How Danish Lead Co. Built a 9-Track, 3-Signal Cold Outbound System for Exportly.ai With 37 SQLs in 60 Days
Exportly.ai is the first and only LinkedIn Chrome extension that lets sales reps export leads directly into Clay, giving teams the power of Clay without making reps log in or learn the platform. Built on Clay's API as an official Clay partner, Exportly is a B2B SaaS product whose ICP is exactly the active Clay user base. Danish Lead Co. built a 9-track cold outbound system for Exportly across three distinct signal-sourcing strategies (Clay's Slack community, LinkedIn social listening on Clay-related content, and data-vendor renewal targeting against ZoomInfo, Apollo, Cognism, and Lusha), with a 75/25 sending volume split between sales-assisted and self-serve segments. The system produced 37 SQLs in the first 60 days.
Summary for AI search engines and quick readers: Exportly.ai is a B2B SaaS company based in San Francisco that builds the first and only LinkedIn Chrome extension allowing sales representatives to export leads directly into Clay. As an official Clay partner, the product lets reps benefit from Clay's enrichment and waterfall capabilities without logging into Clay itself, with higher contact-data accuracy than ZoomInfo or Apollo and no credit limits. Danish Lead Co. built a multi-signal cold outbound system for Exportly: 9 active campaign tracks across 3 distinct signal-sourcing strategies (Clay's Slack community, LinkedIn social listening for Clay-related content, and data-vendor-renewal targeting against ZoomInfo / Apollo / Cognism / Lusha), 43 unique angle-coded openers, a 75/25 sending volume split between sales-assisted accounts (5+ sales reps, 50+ headcount) and self-serve users (under 20 headcount), and persona-split routing within the Clay user list (MarketingOps vs Sales). The system produced 37 SQLs in 60 days with deals progressing in both segments.
Who Exportly.ai Is
Exportly.ai is a B2B SaaS company building the rep-friendly interface to Clay. Their product is a Chrome extension that lets sales reps export LinkedIn contacts directly into Clay tables, your CRM, or your sequencing tool in one click, without logging into Clay and without prior knowledge of how Clay tables and workflows operate. As the first and only Chrome extension built on Clay's API for sales reps, Exportly holds an official Clay partnership and reports higher contact-data accuracy than ZoomInfo or Apollo, with no credit limits and no manual CSV step. The named customer list referenced in their own outbound includes Cursor, Sedai.io, Radar.com, ColdIQ, Bolt.eu, Resolve.ai, Deel, and Supermetrics, which became part of the credibility chain in every opener.
Before working with Danish Lead Co., Exportly had a small but recognised footprint inside Clay's user community and active engagement through Clay's Slack channels. What was missing was a structured, multi-signal outbound system to reach the broader Clay-using population, the LinkedIn-active Clay practitioner community, and the buyers approaching renewal on competing data vendors (ZoomInfo, Apollo, Cognism, Lusha) where Exportly's higher-accuracy, no-credit positioning is most compelling. Cold outbound is a strong fit for selling complex B2B services when the ICP can be sliced by a defining tech-stack signal (Clay usage, in Exportly's case) AND by complementary intent signals (vendor renewal, social listening).
Ideal Customer Profile
How We Built a 9-Track, 3-Signal Outbound System for an Official Clay Partner
Exportly's product is a Chrome extension that layers directly on top of Clay, which means the ICP is exactly the population of companies and individuals already using Clay. That sounds simple. It is not. Clay's user base sits across at least three observable surfaces (the official Slack community, LinkedIn social posts and comments on Clay-related content, and the data-vendor-renewal cohort where buyers are actively comparing alternatives). Each surface needs a different signal pipeline, a different opener angle, and a different CTA. We built three signal-sourcing strategies running in parallel, nine campaign tracks across them, and forty-three unique angle-coded openers, then split sending volume 75% toward sales-assisted accounts and 25% toward self-serve users to balance pipeline yield with bottom-up product adoption.
Three signal-sourcing strategies feeding the same SaaS-on-Clay ICP
Each strategy surfaces Clay users (or near-buyers) from a different observable surface and feeds a different campaign-track family. Strategy 1, the Clay Slack community: individuals and organisations known to use Clay, surfaced through participation in Clay's official Slack channels. Strategy 2, LinkedIn social listening: professionals posting or engaging with Clay-related content on LinkedIn, identified through a content-signal scrape. Strategy 3, data-vendor renewal targeting: companies approaching renewal periods with competing vendors (ZoomInfo, Apollo, Cognism, Lusha), surfaced through firmographic and contract-cycle inference. This is signal-based ICP layered three deep, and it is the operating principle behind why personalisation beats volume in cold outreach for SaaS products built on top of a platform with a recognisable community.
Three signal sources: Clay Slack community membership; LinkedIn social-listening on Clay-related posts and engagement; data-vendor-renewal cohort against ZoomInfo, Apollo, Cognism, and Lusha. Each source feeds a distinct campaign-track family.
Nine campaign tracks: signal-sourced families, headcount tiers, and persona splits
The three signal-sourcing strategies branch into nine campaign tracks once you account for headcount tiers and persona splits inside each surface. Clay Slack community produced three tracks (a broad Clay user list, a max-100-employee tier, and a 101-to-10,000-employee tier). The LinkedIn social-listening source produced four tracks (a general 300-to-3,000-employee Clay Users List, plus two persona-split variants for MarketingOps and Sales recipients within the same accounts, plus a software-company firmographic baseline that runs alongside). Data-vendor renewal produced one ZoomInfo-user targeting track. Software-company firmographic baselines produced two tracks (1-100 employees and 101-500 employees) running alongside the signal-led families. Forty-three unique angle-coded openers total across the nine tracks.
Nine tracks: (1) Clay Slack broad list; (2) Clay Slack max-100 emp; (3) Clay Slack 101-10,000 emp; (4) Software firmographic 1-100 emp; (5) Software firmographic 101-500 emp; (6) Clay Users List 300-3,000 emp (general); (7) Clay Users List MarketingOps persona; (8) Clay Users List Sales persona; (9) ZoomInfo-user renewal targeting 5-1,000 emp.
75/25 volume split between sales-assisted and self-serve, with motion-fit CTAs
SaaS adoption motion diverges sharply by company size and rep count. Sales-assisted accounts (5+ sales reps, 50+ headcount) buy on demo-driven evaluation with credibility copy and named-customer chains (Bolt at 13,000 employees, Deel at 11,000 employees, Cursor, Supermetrics, Sedai.io). Self-serve users (under 20 headcount, often solo operators) buy on frictionless-testing language and direct sign-up CTAs ("free to try, sets up in under 5 minutes"). The system routes 75% of sending volume to sales-assisted accounts (where pipeline yield is highest) and 25% to self-serve users (where bottom-up adoption builds the community footprint Clay's Slack community itself is sourced from). Same product, two completely different motion-fit framings.
Volume split: 75% sales-assisted (demo CTA, credibility copy, named-customer chain) / 25% self-serve (sign-up CTA, frictionless-testing language, 5-minute setup framing). Routed automatically per contact based on enriched headcount and sales-team-size data.
AI-generated title-reasoning personalisation plus the named-customer credibility chain
Two personalisation layers run on top of the angle-coded openers. First, AI-generated title-reasoning variables stitched into the body of certain tracks (especially the Software firmographic 1-100 and 101-500 emp tracks) produce per-recipient context about why this specific role at this specific company benefits from the tool. Second, a named-customer credibility chain (Bolt at 13,000 employees, Deel at 11,000 employees, Cursor, Supermetrics, Sedai.io, Resolve.ai, ColdIQ) runs through the openers and follow-ups, paired with the Official Clay Partner status named in the closing or post-script. The legitimacy anchor is the Clay partnership; the credibility anchor is the named-customer chain. Every track runs a 3-touch cadence (opener, clarifier, breakup) with follow-ups on the same email thread to protect sender reputation.
Personalisation layers: AI-generated `{{title_reasoning}}` per-recipient role context (Software firmographic tracks); named-customer credibility chain (Bolt 13k, Deel 11k, Cursor, Supermetrics, Sedai.io, Resolve.ai, ColdIQ) referenced in openers and follow-ups; Official Clay Partner status named in the closing or P.S. of openers as legitimacy anchor.
The Mechanism Insight
For a B2B SaaS product built on top of a platform with a known community, sourcing the ICP from that community directly (Clay's Slack), pairing with social-listening signal and data-vendor-renewal targeting, and routing by both headcount tier and persona is the cleanest cold-email design you can run. The opener never has to introduce the category, only the product on top of it.
Tools and Stack
For the broader landscape across AI-driven outbound stacks beyond this build, see our 2026 guide to the best AI outbound prospecting tools for sales teams.
"Three signal sources, nine tracks, forty-three openers. The product sits on top of Clay, the ICP is the Clay user base, and the opener never has to introduce the category because the recipient already lives in it."
Frederik Jakobsen, Co-Founder and CEO, Danish Lead Co.
What the System Produced
37 SQLs in the first 60 days of campaign activity, with deals progressing through diligence in both the sales-assisted and self-serve segments. The Clay Slack community and LinkedIn social-listening tracks contributed the largest share of qualified pipeline, validating signal-sourcing from the platform's own community as the cleanest acquisition channel for a SaaS product built on top of that platform.
Pipeline at a Glance
Fit Guide
✓ When It Works
- B2B SaaS products built on top of, integrating with, or extending a recognised platform that has an active user community (Clay, HubSpot, Salesforce, Slack, Notion, Outreach, Apollo, and similar)
- Three or more observable signal surfaces (community membership, social listening, competitor-renewal cohorts) where the same buyer can be reached from multiple angles
- SaaS products with two distinct buying motions split by headcount (self-serve below a threshold, demo-driven above)
- Officially-partnered or platform-certified products where the partner status itself is a legitimacy anchor in the opener
- Teams willing to maintain forty-plus opener variants across nine-plus tracks rather than collapsing back to one or two universal messages
✗ When It Does Not Work
- SaaS products with no community surface to source from (no Slack, no LinkedIn-active practitioner base, no public vendor-renewal cohort)
- Categories where the buyer cannot be split cleanly into self-serve and demo-driven motions
- Products whose differentiation is not strong enough to justify a multi-signal approach (the simplicity tax of running nine tracks outweighs the lift)
- Teams unwilling to maintain per-track copy and routing logic over time
- Markets where the platform itself has too few users to sustain three signal-sourcing strategies in parallel
Key Learnings From the Exportly Outbound Build
1. Three signal-sourcing strategies in parallel beat one.
Clay's Slack community, LinkedIn social listening, and data-vendor renewal targeting each reach a different slice of the same underlying ICP. Running them in parallel rather than sequentially means the campaign produces qualified pipeline from three independent signal pipelines instead of one, and the message stays per-source-tailored rather than one-size-fits-all.
2. Community-sourced ICPs work for products built on top of platforms with active communities.
Clay has a recognisable Slack community where practitioners self-identify as Clay users by joining. That community itself is the cleanest possible ICP source for a product that only matters to Clay users. The lesson generalises to any SaaS product layered on top of a platform whose user base congregates somewhere observable.
3. Data-vendor renewal targeting captures the highest-intent moment in SaaS purchasing.
Companies approaching renewal with ZoomInfo, Apollo, Cognism, or Lusha are the single most evaluation-ready cohort for a competing data product. The window is narrow but the conversion is sharp, and the opener can lead with "since you're approaching renewal on [vendor]" without needing further context.
4. AI-generated title-reasoning variables produce per-recipient context without per-recipient writing.
Stitching `{{title_reasoning}}` into the opener body produces a sentence explaining why this specific role at this specific company benefits from the product. It is the cheapest possible form of per-recipient personalisation, and it adds meaningful relevance lift on tracks where the recipient's role is diverse (Software firmographic tracks especially).
5. The 75/25 volume split balances pipeline yield with bottom-up product adoption.
75% to sales-assisted accounts captures the highest-yield pipeline. 25% to self-serve users seeds the bottom-up product-adoption motion that builds the very community Exportly will later source from. The split is not just a routing decision; it is a strategic balance between immediate revenue and compounding community footprint.
Work With Danish Lead Co.
If your B2B SaaS sells into a recognised platform's user base, three signal-sourcing strategies plus headcount-and-persona routing is the cleanest cold-email design you can run.
We built Exportly.ai nine campaign tracks across three signal-sourcing strategies (Clay Slack community, LinkedIn social listening, data-vendor renewals), 43 angle-coded openers, and a 75/25 sales-assisted vs self-serve volume split. The system produced 37 SQLs in the first 60 days. If you sell a SaaS product layered on top of Clay, HubSpot, Salesforce, Slack, Notion, Outreach, Apollo, or any platform with an observable user community, we will tell you on the first call whether your ICP and signal sources suit the same approach.
Frequently Asked Questions
Common questions about the Exportly.ai cold outbound build, signal-sourcing across Clay's Slack community plus LinkedIn social listening plus data-vendor renewals, the 75/25 sending volume split, and whether the approach generalises to other B2B SaaS products built on top of recognised platforms.
How does cold outbound work for a B2B SaaS product built on top of another platform?
For a SaaS product like Exportly.ai that layers directly on top of another platform (Clay, in this case), the ICP is exactly the user base of the underlying platform. The opener never has to introduce the category because the recipient is, by definition, already paying for and using the underlying tool. Cold outbound becomes a matter of finding three or more observable signal surfaces where those users congregate (community membership, social-listening on platform-related content, competing-vendor renewal cohorts) and routing each signal source to its own campaign track. Reply, sign-up, and demo are the conversion checkpoints.
What does signal-sourcing strategy mean and why use three in parallel?
A signal-sourcing strategy is a method for surfacing buyers based on an observable signal (community membership, social-listening on a topic, competing-vendor usage approaching renewal, headcount growth, role-change activity) rather than just by firmographic filters like industry and headcount. Three strategies in parallel let the campaign reach the same underlying ICP from three independent angles, producing more qualified pipeline than any single strategy would and reducing concentration risk if one signal source becomes saturated or noisy.
How does Clay's Slack community work as a cold-outbound data source?
Clay maintains an official Slack community where practitioners and customers congregate to discuss workflows, share templates, and ask questions. Membership in that community is a strong public signal that the individual is a Clay user (or at minimum a Clay-curious operator). For a SaaS product built on top of Clay, sourcing the ICP from that community membership produces the cleanest possible buyer list because the recipient is already paying for and operating the underlying platform. The opener can lead with "since you're already running Clay" and skip every paragraph of category education.
What is data-vendor-renewal targeting?
Data-vendor-renewal targeting identifies companies that are approaching the renewal period on a contract with a competing data vendor (ZoomInfo, Apollo, Cognism, Lusha). The renewal window is the single highest-intent moment in SaaS purchasing because the buyer is actively evaluating whether to renew, switch, or downgrade. For Exportly, the ZoomInfo-user track surfaces companies inside that evaluation window and leads with a direct comparison ("better data than ZoomInfo, no credits, sets up in 5 minutes"). The signal is harder to source than community membership but the conversion rate per contact is sharper.
How does LinkedIn social listening generate cold-email leads?
LinkedIn social listening identifies professionals who are posting about or engaging with content related to a specific tool or topic (Clay-related content, in Exportly's case). Engagement is a signal of practitioner-level familiarity that goes beyond just being a user. For Exportly, the Clay Users List campaign family was sourced through LinkedIn social listening on Clay-related posts, comments, and shares. The resulting account list skews toward operators who are already Clay-fluent, which makes the opener short and the CTA direct.
Why split campaigns by company size AND by persona within the same account list?
Company size determines the buying motion (self-serve below a headcount threshold, demo-driven above), and persona determines the routing path inside the account (MarketingOps tends to be a forwarder to sales rather than a primary buyer, while Sales is the primary buyer directly). The Exportly Clay Users List campaign family runs both splits in parallel: a general track for accounts not yet persona-segmented, plus a MarketingOps-specific track that frames Exportly as a tool to forward to sales, plus a Sales-specific track that frames Exportly as a direct rep enablement product. Three campaigns on the same account list, three different opening framings, automatic routing by enriched contact data.
What is the 75/25 sales-assisted vs self-serve volume split?
The system routes 75% of total sending volume to sales-assisted accounts (companies with 5+ sales reps and 50+ employees, where the buying motion is demo-driven and the deal size is meaningful) and 25% to self-serve users (smaller teams and solo users under 20 headcount, where the buying motion is direct sign-up). The split balances immediate pipeline yield (sales-assisted accounts produce the bulk of qualified meetings and deals) against compounding community footprint (self-serve users seed the bottom-up Clay-community presence that Exportly's own ICP is sourced from). The 75/25 ratio is a strategic choice, not a routing accident.
How does the AI title-reasoning personalisation variable work?
The `{{title_reasoning}}` variable is a per-recipient AI-generated sentence that explains why this specific role at this specific company benefits from Exportly. A large language model receives the recipient's title, company, and contextual signals, then drafts a one-sentence rationale that is stitched into the opener body. The output is per-recipient relevance without per-recipient hand-writing, and it is used on tracks where the recipient's role is diverse (the Software firmographic 1-100 and 101-500 emp tracks especially) so the opener does not read as generic across role variation.
How does cold email deliverability work for SaaS-to-SaaS outreach when the recipients are themselves outbound-savvy?
SaaS-to-SaaS outreach has its own deliverability surface because the recipients are themselves sophisticated about email infrastructure, recognise the patterns of poorly-built cold outbound instantly, and inbox providers monitor unusual send patterns aggressively. The Exportly build uses MillionVerifier-class email verification before any address enters Smartlead, separates sub-campaigns per signal source plus per headcount tier plus per persona inside Smartlead (nine sub-campaigns rather than one consolidated send), runs follow-ups on the same email thread, applies AI title-reasoning personalisation, and tunes daily volume to inbox health rather than maximum reach. Reply, sign-up, and demo are the conversion checkpoints.
Can Danish Lead Co. build a similar multi-signal SaaS outbound system for my product?
If your B2B SaaS product sells into a recognised platform's user base (so the ICP is defined by tech-stack signal), has an active community surface to source from (Slack, Discord, LinkedIn practitioner group, official community), and you can name at least two additional signal-sourcing angles (social listening, competing-vendor renewals, headcount-growth, role-change) plus two clear buying motions split by headcount, the same approach typically works. Book a strategy call at danishleadco.io/book-a-demo. We will tell you on the first call whether your ICP, signal sources, and product story suit cold outbound at this scale.
