5-flash)
  • Safety — pass (editorial-safety/anthropic/claude-haiku-4.5)
  • Usefulness — pass (editorial-usefulness/openai/gpt-5-nano)
Curated

Ask a happy customer for a referral without the cringe

Write an email to this customer asking for an introduction. Structure: one line of specific gratitude tied to their actual result (from the notes — never invent numbers), the direct ask naming the kind of person we want to meet, and a pre-written forwardable blurb they can send as-is (labeled 'Forwardable:'). The blurb describes US and what we do in neutral third person — it must never put words, endorsements, or intent in the customer's mouth (the customer is forwarding it, not authoring it), and must not read as an ad written in their voice. Make declining easy in one sentence. Use only facts from the notes. Customer notes: {{notes}} Who we want to meet: {{target}}

Fill in: Notes on the customer's actual results and relationship, and a description of who you want introductions to.

Known limits: Referral asks spend relationship capital — a customer mid-renewal or mid-support-escalation is the wrong recipient.

Run evidence

Sandbox run 2026-08-19 · openai/gpt-5-mini

Input fixture
CUSTOMER NOTES: Tomas Adeyemi, Support Director at Coastway Logistics.
Customer 14 months. December peak: handled 3x ticket volume with 2 fewer seasonal
hires than planned; renewed early in March and expanded seats 20%. Gave a quote for
our case study voluntarily. Responds warmly, usually within a day.

TARGET: Support/CX leaders at other freight or 3PL companies with seasonal volume,
especially anyone he knows from the SupportDriven community.

Model output (unedited)

Subject: Quick intro request

Hi Tomas — thank you again for partnering with us and for helping Coastway handle 3x ticket volume in December with two fewer seasonal hires than planned.

Would you be willing to introduce me to Support/CX leaders at other freight or 3PL companies with seasonal volume, especially anyone you know from the SupportDriven community?

Forwardable:
The team behind this message provides a platform used by support teams at freight and 3PL companies that experience seasonal ticket volume. Coastway Logistics has been a customer for 14 months; in December they handled 3x ticket volume with two fewer seasonal hires than planned, they renewed early in March and expanded seats 20%, and they provided a quote for the company's case study.

If you'd rather not, no problem — just let me know.

Thanks again,
[Your name]

Editorial review (independent AI agents)

  • Accuracy — pass (editorial-accuracy/google/gemini-2.5-flash)
  • Safety — pass (editorial-safety/anthropic/claude-haiku-4.5)
  • Usefulness — pass (editorial-usefulness/openai/gpt-5-nano)
Curated

A voicemail that earns the callback email

Write a voicemail script for this prospect that a human can say naturally in one breath-paced pass: who's calling, the one specific reason this call is for THEM (from the research), and a callback path that assumes they won't call back — point them to the email you'll send instead. No fake familiarity, no 'quick question' bait. Then write the one-line email subject that voicemail should make them look for. Mark pauses with (—). Base everything on the research given. Research: {{research}} Product: {{product}}

Fill in: Prospect research and your product in plain words.

Known limits: Voicemail works as an email amplifier, not a standalone channel — without the paired email it's a dead end.

Run evidence

Sandbox run 2026-08-19 · openai/gpt-5-nano

Input fixture
RESEARCH: Ravi Chandra, Director of Field Operations at Suncrest Solar
(residential solar installer, ~300 techs across 4 states). Posted on LinkedIn that
missed appointment windows are their #1 review complaint; company Glassdoor mentions
dispatchers juggling three tools.

PRODUCT: RouteHive — field-service scheduling that consolidates dispatch into one
board and auto-notifies homeowners of arrival windows.

Model output (unedited)

- Voicemail script (one-breath-paced pass, with pauses marked by —):
Hi Ravi, this is [Your Name] with RouteHive — Suncrest Solar’s top review complaint is missed appointment windows, and dispatchers juggling three tools across four states — RouteHive consolidates dispatch into one board and auto-notifies homeowners of arrival windows. Since you’ll likely be busy and won’t call back, I’ll send you a concise email with the essentials and the first steps to evaluate RouteHive — look for that message shortly after this voicemail.

- One-line email subject the voicemail should trigger:
RouteHive: Consolidated dispatch to reduce missed appointment windows for Suncrest Solar

Editorial review (independent AI agents)

  • Accuracy — pass (editorial-accuracy/google/gemini-2.5-flash)
  • Safety — pass (editorial-safety/anthropic/claude-haiku-4.5)
  • Usefulness — pass (editorial-usefulness/openai/gpt-5-nano)
Curated

Cold email built from real prospect research

Write a cold email to this prospect using only the research provided. Open with the single most specific, recent fact from the research and connect it to one problem we plausibly solve — no flattery, no 'I hope this finds you well'. State what we do in one plain sentence, then make one small ask (a reply or a look, not a meeting). Use only facts from the research and product description; if the research is too thin to personalize honestly, say so and list what to find instead of writing a generic email. Begin your response with the email itself: subject line first, then body. Research: {{research}} Our product: {{product}} Sender: {{sender}}

Fill in: Your prospect research (their role, company, recent activity), a plain description of your product, and who is sending.

Known limits: Personalization quality is capped by research quality — a scraped headline produces a scraped-headline email.

Run evidence

Sandbox run 2026-08-19 · openai/gpt-5-mini

Input fixture
RESEARCH: Prospect is Dana Reyes, VP Customer Support at Meridian Freight
(3PL logistics, ~400 employees). Last month she posted on LinkedIn about cutting their
support backlog from 9 days to 4 and asked followers how they handle seasonal ticket
spikes. Meridian is hiring 6 seasonal support agents for Q4 per their careers page.
Their support portal runs on Zendesk (visible in page source of help.meridianfreight.com).

OUR PRODUCT: Relay is a support-ticket triage tool that plugs into Zendesk and
auto-routes and drafts first responses for repetitive ticket types. Teams typically
deflect or fast-track 30-50% of tickets in the first month (range across our 40
customers; varies by ticket mix).

SENDER: Sam Okafor, founder of Relay.

Model output (unedited)

Subject: You cut backlog from 9 days to 4 — handling Q4 ticket spikes?

Last month you posted on LinkedIn that Meridian's support backlog dropped from 9 days to 4 and asked how folks handle seasonal ticket spikes. I also saw Meridian is hiring six seasonal support agents for Q4 and that your support portal runs on Zendesk.

Relay is a support-ticket triage tool that plugs into Zendesk and auto-routes and drafts first responses for repetitive ticket types. Teams typically deflect or fast-track 30–50% of tickets in the first month (range across our 40 customers; varies by ticket mix).

Would you like a one-page example applying that 30–50% range to a ~400-employee 3PL like Meridian? Reply "yes" and I’ll send it, or "no" if not useful.

Sam Okafor
Founder, Relay

Editorial review (independent AI agents)

  • Accuracy — pass (editorial-accuracy/google/gemini-2.5-flash)
  • Safety — pass (editorial-safety/anthropic/claude-haiku-4.5)
  • Usefulness — pass (editorial-usefulness/openai/gpt-5-nano)
Curated

Cold email subject lines that survive the inbox

Write five subject line candidates for this cold email. Constraints: each must be honest about what the email contains (no fake 'Re:', no fake urgency, no clickbait), short enough for a phone inbox, and specific to this prospect or their problem — a subject that could top any email to anyone fails. For each candidate, one line on the psychological angle it plays (curiosity, relevance, peer proof, directness) and the risk it carries. Then recommend one and say why. Do not predict open rates. The email: {{email}} The prospect: {{prospect}}

Fill in: The cold email body you'll send and one line on who receives it.

Known limits: A great subject on a weak email raises opens, not replies — fix the email first.

Run evidence

Sandbox run 2026-08-19 · openai/gpt-5-nano

Input fixture
EMAIL: Hi Dana — saw your post about cutting Meridian's support backlog to
4 days. Genuinely impressive for a 3PL at your volume. My question: does that survive
Q4, when you're onboarding 6 seasonal agents? Relay plugs into Zendesk and auto-triages
the repetitive half of the queue — two other 3PLs use it specifically for peak season.
If it's worth 6 minutes, here's a recorded demo — no call needed. — Sam, founder of Relay

PROSPECT: VP Customer Support at a 400-person logistics 3PL, active on LinkedIn,
gets heavy vendor outreach.

Model output (unedited)

Here are five honest, short subject lines tailored to the prospect and problem, each with a single psychological angle and a risk note. Then I’ll pick a recommended one.

1) Will 6 seasonal agents in Q4 break your backlog?
- Angle: Relevance
- Risk: Highlights potential trouble; may feel a bit negative or alarming.

2) Relay + Zendesk: auto-triage for peak-season queues
- Angle: Curiosity
- Risk: Very product-focused; may read as a straight-up pitch rather than a personalized check-in.

3) Two 3PLs use Relay for peak season—demo?
- Angle: Peer proof
- Risk: Mentions competitors in generic terms; could seem salesy if not backed by specifics.

4) Dana: does your backlog survive Q4 onboarding?
- Angle: Directness
- Risk: Very direct personalization; could feel abrupt if not welcomed by the recipient’s tone.

5) Peak-season support: how you handle repetitive queues
- Angle: Relevance
- Risk: Slightly generic; may feel like a broad outreach rather than personal.

Recommended: Subject 4 — “Dana: does your backlog survive Q4 onboarding?”
- Why: It’s highly personalized, directly tied to the prospect’s stated challenge, and signals a thoughtful, problem-focused check-in rather than a generic pitch. It pairs cleanly with the message’s context (Q4 onboarding, backlog management) without sounding pushy, and invites a straightforward reply. If you want a slightly softer opener, you can swap Dana for the prospect’s name or omit it, but using the name adds a strong personalization edge.

Editorial review (independent AI agents)

  • Accuracy — pass (editorial-accuracy/google/gemini-2.5-flash)
  • Safety — pass (editorial-safety/anthropic/claude-haiku-4.5)
  • Usefulness — pass (editorial-usefulness/openai/gpt-5-nano)
Curated

Diagnose a sequence's reply rate from the copy

This sequence underperforms. Diagnose why from the copy alone: for each touch, name the single biggest reply-killer (seller-centric opening, oversized ask, fake personalization, no new value, guilt) with the exact phrase as evidence, quoted. Then, under 'Rewrite priorities', rank the three changes that would most plausibly move replies, each tied to the evidence — not generic best practices. Judge only what's in the copy; where the problem could be targeting or deliverability instead of copy, say so explicitly rather than inventing a copy fix. Sequence: {{sequence}} Audience: {{audience}}

Fill in: The full sequence copy, touch by touch, and one line on the audience it goes to.

Known limits: Copy diagnosis can't see list quality or spam placement — a perfect sequence to a dead list still gets zero.

Run evidence

Sandbox run 2026-08-19 · openai/gpt-5-mini

Input fixture
SEQUENCE (to Heads of Engineering, 50-200 person startups):
Touch 1: "Hi {{first}}, I hope you're doing well! I'm reaching out because we help
engineering leaders like yourself accelerate velocity by 40% with our AI-powered
sprint analytics platform. Do you have 30 minutes Thursday?"
Touch 2 (day 3): "Hi {{first}}, just floating this to the top of your inbox!"
Touch 3 (day 7): "Hi {{first}}, I know you're busy, but I'd hate for you to miss out.
We're offering 20% off annual plans this month. Can I get 15 minutes?"
Touch 4 (day 12): "Should I close your file?"

AUDIENCE: cold list scraped from a conference attendee page; no prior brand contact.

Model output (unedited)

Touch-by-touch diagnosis (single biggest reply-killer + exact quoted evidence)

1) Touch 1 — Biggest reply-killer: seller-centric opening
   Evidence: "I'm reaching out because we help engineering leaders like yourself accelerate velocity by 40% with our AI-powered sprint analytics platform."
   Why: Opens with a product/claim about you instead of a prospect-focused hook tied to anything specific about the recipient.

2) Touch 2 — Biggest reply-killer: no new value
   Evidence: "just floating this to the top of your inbox!"
   Why: Adds nothing to the conversation — no new reason to reply.

3) Touch 3 — Biggest reply-killer: guilt
   Evidence: "I'd hate for you to miss out."
   Why: Uses pressure language rather than offering relevance or a low-friction reason to engage.

4) Touch 4 — Biggest reply-killer: guilt (closing pressure)
   Evidence: "Should I close your file?"
   Why: This reads like a coercive close that usually shuts down replies from cold prospects.

Rewrite priorities (ranked — each tied to the copy evidence)

1) Replace the seller-centric opener with a specific, prospect-focused trigger tied to the conference scrape (fix for Touch 1)
   - Evidence tie: swap out "I'm reaching out because we help engineering leaders like yourself accelerate velocity by 40%..." with one line referencing the conference detail you scraped (role/session/company problem) and a concise, relevant question.  
   - Why this moves replies: cold recipients respond more to a short observation or tailored question about something they did/said (conference session, role, or public signal) than to a generic product claim. The current "we help..." claim is the primary barrier in touch 1.

2) Change asks to micro-commitments instead of calendar-sized asks (fix for Touch 1 & 3)
   - Evidence tie: replace "Do you have 30 minutes Thursday?" and "Can I get 15 minutes?" with a single 1–2 sentence, low-friction CTA (e.g., "Can I send one quick data point that’s helped teams like X?" or "One quick question — 2 min?").  
   - Why this moves replies: 30- and 15-minute asks from a cold outreach are oversized relative to trust; asking for a tiny next step materially increases response rates.

3) Remove guilt/pressure and replace follow-ups with incrementally new, specific value (fixes for Touch 2, 3 & 4)
   - Evidence tie: eliminate lines like "just floating this to the top of your inbox!", "I'd hate for you to miss out.", and "Should I close your file?" and instead include a single new, concrete item in each follow-up (a one-sentence insight about their likely pain, a micro-case study from a similar-sized company, or a quantified benchmark).  
   - Why this moves replies: follow-ups that add a new, relevant data point or a tiny win are reasons to reply; filler nudges and guilt-closing language are reasons not to.

Important non-copy callout (judging only the copy as requested)
- The list source (cold scrape from a conference attendee page / no prior brand contact) strongly suggests targeting and deliverability issues could be large contributors (spam flags, wrong role, stale emails, illegibility of personalization tokens). That’s outside copy and should be checked — don’t assume copy alone is the only problem.

If you want, I can rewrite the four touches with these three prioritized changes applied (examples that reference a conference signal, ask for a 2-minute next step, and add micro-value in follow-ups).

Editorial review (independent AI agents)

  • Accuracy — pass (editorial-accuracy/google/gemini-2.5-flash)
  • Safety — pass (editorial-safety/anthropic/claude-haiku-4.5)
  • Usefulness — pass (editorial-usefulness/openai/gpt-5-nano)
Curated

Follow-up that adds something instead of 'bumping'

Write a follow-up email for this thread. Rule: it must give the prospect something new — a relevant resource, a sharper framing of their problem, or an easier version of the ask — never 'just bumping this' or guilt. Read the thread and pick the follow-up angle the silence most likely calls for, then state in one line (before the email, labeled 'Angle:') which angle you chose and why. Then the email. Use only facts from the thread and the material provided; do not invent new offers or urgency. Thread so far: {{thread}} Material we could share: {{material}}

Fill in: The email thread so far (your send + any replies or silence), and any genuinely shareable material (posts, docs, results).

Known limits: A value-add follow-up needs actual value to add — with an empty material list it can only sharpen the framing.

Run evidence

Sandbox run 2026-08-19 · openai/gpt-5-nano

Input fixture
THREAD: [Mar 4, me → prospect] Subject: seasonal ticket spikes at Meridian.
Body: saw your post about cutting backlog to 4 days — impressive. When Q4 volume hits,
does that hold? Relay auto-triages repetitive Zendesk tickets; happy to show how 2 other
3PLs handle peak season. Worth a look? — Sam
[No reply for 9 days.]

MATERIAL: A 6-minute recorded demo of the Zendesk integration; a blog post 'How Coastway
Logistics handled 3x December ticket volume with 2 fewer temps' (real customer, published
with their approval); a pricing page.

Model output (unedited)

Angle: Share concrete, low-friction resources (a short Zendesk integration demo and a real customer case study) to illustrate how peak-season ticket volume can be managed, giving Meridian tangible examples without pressure.

Subject: A quick resource to address Meridian’s peak-season backlog

Hi Meridian team,

Since your Q4 backlog question came up, I wanted to share two concise resources that directly relate to handling peak-season ticket volume without added hiring:

- A 6-minute recorded demo of the Zendesk integration, showing how auto-triaging can streamline repetitive tickets.
- The Coastway Logistics case study: "How Coastway Logistics handled 3x December ticket volume with 2 fewer temps" (real customer, published with their approval) to illustrate how a peer managed a spike without increasing headcount.

If you’d like, I can send the links to these resources or walk through any specific questions you have after reviewing them. Would you prefer I share the materials or set up a quick 15-minute walkthrough at your convenience?

Editorial review (independent AI agents)

  • Accuracy — pass (editorial-accuracy/google/gemini-2.5-flash)
  • Safety — pass (editorial-safety/anthropic/claude-haiku-4.5)
  • Usefulness — pass (editorial-usefulness/openai/gpt-5-nano)
Curated

LinkedIn connection note that isn't a pitch

Write a LinkedIn connection request note to this person. It must fit LinkedIn's short note field, reference one specific thing they said or did (from the research), and contain no pitch, no link, and no meeting ask — the only goal is an accepted connection from a person who'd recognize why you asked. If the research contains nothing specific enough to reference honestly, say so and list two things to look for instead of writing a generic note. Begin your response with the note itself. Research: {{research}} Who I am: {{sender}}

Fill in: What you actually know about them (posts, talks, work), and one line on who you are.

Known limits: The note wins the connection, not the deal — pitching in the accept-thanks message afterwards undoes it.

Run evidence

Sandbox run 2026-08-19 · openai/gpt-5-nano

Input fixture
RESEARCH: Priya Nair, Head of Sales Enablement at Corvid Health (series B,
~200 people). Spoke on the 'Enablement That Sticks' podcast in July about killing their
40-slide onboarding deck and replacing it with call-recording reviews; argued new reps
should shadow lost-deal calls before won-deal calls.

SENDER: Alex Fontaine, building a call-library tool for enablement teams (Corvid is not
a customer; genuinely found the lost-deals-first take counterintuitive and smart).

Model output (unedited)

Priya, your take on killing the 40-slide onboarding deck and replacing it with call-recording reviews from the Enablement That Sticks episode resonated with me.

Editorial review (independent AI agents)

  • Accuracy — pass (editorial-accuracy/google/gemini-2.5-flash)
  • Safety — pass (editorial-safety/anthropic/claude-haiku-4.5)
  • Usefulness — pass (editorial-usefulness/openai/gpt-5-nano)
Curated

Plan a multi-touch sequence that doesn't harass

Design an outreach sequence for this prospect segment: for each touch give the channel, the day offset, the job that touch does (labeled 'Job:'), and a two-line sketch of its content — not full copy. Constraints: every touch must carry something new (no 'bumping'); mix channels only where the segment plausibly lives; the sequence ends with a clean breakup, not a fade-out. Then, under 'Kill criteria', state the reply signals that should immediately end or redirect the sequence. Ground everything in the segment description — where it's too vague to choose a channel or angle, say so explicitly. Segment: {{segment}} Product: {{product}} Assets we have: {{assets}}

Fill in: Who the segment is (role, company type, where they hang out), your product, and the content assets you can use.

Known limits: A sequence plan is a hypothesis — without reply-rate data per touch it cannot be optimized, only reasoned about.

Run evidence

Sandbox run 2026-08-19 · openai/gpt-5-mini

Input fixture
SEGMENT: Heads of Customer Support / Support Ops at US 3PL and freight
companies, 200-1000 employees, Zendesk stack, hiring seasonal agents for Q4 (hiring
signal = in-market). Active on LinkedIn; industry Slack (SupportDriven) membership
common; conference: Support Driven Expo in October.

PRODUCT: Relay — Zendesk ticket auto-triage for peak season.

ASSETS: 6-min recorded demo; Coastway Logistics case study (3x December volume, 2
fewer temps); free 'peak season staffing calculator' web tool; founder available for
15-min teardowns of a prospect's public help center.

Model output (unedited)

Sequence (target = Heads of Customer Support / Support Ops at US 3PL/freight, 200–1000 employees, using Zendesk and hiring seasonal agents for Q4)

Notes before the sequence
- Channels used: LinkedIn (connection + InMail/messages), email, SupportDriven Slack (DM or thread) — chosen because the segment is active on LinkedIn and commonly members of SupportDriven Slack. Use Slack touches only when the prospect’s membership is confirmed; if unknown, substitute the Slack touch with a LinkedIn message.
- Conference tie-ins reference Support Driven Expo (October). Do not assume the prospect will be there unless their profile or public event RSVP indicates attendance; where that’s unknown I specify the alternate copy.
- Every touch adds something new (tool, stat, demo, personalized insight, founder teardown, event ask). No bumping.
- Sequence length: 21 days, ends with an explicit breakup.

Touch 1
- Channel: LinkedIn connection request
- Day offset: 0
- Job: Get permission & establish relevance
- Sketch: Quick note: saw you run support for a 3PL on Zendesk and are hiring for Q4 — we help Ops teams avoid hiring extra temps with ticket auto-triage. Low-friction ask to connect.

Touch 2
- Channel: Email
- Day offset: 2
- Job: Deliver immediate utility and start a data-driven conversation
- Sketch: Link to the free “peak season staffing calculator” and one-line on how it models temp hires vs triage automation; CTA: try the calculator and ping back a number you don’t like.

Touch 3
- Channel: SupportDriven Slack DM (if confirmed member) — otherwise LinkedIn message
- Day offset: 5
- Job: Provide targeted social proof and prompt a lightweight reply
- Sketch: One-paragraph highlight from Coastway Logistics case study (3x December volume handled, while using 2 fewer temps) and a quick question: “Is your December the same shape as this?” (easy yes/no).

Touch 4
- Channel: Email
- Day offset: 9
- Job: Show product in-action (low time cost)
- Sketch: 6‑minute recorded demo link with two-line TL;DR: how Relay auto-triages Zendesk to deflect repetitive tickets and reduce temp headcount; CTA: 6 mins to see if it maps to your spike.

Touch 5
- Channel: LinkedIn message (or Slack DM if active and previously engaged)
- Day offset: 12
- Job: Personalize with a quick, public-help-center observation to build credibility
- Sketch: Two tactical observations from their public help center or Zendesk-facing pages (e.g., repetitive ticket type, missing automation) and one suggested quick win; soft CTA: “Want a free 15‑min teardown to flesh these out?”

Touch 6
- Channel: Email (Founder outreach)
- Day offset: 15
- Job: High-value conversion ask (low-commitment, high-signal)
- Sketch: Founder offering a free 15‑minute teardown of their public help center — promise: 2–3 tactical fixes + estimated impact on ticket volume/temp hires; calendly link / offered time slots.

Touch 7
- Channel: LinkedIn message (or SupportDriven Slack if they engage there) — conditional
- Day offset: 18
- Job: Event tie-in / next-step urgency (or virtual alternative)
- Sketch: If profile/event shows they’re attending Support Driven Expo: quick “We’ll be at Support Driven Expo in Oct — 15 mins to compare notes?” If attendance unknown: “If you’re not going, happy to meet virtually that week — still offering teardown.”

Touch 8 (Breakup)
- Channel: Email (final)
- Day offset: 21
- Job: Clean breakup with a clear, low-effort keep-in-touch option
- Sketch: Short note: last outreach for now; recap one line of value (Coastway result + calculator link), invite to book teardown anytime, and ask to reply with “not interested” or a referral if so.

Kill criteria (immediately end or redirect the sequence)
- Positive interest / booking signals (end sequence and hand off to AE/SDR):
  - Prospect replies asking to schedule a demo, teardown, or meeting.
  - Prospect asks for pricing, pilot details, or a procurement next step.
  - Prospect asks for the demo/case study/calculator (send immediately and hand off).
- Explicit negative signals (stop outreach; add appropriate tag/CRM note):
  - “Not interested,” “Don’t contact me,” unsubscribe, or asks to be removed from lists.
  - Prospect confirms they’re not hiring for Q4 / not in-market for seasonal staffing.
  - Prospect says they already have an equivalent solution in production and are locked into it for the season (unless they ask to revisit).
- Redirect signals (stop sequence and move to long‑term nurture):
  - Prospect says “we’ll revisit after Q4 / next budget cycle” — pause sequence and set a timed nurture reminder for the stated time.
  - Prospect refers you to another person — end current cadence and start a new, targeted sequence to the referred contact.
- Administrative / compliance:
  - Engagement indicates corporate vendor-block or procurement do-not-contact list — stop immediately and note in CRM.

If any reply requests an asset or meeting, the sequence should not continue the predefined touches — instead, immediately fulfill the request and hand off to the appropriate rep.

Editorial review (independent AI agents)

  • Accuracy — pass (editorial-accuracy/google/gemini-2.5-flash)
  • Safety — pass (editorial-safety/anthropic/claude-haiku-4.5)
  • Usefulness — pass (editorial-usefulness/openai/gpt-5-nano)
Curated

Post-event follow-up that proves you listened

Write a follow-up email to someone met at an event, from the conversation notes. It must reference the specific thing THEY said (not the event generally), continue that exact thread with one useful addition — a thought, a resource from our material, an intro we can actually make — and only then gesture at what we do in one sentence. If the notes are too thin to recall a real thread, say so and write the honest 'good to meet you' version instead, stating that choice in one labeled line ('Read:') first. Notes: {{notes}} Our material: {{material}}

Fill in: Your notes on who they were and what you talked about, plus material you could genuinely share.

Known limits: Written from your notes — if you misremembered their problem, the email confidently continues the wrong conversation.

Run evidence

Sandbox run 2026-08-19 · openai/gpt-5-nano

Input fixture
NOTES: Met Ingrid Salo (RevOps lead, Nordwind Travel — corporate travel
platform) at SaaStock booth crawl. She complained their SDRs burn 40% of their time
researching accounts that never fit ICP; asked whether anyone actually automates
account scoring 'without it being astrology'. Skeptical of AI tools, likes seeing
methodology. We ran out of time mid-conversation.

MATERIAL: Our methodology doc explaining exactly which signals our account scorer
uses and how weights are validated (public, no gate); a 10-account free scoring
sample we offer prospects.

Model output (unedited)

Subject: Re: Reducing research time on non-ICP accounts

Hi Ingrid,

You mentioned SDRs burn 40% of their time researching accounts that never fit ICP—that really resonates with the challenge RevOps teams face in staying focused on ICP.

To help address that, I can share our public methodology doc that explains exactly which signals our account scorer uses and how the weights are validated (no gate). We also offer a 10-account free scoring sample prospects can run to see how the scoring behaves against their ICP.

If it would be helpful, we can set up a quick 15–20 minute call with our product/data science lead to walk through the methodology and discuss how Nordwind Travel could apply it to reduce wasted research time.

We provide transparent, signals-based account scoring that is explainable and aligned with ICP, to automate prioritization and reduce blind guessing.

Editorial review (independent AI agents)

  • Accuracy — pass (editorial-accuracy/google/gemini-2.5-flash)
  • Safety — pass (editorial-safety/anthropic/claude-haiku-4.5)
  • Usefulness — pass (editorial-usefulness/openai/gpt-5-nano)
Curated

Reply to a warm 'tell me more' without overplaying it

A prospect replied with mild interest. Write the response that converts interest into a concrete next step without overwhelming them: answer their actual question first in plain language, then offer exactly one next step sized to their energy level (a curious one-liner gets a resource; a detailed question gets a short call offer). Read their reply carefully for what they did NOT ask — do not dump features they showed no interest in. Use only facts from the material provided. Begin your response with the email. Their reply: {{reply}} Original thread: {{thread}} Product facts: {{facts}}

Fill in: Their reply verbatim, the thread before it, and the product facts you're allowed to claim.

Known limits: The fastest way to lose a warm reply is answering it with a calendar link and a feature dump.

Run evidence

Sandbox run 2026-08-19 · openai/gpt-5-nano

Input fixture
THEIR REPLY: "Interesting. How does it handle tickets in Spanish? Half our
volume is LATAM."

ORIGINAL THREAD: Cold email about Relay auto-triaging repetitive Zendesk tickets for
3PL logistics companies during peak season.

PRODUCT FACTS: Relay classifies and drafts responses in English, Spanish, and
Portuguese; Spanish accuracy is measured at parity with English on our benchmark;
drafts always route through a human agent for send; setup is a Zendesk app install,
~30 minutes; pilot is 14 days on real ticket history.

Model output (unedited)

Hi there,

Yes—Relay handles tickets in Spanish. It classifies and drafts responses in Spanish (as well as English and Portuguese). On our benchmark, Spanish accuracy is parity with English, and drafts always route through a human agent before sending.

Next step: Want a quick read? I can share a 1-page benchmark summary showing Spanish parity with English.

Editorial review (independent AI agents)

  • Accuracy — pass (editorial-accuracy/google/gemini-2.5-flash)
  • Safety — pass (editorial-safety/anthropic/claude-haiku-4.5)
  • Usefulness — pass (editorial-usefulness/openai/gpt-5-nano)
Curated

Shrink the ask until yes is easy

This outreach asks for too much commitment. Rewrite its ask into three versions, each one step smaller: the smallest possible yes (a one-word reply or a click), a middle ask (async: a look at something, an opinion), and the original meeting ask repositioned as optional. For each version, one line on when it's the right size (cold list vs warm signal vs referral). Keep the email's substance; change only the ask and what leads into it. Begin your response with version one. Email: {{email}} Context: {{context}}

Fill in: The outreach email and one line on how cold this audience is.

Known limits: Small asks raise reply rates but lengthen the path — a referred, in-market prospect can handle the meeting ask directly.

Run evidence

Sandbox run 2026-08-19 · openai/gpt-5-nano

Input fixture
EMAIL: Hi Marcus — I run GridWatch, we help utilities monitor transformer
health with existing SCADA data instead of new sensors. Companies like yours are
losing $2M+/yr to preventable transformer failures. Do you have 45 minutes this week
for a demo of how we'd map this to your grid? — Lena

CONTEXT: Cold list of grid-reliability engineers at mid-size US utilities; no prior
touch; the $2M figure is an industry-report average, not verified for the prospect.

Model output (unedited)

Version 1
EMAIL: Hi Marcus — I run GridWatch, we help utilities monitor transformer health with existing SCADA data instead of new sensors. Companies like yours are losing $2M+/yr to preventable transformer failures. If you can simply reply YES to this email, I’ll share a 60-second explainer video showing how we’d map this to your grid. — Lena
Right size: cold list — a one-word yes is the smallest, simplest test here.

Version 2
EMAIL: Hi Marcus — I run GridWatch, we help utilities monitor transformer health with existing SCADA data instead of new sensors. Companies like yours are losing $2M+/yr to preventable transformer failures. Could you take a quick look at this one-page overview showing how we'd map transformer health to your grid and share your thoughts? Link: [brief] — Lena
Right size: warm signal — a quick look at something plus an opinion fits a warmer audience.

Version 3
EMAIL: Hi Marcus — I run GridWatch, we help utilities monitor transformer health with existing SCADA data instead of new sensors. Companies like yours are losing $2M+/yr to preventable transformer failures. If you'd like, we can schedule a 45-minute demo this week to map this to your grid. It's completely optional—if you prefer not to schedule, I can share a brief written overview instead. — Lena
Right size: referral — an optional demo is best when a referral or warm introduction is present or expected.

Editorial review (independent AI agents)

  • Accuracy — pass (editorial-accuracy/google/gemini-2.5-flash)
  • Safety — pass (editorial-safety/anthropic/claude-haiku-4.5)
  • Usefulness — pass (editorial-usefulness/openai/gpt-5-nano)
Curated

The breakup email that keeps the door open

Write the final email in this dead thread. Tone: gracious exit, zero guilt, zero passive aggression — assume they were busy, not rude. Close the loop in a way that makes replying easy if timing was the issue: state you'll stop following up, leave one concrete artifact they can use without talking to us, and one sentence on when it makes sense to reconnect. Do not manufacture scarcity or a fake deadline. Begin your response with the email, subject line first. Thread summary: {{thread}} Artifact we can leave: {{artifact}}

Fill in: A summary of the thread (what was sent, what happened), and the artifact you can leave behind (guide, benchmark, tool).

Known limits: Breakup emails get replies precisely because they're rare and honest — using one on every thread burns the effect.

Run evidence

Sandbox run 2026-08-19 · openai/gpt-5-nano

Input fixture
THREAD SUMMARY: Four emails over 6 weeks to the Head of RevOps at a
120-person fintech: intro (no reply), value-add follow-up with a benchmark report
(opened 3 times, no reply), a short check-in (no reply), and a case-study share
(no reply). No unsubscribe, no negative signal — just silence.

ARTIFACT: Our free 'SaaS outbound benchmarks 2026' report (no email gate) at
example.com/benchmarks — reply rates and send volumes across 400 anonymized teams.

Model output (unedited)

Subject: Free benchmark resource you can use now + a closing note

Hi there,

I know your schedule is demanding, so I’ll keep this concise.

- The free 'SaaS outbound benchmarks 2026' report (no email gate) at example.com/benchmarks — reply rates and send volumes across 400 anonymized teams.

I’ll pause follow-ups to respect your time. If timing aligns in the next quarter or when you’re evaluating outbound benchmarks, we can reconnect briefly to discuss quick takeaways or next steps.

Best regards,
[Your Name]
[Title]
[Company]
[Email]
[Phone]

Editorial review (independent AI agents)

  • Accuracy — pass (editorial-accuracy/google/gemini-2.5-flash)
  • Safety — pass (editorial-safety/anthropic/claude-haiku-4.5)
  • Usefulness — pass (editorial-usefulness/openai/gpt-5-nano)
Curated

Turn raw company signals into an outreach angle

From these raw signals about a company, extract the strongest outreach angle for what we sell. Under a heading 'Signals ranked', list each signal with a one-line read of what it implies about their current pain and priorities, ranked by how directly it connects to our product. Under 'The angle', commit to one angle: the specific tension between what they're visibly trying to do and what our product changes. Under 'Do not use', flag any signal that would feel invasive or creepy to reference in an email. Base everything strictly on the signals given. Signals: {{signals}} Our product: {{product}}

Fill in: Raw signals you collected (job posts, news, tech stack, posts, funding) and a plain product description.

Known limits: Signals age fast — a job post filled two months ago flips the read from 'scaling' to 'already staffed'.

Run evidence

Sandbox run 2026-08-19 · openai/gpt-5-mini

Input fixture
SIGNALS about Brightpath Learning (B2B corporate-training platform, ~150
employees): 1) hiring 3 SDRs and a 'RevOps Manager - HubSpot' (careers page, posted 2
weeks ago); 2) CEO posted that they missed their H1 pipeline goal and are 'rebuilding
top of funnel from scratch'; 3) switched their website chat from Drift to a free tool
(page source, last month); 4) their VP Sales left for a competitor in June (LinkedIn);
5) G2 reviews mention slow sales follow-up twice in Q2.

OUR PRODUCT: Cadence-audit tool that scores outbound sequences against reply-rate
benchmarks and rewrites the weakest steps.

Model output (unedited)

Signals ranked
1) Hiring 3 SDRs + “RevOps Manager - HubSpot” (careers page, 2 weeks ago)
   - Implies they’re scaling outbound capacity and want to standardize sequences in HubSpot ASAP.

2) CEO: missed H1 pipeline goal; “rebuilding top of funnel from scratch” (public post)
   - Implies pressure to produce pipeline quickly and a willingness to change tactics/stack.

3) G2 reviews: “slow sales follow-up” mentioned twice in Q2
   - Implies execution gaps in outbound/follow-up that are costing pipeline conversion.

4) VP Sales left for a competitor in June (LinkedIn)
   - Implies sales leadership disruption and a likely short-term loss of process continuity.

5) Switched website chat from Drift to a free tool (page source, last month)
   - Implies either cost pressure or deprioritizing paid chat/real-time channels, potentially shifting reliance to outbound/email.

The angle
They’re aggressively rebuilding top-of-funnel and ramping SDR headcount (including a HubSpot-focused RevOps hire), but public signals show weak follow-up and missing pipeline — the tension is between “hire/ramp more reps fast” and “their current outbound sequences/processes aren’t converting.” Position Cadence as the quick, low-friction lever that raises reply rates and fixes the weakest steps in their outbound playbook so new SDRs ramp into higher-performing outreach and RevOps can deploy proven sequence rewrites into HubSpot without waiting months for trial-and-error.

Do not use
- “Switched website chat from Drift to a free tool (page source)” — calling out page-source detection or specific tool changes can feel like intrusive technical snooping.
- “VP Sales left for a competitor (LinkedIn)” — referencing an individual personnel move (or naming the competitor) can feel personal or opportunistic.

Editorial review (independent AI agents)

  • Accuracy — pass (editorial-accuracy/google/gemini-2.5-flash)
  • Safety — pass (editorial-safety/anthropic/claude-haiku-4.5)
  • Usefulness — pass (editorial-usefulness/openai/gpt-5-nano)
Curated

Warm handoff email between seller and specialist

Write the handoff email that introduces a new person into this deal thread (SDR to AE, AE to founder, sales to solutions engineer). It must transfer context so the prospect repeats nothing: name why the new person specifically (their relevant expertise, from the notes), summarize the prospect's situation in two labeled lines ('Where you are:' / 'What's next:') the prospect would agree with, and set the next step with the new owner. Never inflate the new person's title or invent expertise. Deal notes: {{notes}} New person: {{who}}

Fill in: Deal notes (who the prospect is, what's been discussed, where it stands) and who is being introduced with their real background.

Known limits: A handoff that summarizes the deal wrong forces the prospect to correct it — worse than no summary.

Run evidence

Sandbox run 2026-08-19 · openai/gpt-5-nano

Input fixture
DEAL NOTES: Prospect: Meridian Freight (Dana Reyes, VP Support). Watched
demo video, replied asking about Spanish ticket handling and pilot logistics. Wants to
pilot on Q3 historical tickets before Q4 lock-in. Concerned about agent adoption after
a failed chatbot rollout last year. Timeline: decision by Sep 15.

NEW PERSON: Maria Duarte, Relay's solutions engineer — built the Spanish/Portuguese
classification models, ran the last 9 pilot onboardings including two logistics
companies.

Model output (unedited)

Subject: Handoff: Meridian Freight pilot — Maria Duarte taking over

Hi Dana,

I’m handing the baton to Maria Duarte, Relay’s solutions engineer, who will be your primary contact for the pilot moving forward. Maria built the Spanish/Portuguese classification models and led the last 9 pilot onboardings, including two logistics companies, so she has the right background to address your Spanish ticket handling and pilot logistics questions.

Where you are:
- You want to pilot on Q3 historical tickets before Q4 lock-in, and you’re concerned about agent adoption after last year’s chatbot rollout.

What’s next:
- You’re aiming for a decision by Sep 15; Maria will work with you to finalize the pilot scope (Spanish ticket handling and pilot logistics) and plan the pilot execution. Next step: schedule a 45–60 minute session with Maria to lock in scope, success metrics, and timing.

Please share your availability for this week, and Maria will coordinate.

Best,
[Your Name]

Editorial review (independent AI agents)

  • Accuracy — pass (editorial-accuracy/google/gemini-2.5-flash)
  • Safety — pass (editorial-safety/anthropic/claude-haiku-4.5)
  • Usefulness — pass (editorial-usefulness/openai/gpt-5-nano)