Skip to main content

    Filter by status

    Filter by product area

    740 Ideas

    Heric
    HericSmooth talker

    Advanced Permission and Visibility Settings per Team MemberNew

    Hi Manychat Team, I’d like to suggest a significant improvement regarding team member permissions and visibility controls within the platform.Currently, the only customizable access available for a team member is billing-related. It would be extremely helpful to have more granular control over permissions and visibility for each individual team member — rather than applying settings globally. Key Suggestions: Allow admins to assign specific permissions individually, such as: Access to add or delete contacts without requiring admin status. Ability to view conversations of specific team members (not all). Ability to access conversations in the "Unassigned" inbox. Ability to create, edit, or delete tags. And ideally, the ability to assign any permission that an admin currently holds to a specific member, depending on their role.  Use Case Examples: I want a team member to manage contacts, but not access billing or platform settings. I want a supervisor to view conversations from selected team members only, without granting full access to everyone’s inbox. I want to allow a support agent to monitor unassigned conversations, but not see automations or settings they don’t need. I want to allow a member to create and manage tags, without making them an admin.  Additional Request – Visibility Controls:It would also be helpful to control which resources each member can see: Automations Custom fields Sequences Menus Templates Configuration tabs  For example, a support agent doesn't need to see all flows or system configurations that are irrelevant to their tasks. Restricting visibility helps avoid confusion and keeps each team member focused on what matters to their role.This level of customization would make Manychat much more scalable and secure for teams of any size, especially those who work with sensitive data or need clear role separation. Could you help me with this, ​@Raquel C , ​@Marina? Thank you for considering this improvement!Best regards,Heric Fernandes

    LourdesPallas
    LourdesPallasUp-and-comer

    Idea para ManyChat: integración JSON para flujos desde ChatGPTNew

    ¡Hola equipo de ManyChat! 👋Soy Lourdes, especialista en marketing digital y lanzamientos de infoproductos centrados en embudos de venta por Instagram. Actualmente me estoy especializando en chat funnels.Últimamente he empezado a usar ChatGPT para esbozar estructuras de flujos conversacionales antes de construirlos manualmente en ManyChat. Esto me ahorra mucho tiempo en la fase creativa, pero el traspaso manual a la plataforma es repetitivo y consume demasiados recursos.Por eso, me encantaría proponer lo siguiente:✅ Una funcionalidad que permita importar estructuras de flujos a través de archivos JSON generados por herramientas de IA (como ChatGPT) o plataformas low-code, directamente al constructor de ManyChat.¿Por qué esto sería potente? Ahorro de tiempo enorme para creadores avanzados y agencias Colaboración fluida entre humanos e inteligencia artificial Escalabilidad: más fácil clonar, iterar y reutilizar flujos Impulso a la creatividad: estructuramos con lógica, diseñamos con alma Sé que actualmente los flujos solo se pueden duplicar manualmente o entre espacios de trabajo. Pero permitir la importación vía JSON (quizá a través de una estructura validada o un endpoint API) abriría la puerta a una forma mucho más ágil de trabajar para los usuarios más avanzados.Ya sea como funcionalidad nativa o como una capa de integración con partners verificados, esto podría revolucionar la manera en que construimos y escalamos automatizaciones dentro de ManyChat.Gracias por considerar esta idea y por construir una plataforma tan potente. ¡Estoy deseando saber qué opináis!—Lourdes Pallas@lourdespallas.mkt

    nocodedude
    nocodedudeUp-and-comer

    Enable Second-Level Granularity in Conditional FiltersNew

    Hi ManyChat team and fellow builders,I’d like to propose adding second-level filtering in Conditional blocks (and anywhere we compare timestamps). Right now the smallest time unit we can work with is one minute. For most automations that’s fine, but when you’re trying to build responsive, conversational experiences it becomes a real bottleneck.Why seconds matter Smart Delay + Conditional check loops A common pattern is: set a short Smart Delay, check the last user message time, decide whether to bundle new input or push a follow-up. With minute-only precision we’re forced to wait at least 60 seconds before the Condition can evaluate, which feels like an eternity in live chat. Message grouping & spam prevention Many builders try to merge multiple quick user replies into a single logical block, or throttle highly active users so we don’t spam agents. We currently can’t distinguish someone who answered 3 s ago from someone who answered 58 s ago. Proposed change Allow seconds as a valid unit anywhere we compare or add time (e.g., {{last_input}} is less than 15 seconds ago). If UI clutter is a concern, hide “seconds” behind an “Advanced” toggle—builders who need it will find it. Impact Faster user experience → conversations feel natural, which improves retention and conversion. Cleaner flows → no more hacky work-arounds (multiple branches, external APIs, or unnecessary tags). Competitive edge → other bot platforms already allow sub-minute delays; adding this keeps ManyChat best-in-class. If you’ve run into the same limitation—or have ideas on implementation—please add your voice below. The more real-world examples we share, the easier it’ll be for the product team to prioritize.Thanks for considering, and happy building! 🚀

    Vadim Ciobanu
    Vadim CiobanuSmooth talker

    Feature Suggestion for ManyChat: Tracking Last Live Chat Agent InputNew

    I appreciate the powerful automation tools ManyChat provides, especially the ability to access the last_user_input variable. This functionality enables seamless integration with external tools, such as an AI assistant, by transmitting the user's last message.However, in real-world scenarios, live chat agents frequently step into conversations between users and the chatbot. Currently, there is no built-in way to distinguish between messages sent by a bot and those sent by a live chat agent. This presents a challenge when integrating with AI assistants, as they may lose critical conversation context when automation resumes.Feature Request: I propose adding two new variables: last_agent_input – Capturing the last message sent by a live chat agent. last_agent_input_timestamp – Storing the date and time of the last message from a live chat agent. (requested also here  ) Benefits: Enhanced AI Training & Adaptation: AI assistants, such as GPT-based integrations, could learn from agent responses, which are often superior to bot-generated messages. This would help improve chatbot responses over time. Maintaining Conversation Context: When automation is paused while an agent handles a conversation, the AI assistant should still receive and process the agent’s messages. This ensures the AI retains full context once automation resumes. Seamless AI-Assisted Live Support: By forwarding agent messages to an AI assistant, businesses can refine responses, analyze customer interactions, and improve chatbot accuracy based on real human interactions. By implementing these variables, ManyChat would empower users to build smarter, more context-aware AI integrations, ultimately improving the quality of automated conversations.Thank you for considering this feature request. I believe it would be a valuable addition to ManyChat’s capabilities, helping businesses provide a more seamless and intelligent customer experience.