Comparison guide · CRM support AI
HubSpot Breeze vs Fin: outcome pricing for support AI
HubSpot Customer Agent charges outcome credits (~50 credits / resolved conversation ≈ $0.50 on Pro/Enterprise). Fin (ex-Intercom) still prices around ~$0.99 per resolution. Definitions differ — and Fin’s Salesforce deal is signed, not closed.
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What actually matters
- Compare resolution definitions, not sticker unit prices — HubSpot’s “resolved” window and Fin’s resolution meter are not identical.
- Budget seats + credit packs (HubSpot) or seats + resolutions (Fin), plus UK VAT/FX on USD lists.
- Ask whether Salesforce gravity after the Fin deal matters for your stack over a 2–3 year contract.
- Pilot with real ticket categories and an explicit spend cap before enabling auto-upgrades.
- Governance: who owns prompts, knowledge sources, and escalation rules when the agent fails.
The shortlist
- HubSpot when marketing–sales–service already live in HubSpot and outcome credits beat per-attempt chat bots.
- Fin when conversation quality and Messenger context are the product and you accept ~$0.99/resolution economics.
- Stay on a classic help desk without AI resolution meters when volume is low or human-first is the brand.
Evidence-backed entries
A sensible test workflow
- 01Pull 50 recent tickets and score which ones an agent may safely close without a human.
- 02Run a two-week capped pilot on each platform (or one if you already own a hub) and measure cost per successful close.
- 03Document escalation paths and knowledge ownership before rolling out company-wide.
Common mistakes
- Treating “included AI” as unlimited — both products meter outcomes.
- Signing multi-year Fin deals solely because Salesforce acquisition headlines feel inevitable.
- Ignoring reverse-charge VAT and FX when modelling HubSpot credit spend from a UK entity.
Popular-AI shortlist snapshot: August 6, 2026. This guide is a starting framework, not a permanent ranking. Model prices, access, policies, and capabilities move quickly. Check the provider before committing spend or sending sensitive data.