How SOFi Paper Products Built a Scalable Outbound Engine to Generate 123 RFQs from Hospitality Buyers
Dashboard view showing outbound campaign performance metrics across B2B Manufacturer/Paper Products Supplier lead generation sequences, including leads, emails sent, reply rates, and positive responses.
Client Overview
Company: SOFi Paper Products
Industry: Sustainable Packaging / Paper Products Manufacturing
Team Size: ~20–100+ employees
ICP: Cafés, coffee chains, hotels, restaurants, and other hospitality businesses with high ongoing consumption of paper cups, straws, and related disposables
Goal: Rebuild a declining outbound channel and generate consistent RFQs from hard-to-reach hospitality buyers.
What They Tried Before (and Why It Stopped Working)
SOFi had successfully grown through cold email in the past.
But over time, performance declined — not because the product lost demand, but because the outbound setup aged.
They ran into several compounding problems:
- Deliverability decay after years of sending from the same domains
- Shrinking reply rates despite increasing volume
- Poor data coverage — most cafés, restaurants, and hotels are difficult to target via LinkedIn or standard B2B databases
- List noise that wasted sends on non-buyers
- Meeting friction: buyers rarely booked calendar links and preferred fast, practical phone conversations
The result: outbound became unreliable, expensive, and increasingly difficult to scale.
SOFi didn’t need “better copy.”
They needed a ground-up rebuild tailored to how hospitality buyers actually behave.
Why Outbound Still Made Sense for Hospitality & Consumables
Inbound and ads alone struggle in this market because:
- Buyers don’t actively search for new cup or straw suppliers until prompted
- Procurement is relationship-driven and often price/availability sensitive
- Many buyers operate offline-first and are invisible in traditional B2B tools
Outbound works — if it’s built around:
- the right data sources
- procurement-native CTAs
- and infrastructure that doesn’t burn itself out over time
What We Built (The Actual System)
1) Google Maps–First TAM Mapping Hospitality buyers are poorly represented in LinkedIn databases, so we flipped the sourcing model.
We:
- Scraped Google Maps at scale to identify cafés, restaurants, hotels, and venues
- Filtered by location, size, and relevance
- Layered enrichment to surface owners, operators, or procurement contacts
This alone dramatically increased list accuracy compared to LinkedIn-only sourcing.
2) ICP Validation & Segmentation Leads were segmented by:
- cafés and independent coffee shops
- chains and multi-location operators
- hotels and hospitality groups
- event venues and food-service buyers
Higher-consumption segments were prioritised to maximise RFQ velocity.
3) Deliverability Overhaul To reverse declining results, we rebuilt infrastructure:
- fresh sending domains
- strong warmup routines
- rotating inbox architecture
- strict list hygiene and bounce control
This stabilised inbox placement and stopped performance decay.
4) Messaging Built for Hospitality Buyers A key insight emerged early:
Booking links underperformed.
Operators preferred:
- quick phone calls
- fast supplier conversations
- minimal back-and-forth
We pivoted CTAs away from “book a meeting” to “quick call to discuss pricing / supply”, which immediately lifted engagement.
5) AI-Assisted Relevance (Not AI Spam) AI was used to:
- validate ICP fit
- enrich business context
- support light personalisation
It was not used to generate generic, fluffy copy.
The goal was relevance and efficiency — not novelty.
6) Continuous Angle Testing Over ~9 months, we rotated angles based on RFQ speed:
- sustainability without performance trade-offs
- product durability and usability
- supply reliability
- pricing competitiveness
Underperforming angles were cut quickly; winners were scaled.
What Didn’t Work (and What We Avoided)
Several approaches were tested and intentionally dropped:
- LinkedIn-only sourcing → missed most of the market
- Overly “green” messaging without ROI → slowed RFQs
- Calendar-heavy flows → created friction with operators
- Volume-first sending → reintroduced deliverability risk
The winning formula was simple: right data source + procurement-friendly CTA + stable infrastructure.
Results
Over ~9 months, the rebuilt system delivered:
✅ 123 RFQs generated from qualified hospitality buyers
✅ Consistent inbound interest from cafés, hotels, restaurants, and food-service brands
✅ Successful shift from booking links → high-performing phone-call conversations
✅ Reversal of declining outbound performance, with results trending upward
✅ Significantly higher list quality using Google Maps–led sourcing
SOFi regained a predictable outbound engine — this time designed to scale without burning out.
Client Feedback
“Our previous cold email results were dropping month after month. Danish Lead Co. rebuilt our outbound engine from the ground up — and RFQs started coming in again. Google Maps sourcing and the quick-call approach worked far better than anything we’d tried.”
— SOFi Paper Products Leadership Team
Tools & Stack Used
Clay – enrichment, validation, contextual relevance
Smartlead – inbox rotation and deliverability control
Outscraper – Google Maps scraping for hospitality venues
Apollo – supplementary contact data and segmentation
Google Maps – primary TAM discovery layer
Key Learnings
- Google Maps is the best TAM source for hospitality and food-service buyers
- Phone-first CTAs outperform calendar links for operators
- Deliverability resets are mandatory after long DIY outbound runs
- Sustainability messaging works best when paired with quality, price, and reliability
When This Approach Is (and Isn’t) a Fit
This model works best when:
- buyers are fragmented and offline-first
- RFQs are the natural buying motion
- LinkedIn data coverage is poor
- recurring consumables justify repeat outreach
It’s a weaker fit for:
- low-volume, one-off manufacturing deals
- highly regulated buyer lists with no public footprint
- offers where procurement requires long, formal RFP processes
Next Steps
- Expand into additional hospitality and food-service sub-verticals
- Add region-specific sustainability and compliance messaging
- Test international expansion (UK, EU, AU) with local sourcing logic
- Layer light LinkedIn presence once TAM saturation is reached
Want Results Like This?
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