Feature Request

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.

Business problem: As a user, I want the option to decide whether an Instagram Story reply opens a new conversation in my inbox, so that I can focus on leads coming from Story replies only during active campaigns. Desired outcome: Control inbox behavior for Story replies Filter and prioritize conversations from campaign-specific Stories Reduce noise from non-campaign interactions Use Cases: Only open new chats from Story replies during a product launch Ignore Story replies outside of active lead-gen campaigns The current workaround: N/A

Business Problem: Digital marketing teams running Google Ads face challenges connecting ad performance directly to messaging outcomes. While Google Ads supports Click-to-WhatsApp CTAs, attribution is unreliable because WhatsApp does not allow referrer tracking. Without proper attribution, businesses cannot measure ROI accurately, optimize campaigns, or connect Google Ads conversions to lifecycle reporting. Desired Outcome: Provide clear source and campaign attribution for leads entering via Google Ads Click-to-WhatsApp campaigns. Surface Google Ads campaign performance in lifecycle reporting alongside other marketing channels. Use Cases: A retail business runs Google Ads campaigns with Click-to-WhatsApp buttons. Each incoming lead is automatically tagged with campaign source for accurate ROI measurement. A company wants to optimize ad spend by sending conversion goals (e.g., qualified leads, closed deals) back to Google Ads for smarter bidding. Marketing teams can view Google Ads contribution directly in lifecycle reports

Business Problem: AI Agents can perform follow-up actions when instructed, but users have no clear way to see when a follow-up has been scheduled or executed. The only current method is to manually watch the conversation and infer the action from the messages, which is unreliable and time-consuming. This lack of visibility makes it harder for users to audit the AI Agent’s behavior and trust its automation. Desired Outcome: Provide a clear, visible indicator that shows when an AI Agent has scheduled or carries out a follow-up action, giving users immediate clarity and confidence during verification or review.

Business Problem Currently, AI Agent doesn’t understand a contact’s channel source (e.g., TikTok Ads, Messenger, Instagram Story, CTC ads) or channel events (e.g., CTA button clicks, story replies, in-app actions). As a result, the AI Agent can’t: Route leads accurately based on where they came from. Respond contextually when customers take in-channel actions. For example, when someone clicks an ad or replies to a story, the AI Agent starts fresh with generic greetings and questions — creating friction and increasing drop-offs. Desired Outcome Enable the AI Agent to understand and act on channel sources and events — for example, by reading campaign or ad metadata (like ID or name). This would let it: Auto-route leads to the right agents Deliver real-time, context-aware responses the moment users interact — skipping generic greetings and jumping straight into what they care about.

Currently, users can send text, emoji, and tag users in the internal comment. It will be good if the internal comment support sends files as well so that the team can share files or documents with each other to facilitate communication. The current workaround to send images in a comment is by copying and pasting the image’s URL into the comment.

Business Problem: Our current Growth Widget lacks the ability to track the specific page or CTA button that leads customers to initiate conversations. This limitation prevents us from fully understanding how users interact with our site before engaging on conversation, thus missing out on crucial data that could inform better marketing and support strategies. Desired Outcome: Implement a feature within the Growth Widget that captures and reports the exact source of user engagement—be it a specific webpage or a CTA button. This data will enable us to tailor our user experience more effectively, improve customer support, and refine our marketing efforts based on precise customer journey analytics.

Business Problem: Currently, the AI Agent does not have the ability to check whether a user (agent) is online before assigning a contact. As a result, contacts may be routed to offline agents, leading to delays in responses and a poor customer experience. Desired Outcome: Enhance the AI Agent’s Assign to Agent or Assign to Team action so that it verifies agent availability first. The AI should: Detect whether the target agent/team members are online and available. If the chosen agent is offline, automatically assign the contact to another available agent within the team. Optionally, allow businesses to configure fallback behavior (e.g., queue until online, assign to backup team).

Business problem: As a user, I want IVR and call queuing capabilities for calls so that I can efficiently manage and direct incoming customer inquiries, reducing wait times and improving customer satisfaction. Desired outcome: Interactive Voice Response (IVR) for automated call routing. Call queuing system with customizable hold messages. Reporting on call queue metrics. Use Cases: Directing customers to the appropriate department automatically. Managing high call volumes effectively. The current workaround: N/A

Business Problem: Currently, contacts in HubSpot and respond.io are automatically matched based on predefined criteria (email or phone number), but users have no way to manually link or unlink a contact when necessary. This lack of manual control leads to: Incorrect contact associations, especially in cases where duplicate contacts exist. Limited flexibility, as users cannot override or adjust mappings between contacts in HubSpot and respond.io . Desired Outcome: Manual Linking Option: Allow users to manually associate a respond.io contact with a HubSpot contact if the automatic match is incorrect or missing. Manual Unlinking Option: Enable users to unlink a contact from HubSpot in case the association is no longer relevant or was made in error. Use Cases: Fixing Incorrect Matches: A contact is linked to the wrong HubSpot contact. Current Workaround: Modify the contact details to force an automatic rematch.