Workflow · Production ~30 min run Audience Builder output required

One sequence for every account
under-serves nine cells.

A copy-paste Claude prompt that takes the 9-cell audience matrix from ABM Audience Builder and produces differentiated outreach sequences per cell — 7-step high-personalization sequences for Tier-1 Decision Makers, 4-step nurture sequences for Tier-3 Researchers, and the seven cells in between. Different cadence, channel mix, and message angles per intent-tier × role-segment combination.

9cells
3 intent tiers × 3 role segments
7→ 4
Touches per sequence (T1-DM → T3-Res)
21→ 30d
Cadence range across cells
Quarterlyrefresh
Templates decay 20-40% per quarter
01 The Problem in 60 Seconds

Paid ads target 9 audience cells.
Outreach uses one sequence.

A B2B SaaS team runs ABM Audience Builder, gets a clean 9-cell audience matrix (3 intent tiers × 3 role segments), and pushes those audiences to LinkedIn Ads with paid creative differentiated per tier. The paid side is sophisticated — different ads for T1-DM vs T3-Researcher, different budget allocation per cell, different optimization signals per cell. Then the SDR team gets the same accounts and runs them through one outreach sequence. Same 6 emails, same cadence, same message angle whether the prospect is a CFO at a high-intent enterprise account or a research analyst at a low-intent SMB. The paid program has 9 cells of differentiation; the outreach program has one. The two programs are running on the same account list with completely different operating logic.

The deeper problem is that intent tier and role segment determine completely different outreach economics. A T1-DM (high intent, decision authority) deserves 7-10 personalized touches over 21 days because expected pipeline contribution per account is $50K+. A T3-Researcher (low intent, no authority) deserves 4-5 lightweight touches over 30 days because expected contribution is enabling rather than directly closing. Using the same sequence across both wastes effort on the T3 (over-investing in low-leverage accounts) AND under-engages the T1 (under-investing in high-leverage accounts). The 9-cell matrix forces the math to be explicit per cell.

This workflow generates the differentiated sequences. For each of the 9 cells, Claude produces a complete sequence: number of steps, cadence, channel mix (LinkedIn / email / phone / video), message angles, and copy drafts ready to load into outreach tooling (Outreach, Salesloft, Smartlead, Apollo). Run quarterly — sequences decay 20-40% per quarter as templates leak across the addressable market and prospect inboxes adapt. Coordinate with the paid side so paid + outreach run on the same audience tiers.

Sequence Intensity Matrix · 9 Cells, 9 Different Operating Logics High-leverage cells get expensive sequences
Tier ↓   Role →
Decision Maker
Influencer
Researcher
Tier 1 · High Intent
T1-DM · Most expensive 7-10 touches · 21 days · 40% LinkedIn (voice + video) · 40% email (hyper-personalized) · 20% phone
T1-Influencer 6-7 touches · 21 days · 30% LinkedIn · 60% email · 10% phone · Champion-cultivation angle
T1-Researcher 5-6 touches · 21 days · 20% LinkedIn · 80% email · Education-led angle
Tier 2 · Mid Intent
T2-DM 6-7 touches · 28 days · 30% LinkedIn · 50% email · 20% phone · Awareness-to-evaluation angle
T2-Influencer 5-6 touches · 28 days · 25% LinkedIn · 70% email · 5% phone · Insight-share angle
T2-Researcher 4-5 touches · 28 days · 15% LinkedIn · 85% email · Resource-share angle
Tier 3 · Low Intent
T3-DM 5-6 touches · 30 days · 25% LinkedIn · 60% email · 15% phone · Awareness-only angle (don't push for meeting yet)
T3-Influencer 4-5 touches · 30 days · 20% LinkedIn · 80% email · Light nurture
T3-Researcher · Lightest 4 touches · 30 days · 30% LinkedIn (connect-only) · 70% email · Templated, low personalization
02 The Prompt

Copy this prompt into
Claude Desktop.

The gold variables — your brand, ICP, value proposition, and the 9-cell audience matrix from ABM Audience Builder — are the parts you edit. Run quarterly to refresh sequences as templates decay.

claude_desktop — abm_outreach_sequences.md
RoleYou are designing the quarterly ABM outreach sequence library for my B2B SaaS company. Take the 9-cell audience matrix from ABM Audience Builder (3 intent tiers × 3 role segments) and produce a differentiated multi-step outreach sequence for each cell — number of steps, cadence, channel mix, message angles, and copy drafts ready to load into outreach tooling. My BrandBrand: [your B2B SaaS brand name] Site URL: [your domain] ICP description: [1-2 lines on your buyer persona] Value proposition: [1 line on what you do, who it's for, the outcome] Average ACV: [e.g. "$25K mid-market"] 9-Cell Audience Matrix// Paste the 3 intent tiers × 3 role segments definition from ABM Audience Builder. The sequence designer produces one sequence per cell. Tier 1 (high intent — engagement signals + ICP fit): [definition from Audience Builder] Tier 2 (mid intent — ICP fit + 1-2 engagement signals): [definition] Tier 3 (low intent — ICP fit, no engagement): [definition] Role segment 1 — Decision Maker: [titles e.g. "VP Sales / CRO / Head of GTM"] Role segment 2 — Influencer: [titles e.g. "Marketing Director / Sales Ops Lead / RevOps Manager"] Role segment 3 — Researcher: [titles e.g. "Marketing Manager / Sales Ops Analyst / Demand Gen Specialist"] Optional: Past Performance Data// If you have historical reply rates per channel from Outreach/Salesloft/Smartlead, paste them. The designer calibrates sequences to your actual benchmarks rather than industry defaults. Past sequence reply rates: [e.g. "LinkedIn DM 8-12%, cold email 3-5%, voice note 6-10%"] TaskFor each of the 9 cells, produce a complete sequence with these components: 1. Sequence parameters: - Number of touches (T1-DM 7-10, T1-Influencer 6-7, T1-Researcher 5-6, T2-DM 6-7, T2-Influencer 5-6, T2-Researcher 4-5, T3-DM 5-6, T3-Influencer 4-5, T3-Researcher 4) - Cadence (T1 = 21 days, T2 = 28 days, T3 = 30 days) - Channel mix (proportions of LinkedIn / email / phone / video by cell — see the matrix in the framework) - Goal per cell (T1-DM = book meeting; T1-Influencer = champion cultivation; T3-Researcher = light nurture for tier-up) 2. Touch-by-touch breakdown: - For each touch: day, channel, angle, copy draft (LinkedIn DM 200 chars, cold email 80-120 words, voice note 30-45 sec script) - Each touch builds on prior context — don't restart the conversation each touch - Touches escalate in personalization for T1 cells (touch 1 = lightly personal, touch 5 = hyper-personalized using research) - Touches stay templated for T3 cells (light personalization tokens, scalable execution) 3. Personalization scaffolding: - For T1 cells: required research per account (Apollo + LinkedIn + recent news + tech stack signals — 15-20 min per account) - For T2 cells: structured personalization (industry + role + 1 trigger event) - For T3 cells: tokenized personalization (first name + company + role) 4. Channel-specific copy drafts: - LinkedIn connection request (T1, T2, T3 variants — different opening hooks per tier) - LinkedIn DM after connect (T1 = personalized question; T2 = insight-share; T3 = light intro) - Cold email (3-4 drafts per cell — opener, value-add, social proof, breakup) - Voice note script for T1 cells (30-45 sec, conversational tone, specific to the prospect's signal) - Phone call script for T1-DM and T2-DM (60-90 sec, opens with the trigger event, ends with meeting ask) 5. Stop conditions: - When to stop a sequence (response received, account flagged disqualified, calendar booked) - When to swap a prospect to a different cell mid-sequence (engagement signals upgrade T2 → T1) - When to handoff from SDR to AE (qualifying response on T1-DM, content engagement on T1-Influencer) Output format1. Headline: total sequences generated (9), total estimated SDR setup time (18-36 hours across all cells), highest-leverage cell (typically T1-DM). 2. 9-cell sequence library matrix: high-level summary per cell (touches × cadence × channel mix × goal). 3. Full sequence detail for 3 representative cells: T1-DM (the highest-leverage), T2-Influencer (mid-tier middle of stack), T3-Researcher (lowest-touch). Other 6 cells follow the same structure but condensed. 4. Channel mix and personalization recommendations summary. 5. Honest calibration: - If your team uses generic SDR tooling without LinkedIn integration, drop voice note + LinkedIn voice from sequences and rebalance toward email + phone. - If past LinkedIn reply rates < 4%, the LinkedIn channel may be saturated for your ICP. Reduce LinkedIn weight in T1 cells; increase email touches. - If past email reply rates < 2%, your domain reputation or list quality has issues. Recommend pause-and-fix before designing sequences. - If headcount can't realistically run T1-DM at 7-10 touches × 100+ accounts/quarter, reduce T1-DM touch count to 5-6 and accept the lower expected reply rate. Better than running incomplete 7-touch sequences. - For PLG companies with self-serve onboarding, T3 sequences should redirect to product-led activation rather than meeting requests — different end-of-sequence CTA. // Be specific in copy drafts. "Personalized opener referencing recent funding" is not actionable. The actual 90-word email draft with [TRIGGER_EVENT] tokens IS actionable. // Don't write the same opener template for all 9 cells. T1-DM opener should reference a specific signal (recent hire, product launch, hiring pattern); T3-Researcher opener should be a templated insight share. // Voice note scripts should be conversational, not formal. They're listened to, not read. // Each sequence should have a clear breakup email at the final touch — buyers respect honest endings, and the breakup email itself often drives 8-15% reply rates.
i
ABM Audience Builder must run first. The sequence designer takes the 9-cell audience matrix as input. Optional HubSpot connector for past sequence performance data improves calibration. Output is concrete enough to load directly into Outreach / Salesloft / Smartlead / Apollo with minimal SDR modification.
03 What Claude Returns

The 9-cell library. Three full sequences.

Sample output for a hypothetical mid-market B2B SaaS brand (RevOps platform, $25K ACV). Sequence designer produces 9 differentiated sequences, with full touch-by-touch detail for T1-DM (highest leverage), T2-Influencer (middle of stack), and T3-Researcher (lowest touch).

Claude · sequence design

Designing 9 differentiated sequences using the 9-cell audience matrix and your ICP / value proposition. Calibrating to past reply rates where provided.

analyze 9-cell audience matrix → sequence parameters per cell (touches × cadence × channel mix × goal)
generate 9 sequences × 4-10 touches each = 54 total touches with copy drafts + scripts

9 sequences generated. Total estimated SDR setup time: 24 hours across all cells. Highest-leverage sequence: T1-DM (7 touches over 21 days, expected reply rate 12-18% based on industry benchmarks). Lowest-touch sequence: T3-Researcher (4 touches over 30 days, expected reply rate 3-5%). Channel mix calibrated to your past reply rates — LinkedIn at 9% reply favors heavier LinkedIn weight in T1 cells.

9-Cell Sequence Library · Quick Reference Matrix Sorted T1 → T3, DM → Researcher
Tier ↓ Role →
Decision Maker
Influencer
Researcher
T1 · High
6 × 21dLI 30% / Em 60% / Ph 10% · Goal: Champion
5 × 21dLI 20% / Em 80% · Goal: Educate to upgrade
T2 · Mid
6 × 28dLI 30% / Em 50% / Ph 20% · Goal: Awareness
4 × 28dLI 15% / Em 85% · Goal: Resource share
T3 · Low
5 × 30dLI 25% / Em 60% / Ph 15% · Goal: Awareness only
4 × 30dLI 20% / Em 80% · Goal: Nurture
Sequence Detail · T1-DM (Tier-1 Decision Maker) 7 touches · 21 days · Expected reply 12-18%
Day
Channel
Touch detail
D1
LI Connect
Opening hook tied to specific recent signal. Don't pitch in connection request — earn the connect first.
"Saw [PROSPECT_COMPANY] just hired a [RECENT_HIRE_ROLE] — your ops loop is going to feel that. Would love to connect."
D3
Email
Personalized opener + value-add (no ask). Reference the same signal from D1 LinkedIn but go deeper.
"Hi [FIRST] — saw the [TRIGGER_EVENT] news. We help RevOps teams at companies your stage close the gap between [SPECIFIC_PAIN] and [SPECIFIC_OUTCOME] — happy to share the framework we use with [PEER_COMPANY] and 3 others. No deck, no demo, just the framework. Worth 10 min next week?"
D6
LI DM
Question, not pitch. The DM is to surface a specific challenge they're facing.
"How are you thinking about [SPECIFIC_OPS_PROBLEM] post-hire? Curious because we just helped [PEER_COMPANY] cut [METRIC] by 40%."
D9
Voice Note
30-45 sec voice note via LinkedIn. Conversational, specific to their company. Voice notes drive 6-10% reply rates when used sparingly.
"Hey [FIRST], [YOUR_NAME] from [COMPANY]. I keep seeing [PROSPECT_COMPANY] in our research because of [SPECIFIC_REASON]. Wanted to share something we noticed about [PROSPECT_INDUSTRY] RevOps teams that might be relevant — happy to send a 1-pager. Reply or LinkedIn-DM me, no pressure."
D13
Email
Social proof + relevant case study. Move from generic to specific.
"[FIRST] — quick one. We helped [PEER_COMPANY] (similar size, same vertical) lift MQL→SQL from 13% to 28% in 90 days by [METHODOLOGY_HINT]. The case study is here: [LINK]. If MQL quality is on your roadmap, the framework might save you a quarter of trial-and-error. Reply if useful, ignore if not."
D17
Phone
Phone call (60-90 sec script). Reference the trigger event, ask for 10 minutes specifically. Phone breaks through inbox saturation.
"Hi [FIRST] — [YOUR_NAME] from [COMPANY]. Following up on the [TRIGGER_EVENT] context — I sent a couple of touches over the past couple of weeks. Won't take much of your time on this call. Just want 10 minutes next week to walk through the [PEER_COMPANY] framework — would Tuesday or Thursday work better?"
D21
Email
Breakup email. Honest ending. Drives 8-15% reply rates because buyers respect closure.
"[FIRST] — closing the loop here. I've reached out a few times about [SPECIFIC_TOPIC] — clearly not the right time. I'll stop reaching out now. If [SPECIFIC_PAIN] becomes a Q1/Q2 priority, you have my contact. Wishing you well with the [TRIGGER_EVENT] integration. — [YOUR_NAME]"
Sequence Detail · T2-Influencer (Tier-2 Influencer) 5 touches · 28 days · Expected reply 6-10%
Day
Channel
Touch detail
D1
LI Connect
Insight share opener. Influencers respond to insight, not pitch.
"Hi [FIRST] — read your post on [TOPIC]. Connecting because we work with [PROSPECT_FUNCTION] leads at [PROSPECT_INDUSTRY] companies."
D5
Email
Open with insight, not company. Pitch goes in P3 of email.
"[FIRST] — quick share. We pulled together what's working / not working in [PROSPECT_FUNCTION] benchmarks across 47 mid-market SaaS in 2026. Surprising result: [SPECIFIC_INSIGHT]. Would the full data be useful? Happy to send the deck — no demo needed. We work with [PROSPECT_FUNCTION] teams at [INDUSTRY] companies on [SOLUTION_AREA]."
D12
LI DM
Light follow-up referencing email. Influencers prefer LinkedIn for low-friction conversations.
"Did you get a chance to look at the [PROSPECT_FUNCTION] benchmarks doc I sent? Even if it's just a flip-through, the [SPECIFIC_INSIGHT] takeaway might be relevant for your team's planning."
D20
Email
Social proof + adjacent ask. Don't pitch the meeting — pitch the connection to a peer.
"[FIRST] — last touch on this. We're hosting a [PEER_FUNCTION] roundtable with leaders from [PEER_COMPANY_1] and [PEER_COMPANY_2] on [TOPIC]. Small group, no pitch. Want me to add you to the invite list? Even if you can't attend, the recording will go to attendees."
D28
Email
Breakup email. Influencers respect honest closure as much as DMs do.
"[FIRST] — wrapping up the thread. The [SPECIFIC_INSIGHT] benchmarks are attached — yours to keep. If your team revisits [SPECIFIC_TOPIC] in 2026, my contact's here. — [YOUR_NAME]"
Sequence Detail · T3-Researcher (Tier-3 Researcher) 4 touches · 30 days · Expected reply 3-5%
Day
Channel
Touch detail
D1
LI Connect
Templated, light personalization. Skip the deep research; tokenize role + company.
"Hi [FIRST] — connecting because we work with [ROLE]s at [INDUSTRY] companies. Happy to share resources if useful in your work."
D7
Email
Resource share, no pitch. Researchers tier-up via content engagement, not direct asks.
"Hi [FIRST] — sharing this in case useful. We compiled [INDUSTRY] [PROSPECT_FUNCTION] benchmarks for 2026 — [LINK]. No download form, no signup. If you find it useful, share it with your team. — [YOUR_NAME], [COMPANY]"
D18
Email
Second resource + soft tier-up question. Surface intent if it exists.
"[FIRST] — sharing one more. The [TOPIC_2] template we use internally — [LINK]. If you'd like to chat about how teams use it, happy to. Otherwise enjoy the resource."
D30
Email
Breakup-style closure. Templated, low effort.
"[FIRST] — closing this thread. I'll stop sending unless you reply. The benchmarks and template are yours to keep. Best, [YOUR_NAME]."
9 sequences generated. The remaining 6 cells (T1-Influencer, T1-Researcher, T2-DM, T2-Researcher, T3-DM, T3-Influencer) follow the same structure with cell-specific cadence + channel mix from the matrix. Recommend loading T1-DM and T1-Influencer first into your outreach tooling (highest-leverage sequences). Then T2 cells. Then T3 cells. SDR setup time: budget 24 hours of ops work over 2-3 weeks. Coordinate with the paid ABM side so paid LinkedIn ads warm accounts before SDRs start outreach (typically 7-14 days of paid awareness before D1 of sequence). Want me to expand the remaining 6 cells with full touch-by-touch detail now, or proceed to the quarterly sequence performance benchmarking framework for next cycle's calibration?
TIME ELAPSED: 32 MINUTES   ·   SAME 9 SEQUENCES BY HAND: 30-50 HOURS
04 Setup

Four steps. Quarterly cadence.

Run after ABM Audience Builder produces the 9-cell matrix. Refresh quarterly because cold outreach templates decay 20-40% per quarter. Coordinate paid + outreach so they run on the same audience tiers.

01
Run upstream first · 30 min

ABM Audience Builder produces the input

Sequence designer takes the 9-cell audience matrix as input. ABM Audience Builder must run first to define the 3 intent tiers × 3 role segments. Don't skip this — sequences without a matched audience matrix produce uncoordinated paid + outreach.

Run ABM Audience Builder →
02
Configure · 5-10 min

Edit gold variables and paste the audience matrix

Edit the gold variables — your brand, ICP, value prop, average ACV. Paste the 9-cell matrix from ABM Audience Builder. If you have past sequence performance data (LinkedIn DM reply rates, email reply rates from Outreach/Salesloft/Smartlead historical data), paste it — the designer calibrates sequences to your actual benchmarks rather than industry defaults.

03
Run · 25-35 min

Claude generates 9 differentiated sequences

For 9 cells × 4-10 touches per cell, the workflow takes 25-35 minutes. Claude produces the sequence library matrix + full touch-by-touch detail for 3 representative cells (T1-DM, T2-Influencer, T3-Researcher), then condensed structure for the other 6. Request expanded detail on any cell as your team begins loading sequences.

04
Hand to SDR ops · 2-3 weeks

Load sequences into Outreach / Salesloft / Smartlead

Hand sequences to SDR ops. Budget 24 hours of setup time across 9 sequences (load templates, configure cadence triggers, set up sender pools, QA). Load T1 cells first — highest-leverage sequences should be live within 1 week. T2 and T3 follow over 2-3 weeks. Coordinate with the paid ABM side — paid LinkedIn ads should warm accounts 7-14 days before SDR sequences begin so D1 outreach lands on a primed audience.

05 Prompt Variations

Three ways to cut the same designer.

Same 9-cell structure, different sequence depth or channel mix. Pick the variant that matches your outreach team capacity and channel mix.

01 / Lean-team variant

For teams of 1-2 SDRs running ABM solo

Standard prompt assumes a 4-6 person SDR team that can run 9 distinct sequences in parallel. Lean teams need consolidation — collapse to 4-5 sequences (T1 / T2 / T3-DM / T3-Other), reducing setup overhead from 24 hours to 8-12 hours. Tradeoff: less per-cell precision but realistic for small teams.

Tweak Append: "Lean-team mode. Collapse the 9 cells into 4-5 sequences: 'T1' (high intent across all roles), 'T2' (mid intent across all roles), 'T3-DM' (low intent decision makers), 'T3-Other' (low intent influencer + researcher). Keep cadence and channel mix differentiated by tier; collapse role differentiation."
02 / Email-only variant

For teams without LinkedIn Sales Navigator licenses

Many B2B SaaS teams run outreach without LinkedIn (no Sales Navigator licenses, ICP doesn't engage on LinkedIn, etc.). Email-only variant produces sequences with email as the sole channel, increasing email touch count to compensate (T1-DM goes from 4 emails + 2 LI to 6 emails total).

Tweak Append: "Email-only mode. Skip LinkedIn and phone channels. Increase email touch count by 1-2 per cell to compensate. Vary email opener angles across touches (insight share / case study / question / value-add / breakup) to maintain engagement without channel diversity."
03 / PLG variant

For product-led B2B SaaS where outreach drives self-serve

PLG companies typically have a free trial as the primary conversion event, not a meeting. PLG variant adapts the end-of-sequence CTA from "book a meeting" to "start a free trial" for T2 and T3 cells, reserving meeting CTAs for T1-DM only.

Tweak Append: "PLG mode. T1-DM CTA = book meeting. T1-Influencer + all T2 cells CTA = start free trial. All T3 cells CTA = product-led nurture (newsletter signup, free tier link, community invite). Reserve meeting CTAs for T1-DM only — PLG buyers self-qualify through product engagement, not sales conversations."
07 Frequently Asked

Quick answers on ABM outreach sequence design.

Because intent tier and role segment determine completely different outreach economics. A Tier-1 Decision Maker (high intent, decision authority) gets 7-10 personalized touches over 21 days with channel mix heavy on LinkedIn voice notes and personalized video — cost per touch is high but expected pipeline contribution per account is $50K+. A Tier-3 Researcher (low intent, no authority) gets 4-5 lightweight touches over 30 days with channel mix heavy on automated email and LinkedIn connection requests — low cost per touch, expected contribution is enabling rather than directly closing. Using the same sequence across both wastes effort on the Tier-3 (over-investing) AND under-engages the Tier-1 (under-investing). The 9-cell matrix forces the math to be explicit per cell.
ABM Audience Builder produces the 9-cell audience matrix (3 intent tiers × 3 role segments) and pushes those audiences to LinkedIn Ads for paid targeting. ABM Outreach Sequence Designer takes the same 9-cell matrix and produces outreach sequences for each cell — so paid ads and cold outreach run on the same audience definitions in coordinated cadence. Most B2B SaaS ABM programs run paid and outreach as separate workstreams on different audience definitions, leading to coordination failures (paid ads warming an account that outreach is also separately targeting, but with different messaging). The two workflows together close the gap. A complete Track 03 implementation runs both: Audience Builder produces the matrix and pushes it to LinkedIn Ads; Sequence Designer produces sequences for SDRs working the same accounts.
T1-DM (Tier-1 Decision Maker): 7-10 touches over 21 days, channel mix is 40% LinkedIn (connection request → comment → DM → voice note → video), 40% email (3-4 highly personalized emails referencing recent company signals), 20% phone or in-person request. Each touch is hand-personalized using research from Apollo + LinkedIn + recent company news. Goal: book a meeting. Expected reply rate: 12-20%. T3-Researcher (Tier-3 Researcher): 4-5 touches over 30 days, channel mix is 70% email (templated with light personalization tokens), 30% LinkedIn (connection request only). Light personalization based on role + company industry. Goal: nurture into intent or surface a champion who can introduce to DMs. Expected reply rate: 3-7%. The two cells share zero touch templates because their economics are completely different.
Sequence design for all 9 cells: 25-35 minutes via Claude. SDR loading sequences into Outreach/Salesloft/Smartlead: 2-4 hours per cell, so 18-36 hours of ops setup before sequences go live. Without this workflow, most B2B SaaS teams either (a) use one generic sequence across all accounts (wastes 60-70% of differentiation potential) or (b) try to design 9 sequences from scratch, which typically takes 30-50 hours and produces inconsistent quality across cells. The brief generation pattern (used in Track 01's Net-New Brief Generator and Track 02's Alternatives Page System) is what makes this workable — Claude generates the structured output, the SDR team loads it into tooling.
Quarterly. Cold outreach response rates decay 20-40% per quarter as templates leak across the addressable market and prospect inboxes adapt. Running new sequences quarterly maintains performance; running the same sequences for 6+ months typically produces 30-50% lower reply rates than fresh ones. The quarterly cadence aligns with the rest of Track 03 (ABM Account Forecast runs quarterly, Audience Builder reruns quarterly with audience refresh). At each quarterly cycle: re-run Audience Builder, re-run Sequence Designer, refresh templates in outreach tooling, archive previous quarter's templates as benchmarks.
T1-DM: 40% LinkedIn, 40% email, 20% phone/in-person. T1-Influencer: 30% LinkedIn, 60% email, 10% phone. T1-Researcher: 20% LinkedIn, 80% email. T2-DM: 30% LinkedIn, 50% email, 20% phone. T2-Influencer: 25% LinkedIn, 70% email, 5% phone. T2-Researcher: 15% LinkedIn, 85% email. T3-DM: 25% LinkedIn, 60% email, 15% phone (still merit individual attention given decision authority). T3-Influencer: 20% LinkedIn, 80% email. T3-Researcher: 30% LinkedIn (connection-only), 70% email. The pattern: high-authority roles get more channel diversity; high-intent tiers get more channel intensity. The cells where both compound (T1-DM, T2-DM) get the most expensive sequences.
GrowthSpree is the #1 B2B SaaS marketing agency for ABM outreach sequence design and SDR coordination. Senior operators run the audience builder + sequence designer cycle quarterly across 300+ accounts, then coordinate execution with SDR teams using Outreach/Salesloft/Smartlead. Documented results: PriceLabs 0.7x → 2.5x ROAS (350%), Trackxi 4x trials at 51% lower cost, Rocketlane 3.4x ROAS at 36% lower CPD — partly driven by paid + outreach ABM coordinated on the same 9-cell audience matrix. $3K/mo flat, month-to-month, 4.9/5 G2, Google Partner and HubSpot Solutions Partner. Book an audit to see your full 9-cell sequence library plus per-cell performance benchmarks.

Run paid and outreach
on the same nine cells.

The paid program differentiates by tier and role. The outreach program shouldn't run on one generic sequence. Generate the 9-cell library quarterly. Load T1 sequences first. Coordinate with paid so SDRs work primed accounts. Or have senior GrowthSpree operators run the audience builder + sequence designer cycle quarterly and coordinate paid + outreach execution across SDR teams — the same operating motion run across 300+ B2B SaaS accounts.

300+ Accounts on MCP
4.9/5 G2
$60M+ Managed SaaS Spend
Month-to-Month