Pros:
- Highly customizable data structure
The platform allows for extensive use of custom fields and filters, making it possible to structure customer data in a way that aligns closely with our operational and business needs.
- Strong workflow capabilities
Both email workflows and project (workflow) management features are robust and support a wide range of use cases, from onboarding and implementations to ongoing customer operations.
- Data visibility and hygiene
Certain field types can be highlighted when missing, which improves visibility and helps teams maintain data quality.
- Flexible views and data segmentation
The ability to create multiple views, group data, and organize fields into logical sections enables different teams (e.g. CSMs, Implementation Managers) to work efficiently within the same system.
- AI functionality
Built-in AI features are continuously evolving and provide additional value, particularly when integrated into workflows and communication processes.
- Custom billing and operational tracking
While Planhat offers native billing functionality, we’ve successfully adapted the platform to support our own invoicing and operational tracking processes.
- Intuitive project/workflow management
Workflow-based project management is easy to understand and implement, even for complex operational processes such as installations, changes, and logistics.
- Strong integration capabilities
Planhat integrates well with tools like Typeform, Zapier, and internal systems. We’ve also integrated external AI (Claude) into our environment, which works effectively alongside Planhat.
- Comprehensive onboarding resources and support
There is a significant amount of documentation available for self-learning, and the support team is responsive and helpful when needed.
- Powerful automation capabilities
The platform enables a high degree of automation and customization, allowing us to streamline complex operational processes. Reseña recopilada por y alojada en G2.com.
- Data duplication for reporting and filtering
Creating dashboards or widgets often requires duplicating data across objects (e.g. syncing company-level data to workflows, tasks, or billing objects). This requires additional fields and automations to maintain consistency, which increases complexity and cost.
- Reliance on manual data population
Many workflows depend on accurate company-level data being populated upfront. While this can be automated to some extent, it requires significant setup and ongoing maintenance.
- Complex workflow logic setup
Achieving relatively straightforward business logic in workflows can require detailed condition building and careful planning, which increases the setup effort.
- Limitations around required fields
Not all fields can be visually highlighted when missing, which forces the use of “mandatory” fields. There are also limitations and inconsistencies (particularly within workflows) in how mandatory fields behave.
- Limits on views and customization
There are caps on the number of object profile views, which can restrict flexibility unless additional cost is incurred.
- Usage-based pricing for AI and automations
AI usage and automation runs are limited, and exceeding these thresholds results in additional costs. This becomes more relevant at scale.
- Edge cases and system limitations
While most use cases are technically possible, pushing the platform into more complex or non-standard scenarios can expose bugs or limitations that require support intervention.
- Complexity in process control and integrations
Maintaining reliable process control across workflows and external integrations requires careful setup and monitoring. Without this, there is a risk of inconsistencies in data or execution. Reseña recopilada por y alojada en G2.com.
