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6 UX Characteristics of a Great Virtual Agent

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A virtual agent is an excellent way to elevate your company’s customer experience. However, if a virtual agent does not have the basic traits needed for success, it can do more harm than good. 

Our team performs chatbot UX audits regularly and uses our standard 6 point review process to ensure every bot has the best user experience possible.

1. Discoverable

A virtual agent needs to be easy to find for your customers. Some criteria for ideal virtual agent placement include:

  • Funnel and webpage traffic: Does the virtual agent direct your customers where you want them to go?
  • Virtual agent purpose and topic coverage: Is the virtual agent on the social media platform or website page that best aligns with its capabilities? 
  • Reactive and proactive virtual agent: Does the widget for the virtual agent appear at the right time in the customer journey? 
  • The right channel(s): Is your virtual agent where your customers are?
  • Leverage usability testing to make data-informed decisions: Is the channel or website page the virtual agent is located on aligned with customer needs and data?

2. Distinctive

A virtual agent needs to have a clear identity and personality that aligns with the brand it represents.

  • Perception: Customers will draw perceived personality traits from your virtual agent, whether you design for it or not. Be intentional about your virtual agent’s personality so that it can produce the best results for your company.
  • Connection: Customers find it hard to connect with a ‘lifeless’ design, product, or code. The right persona will trigger an emotional connection to the virtual agent and acts as a competitive differentiator.
  • Higher adoption rate: A virtual agent’s personality is a key driver of customer engagement and adoption.
  • Human behaviour: Customers prefer the virtual agent interface to behave like a human.

3. Useful

A virtual agent needs to fulfill customer needs.

  • Resolution time: A virtual agent is only useful to customers if it can efficiently and effectively resolve user issues. 
  • NLU design: Enhanced NLU design allows a virtual agent to capture user intent and specific details to avoid asking users for information already provided. 
  • Transactional: Users want to be able to complete actions in the virtual agent environment. Users often find self-serve FAQ’s to be the biggest challenge with conversational agents.

4. Useable

A virtual agent needs to be both intuitive and easy to use.

  • Informative greeting: Clarify the virtual agent’s abilities in its greeting to the customer. The greeting should be clear about the virtual agent’s purpose and scope, i.e. problems it can solve, ability to redirect to relevant content or agent, etc.
  • Menu options: Menus should be clear and have a flow that includes sub-options when applicable. 
  • Defining usability: Discerning if users know what to say or do at each interaction turn helps ascertain usability.
  • Make data-informed choices: Analytics on abandonment and confusion rates at specific points highlight potential design improvements.

5. Credible

A virtual agent needs to be easy to understand, and trustworthy enough that users trust it with their queries and secure information.

  • Incorrect redirection: If a virtual agent often misunderstands customer queries and redirects them to the wrong place, users will not trust it to solve their problems.  
  • Technical ‘bugs’: If the virtual agent often expresses incomprehension when a customer follows prompts, such as clicking on menu buttons, users will lose trust in it.
  • Broken links: A virtual agent should never redirect a customer to a broken link.
  • Secure information: A virtual agent that collects secure information from customers should ensure that the user is aware their information is protected.

6. Valuable

A virtual agent needs to provide value to the customer using it, and engage them in a personalized manner.

  • Value addition: The value of a virtual agent is derived from optimizing customer engagement and NLU performance.
  • Leveraging virtual agent “memory”: Storing data points that were previously shared by users, rather than asking for those details again, greatly enhances the value of a virtual agent.
  • Understanding customer needs: Training a virtual agent to recognize the true intentions behind the many ways customers express their needs is critical for successful implementation and maintenance.
  • Knowing the customers: To meet customer needs, it’s important to steer away from “generic” responses, and offer a more personalized experience by leveraging customer data, past conversations, etc.

Let’s supercharge your virtual agent together, contact us today.

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Data Scientist

As a Data Scientist, your day-to-day will involve writing queries, building dashboards, and preparing analytical reports about product performance for our clients and the Wysdom.AI team.  You will work with SQL, Tableau, and Python and ML Frameworks/libraries (among other tools) to create stunning visuals showing how Wysdom.AI is making their customers’ experience even better.

Implementation Engineer

As an Implementation Engineer you will be responsible for the solution integration of an enterprise grade conversational AI experience from a technical perspective. You will work closely with the lead solutions architect and be the technical face of the implementation team and lead the customer through the entire implementation cycle. You will work with one of the most diverse teams of linguists, data scientists, and innovators to deliver the best AI enabled customer experience.

Solution Architect

As a Solutions Architect within the Client Services team, you act as trusted advisor, responsible for the technical requirements and end to end solutions integration of Wysdom cognitive services within the client’s environment.  You will work with one of the most diverse teams of linguists, data scientists, and innovators to deliver the best AI enabled customer experience.

Cognitive Data Specialist

As a Cognitive Data Specialist, you will be responsible for the performance of the AI and quality of the corpus and will focus primarily on the VA training.  You will work with the client as required to ensure corpus is performing in an optimal manner.

Conversational Experience Designer

As a Conversational Experience Designer, you will be responsible for the designs of the overall customer experience, including the end-to-end dialog flows & journeys of the solution ensuring  design leverages  UxD best practices for optimal customer experience.

Conversational AI Specialist

As a Conversational AI Optimization Specialist, your responsibility will be to help drive the success of our solution for our clients. This involves building conversation flows, performing AI training, and partnering with clients to enhance their deployments.

Conversational AI Lead

As a Conversational AI Lead, you will be responsible for leading all Conversational AI program activities.  You will work with all team members to ensure deliverables are completed on time, with high quality and exceeds client expectations and goals.

Program Director

Responsible for the overall success for the client, including the end-to-end delivery and optimization of the solution, you will manage the sales process from pillar to post, including technical and commercial proposals, pipeline management, sales forecasting, and contractual documentation.

David Trotter, Wysdom

David Trotter

SVP, Sales & Marketing

David has 30 years of global sales leadership experience as a collaborative leader who believes in a strong team concept within sales and marketing organizations. David has spent many years working with growth companies and enjoys being face to face with customers and partners to create solutions that have a lasting effect on the customer’s business environment. 

Prior to joining Wysdom, David was the Vice President, Sales at Scalepad, and previously spent 11 years as Vice President for Latin America and Asia Pacific for Absolute Software. He also held senior sales management positions at GE Capital and Clevest.  

Michel Benitah

VP, Optimization & Delivery

Michel has 20 years of experience in leading the successful delivery of Conversational AI and Natural Language Customer Care solutions to some of the largest financial, telco, healthcare, utilities, and retail enterprises throughout North America. 


Prior to joining Wysdom, Michel spent 20 years at Nuance Communications, holding senior management and leadership positions within the enterprise division, most recently as director of the Toronto office and professional services team.

Frederic Lam

SVP, Sales

Fred brings in 25 years of international experience in sales and business development across North America, the Caribbean, Asia-Pacific, Europe, and the Middle-East.


Prior to Wysdom.AI, he held sales leadership positions at Oracle, Redknee, and Movius/Glenayre, successfully growing revenues in both large and small organizations. Fred has also been involved in the start-up community in the earlier stages of his career as an Investment Manager with SP Capital and was an alternate director on a few investee companies.

Karen Chan

Chief Engineering Officer, Co-Founder

With 20 years of experience in software and mobile, Karen has held senior technical roles at 5 startups, including Wysdom.AI, Clickfree, Mobile Diagnostix (HP), Teamatic, and Virtualthere.

Karthik Balakrishnan

Chief Technology Officer

Karthik has over a decade of hands-on, proven global expertise in emerging technologies and implementing intricate platforms and solutions for telecommunications and enterprise during his time at Amdocs, with senior positions in their India, Cyprus, America, and Canada offices.

Nitin Singhal

Chief Operating Officer

Nitin has over 20 years of success in global executions of business technology, driving operational efficiency and digital scalability for some of the world’s largest enterprise clients. 


Nitin spent 16 years at Redknee holding executive positions in Research and Development, Customer Operations, Partner Alliances, and most recently as COO.

Jeff Brunet​

President, Co-Founder

Jeff has more than 20 years of experience in the startup world, founding and growing 4 software companies: AracNet, Mobile Diagnostix (HP), ClickFree, and Wysdom.AI. 


His in-depth understanding of software development and the challenges in making new technologies successful in the startup world prove invaluable as he serves on the boards of XMG, SurfEasy (Opera), Locationary (Apple), Groupie, and as an advisor to Pushlife (Google), LogMeIn (IPO) and HP. 


Jeff holds 23 issued patents in the wireless and consumer electronics spaces and is the lead inventor on 30+ pending patents.

Ian Collins​

CEO, Co-Founder

Ian has founded and grown 6 technology companies over the past 20 years, primarily in the enterprise software space including Wyrex, Mobile Diagnostix (HP), Clickfree, and most recently Wysdom.AI. 


Ian invests, mentors, and sits on the boards of several startups in the Toronto area.