Customer service is becoming the epicenter of transformation. Enterprises learn better to connect to customers with self service strategies. Conversational user interfaces add a dimension of simplicity to self service. Digital assistants (chat bots) are an important element of service for the reason that we can leverage a set of pre trained models. Conversations have the inherent benefit of remembering the past and as a result help users to connect to the future. Almost all of our leading analysts predict more than 50% of users will migrate to the newer avenues. They also acknowledge the booming adoption of new conversational devices and wider acceptance of the new mode of experience. Customer experience by conversations has a wider set of considerations when it comes to implementation.
One of the benefits of conversational approaches are the ability to be on any channels – omni conversations become a day-one design consideration. Furthermore conversations get designed to enable omni-channel and multi-modal experiences. Context became the key element that helps to understand the user better and for the reason that it can suggest hyper-personalized approaches. As result the element of trust is higher in these kinds of interactions and above all the context gets built on what is being discussed. This is even more encouraging than the approach of what is being discovered while transactions are being made in a typical application/ browser experience.
Personalized approaches are faster with conversations. Every conversation helps us understand the personality of the customer. Every transactions of the person can be used to analyze and hence understand how close the person is getting to the brand. As a result this enables businesses to devise crisper strategies for customers.
The Design consideration
Most of the conversational eco systems follow a similar design approach. The typical approach is to slice the conversations into components. As a result we modularize conversations and build the conversational tree. Some of these components are
- Invocation – The starting point
- Events – The trigger
- Intents – The mapping of what user says to action
- Utterance -What the user says
- Entities – The data model extracted
- Contexts – The data model that can be remembered as context
- Slots- An alternate way to look at entities
- Actions – The outcome of a conversation that builds a response
- Fulfillment – The cloud functional model that aggregates the response
- Dialogue Model – The scenarios of a linear or a non linear dialogue model
All leading players like Google, Amazon, IBM , Microsoft have varying proportions around these capabilities for a conversation design. As a result there are various orchestrations binding some or many of the above elements that design a conversation. These platforms and capabilities for conversations are the basic platform enablers , the tip of iceberg. Furthermore the real customer experience in an enterprise context achieved by conversations has many many more dimensions beyond these very basic design elements.
The CX Centric Conversational Design
Customer experience needs elements for understanding and predicting customers. Hence it is essential to have CX designs beyond the platform capability orchestration. The top most elements of CX Centric conversational design are
- Multi modal experience design – The ability to seamlessly complement a conversation with other touchpoints (Mobile/Web)
- Omni conversation capability – The ability to pause and resume at any other touchpoint
- Conversation personalization – The ability to learn the use from history , from the conversation and create personalized responses
- Context aggregation and selection – The ability to accumulate the user contexts and traits that can aid for a future recommendation
- Digital engagement platform bidirectional binding – The ability to tightly couple with a CX Platform workflow ( Eg : CRM sales workflow ) and create a new value added experience
Conversations could simultaneously exist across the traditional applications and the new interfaces. As a result intermodal experiences of a connected device (like a smartphone) working seamlessly as part of the conversation . This will enable supplement additional data for the workflow which will circumvent most of the limitations of a conversational channels. Building a bot that sounds like a machine is not a conversational design. Two levels of personalization exists; the content and the rendering. Either of these will change with the mode – the chat , the voice, the device. While the conversation platform learns the context of the user (user and the traits) , the enterprise context of the user ( user in an enterprise) that helps solve a business problem, is a different aspect . An experience context engine empowers use cases with the enterprise context . The foundation layer is still the digital engagement (CX) platform ( Content management, Digital marketing, Commerce , CRM Sales – service , Business process management systems etc ) which forms the core engagement workflow engine. A bidirectional tight coupling of the conversational eco system to enrich the core workflow of the digital engagement platform governs the success of the implementation.
We see a wide range of use cases in digital customer experience domains where conversations are disrupting the way businesses are engaging with customers.
Some of the key scenarios are;
- Simplified B2C engagements with a whole new level of assistance
- Self-service scenarios
- Trouble ticket management
- Travel experiences
- Concierges applications
- Empowering productivity applications with individualized micro workflows
- CRM Sales force automations
- Field audit and inspections
- Field service and work order automations
- Request and approval applications
- Life cycle engineering applications
- Adding the power of context to digital commerce to have purposeful interactions
- B2C Omni-channel conversational enhancements
- B2B commerce workflow acceleration
- Conversations with product lookups, loyalty details etc.
- Employee concierges by conversations with quick productive approaches
- Payroll, leave, profile management
- Travel and claims management
- Performance management
- Dealer acceleration with enhanced customer experience by conversations adding value to brand experience
- Quote management
- Audit and compliance
- Stock and Inventory management
- Talking catalogs triggering a conversation anywhere anytime
- Coupling customer assistance workflows in marketing catalogs
- Service catalogs with assist experiences
Conversational interfaces and gaining wider acceptance because it’s ability to be designed faster and simpler. However under the simpler model there can be complex digital ecosystems that power the bots. We will see more capabilities and usecases added to the conversation channels in coming days .