Case Study Swiss SAP Gold Partner Signal-Based Outbound

12,690 companies sourced for a team that closes 80-90% of its meetings

A Swiss SAP Gold Partner wins almost every deal it pitches. The bottleneck was at-bats. This system found the whole addressable market and got reply rates to 11.3% at peak.

12,690 Companies Sourced
11.3% Peak Reply Rate
9+ Interested Replies
80-90% Client Close Rate

The Client

Swiss SAP Gold Partner specializing in HR tech and SAP migrations.

The Problem

World-class close rate, not enough first meetings.

The Build

Full-market sourcing, migration-deadline signals, segmented sequences.

The Outcome

3.9% and 2.8% reply rates across campaigns, 11.3% at peak, 9+ interested replies.

Context

The client

A Swiss SAP Gold Partner specializing in HR technology migrations and HR process digitalization. Their core offering: help mid-market and enterprise Swiss companies define their HR-IT roadmap before the SAP ECC end-of-maintenance deadline in December 2027, guiding them to choose between migrating to S/4HANA HR or moving to SAP SuccessFactors in the cloud.

They also sell 11 proprietary add-on products that solve specific HR pain points: automated reference letters, digital employee files, secure payslip delivery, onboarding workflows, absence reporting, and more. Each add-on maps to a measurable operational problem in companies still running legacy SAP HR infrastructure.

Their close rate once they get into a conversation is 80-90%. The consultants are excellent, the product portfolio is deep, and the social proof includes cantonal governments, national utilities, major hospitals, and household-name Swiss brands. The only problem: they had no systematic way to start those conversations at scale.

Constraints

Why this was hard

Architecture

The system

One engine, five layers. Data flows left to right: full-market company intelligence feeds SAP signal detection, a 12-provider email waterfall recovers contacts other tools miss, AI-driven copy matches signals and add-ons to each prospect, and a five-layer DNC system sits under everything before a single email leaves.

Hand-drawn system map: full market sourcing of 12,690 companies feeding migration-deadline signal detection, then segmented sequences through a 12-provider email waterfall, ending in replies at 3.9 and 2.8 percent with an 11.3 percent peak, handed to a client sales team that closes 80 to 90 percent
The full system, as I'd sketch it on a whiteboard. Click to open full size.
LAYER 01

Industrial-scale company intelligence

Three parallel Clay pipelines sourced, enriched, and qualified 12,690 Swiss companies: an SAP customer list, a broader SAP partner masterfile filtered to German-speaking cantons and 100+ employees, and an add-on matrix scored with pain signals. When MixRank delivered only 7% contact coverage, I pivoted to Apollo and unlocked 1,144 additional contacts.

LAYER 02

Four-type SAP signal detection

An AI signal system classified every company into migration_announced, erp_modernization, sap_hiring, or hr_transformation. Each signal generated a different opening sentence with source attribution. Companies with no detectable signal got a deadline-anchored fallback, still relevant, but without specificity.

LAYER 03

12-provider email waterfall

A sequential waterfall of 12 providers: BetterContact, Findymail, Hunter, Prospeo, Kitt, Datagma, Wiza, Icypeas, Enrow, Dropcontact, LeadMagic, SMARTe. Every email passes Findymail verification before entering the send queue, and the long tail collectively recovers another 10-15% of contacts the top providers miss.

LAYER 04

AI copy with add-on matrix scoring

SAP migration emails carry an anchor line on the 2027 deadline, a signal sentence in four variants, a roadmap question, and industry-specific social proof. Add-on matrix emails map 11 products with trigger logic and pain scoring (0-5), using specialized AI models for signal finding, copywriting, translation, and research.

LAYER 05

Five-layer DNC compliance

A company domain blocklist (customers, partners, competitors), previous contact lists from every campaign, a campaign-specific blocklist of negative replies and removals, a SmartLead bounce list, and a shared community exclusion list of SAP consultancies and major system integrators.

The bottleneck was at-bats, not closing. A team that wins 80-90% of the deals it pitches just needed a systematic way to start more conversations.

Results

Campaign performance

11.3% Peak reply rate on a Campaign 3 sub-segment
12,690 Companies sourced across the addressable market
9+ Interested replies handed to the client's closers
Metric Result
Total leads across all campaigns2,000+
Total emails sent5,000+
Campaign 1 (SAP ECC) reply rate3.9% (21 / 545)
Campaign 3 (Matrix Add-Ons) reply rate2.8% (121 / 4,378)
Campaign 3 sub-segment peak reply rate11.3%
Total interested replies9+
Estimated closed deals (at 80-90% close rate)7-8 (estimated)
Companies sourced (Matrix pipeline)12,690
Email waterfall providers12
Email accuracy (post-verification)95%+
DNC layers5
Campaign statusActive

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Fit

Who this is for

Stack

Tools used

Clay Logo
Clay
Data Enrichment
SmartLead Logo
SmartLead
Email Sequencing
Apollo Logo
Apollo
Lead Database
MixRank Logo
MixRank
Contact Database
BetterContact Logo
BetterContact
Email Enrichment
Findymail Logo
Findymail
Email Verification
Claude AI Logo
Claude AI
AI Signal Detection
DiscoLike Logo
DiscoLike
Company Discovery

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