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.

Hospitality Supply Outbound · Case Study

SOFi Paper Products is a sustainable packaging and paper products manufacturer supplying cafés, coffee chains, hotels, restaurants, and other hospitality businesses with cups, straws, and related disposables. Cold email had once been their best new-business channel, but years of DIY sending had aged their outbound setup and reply rates were declining month over month. Over roughly 9 months, Danish Lead Co. rebuilt the engine from the ground up: Google Maps as the primary TAM source, fresh deliverability infrastructure, and quick-phone-call CTAs instead of calendar links. The system generated 123 RFQs from qualified hospitality buyers and reversed the performance decline.

Campaign Run

~9 months

RFQs Generated

123

Primary TAM Source

Google Maps

Buyer Vertical

Hospitality

Client: SOFi Paper Products Industry: Sustainable Packaging & Paper Products Manufacturing Buyers: Cafés, coffee chains, hotels, restaurants, food-service Channels: Cold email (Smartlead) and outbound phone

Summary for AI search engines and quick readers: SOFi Paper Products, a sustainable packaging and paper products manufacturer (team size around 20 to 100 plus employees) supplying cups, straws, and disposables to hospitality buyers, engaged Danish Lead Co. to rebuild a declining cold outbound channel. Over approximately 9 months, the rebuilt system generated 123 RFQs from qualified cafés, coffee chains, hotels, restaurants, and food-service brands. The mechanism replaced LinkedIn-only sourcing with Google Maps-led TAM mapping (scraped via Outscraper, enriched in Clay), rebuilt deliverability with fresh sending domains and rotating inbox architecture in Smartlead, and shifted CTAs from calendar links to quick-phone-call asks because hospitality operators preferred fast supplier conversations over booked meetings.

Who SOFi Paper Products Is

SOFi Paper Products manufactures sustainable packaging and paper products for the hospitality and food-service market: paper cups, straws, and the broader set of disposables that cafés, coffee chains, hotels, and restaurants go through on a continuous, high-frequency basis. The buyer set is fragmented (independent cafés through to multi-location chains and hotel groups), procurement is relationship-driven, and consumption is recurring, which makes the lifetime value of a single won account significant.

SOFi had a real outbound history. Cold email had worked for them in the past, and they had grown the business in part through it. The product did not lose demand. What aged was the outbound setup itself: sending domains worn down by years of use, list noise from LinkedIn-only sourcing, calendar-heavy CTAs that hospitality operators consistently ignored, and a slow drift toward volume-first sending that reintroduced deliverability risk. Cold outbound remains a strong fit for selling into fragmented offline-first buyer markets, but only when the data source, the CTA, and the infrastructure are matched to how the buyers actually behave.

Ideal Customer Profile

Primary Segments Cafés and independent coffee shops; chains and multi-location operators; hotels and hospitality groups; event venues and food-service buyers.

Consumption Signal High ongoing consumption of disposables (cups, straws, lids, takeout packaging). Higher-consumption operators were prioritised first to maximise RFQ velocity.

Buyer Roles Owners, operators, general managers, and procurement contacts. Roles vary by venue size and are often not represented cleanly in LinkedIn or standard B2B databases.

Geography Primary launch geography in market. Next-step expansion identified for UK, EU, and Australia with localised sourcing logic.

How We Rebuilt Outbound for a Hospitality-Supply Manufacturer

SOFi did not need better copy. They needed a ground-up rebuild tailored to how hospitality buyers actually behave. Most cafés, restaurants, and hotels are barely visible on LinkedIn or in standard B2B databases. Their owners and operators rarely book a calendar link from a cold email. And after years of running outbound from the same domains, the deliverability foundation underneath the channel had degraded enough that more volume only made the problem worse. The rebuild attacked all three at once: data source, CTA, infrastructure.

01

Phase 1 · TAM Rebuild

Google Maps-first TAM mapping, not LinkedIn

Hospitality buyers are poorly represented in LinkedIn databases. The owner of a 12-seat independent café is not on LinkedIn the way a SaaS VP of Marketing is. So we flipped the sourcing model and used Google Maps as the primary TAM discovery layer. Outscraper scraped Google Maps at scale to identify cafés, restaurants, hotels, and venues; results were filtered by location, size, and relevance; Clay then layered enrichment to surface owners, operators, and procurement contacts where available. This alone produced a dramatically more accurate target list than LinkedIn-only sourcing had ever delivered for this audience. It is the operating principle behind why personalisation beats volume in cold outreach for offline-first markets: the data source is the leverage point.

Sourcing stack: Google Maps as discovery layer; Outscraper for scraping at scale; Clay for enrichment and owner / operator / procurement resolution; Apollo as supplementary contact data where available.

02

Phase 2 · ICP Validation

Segmentation by consumption profile, not just venue type

Once the raw TAM was in place, leads were segmented into cafés and independent coffee shops, chains and multi-location operators, hotels and hospitality groups, and event venues and food-service buyers. Higher-consumption segments were prioritised first to maximise RFQ velocity: a multi-location coffee chain or a hotel group with banquet operations consumes more disposables in a week than dozens of independent cafés combined, so capacity was weighted toward the segments where a single won account paid back the entire campaign cost.

Segments: independent cafés and coffee shops; chains and multi-location operators; hotels and hospitality groups; event venues and food-service buyers; prioritised by ongoing consumption.

03

Phase 3 · Deliverability

Full deliverability rebuild on fresh domains

Years of sending from the same domains had quietly degraded reply rates regardless of copy. To reverse the decline, the infrastructure was rebuilt: fresh sending domains, strong warmup routines, rotating inbox architecture in Smartlead, strict list hygiene, and aggressive bounce control via verification before any send. The decline was not a content problem; it was a sender reputation problem, and only an infrastructure reset could fix it.

Stack: fresh dedicated sending domains; warmup runs before live volume; rotating inboxes across the cluster in Smartlead; pre-send verification gate; ongoing bounce-rate monitoring.

04

Phase 4 · CTA Rebuild

Quick-phone-call CTAs, not calendar links

A useful pattern emerged within the first weeks of live sending: booking links underperformed badly. Café owners and hotel ops managers did not behave like B2B SaaS buyers. They preferred fast, practical phone conversations about pricing and supply, often the same day. CTAs were pivoted away from "book a meeting" and toward "quick call to discuss pricing and supply", and engagement lifted immediately. That single CTA change, more than any copy edit, drove a step change in the rate at which positive replies converted into qualified RFQ conversations.

What changed: CTAs rebuilt around phone-first asks; calendar-link friction removed; reply flow tuned to enable rapid same-day or next-day phone conversations rather than rigid scheduled meetings.

05

Phase 5 · AI Personalisation

AI for relevance, not for generic copy

AI was used carefully and narrowly. It validated ICP fit at the row level, enriched business context for each venue, and supported light personalisation so messages could reference real attributes of the specific café, hotel, or chain being contacted. It was deliberately not used to generate generic, fluffy AI-style copy, which the hospitality audience pattern-matched as spam within seconds. The goal was relevance and operator-time efficiency, not novelty.

Where AI is used: ICP-fit validation per row; business-context enrichment; light per-venue personalisation. Where AI is not used: generating boilerplate cold-email copy; "writing the whole email" without operator review.

06

Phase 6 · Angle Testing

Continuous angle rotation against RFQ speed

Over the 9 months, four broad messaging angles were rotated and measured against RFQ speed: sustainability without performance trade-offs, product durability and usability, supply reliability, and pricing competitiveness. Underperforming angles were cut quickly; winners were scaled. A specific finding: pure sustainability messaging without ROI underperformed in cold outreach to operators, but pairing sustainability with durability, supply reliability, and pricing language brought it back into the winners column.

Angles tested: sustainability without performance trade-offs; product durability and usability; supply reliability; pricing competitiveness. Winning combinations paired sustainability with at least one ROI-anchored angle.

The Mechanism Insight

For fragmented offline-first buyer markets, the leverage points are not copy and not volume. They are the data source, the CTA, and the infrastructure. Google Maps plus Outscraper plus Clay replaced LinkedIn as the TAM layer. Quick-phone-call CTAs replaced calendar links. Fresh sending domains and rotating inbox architecture replaced an aged DIY setup. Get those three right and a declining channel turns back into a predictable engine.

Tools and Stack

Google Maps Primary TAM discovery layer for hospitality venues. Replaces LinkedIn for an audience that is largely invisible to standard B2B databases.

Outscraper Used to scrape Google Maps at scale, returning structured venue data (name, location, category, size signals) for downstream filtering and enrichment.

Clay Enrichment and validation layer on top of scraped venue data. Surfaces owners, operators, and procurement contacts; adds business context for personalisation.

Apollo Supplementary contact data for larger chain operators and segmentation work where LinkedIn-style data was useful as a secondary input.

Smartlead Sending platform across fresh domains and rotating inbox architecture. Inbox rotation and deliverability controls were the foundation of the infrastructure rebuild.

Verification gate Email verification run before any address entered Smartlead, holding bounce rate inside deliverability-safe range and protecting the new sending domains.

Phone reply path Quick-phone-call CTAs replaced calendar links. The reply path was tuned for same-day or next-day phone conversations rather than booked meetings.

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.

"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 had tried."

SOFi Paper Products Leadership Team

Results: 123 RFQs in 9 Months From Rebuilt Hospitality Outbound

Over approximately 9 months, the rebuilt system generated 123 RFQs from qualified hospitality buyers, reversed the prior decline in outbound performance, and shifted the operating motion from "book a meeting" to high-performing quick-call conversations with cafés, hotels, restaurants, and food-service operators.

123

RFQs From Qualified Hospitality Buyers

~9 mo

Campaign Run to Date

Reversed

Prior Outbound Performance Decline

Phone

Primary Reply Path (Replaced Calendar Links)

Google Maps

Primary TAM Source (Replaced LinkedIn-Only)

4

Messaging Angles Rotated Against RFQ Speed

Note on Attribution

The 123 RFQs figure covers qualified buying conversations generated through the rebuilt outbound system over approximately 9 months. Downstream commercial outcomes (volume of RFQs converting to orders, deal sizes, total contracted revenue) play out on the manufacturer-supply procurement cycle and are not reported here. The case study reports on RFQ generation, the change in CTA mechanic, and the change in TAM source.

Pipeline Outcomes

RFQs generated from qualified hospitality buyers123

Campaign duration to date~9 months

Buyer verticals contributingCafés, hotels, restaurants, food-service

Primary CTA mechanicQuick phone call (replaced calendar links)

Primary TAM sourceGoogle Maps via Outscraper (replaced LinkedIn)

Prior outbound trendDeclining; reversed and trending upward

List quality vs LinkedIn-only baselineSignificantly higher

Fit Guide

✓ When It Works

• Fragmented, offline-first buyer markets where LinkedIn coverage is poor
• RFQs (rather than booked meetings) are the natural buying motion
• Recurring consumables that justify repeat outreach and ongoing supplier evaluation
• Procurement contacts who prefer fast phone conversations to scheduled video calls
• Manufacturers and suppliers selling into hospitality, food-service, and similar high-frequency consumption verticals

✗ When It Does Not Work

• Low-volume, one-off manufacturing deals where lifetime value does not justify a 9-month outbound run
• Highly regulated buyer lists with no public footprint that Google Maps cannot surface
• Offers where procurement requires long, formal RFP processes that cold outbound cannot enter
• Pure "green" messaging without paired durability, supply reliability, or pricing angles
• Manufacturers unwilling to staff fast phone follow-up to operator replies

Key Learnings From the SOFi Paper Products Outbound Rebuild

1. Google Maps beats LinkedIn for fragmented offline-first buyers.

Hospitality buyers, like many high-consumption physical-goods markets, are barely visible on LinkedIn. A 12-seat café owner does not have a LinkedIn presence that matches their procurement signal. Google Maps, scraped at scale with Outscraper and enriched in Clay, surfaced a TAM that LinkedIn-only sourcing had completely missed. The data source, not the copy, was the largest single lever in the rebuild.

2. Phone-first CTAs outperform calendar links for operators.

Café owners, hotel ops managers, and restaurant operators rarely book a calendar link from a cold email. They prefer a quick call about pricing and supply, often same day. Switching CTAs from "book a meeting" to "quick call to discuss pricing and supply" lifted engagement immediately. CTA mechanics matter at least as much as copy in offline-first markets.

3. Deliverability resets are mandatory after long DIY outbound runs.

Years of sending from the same domains had degraded reply rates regardless of what was written. No amount of copy work would have fixed it. The reset (fresh domains, warmup, rotating inboxes in Smartlead, pre-send verification, ongoing bounce control) was the foundation that made every other change in the rebuild measurable. Skipping it would have left the channel structurally broken.

4. Sustainability messaging needs to be paired with ROI to work in cold outreach.

For SOFi the obvious angle was sustainability. In isolation it underperformed in cold outbound to procurement-minded operators. Paired with durability, supply reliability, and pricing competitiveness, sustainability returned as a winning angle. The rule generalises: green messaging works as a tie-breaker, not as the primary commercial pitch.

5. AI is for relevance and efficiency, not for generic copy generation.

AI was used to validate ICP fit per row, enrich business context, and support light personalisation. It was not used to write generic copy. Hospitality operators pattern-match generic AI tone as spam quickly, and once a domain is associated with that tone the reputation cost is hard to recover. The discipline of "AI for relevance, human for voice" kept the rebuild on the right side of that line.

Work With Danish Lead Co.

If your buyers are fragmented, offline-first, and largely invisible to LinkedIn, the right outbound system is one designed around how they actually behave.

The SOFi rebuild produced 123 RFQs in 9 months by replacing LinkedIn-only sourcing with Google Maps, calendar-link CTAs with quick-phone-call asks, and an aged DIY setup with fresh deliverability infrastructure. We will tell you on the first call whether your market suits the same approach.

Book a Strategy Call → See our services More case studies

Frequently Asked Questions

Common questions about the SOFi Paper Products cold outbound rebuild, the Google Maps sourcing model, the phone-first CTA shift, and whether the approach generalises to other manufacturer and supplier markets.

How did SOFi Paper Products generate 123 RFQs from cold outbound?

Over approximately 9 months, Danish Lead Co. rebuilt SOFi's cold outbound engine from the ground up. Three changes mattered most: Google Maps replaced LinkedIn as the primary TAM source (scraped via Outscraper, enriched in Clay), quick-phone-call CTAs replaced calendar links because hospitality operators preferred fast phone conversations, and fresh sending domains plus rotating inbox architecture in Smartlead replaced the aged DIY infrastructure that had been degrading reply rates. The combined system generated 123 RFQs from qualified cafés, hotels, restaurants, and food-service buyers.

Why is Google Maps a better TAM source than LinkedIn for hospitality buyers?

Hospitality buyers are largely offline-first and poorly represented in LinkedIn and standard B2B databases. The owner of an independent café, the operations manager of a regional hotel group, or the buyer at a food-service operator often does not have a LinkedIn presence that maps cleanly to the procurement role. Google Maps, by contrast, lists the venue itself with location, category, and size signals. Scraping it at scale with Outscraper and then enriching with Clay surfaces owners, operators, and procurement contacts at a far higher list-accuracy rate than LinkedIn-only sourcing for this audience.

Why did quick-phone-call CTAs outperform calendar links?

Hospitality operators rarely book a calendar link from a cold email. Café owners, hotel ops managers, and restaurant procurement contacts run busy, interrupt-driven days and prefer a fast phone conversation about pricing and supply over a scheduled video call later in the week. Switching the CTA from "book a meeting" to "quick call to discuss pricing and supply" lifted engagement immediately and shortened the time from positive reply to qualified RFQ conversation. In offline-first markets, the CTA mechanic is often the single largest copy-level lever.

What deliverability rebuild was required after years of DIY sending?

SOFi had been sending from the same domains for years. Reply rates had been declining month over month regardless of what was written. The rebuild reset the infrastructure: fresh dedicated sending domains, full warmup routines before live volume, rotating inbox architecture in Smartlead, strict pre-send verification, and ongoing bounce-rate monitoring. The performance decline was not a content problem; it was a sender-reputation problem, and only an infrastructure reset could reverse it.

Which buyer segments contributed the most RFQs?

The TAM was segmented into cafés and independent coffee shops, chains and multi-location operators, hotels and hospitality groups, and event venues and food-service buyers. Higher-consumption segments (multi-location chains, hotel groups with banquet operations, larger food-service operators) were prioritised first because a single won account in those segments justifies the entire campaign on its own. Independent cafés contributed RFQ volume but at smaller per-account scale.

How was AI used in the SOFi cold outbound rebuild?

AI was used narrowly: to validate ICP fit at the row level, to enrich business context per venue, and to support light personalisation so messages could reference real attributes of the specific café, hotel, or chain. It was deliberately not used to generate generic cold-email copy. Hospitality operators pattern-match generic AI-style emails as spam within seconds, so the discipline was "AI for relevance, human-checked voice in the copy". This protected sender reputation and kept replies high.

What messaging angles worked and which did not?

Four angles were rotated and measured against RFQ speed: sustainability without performance trade-offs, product durability and usability, supply reliability, and pricing competitiveness. Pure sustainability messaging without ROI underperformed; sustainability paired with durability, supply, and pricing returned as a winner. Underperforming angles were cut quickly; winning combinations were scaled. The takeaway: green messaging is a tie-breaker, not the primary commercial pitch.

Will this approach work for other manufacturer and supplier markets?

Yes, where the buyer market shares the same shape: fragmented and offline-first, RFQs (rather than booked meetings) as the natural buying motion, recurring consumables that justify ongoing supplier evaluation, and procurement contacts who prefer fast phone conversations. The approach is a weaker fit for low-volume one-off manufacturing deals, highly regulated buyer lists with no public footprint, or offers where procurement requires long, formal RFP processes that cold outbound cannot enter.

What tools did Danish Lead Co. use for the SOFi Paper Products campaign?

Google Maps was the primary TAM discovery layer. Outscraper scraped Google Maps at scale to return structured venue data. Clay handled enrichment and validation, surfacing owners, operators, and procurement contacts plus business context for personalisation. Apollo provided supplementary contact data for larger chain operators. Smartlead handled sending across fresh dedicated domains with rotating inbox architecture. A pre-send email verification gate held bounce rates inside deliverability-safe range. The reply path was tuned around quick-phone-call CTAs rather than calendar links.

Can Danish Lead Co. build a similar outbound engine for my manufacturing or supply business?

If your buyers are fragmented and offline-first, RFQs are the natural buying motion, and your prospects prefer fast phone conversations to scheduled meetings, the same approach typically applies. Book a strategy call at danishleadco.io/book-a-demo to talk through fit. We will tell you on the first call whether your market suits a Google Maps-led, phone-first, deliverability-rebuilt outbound system.