What do you dislike about Plain?
Plain lacks many essential workflows and features required for modern SaaS support, making it challenging to deliver enterprise-grade service. While it is encouraging to see their team responsive and attentive to product issues, it sometimes feels as though the product was developed by those unfamiliar with support environments, placing the burden of product QA on users. As a result, we often find ourselves working around Plain rather than with it.
Although Plain offers an open API, several methods are restricted to their internal API explorer and do not function outside that environment. This limitation prevents building integrations or workflows needed by support teams. For example, their integration with Linear depends on each user’s personal access token rather than an app-level OAuth token. While this may seem minor, it means Plain acts as individual users within Linear rather than as an app on their behalf. Consequently, programmatic linking of Linear issues to Plain threads—though possible in the API explorer—is not feasible in custom applications or workflows. Such undocumented implementation details and API constraints undermine the developer experience and complicate custom workflow development.
Reporting capabilities are currently very limited. To obtain granular insights into individual performance or more detailed ticket-level data beyond the default reports, users must configure ETL pipelines and build external dashboards. Although improvements are underway, gaining meaningful insights from support data remains more difficult and resource-intensive than expected.
Several common support workflows are missing. For instance, most platforms enable agents to respond to frequent questions with macros or snippets that can also automate labeling or add metadata to tickets, reducing manual effort. Plain’s snippets are restricted to response text only, requiring agents to manually apply any ticket labels or changes, which reduces efficiency.
Additionally, Plain's webhook content can't be modified. Webhook payloads include the entire thread content, resulting in payloads and network requests that are larger than necessary. Teams must build backend handlers to filter out irrelevant data. Additionally, this approach complicates compliance efforts such as GDPR or CCPA data deletion requests. A better option would be allowing users to specify the data included in webhook payloads, limiting it to what is strictly necessary.
Plain’s AI features are a a bit of a black box. There is no way to train their language model on your specific product support context or to consistently guide the AI to improve accuracy beyond rejecting certain responses. This limitation also applies to automatic ticket labeling. Depending on the environment, AI-generated responses may hinder rather than help support efficiency.
Text formatting is unreliable, especially in code-heavy environments. Customer-submitted code blocks often require manual correction to be understandable. Likewise, code blocks sent by agents may be displayed incorrectly to recipients, burdening customers with deciphering malformed content. This issue is especially apparent when supporting customers via Slack or Microsoft Teams. However, Plain is actively working to improve formatting consistency, and we've seen some improvements.
In summary, Plain lacks essential features and workflows required for enterprise-grade SaaS support, presenting challenges in automation, reporting, and API integration, which often forces users to implement workarounds and reduces efficiency. Review collected by and hosted on G2.com.
