How Gorgias scaled to 80m+ ARR without cold calls
11 outbound differentiators
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While your competitors burn cash on SDR teams that can't make unit economics work, Gorgias cracked the code on automated outbound that actually scales. They proved you can reach $80M ARR without following the traditional playbook.
Here's exactly how they built an outbound engine that sends 1 million emails per quarter while keeping costs 2.4x lower than SDR teams, and the different strategies that will reshape how you think about outbound in 2025:
Automate first, hire humans second. Unit economics favor machines over SDRs for SMB deals
Signal-based outreach beats spray-and-pray: Behavioral triggers deliver 3-4x higher contract values
Multi-channel coordination creates surround-sound: Email + ads + referrals outperform single-touch sequences
RevOps infrastructure is your competitive advantage: Data-driven systems scale without proportional headcount growth
Gorgias Snapshot - Scaling to $80M ARR
ARR: 80m+ (source LinkedIn)
Growth Rate: 34% YoY (2024)
Valuation: Gorgias was valued at $530 million in 2024
Total Funding: 129 million
Industry: Ecommerce support/helpdesk (Vertical SaaS)
Target: SMB to midsize ecommerce businesses with seasonal support needs
Annual Contract Value (ACV): $7,750 (2025)
High-velocity Sales
P.S. Another example that’s super close to this, SMB segment, low ACV, is Owner.
Industry: Restaurants (Vertical SaaS)
Target Customers: SMB restaurant owners
ACV: $6K
If you didn’t read it yet, here’s the link.
11 outbound differentiators
Gorgias did a bunch of things differently to make outbound actually work. I pulled 11 things they did that we can learn from:
1. They Skipped the SDR Army and Automated their Way to Scale
In their early days, Gorgias explicitly avoided hiring SDR teams because the unit economics don't work for their $3k ACV.
Instead, they built an automated outbound engine that could reach thousands of SMB prospects economically.
"Building an outbound engine is really important. So many teams are hiring SDR/BDR teams, and it's really tough to make that work in SMB sales."
Their automated system sends ~1 million emails per quarter, touching each company in their TAM multiple times while maintaining 2.4x lower average cost per contact than manual SDR approaches. The marginal cost difference? A staggering 8x cheaper once the system is running.
Around 2023-2024, they launched an SDR team to go on top of this outbound automated engine.
2. They Started Outbound Before Going Product-Led
Everyone tells SMB SaaS companies to focus on inbound and self-service.
Gorgias did the opposite.
They focused on outbound in a segment where conventional wisdom says "product-led growth only." Their CEO Romain Lapeyre credits data-driven outbound for acquiring 10,000+ SMB customers, stating that data must be intrinsic to customer acquisition strategy. They proved you can do profitable outbound in SMB if you reinvent the model.
While competitors relied on marketing funnels and free trials, Gorgias built a machine to economically target thousands of tiny e-commerce merchants.
SMB markets can absolutely support outbound.
3. You Can't "Burn" Your TAM
The fear of "spamming" prospects is killing your pipeline potential.
In their early days, Gorgias's high-volume approach reflected a mindset that repeatedly hitting prospects is not only OK, it was necessary. They re-engaged prospects whenever fresh signals emerge (new hires, tech changes, growth milestones), treating outbound as always-on rather than one-and-done.
This persistence delivered massive results: Prospects contacted with contextual triggers had contract values 3-4x higher than cold prospects with no signal. As one expert noted about similar programs: "It's borderline impossible to burn your TAM. Hit them with new messaging, try new angles, or use signals as a reason to reach out again."
P.S. This used to work really well when they were just starting out. But now? They don’t do it like that anymore, and everyone knows them. So these days, they’re way more careful about who they reach out to.
4. They Map Every Account in their market
They mapped all 2 million Shopify stores but identified 700,000 as their true TAM using multiple data vendors:
Store Leads for e-commerce business data
BuiltWith for tech stack analysis
HubSpot as their CRM hub.
Within each segment, they created data buckets tracking Companies, Deal Creation rates, Close Rates, ACV, Market Share against Zendesk, and Net Revenue Retention (NRR). This granular mapping revealed exactly where to focus their firepower.
Their predictive analysis then categorized prospects into 5 segments based on website traffic, applying algorithms to prioritize accounts before any outreach began. Every lead got automatically scored and routed based on predicted deal size, demand gen handled small prospects while human reps engaged high-value accounts.
This predictive TAM mapping help make sure to focus on the accounts with the highest ACV/LTV potential and highest fit for the company.
5. Turn Signals Into Revenue
It’s not really new anymore, but Gorgias has been using signals from the start. What’s different is how they do it. They track smart signals to know who to go after first, then use that to trigger automated outbound.
They track specific triggers across the internet:
Hiring for a CX lead, this is a signal for Gorgias to help them figure out a CX motion since their product is a help desk for e-commerce.
When a company starts using another tool in the eComm SaaS world, either:
competitive like Zendesk
complementary to their product like Recharge.
Scanning their prospect social media profiles receiving customer complaints on social media
Past customers moving to a company not using Gorgias
Prospects going to E-commerce events, or tradeshows like Shoptalk, or eTail West
When they outbound a prospect with an intent signal, ACV jump 3-4x higher than prospects with no signal.
Their system automatically triggers outreach the moment buying signals appear.
6. Turn Events Into Revenue
They use platforms like Vendelux to identify attendees of relevant conferences (Shoptalk, eTail West) before events even begin. Pre-event, they invite high-value prospects to exclusive side events hosted by Gorgias. Post-event, engaged attendees get enrolled into automated sequences highlighting specific product differentiators based on their conference interactions.
This strategy doesn't just improve response rates (400%), it fundamentally changes deal economics. Their CEO discovered that prospects who attend events consistently close at higher ACVs, making event-driven outreach one of their highest-ROI channels. The time required to secure qualified leads plummeted as warm introductions replaced cold outreach.
7. A Different Multi-Channel Approach
Email sequences are just the beginning of Gorgias's outbound orchestration.
Their 3-channel engine integrates email, ads, and customer referrals into one seamless prospect journey. A prospect gets an automated email, then targeted ads if they show interest, followed by peer endorsements from happy customers, all orchestrated by the growth team.
They achieved 90% match rates on ad targeting (up from 50%) by syncing contact data to ad platforms, contributing an extra $2M in ARR from paid channels. The referral program turned customers into an extension of the sales team, with incentives like free iPhones for successful referrals.
This multi-channel coordination for SMB creates pipeline that single-channel outreach can't match.
8. They Skipped Cold Calling
With their early $3,000 ACV serving SMB e-commerce merchants, cold calling economics simply don't work. The cost per hour of SDR phone time versus deal size made digital-first outreach the only profitable path. They focused on email sequences, behavioral triggers, and automated touchpoints because these channels could reach thousands of prospects economically.
Phone calls were reserved exclusively for later stages (demos and closing) when prospects had already shown genuine interest through email engagement or ad interactions. This meant the expensive, time-intensive activity of cold prospecting was eliminated from the top of funnel, dramatically improving unit economics.
Match your outreach channels to your ACV, expensive channels only work for high-value deals.
9. Treat Outbound Like a Product Team
Similar culture to the Ramp and Pigment GTM team.
Gorgias treated outbound ops like an engineering problem when most startups wing it with basic tools.
They invested in data infrastructure and ops talent early, unusual for a startup their size.
Also most sales teams stick to rigid playbooks, Gorgias embraced "fail fast and pivot" like a growth hacking lab.
The CEO and the VP Sales met weekly with strong mutual trust, giving sales complete latitude to reconfigure processes, modify sales cycles, and create new outbound motions. "Executives need to enable sales leaders to build... Trust in their expertise since they are closest to the process," Lapeyre explains. The sales team acted like a laboratory for unorthodox ideas, willing to contradict standard advice if data indicated a better path.
This experimentation mindset led to breakthrough discoveries. When they initially tried fully automated self-serve sales for smaller customers, data showed only 30% win rates versus 73% with human demos, so they pivoted immediately. They learned to automate the process, not the conversation, fundamentally reshaping their approach based on evidence rather than assumptions.
10. Audit Your Data Like Your Revenue Depends On It
Bad data kills outbound programs.
Gorgias cross-references data from multiple vendors to eliminate redundancies and ensure accuracy. Regular audits keep lists updated with real-time company changes like funding rounds, leadership shifts, and tech stack modifications. Their proprietary scoring models assign lead values based on firmographic data, engagement history, and intent signals, not just company size.
This obsession with data quality means every outbound dollar works harder.
Clean, cross-validated prospect data dramatically improves response rates and reduces wasted outreach spend.
11. Their Outbound Data Stack + How they use AI
Here's the data stack they use for outbound, and how they plug in AI to make it work.
Bonus: I’m also sharing the exact tech stack 10 other top outbound teams are using. Think Pigment, Ramp, Rippling, Snowflake.
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