Quick signals
What this product actually is
Gorgias is purpose-built for e-commerce: native order lookup, refund actions inside tickets, and Shopify-deep automation macros—priced per ticket volume, not per agent. Breaks when you need multi-channel beyond email/chat.
Pricing behavior (not a price list)
These points describe when users typically pay more, what actions trigger upgrades, and the mechanics of how costs escalate.
Actions that trigger upgrades
- Ticket volume exceeds 50 (Starter)—Basic $60 for 300
- 300 tickets exceeded—Pro $360 for 2,000; overage $40/100
- 2,000 tickets exceeded—Advanced $900 for 5,000
- Need AI Agent—unavailable on Starter; Basic+ required
- Revenue statistics and advanced reporting—Pro+
- Dedicated email server—Advanced tier
When costs usually spike
- Ticket definition: verify what counts (new conversation vs reply); overage math matters
- AI Agent $0.90–1.00/resolution; no flat cap by default; high volume = large add-on
- Starter: no AI Agent; Basic+ for AI deflection
- Omnichannel add-ons: WhatsApp, SMS, Voice priced separately
- Enterprise custom volume; overage $32/100 tickets
- Unlimited users but ticket volume caps drive plan; 10 agents on 50-ticket Starter = constant overage
Plans and variants (structural only)
Grouped by type to show structure, not to rank or recommend specific SKUs.
Plans
- Starter - $10/mo - 50 tickets/mo, basic macros
- Basic - $60/mo - 300 tickets/mo, order lookup
- Pro - $360/mo - 2000 tickets/mo, automation depth
- Advanced - $900/mo - 5000 tickets/mo, full platform
Costs and limitations
Common limits
- E-commerce-only: weak fit for B2B, SaaS, or non-storefront support
- 50 tickets on Starter exhaust quickly; Basic $60/mo (300) next step
- Pro $360/mo (2,000 tickets) = $0.18/ticket; high volume = Advanced $900 (5,000) or Enterprise
- AI Agent $0.90–1.00/resolution; 1,000 resolutions = $900–1,000 add-on
- No native CRM; Zendesk/Freshdesk better for complex contact/account workflows
- Ticketing built for e-commerce; queue depth and SLA less mature than Zendesk
What breaks first
- 50-ticket Starter limit; 51st ticket = $0.40 overage; 100 tickets = $10 + $20 = $30
- AI Agent resolution cost: 2,000 resolutions = $1,800 add-on to Pro $360
- Ticket volume spikes (holidays, promo)—overage $36–40/100 adds unpredictability
- Pro $360 (2,000) to Advanced $900 (5,000)—2.5x cost for 2.5x volume
- Non-e-commerce use cases: order lookup and macros less valuable
- Queue and SLA maturity lag Zendesk; complex routing harder
Decision checklist
Use these checks to validate fit for Gorgias before you commit to an architecture or contract.
- Ticket queue vs conversational support model: Is email/chat resolution threaded or formal tickets?
- Per-agent vs per-ticket pricing model: What is your projected ticket volume vs agent count?
- Enterprise depth vs simplicity and adoption: How many integrations and workflow automations do you need?
- General-purpose vs vertical-specific (e-commerce): Does order lookup and refund-in-ticket dominate your support queue?
- Upgrade trigger: Ticket volume exceeds 50 (Starter)—Basic $60 for 300
- What breaks first: 50-ticket Starter limit; 51st ticket = $0.40 overage; 100 tickets = $10 + $20 = $30
Implementation & evaluation notes
These are the practical "gotchas" and questions that usually decide whether Gorgias fits your team and workflow.
Implementation gotchas
- E-commerce integration depth → Less mature queue and SLA than Zendesk
- No native CRM; Zendesk/Freshdesk better for complex contact/account workflows
Questions to ask before you buy
- Which actions or usage metrics trigger an upgrade (e.g., Ticket volume exceeds 50 (Starter)—Basic $60 for 300)?
- Under what usage shape do costs or limits show up first (e.g., Ticket definition: verify what counts (new conversation vs reply); overage math matters)?
- What breaks first in production (e.g., 50-ticket Starter limit; 51st ticket = $0.40 overage; 100 tickets = $10 + $20 = $30) — and what is the workaround?
- Validate: Ticket queue vs conversational support model: Is email/chat resolution threaded or formal tickets?
- Validate: Per-agent vs per-ticket pricing model: What is your projected ticket volume vs agent count?
Fit assessment
Good fit if…
- Shopify or BigCommerce stores (D2C, subscription, marketplace)
- E-commerce support teams (5–50 agents) where order lookups dominate tickets
- Teams wanting ticket-based pricing; scaling users without per-seat cost
- Stores needing macros for refunds, discounts, order edits in-ticket
- Support-driven revenue: upsell, retention, and order editing in one place
- Integrations with Klaviyo, Recharge, Loop, Yotpo for customer context
Poor fit if…
- Not e-commerce; B2B, SaaS, or services—Zendesk/Freshdesk/Help Scout better
- Ticket volume unpredictable; per-ticket overage can spike ($0.40/ticket Starter)
- Need mature SLA policies and queue governance—Zendesk stronger
- Chat-first, proactive engagement—Intercom's Fin and messaging better
- Collaborative inbox over tickets—Front built for that
- Already on Zoho CRM—Zoho Desk integrates natively
Trade-offs
Every design choice has a cost. Here are the explicit trade-offs:
- Unlimited users, ticket-based pricing → Overage cost when volume spikes
- Native e-commerce order actions → Weak for B2B, SaaS, non-storefront
- AI Agent $0.90/resolution → Variable cost at scale vs flat AI add-ons
- Starter $10 (50 tickets) → AI Agent unavailable; Basic+ required
- E-commerce integration depth → Less mature queue and SLA than Zendesk
Common alternatives people evaluate next
These are common “next shortlists” — same tier, step-down, step-sideways, or step-up — with a quick reason why.
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Zendesk — step-upWhen general-purpose support, SLA depth, and 1,200+ integrations matter more than e-commerce.
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Freshdesk — step-sidewaysGeneral helpdesk at lower per-agent cost; not e-commerce-native.
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Intercom — step-sidewaysChat-first and Fin AI; works for e-commerce but not order-native.
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Help Scout — step-downEmail-centric; Standard $25/user; when e-commerce is secondary.
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Zoho Desk — step-downBudget option; Free 3 agents, Pro $23/agent; Zoho CRM integration.
Sources & verification
Pricing and behavioral information comes from public documentation and structured research. When information is incomplete or volatile, we prefer to say so rather than guess.