§0 Three sequences, three filters, three top combos
The plan in 4 lines
Goal: 3-4 qualified $20K+/mo accounts/month for Avishay.
Persona: CEO/Founder only (B3 data: 94% of all booked meetings).
Volume: 1,400 leads across 3 cohorts. 2-touch sequence. A/B CTA split 50/50 per cohort.
Source list: a_b_valid_contacts_ultra_strict_clean.csv filtered per cohort spec below.
| Cohort | Offer | Filter | Sample | Win-score (matrix) |
|---|---|---|---|---|
| A | Funding Map | CEO · 20-50 emp · funded Series A/B · EU UK+DE+NL+Nordic | 500 | 8.7 |
| B | Hiring Signal | CEO · 20-100 emp · hiring SRE/Platform/DevOps last 90d · cloud-native | 400 | 9.1 |
| C | DXDT Audit | CEO · 20-100 emp · BuiltWith detects BigQuery/Snowflake/Databricks/k8s | 500 | 9.0 |
§0.5 Tier-A Winning Patterns Palette · A_06 forensics
The proven winners (use across all 3 cohorts where applicable)
Subject (lowercase): extend runway (72% W) · question for {{first_name}} (91% W)
Hook openers: are you using AWS or GCP? (50% W) · saw you ... observation (50% W) · I know you get a ton of these (Jan-Feb proven)
Winning phrases in body: extend runway (81% W) · certified partner (60% W) · $50-100k+ credits (57% W) · paid by them, not you (trust frame)
CTAs: worth a look? (48% W) · worth a chat? · can I share more? · can I send the anonymized results from a similar Series B scaleup?
Tier-A KILLERS (never in copy)
Subjects: thoughts · quick one · 60 seconds · Curious
Phrases: premier-tier partner · 30% off cloud bill · as a CEO I'll keep this short · walk you through how it works · P.S. footer · em dashes (use periods/commas)
Hebrew: מענק (Shira flagged 5x) — use קרדיטים instead.
A Cohort A · Funding Map
dxdt <> {{company_name}}Hey {{first_name}},
Saw {{company_name}}'s Series {{round}}. Most scaleups your stage qualify for two or three hyperscaler funding programs the AWS rep never surfaces.
Worth comparing notes? Calendar if easier: [calendar_link]
👋 funding questionHey {{first_name}},
Saw {{company_name}} closed Series {{round}} in {{quarter}}. Quick context on why I'm reaching out.
We work with Series A and B SaaS scaleups across {{geo}} on hyperscaler funding programs. MAP, RAMP, Founders Hub, ISV Accelerate. Most founders at this stage qualify for two or three of these and never hear about them, because the AWS rep is comped on consumption and the Google side is structured the same way.
We're a certified AWS and Google partner. The way we work: we map the programs that apply to your stage and cloud commit, then walk you through the claim. We're paid by AWS and Google on the co-sell side, so it doesn't cost you anything.
MAP alone usually covers a meaningful slice of first-year cloud spend. The rest layer on depending on commit and product stage.
Worth comparing notes on what similar Series {{round}} teams in {{geo}} are claiming? Calendar if easier: [calendar_link]
The annoying part about hyperscaler programs is the eligibility rules. They contradict each other depending on which page you land on. We've watched founders miss programs they qualified for because the AWS side didn't mention it. Same the other way with Google. We mapped the overlap so it's all in one place. Worth me sharing what similar scaleups qualify for?
programs you missed{{first_name}}, quick thought.
Most founders we talk to find out about AWS MAP only after they've finished migrating. By then the funding window has closed. Nothing left to claim.
If your migration is still ahead, MAP alone can come to roughly a quarter of your first-year cloud spend. Paid back as credits. We handle the claim work. No fee.
Can I share more?
Auto-reply on positive intent (3-question intake)
1. Primary cloud (AWS / GCP / Azure / multi)
2. Funding stage (seed / Series A / B / later)
3. Approx monthly cloud spend
→ Personalized 1-page funding-eligibility map sent within 24hr · CTA: "want us to claim them for you?"
Kill criterion
If <2 "yes send the map" replies per 500 sends in 14 days → kill, switch to Cohort B angle on same list.
B Cohort B · Hiring Signal
dxdt <> {{company_name}}Hey {{first_name}},
Saw you're hiring {{hiring_role}}. That role usually inherits cloud waste no one flagged. We map it before they start.
Worth a look? [calendar_link]
🛠 before {{hiring_role}} startsHey {{first_name}},
Saw {{company_name}} is hiring {{hiring_role}}. Quick context.
When we've gone back to founders six months after a new SRE or Platform hire started, most say the first quarter went to cleanup work nobody had flagged. Old commitments, idle resources, oversized storage tiers, the kind of thing that's invisible until someone goes looking.
We're a certified AWS and Google partner. Our AI runs on funded scaleups before the new hire starts and surfaces the same artifacts an SRE team would produce over a couple of months. They walk into a cleaner environment and their first quarter goes to the roadmap you actually hired them for.
We're paid by AWS and Google on the co-sell side, so it doesn't cost you anything.
Worth comparing notes on what we usually find right before someone like {{hiring_role}} starts? Calendar if easier: [calendar_link]
One more thing on the hiring side. We've gone back to founders six months after their new SRE started. Most say the first quarter went to cleanup work they wish they'd handled before the hire arrived. It's runway sitting in your bill. And it's the most boring kind of cleanup to give a new engineer as their first project. Want me to share what we found on a similar peer?
scan before hire{{first_name}}, quick thought.
When {{company_name}}'s new {{hiring_role}} starts, the cloud is exactly as the previous setup left it. Old commitments. Old storage classes. Old idle resources.
Our AI maps the inefficiencies in advance. The new hire's first month goes to what you actually hired them for.
No fee on our end. We're paid by AWS and Google on co-sell. It doesn't cost you anything.
Can I share more?
Auto-reply on positive intent
1. Confirm role (SRE / Platform / DevOps / FinOps / Security)
2. Approx monthly cloud spend bracket
3. Current security stack (Wiz / Orca / Lacework / None)
→ Personalized 1-pager + DXDT demo invitation within 24hr.
Kill criterion
If <1 strong reply per 400 sends in 14 days → kill, swap to Cohort C list.
C Cohort C · DXDT Audit (data-stack signal)
dxdt <> {{company_name}}Hey {{first_name}},
Saw {{company_name}} runs {{detected_stack}}. That stack is the #1 source of unflagged cloud waste at scale.
Worth a scan? [calendar_link]
👋 {{detected_stack}} questionHey {{first_name}},
Saw {{company_name}} is running {{detected_stack}}. Quick context on why that caught my attention.
In our scans, that stack at your headcount is consistently where the largest unflagged cloud spend sits. Idle warehouses, oversized k8s clusters, storage tier mismatches, retention windows nobody touched in two years. The kind of thing that doesn't show up on a monthly report because everything's "working".
We're a certified AWS and Google partner. We've built an AI that runs cost optimization and security checks in one pass on funded scaleups. Same kind of work an SRE team would normally do over a couple of months, surfaced much faster.
We're paid by AWS and Google on the co-sell side, so it doesn't cost you anything.
Worth comparing notes on what we typically find on similar {{detected_stack}} stacks? Calendar if easier: [calendar_link]
One more thing on the savings side. We ran the same scan on a similar funded scaleup recently. About a fifth of their cloud was completely unused. Another chunk could be cut just by adjusting how they'd committed to spend. The security side surfaced a few long-standing gaps their existing tools hadn't flagged. Want me to share what we typically find on similar scaleups?
one click{{first_name}}, here is the short version.
We've built an AI that runs cloud-cost optimization and security checks together. One pass, on funded scaleups. Same kind of work an SRE team would normally do over a couple of months, surfaced much faster.
No fee on our side. We're paid by AWS and Google on co-sell. It doesn't cost you anything.
Can I share more?
Auto-reply on positive intent
1. Primary cloud (AWS / GCP / Azure / multi)
2. Approx monthly spend ($20K / $50K / $100K+)
3. Heaviest workload (data / LLM-AI / k8s / other)
→ Personalized findings PDF + DXDT demo invitation within 24hr.
Kill criterion
If <2 strong replies per 500 sends in 14 days → audience burnt OR offer mis-fit. Pause + diagnose.
§4 Sequencing + Hard Rules (locked across all 3 cohorts)
Locked rules
• NO em dashes in copy. Use periods or commas.
• Subject lines lowercase when personalized.
• Word count 50-90.
• 2-touch only (Day 1 + Day 6). Kill step-3+ default. Day 7-8 is a NEW THREAD, not a step-3.
• NO call ask in first email. All asks are async (PDF / 1-pager / anonymized results / "share more").
• Banned subjects: Curious, Quick question, thoughts, 60 seconds.
• Banned openers: "I hope this email finds you well", "Just wanted to touch base", "Following up", "One more thought".
• CTA answerable in 5 words or less.
• Pricing trust line on every E1: "No mgmt fee. Paid by AWS/Google on co-sell, conditional on satisfaction."
Suppression list (apply BEFORE upload)
17 contacts to suppress per B7 (competitor employees + WideOps own staff): CloudZone CEO Adi Heinisch · 2bcloud's Tehila · WideOps staff · Comm-IT staff · plus 7 others. List in analysis/B_07_competitor_displacement.md.
Variables required in upload
{{first_name}} · {{company_name}} · {{hiring_role}} (Cohort B only) · {{role_title}} (Cohort B subject)
All other phrasing static across the cohort.
§5 Expected Outcome Math
| Step | Conversion (per B3 + B5 data) | Cohort A | Cohort B | Cohort C | Total |
|---|---|---|---|---|---|
| Sent | — | 500 | 400 | 500 | 1,400 |
| "Yes" reply rate (cohort-fit) | ~0.7-1.2% on signal-filtered | 5 | 5 | 6 | ~16 |
| Strong replies (positive + soft + booked) | ~50-65% of "yes" replies | 3 | 3 | 4 | ~10 |
| Meetings booked | 27.8% (B5 funnel) | 1 | 1 | 2 | ~4 |
| Qualified ($20K+/mo confirmed) | 73% (B5) | ~1 | ~1 | ~1 | ~3 |
Hit / miss
Math lands at ~3 qualified $20K+/mo meetings from Wave 1. Lower bound of Avishay's 3-4/mo target. Wave 2 (50-100 emp + Renewal + AI API) layers on for steady-state 3-4/mo.
If Wave 1 OVERSHOOTS (5+ qualified) → kill Wave 2, scale winners. If UNDERSHOOTS (≤1) → diagnose: copy/list/signal failure.
Send + schedule
• Day 1-5: ship 280 sends/day across 3 cohorts (100 + 80 + 100)
• Day 6: Email 2 fires automatically per Instantly sequence
• Day 8: Email 3 (new thread) fires
• Day 14: First metrics check
• Day 21: Kill loser, scale winner to 1,500-2,000 for Wave 2