Experience Optimization: A Journey in Conversational AI

Experience Optimization (XO) is what the future holds for driving enterprise engagement, productivity and innovation for any interaction, external or internal.

Request a Demo

Start with business objectives

Say, speeding your service-delivery model, applying smart deflection mechanisms and streamlining workflows to improve interaction experiences while reducing support costs.

Making this innovative technology work to your competitive advantage and achieving your business KPIs, think of it as an ongoing journey and not a quick fix or short-term initiative.

Drive automation, inside-out

Undertaking this journey enables enterprises to create AI-powered virtual assistants and process assistant solutions that automate business interactions and enhance customer and employee experience. Become a market leader by driving such inside-out efficiencies that affect the topline as well as bottom-line.

Planning the Journey

Effective planning is key to achieving success with conversational AI. Enterprises need to craft an objective plan, find the right technology portfolio and tools and empower a team to execute that plan. Here are some tips for planning your journey:

Build internal partnerships

Coordinate and leverage internal teams effectively. Have the business arm focus on leveraging competitive advantages while tracking time and budget constraints. Allow the IT arm to focus on finding the right platform and overcoming integration and compliance challenges

Assess current capabilities

Learn how the use of language technologies has evolved in your organization. Inventory relevant knowledge bases and data sources. Assess internal resources, such as language experts and analysts, to determine if you require outside help. Test backend systems (like RPA) for interoperability and scalability

Create a conversation team

Consider roles such as a LOB leader for guidance and funding; project lead for management; analysts to provide guidance on personality, language and workflows; data scientists to create ML models; and developers to build and integrate the solution

Define and collect right metrics

Set realistic KPIs for each project stage, such as % increase in call containment, CSAT and NPS. Harvest data from customer reps for chat transcripts; question input tools for common queries; and interviews for insight into customer expectations and language

Drive trial and preference

Select the most compelling use case for your POC (well documented, high volume and repetitive). Focus on driving preference and mindshare with potential evangelists. Continually highlight the importance and value of conversational AI for customers and employee experiences alike

Preparation is key to achieving success in the conversational era.

A Practitioner’s Guide To Deploying Conversational AI

Every virtual assistant journey is unique, based on the industry, organizational maturity, strategic priorities, budget constraints and more. Timelines are also unique, varying by specific use cases, integration and workflow complexities, available resources, compliance and change management requirements. We have identified the following five phases as an inevitable part of every successful conversational AI journey.

Plan

Plan your first digital (email, chat) or voice virtual assistant

Identify the use case
Develop user personas
Document user journeys and pain points
Identify workflows to map tasks
Evaluate and select channels
Storyboard dialog flows

Proof of Concept (POC)

Explore primary and secondary use cases, map out key requirements, determine which vendors and partners are required

Define functionality and implementation
Create virtual assistant interactions blueprint
Design and build your first virtual assistant (typically 30-45 days)
Alternatively, choose a pre-built, scalable solution
Arrange test data/conversations/flows
Train and test internally, tune models
Get ready for deployment

Pilot

Roll out additional tasks and dialog flows to a similar cohort of users

Provide key stakeholders time for testing
Instruct users to try to “break” the virtual assistant
Collect qualitative and quantitative learning
Rollout for a limited set of users in production
Tune as required

Ramp up

This step involves deploying your conversational agent, promoting it to your intended audience and establishing best practices for change management. The primary focus includes:

Ongoing management and optimization
Identifying additional workflows to target
Qualifying new channels and use cases
Continuing to grow internal expertise
Showcasing early impacts on the company

Institutionalize

The final step is all about establishing conversational AI as a baseline competitive advantage within the company. At a glance, key activities include: