Feature Request

The official WhatsApp API currently doesn't support Group Chats. Other platforms supporting WhatsApp Groups use unofficial APIs that often break. We will consider building this feature once it is released officially for WhatsApp API. 🔴 Important Note : This is NOT a limitation on respond.io . This is a limitation set by Facebook's team to all WhatsApp API accounts.

Business Problem: Our platform currently lacks a personalized product recommendation feature. This absence limits our ability to guide customers towards products that best suit their needs and preferences, potentially leading to missed sales opportunities and reduced customer satisfaction. Desired Outcome: Implement a new AI Agent objective that suggest relevant products based on Contact's conversation. This objective should improve user experience by offering tailored suggestions, increasing the likelihood of purchases, enhancing customer engagement and able to capturing intent after recommending products. Use case (Convert): This feature clearly shines in the Convert phase. You're already engaging the customer—they’ve reached out or responded—and now it's time to seal the deal. The AI doesn’t just inform; it persuades. It uses the context of the chat to: Recognize buying signals Suggest products that align with the customer’s use case Help the customer make a confident, informed buying decision So, you're not just solving for engagement—you’re solving for revenue.

Business Problem: The platform currently lacks the ability to trigger workflows based on keywords or phrases within contact messages, limiting automation capabilities. Desired Outcome: Enable triggers to start workflows based on the contact's messages containing specific keywords or phrases, ensuring it also applies to open conversations. Use Cases: Keyword/Phrase-Based Triggers: Enable workflows to be triggered based on specific keywords or phrases in messages, such as automatically sending predefined responses based on certain keywords. Workaround: Filter by incoming message using the Branch step. https://help.respond.io/l/en/broadcasts/workflow-based-on-broadcast-response

Business Problem: As a sales agent using Respond, I want to see the correct contact name when a Contact is created via an echo message (a message sent from the WhatsApp Business App), so I don’t have to rely on the generic name. Currently, contacts created this way display a generic name instead of the actual contact’s name, making it harder to engage personally and efficiently. Desired Outcome: Auto-create the contact with the actual name when the contact is created via an outgoing message from the WhatsApp Business App Current Workaround: Manually ask the customer for their name or check WhatsApp Business App, then update the contact info manually. Important Note: This is a known limitation due to Meta’s platform policy. We are actively working with Meta to explore solutions and will update this request if the policy changes or alternatives become available.

Business Problem: When a business connects their WhatsApp Business App (WABA) to the WhatsApp Cloud API, existing conversations are not imported into the new environment. This creates a disjointed experience for users who expect to see their past chats, leading to confusion, loss of context, and operational inefficiencies for support and sales teams. Desired Outcome: Allow import of existing conversation history from the WhatsApp Business App when transitioning to the Cloud API, allowing users to continue conversations seamlessly without losing prior message context.

I would like to be able to delete or edit a message that I sent by mistake on the Messages module, and for it to also be removed for edited rom the recipient's device. 🔴 Important Note: This is NOT a limitation on respond.io . This is a limitation set by Facebook's team to all WhatsApp API accounts.

Business Problem: Currently, respond.io supports integration with platforms like Zapier and Integromat, but there is no direct integration with n8n.cloud ( n8n.io ). Many businesses prefer n8n due to its lower costs and flexible workflow automation capabilities. Without a native integration, users must rely on workarounds or custom scripts, making automation more complex. Desired Outcome: Enable integration with n8n.cloud ( n8n.io ) to allow seamless automation of workflows. If a full integration is not immediately possible, ensuring that webhook support is available would already help users connect respond.io with n8n efficiently.

Business Problem There are businesses that are using customer built CRMs, niche CRMs, CRMs that don't have native integration with respond io or email platforms like outlook. A very common interaction that employees is to find the contact in respond io then review the conversation, chat with the customer or call the customer. Doing this manually is time consuming and difficult, while building a custom integration would involve developers and management approval. Proposed Solution A Chrome Extension or similar that would be able to provide a shortcut for a user in another platform or on the web to get to the contact in respond io. Hubspot Chrome Extension is an example of this: https://chromewebstore.google.com/detail/hubspot-sales/oiiaigjnkhngdbnoookogelabohpglmd?hl=en

Business Problem: Currently, agent availability must be managed manually, which makes it difficult to plan ahead for shift coverage—especially for businesses that operate 24/7 or have rotating schedules. This results in missed handovers, delayed responses, and inefficient workload distribution. Desired Outcome: Enable a built-in calendar or scheduling feature that allows admins or managers to define agents’ availability in advance (weekly or monthly). Based on the schedule, the platform should automatically: Mark agents as available/unavailable. Trigger relevant automation (e.g. shift-based routing or task reassignment). Use Cases: Customer support teams with rotating shifts (e.g. morning, evening, overnight). Service businesses operating in multiple time zones. Automatically adjust assignment logic based on agent availability without manual intervention.

Business Problem: Currently, Respond AI only supports text data as input for its knowledge source. This limits its ability to generate accurate and helpful responses in scenarios where essential information is provided in image formats—such as product photos, or visual instructions. Without image support, our AI Assist and AI Agent features cannot reference or reason over visual content, leading to incomplete responses and reduced automation potential in image-heavy workflows. Desired Outcome: Enable Respond AI to process and utilize image data uploaded to the knowledge source. The system should be able to extract and index relevant information from images and make that information accessible to both AI Assist and AI Agent for generating contextually rich responses. This enhancement will extend Respond AI’s capabilities beyond text and support more use cases.