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 an agent on the go, I want to handle support Channel calls such as WhatsApp, Messenger, etc. directly from the mobile app, so that I can provide seamless customer service without being tied to a desktop. Desired outcome: Allow agents to initiate and receive calls via the mobile app. Use Cases: Agents resolving customer issues while traveling. Field agents managing customer calls during site visits. The current workaround: N/A

Business Problem: Teams cannot easily identify patterns, bottlenecks, or high-performing stages, limiting their ability to optimize the customer journey. The absence of advanced tools like a Sankey diagrams or conversion matrices means businesses struggle to gain a comprehensive view of lifecycle dynamics, impacting their ability to improve conversion rates and reduce drop-offs. Desired Outcome: Introduce advanced lifecycle analysis reports with the following features: Sankey Diagrams: Visualize customer flow across lifecycle stages and highlight where drop-offs occur or identify stages with the highest retention. Conversion Matrix Table: Display stage-to-stage transition rates in a matrix format that provide clear metrics on movement between specific stages (e.g., Lead → Opportunity → Customer). These reports can include metrics such as: Stage Conversion Rates: How effectively contacts move between stages. Drop-Off Rates: The percentage of contacts lost at each stage. Average Time Spent per Stage: Insights into delays in the pipeline. Stage Re-Entry Rates: Track customers who re-enter a previous stage. Lifecycle Trend Analysis: Track historical lifecycle data to identify seasonal trends or long-term changes in customer behavior.

It helps the agents automatically close the conversation after 30 minutes duration. It enables the agent to save extra time a lot.

Business Problem: Currently, contact information between respond.io and Salesforce does not sync bidirectionally. Changes made in one platform do not automatically reflect in the other, leading to: Data inconsistency, where outdated or mismatched contact details exist across platforms Desired Outcome: Configurable Contact Sync: Allow users to define how contact data syncs between respond.io and Salesforce: One-way sync (Salesforce → respond.io ): Changes made in Salesforce are reflected in respond.io One-way sync ( respond.io → Salesforce): Updates in respond.io are pushed to Salesforce Two-way sync: Changes made in either system update the other automatically. Use Cases: Seamless Updates: A sales rep updates a contact's lead status in Salesforce, and the change is instantly reflected in respond.io . Current Workaround: At present, users must: Manually update contact details in both respond.io and Salesforce. Use third-party automation tools like Zapier or Make.com to sync

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, AI Agent and AI Assist occasionally fail to retrieve accurate information from knowledge sources, even when the information exists. These challenges arise due to: Knowledge Source Formatting: Improperly formatted sources may lead to retrieval errors. Users can follow guidelines here to improve formatting. Non-English Knowledge Sources: Information in languages other than English is not consistently handled by the system. In some cases, the AI may still fail to retrieve accurate information despite correct formatting and content due to technical limitations inherent to AI technology. Desired Outcome: Enhance the knowledge source retrieval system to address these two core issues: Improve AI handling of non-English knowledge sources. Mitigate dependency on perfect formatting by refining retrieval methods. This enhancement would lead to higher accuracy and reliability in AI Agent and AI Assist responses, reducing errors and improving user satisfaction.

Business Problem: As a manager, I want call transcription capabilities, so that I can have accurate, searchable records of conversations for reference and training purposes. Desired Outcome: Real-time transcription during calls. Accurate, formatted transcripts available immediately after calls. Use Cases: Record keeping for client interactions. Generating transcript archives for team collaboration. The Current Workaround: N/A

Business Problem: As a respond.io user, I want to browse and select pre-approved WhatsApp Message Templates from Meta’s Template Library, so that I can quickly use ready-made templates without needing to create or submit my own. Desired Outcome: Enable users to access Meta’s pre-approved WhatsApp Template Library within respond.io . Allow users to search, preview, and select templates from the library before sending. Reduce the need for businesses to manually create and submit their own templates, saving time and effort. Use Cases: A small business owner quickly selecting a WhatsApp template from Meta’s library to send a payment reminder without needing to create a new template. A support agent using a pre-approved customer service template to respond faster without waiting for template approval. Current Workaround: You can create templates from the Template Library via Meta's WhatsApp Manager, and those templates will automatically appear in respond.io

Business Problem: As a first-point-of-contact agent, I want call transfer capabilities, so that I can quickly route calls to the appropriate team or individual, ensuring efficient handling of customer inquiries. Desired Outcome: Ability to transfer live calls seamlessly to another agent or department. Use Cases: Transferring a client to a sales representative for advanced queries. Transferring support calls to specialized teams during escalation. The Current Workaround: N/A