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.
Experience Optimization:
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:
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:
- Set up dedicated functions for monitoring
- Establish training routines
- Analyze key metrics regularly
- Target new use cases and agents
- Continue to promote and evangelize
