TeamworkDesk vs HelpShift: Helpdesk Logiciel Comparaison 2026
TeamworkDesk and HelpShift are both helpdesk and support client platforms, but they are built for different operating models, budgets, and team workflows. This comparaison aviss pricing, IA et automatisation, integrations, use cases, migration considerations, and practical buying trade-offs.
Verdict rapide
TeamworkDesk is usually a stronger fit for SMB teams that value Email, Projects, Collaboration. HelpShift is usually a stronger fit for SaaS / Chat teams that value Mobile, Gaming, SDK. Based on the available G2 rating in this dataset, TeamworkDesk has the higher user rating.
Tarifs comparaison
TeamworkDesk starts at from $15/agent/mo, while HelpShift starts at Custom pricing. Treat this as a starting point, not a full total cost estimate. Real pricing can change with agent count, AI features, phone or messaging channels, advanced reporting, implementation, marketplace apps, and data migration needs.
| Factor | TeamworkDesk | HelpShift |
|---|---|---|
| Starting price | from $15/agent/mo | Custom pricing |
| G2 rating | 4.5 | 4.4 |
| Best fit | SMB | SaaS / Chat |
| Founded | 2015 | 2011 |
| HQ | Cork, Ireland | San Francisco, USA |
| Customers | 20,000+ (Teamwork total) | 3,000+ |
| Known clients | Agencies and project-based businesses | Blizzard, Microsoft Gaming, Supercell, Zynga |
IA et automatisation
TeamworkDesk
Basic AI reply suggestions.
HelpShift
AI-powered in-app bots and smart routing.
For AI buying decisions, compare not only feature names but also automation limits, handoff quality, knowledge base dependency, pricing per resolution or add-on, reporting, and how much configuration your team needs before AI becomes useful.
Intégrations
TeamworkDesk is commonly evaluated by teams that need Email, Projects, Collaboration. HelpShift is commonly evaluated by teams that need Mobile, Gaming, SDK. Before choosing, check native integrations for your CRM, ecommerce platform, chat tools, telephony, BI stack, identity provider, and data warehouse.
When to choose TeamworkDesk
Choose TeamworkDesk when its pricing model, workflow depth, and operational fit match your team better than HelpShift. It may be the better option if the following strengths are central to your support strategy:
- Integrates with Teamwork Projects
- Clean interface
- Shared inboxes
Watch out for these limitations before committing:
- Standalone weaker than dedicated helpdesks
- Best only if using Teamwork
When to choose HelpShift
Choose HelpShift when its ecosystem, product direction, and implementation model are a better fit for your team than TeamworkDesk. It may be the better option if these strengths matter most:
- In-app support for mobile
- Strong for gaming
- SDK-based integration
Check these trade-offs carefully before rollout:
- Niche mobile focus
- Complex SDK integration
- Not for non-mobile
Migration considerations
If you are moving from TeamworkDesk to HelpShift, or from HelpShift to TeamworkDesk, the main challenge is usually not just ticket export. You need to plan how users, organizations, companies, comments, private notes, attachments, tags, statuses, custom fields, knowledge base articles, and record relationships will map into the new system.
Before migration, verify API limits, attachment handling, deleted or archived records, field mapping, ticket status logic, agent matching, knowledge base structure, and whether you need a delta migration close to go-live.
FAQ
The main difference is usually fit: pricing model, workflow depth, integrations, AI capabilities, implementation complexity, and the type of support team each product serves best.
Not universally. TeamworkDesk can be better for some teams, while HelpShift can be better for others. The right choice depends on your support channels, team size, budget, automation needs, and existing logiciel stack.
Yes, in many cases you can migrate tickets, users, companies, comments, attachments, tags, custom fields, and knowledge base data. The exact scope depends on each platform's API and export/import limitations.
Based on listed starting prices, neither platform clearly is cheaper at entry level. However, total cost depends on add-ons, AI usage, number of agents, support channels, and implementation work.