Conversation-Studio

customer channels

Customer Channels

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customer channels

Conversation Studio

Design and run any sequence of in- and outbound customer interactions with Expertflow's Conversation Studio. Open APIs empower you to seamlessly integrate third-party components, bridging gaps and customizing solutions to perfectly fit your requirements.

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Build your own Conversation Flow

Create multi-channel conversations such as 

  • visual IVR by adding chat to an IVR session
  • post collaboration survey via SMS after a voice call
  • Escalate a chat or email session to a voice call to a customer’s mobile phone or video call via WebRTC
  • Create outbound campaigns with multiple attempts at the right time and across multiple channels and view progress in consolidated reporting.
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IVR Call Deflection and Visual IVR

Interactive voice response (IVR) deflection allows your customers who are waiting for an agent to be served faster via a chat channel such as SMS or Whatsapp. Chat channels can be easily automated and AI-enhanced agents can handle multiple conversations at the same time, thereby reducing the cost and waiting time.

See also: Visual IVR with  Hybridchat

Visual IVR

During a phone conversation either the customer or the agent can transfer the call to a Visual IVR(Interactive Voice Response).

Combining voice with chat, Visual IVR allows you to enrich conversations with text, hyperlinks and images. Choosing options from a visual menu is faster than listening through lengthy menus, improving the customer experience. Furthermore, chatbots can speed up response time and free up agent capacity.

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Outbound campaigns

Run agent or agentless campaigns (IVR/ SMS/ Chat / Email), and surveys. Define in the Conversation Studio which clients to reach in what sequence and over which channels (chat, voice, email), by humans or by bots.

For example, you can design your campaign to start with an email to the customer informing them of the upcoming call and allowing them to choose a date that works best for them.

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Further features we provide for Outbound Campaigns include predictive dialing, insert an IVR to jump in when the customer picks up before the agent is ready, and call progress analysis (CPA) to optimize the handover to an agent.

Store interaction data, and trigger agent-based or anonymous surveys and questionnaires.

Agent skill group and Skill Based Routing

Select agents of a skill group to participate in a campaign (agent reservation), or use skill based routing to achieve the best possible matching of agents with individual interests of your customers.

Callback

Your customer can request a callback while maintaining their position in the queue

Offer callback or chatback to your clients when your team is unavailable due to traffic load or opening hours. Provide for courtesy callback (clients maintain their queuing position) or callbacks at scheduled times

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A glance at the technical architecture of our conversation designer

Expertflow Conversation Control is based on a few central elements:

  • The EF SIP proxy allows EFCX to take over control of incoming calls at the earliest possible time.
  • The EF Media server provides a bidirectional audio channel to clients and can serve as a voice input during an IVR or a gateway to integrate third party AI-based voice bots such as voice transcription.
  • The conversation meta data bus shares real-time data between the parties (customer, bots, agents, supervisors) that are part of a conversation. This can be individual activities (a spoken sentence, chat message, geolocation, translation, voice biometrics, answer suggestions,...), key-value pair Conversation Data (customer profile, call tags) and forms.
  • Various Ai engines that can be integrated become part of the conversation control and can be programmed to act at any point in time during the conversation. For example, to implement transcription, the media server would create a unidirectional SIPREC connection to an ai bot which then receives the voice stream. The output of the AI engine (text) would go to the conversation metadata bus and from there it can be displayed on the agent desk and written into the transcript. AI engines can be from standard 3rd party providers or also Open Source components.
  • Various static and also real-time information relating to the conversation is made available on the agent desktop. Which information is visible can be controlled at any point in time during the conversation, provided that the agent has the access rights for a particular data.
  • 3rd Party components, such as Cisco CUBE
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