WestJet Takes the Flying Experience Up a Notch with AI

Written by Emily Cummins  on   Aug 27, 2018

AI is the interface to meet (and exceed) consumer expectations for innovative, convenient and personal support. With the new WestJet online chat support system, Canadian travelers will be able to experience that innovation, convenience, and personalization all in one place.

In the most sophisticated example of an airline AI and the first from a Canadian airline, travelers can now engage with Juliet, WestJet’s new travel chatbot AI on Facebook Messenger. Juliet acts as a single touchpoint for the traveler across pre-booking, booking, day of travel and support, offering a highly immersive and meaningful experience that alleviates many pain-points of traveling today.

Developed in partnership with Netomi, a chatbot vendor, the highly immersive WestJet chat support experience includes:

  • Day-of travel support: Guests access real-time information on flight status, baggage, and a variety of frequently asked questions.
  • Information and resolution: Guests receive instantaneous information and quick resolution on many topics, ranging from in-flight entertainment to traveling with pets. Chatbot tools can elevate specific guest scenarios, for example, missed flights or rebooking, to WestJet agents.
  • Virtual travel concierge: Guests receive destination recommendations based on their personality, interests and vacation style and explore trip options through video content, images, and articles, as well as start the booking process.
  • Flight booking: Guests search available flights by city and dates.
  • Current deals and promotions: Guests receive real-time WestJet deals and promotions.

Discover the key questions to ask when scheduling a chatbot demo.


“Customers expect to be able to engage in an instant, personalized conversations with brands and AI enables companies to exceed these expectations,” said Puneet Mehta, Founder and CEO, Netomi. “With Juliet, WestJet is delivering its guests immediate, friendly and accurate support. WestJet had a lofty goal of bringing the guest journey to a conversational AI experience. What may have seemed futuristic even a year ago, is now a reality.”

To chat with Juliet, please visit https://www.messenger.com/t/westjet. To learn about how Netomi’s chatbot platform can help your company scale customer happiness with AI, request a demo today.

For more information, visit: The 9 Best Live Chat Software for Connecting in Real-Time.

Stranger than fiction: Reinventing Retail

Written by Puneet Mehta  on   Aug 27, 2018

Reinventing Retail CX with AI

Matt Gunn and Puneet Mehta of Netomi, a Silicon Valley startup focused on conversational AI, discuss how deep learning will shape the future of retail as consumers engage with brands (and their AI) to achieve more personalized, intimate shopping experiences.

Listen here.

To get more of our insights on our retail bot and customer service before you contact us to request a demo, check out:

Would You Trust an AI With Your Wallet?

Written by Puneet Mehta  on   Aug 23, 2018

Trust is having a moment. And for good reason.

The backlash Facebook is facing boils down to breaking the trust of consumers in how they protect their data. To rebuild consumer confidence, Facebook is turning to AI to solve their problems.

As AI is used more by brands to improve operations and decision-making, and even more so to interact with consumers on a daily basis, it is now more critical than ever to build a strong foundation of trust. The potential for AI is huge; in the near future, brands and individuals will be represented by an AI on the internet, and the only way for brands to reach their consumers will be to go through their AI. As this new AI era approaches, the trust threshold will remain fragile.

In 2015, when Sony Pictures launched “Slappy,” a conversational chatbot in support of the Goosebumps Movie, they saw astronomical engagement on Facebook Messenger: an average of 10 minutes per conversation, with some conversations lasting up to 2 hours. But the conversational AI was so good that some people thought they’d made an actual new friend. One user even invited Slappy to her chemotherapy appointment the next day.

This raises some serious ethical questions about how brands present their AI to their customers. Should your bot be upfront about being a bot or try to pass off as a human agent? Is it the customer’s responsibility to approach chat, voice or email interactions with caution? [For the record, I would recommend owning the fact that an AI is an AI].

In addition to how an AI is presented, trust in an AI is built (and broken) in many ways. As AI permeates more parts of the customer journey across marketing, sales and service, consumers will need to be able to trust your AI. 

How to get consumers to trust your AI

Trust an AI with your refined intent

Does the AI actually understand what the person is asking or trying to accomplish? If the AI is constantly getting confused, the person will not trust the AI customer support to help accomplish the task at hand and stop engaging.  AIs need to be able to understand the majority of what a person is communicating, including today’s digital slang (emojis, stickers). AIs also need to be built on a deep learning platform so it is constantly expanding its knowledge base, increasing the frequency of classifying intent correctly.

Trust an AI with your identity (piecemeal or not)

A person should never have to reintroduce themselves to an AI and rather all of the information they have revealed to the AI over the course of the relationship should help to drive relevance in future conversations. The AI should also connect to a brand’s CRM in order to personalize the interactions based on cross-channel profiles. However, in order to retain trust, always enable a person to opt-in for data sharing and storing.


Exploring a new CRM solution? Learn more about two of the industry leaders in our Intercom vs. Zendesk review.


Trust an AI with your wallet

AI will soon be the single channel for all brand and consumer activity, including purchases. Being able to trust the AI to store payment information will help to create a completely seamless commerce experience, greatly enhancing the customer experience. If a person doesn’t trust the brand to keep payment information secure, though, the magic of a single channel touchpoint will be lost. Clearly communicate how payment information is secure or stored if held by the brand or connect to a third-party like PayPal or Apple Pay.

Trust an AI with your emotions

If a friend tells a joke when you’re discussing something serious, you would probably grow frustrated or upset. Similarly, an AI needs to be able to read and react to a person’s sentiment and tone.  Beyond the text or spoken word, how is the person feeling? An AI can tap into this by looking at the conversation in its entirety, assigning a sentiment grade to every interaction in order to say the proper thing or send appropriate content. If an AI is a repeat offender of not understanding a person’s emotions (particularly on the poles, really happy / excited or really sad / mad), they might get fed up with the relationship.

Trust an AI to transfer context across AIs

Brands may soon have various AIs at work simultaneously managing different parts of the customer experience. There might be customer support AIs answering questions, AIs supporting human agents to reply quicker and more accurately, AIs that focus on guided selling and personal shopping, etc. AIs will be specialists. If, for instance, someone needs to return something she has ordered (with the personal shopping AI), she might need to be “transferred” to the customer support AI, who can help to facilitate the return.  If this “hand-off” occurs, the necessary information (like items, loyalty status, etc.) needs to be passed along, so the conversation isn’t starting from square one.

Today’s consumers are more comfortable with, and sometimes prefer, interacting with AI. There is no better way for brands to reinforce that positivity than by building trust. If trust is broken, it will be very hard to convince a person to give it another chance.

For more information, check out: The 16 Best AI Chatbot Vendors With Reviews and Features.

Self-driving customer relationships: What marketers could learn from Tesla’s Autopilot AI

Written by Puneet Mehta  on   Aug 23, 2018

AI is becoming the new user interface.

Instead of website searches, there are personalized conversations. Rather than being placed frustratingly on hold for customer support, there is immediate help on a person’s preferred channel. Instead of mass marketing, there are individual, 1:1 relationships.

As conversational AI becomes more central to businesses’ success (Gartner predicts that by 2021, more than 50% of enterprises will spend more on bots than traditional mobile), brands need to start thinking about training their AI just like training their employees. Developments in machine learning–including deep reinforcement learning–promise to revolutionize the way businesses think about AI, making it more intelligent and human-like as compared to simpleton bots, but as the technology continues to advance, so will consumer expectations for AI-driven experiences.

The AI Building Blocks

Context, short-term and long-term “memory”

The AI should not require a person to reintroduce themselves, but rather provide an experience that gets more personal and relevant over time. The little tidbits a person reveals, whether it’s style preferences, needs/goals or even budget, should help to shape future interactions. A person should never have to tell the AI the same thing twice, unless, of course, the data or personal preference is subject to change over time.

Ongoing learning

A core part of an AI’s “DNA” is that it should continuously improve. AI learning falls info a few core categories: improved understanding of natural language and intent mapping; how to best engage with specific audience clusters in a given moment and context; and a user’s propensity to convert based on a confluence of factors. An AI’s learning is never done.

Communication with existing business systems

An AI experience can’t exist in a vacuum. By nature, it’s an incredibly personal interaction and needs to tap into a brand’s CRM, commerce and other systems in order to make the experience as personal and relevant as possible. The AI should also feed the unique insights gleaned from 1-on-1 conversations back into these systems in order to create the most personal cross-channel experience.   A travel chatbot AI should also incorporate as many parts of the customer journey as possible. For an airline, it shouldn’t just provide travel inspiration tools, but also end-to-end booking and day-of travel support, such as rebooking and check-in. Similarly, retailers should provide guided selling and personal shopping, checkout, order tracking and support all within a single AI touchpoint. AIs true benefit comes to life when it’s powering the complete customer journey.

Human escalation protocols

As advanced as AI and customer service gets, there will always be things that a human can do better, such as complex problem solving or showing empathy in unique situations. When a situation arises in which the AI doesn’t have the skillset or emotional maturity to manage, the user can quickly get frustrated and conversations need to be seamlessly escalated to a human to take over. This handoff should happen within the same channel to cause no disruption to the consumer.

Brand safety controls

Brands need to protect themselves and make sure that they are not at risk of falling victim to merciless trolls. Therefore, every AI needs to be trained to disengage from conversations that could put them at risk. Whether it’s ending a conversation immediately when an inappropriate or sensitive topic comes up, warning users and having a three-strikes-and-you’re-out policy, or elevating to a human agent, AIs need to know what topics are off-limits and how to respond appropriately.

Measurements for business impact and AI performance

What good is an AI experience, if you can’t measure its effectiveness? Brands need to set goals and track conversion, whether it’s purchases, engagement, support or loyalty initiatives. Also, understanding how the AI itself is learning and optimizing over time as well as how the brand is saving operating costs typically associated with human agent support are key metrics to measure.

We’re at a critical point in the AI life cycle. Companies like Tommy Hilfiger, Target and others have shown consumers what a great AI experience can look like, and now the brands that don’t meet these raised expectations that are actually helpful risk losing consumers engaging with their AI, and their business altogether.

For more information, check out: The 16 Best AI Chatbot Vendors With Reviews and Features.

From Responding to Resolving: The Evolution of AI and Customer Service

Written by Emily Cummins  on   Aug 23, 2018

Touted as a way to improve customer service, help-desk AI agents have been the industry’s shiny new object for a few years. And while they have been created with the right intention of providing immediate responses to customer questions and issues, and also reducing the resources of strained call centers, most have been underwhelming at best and more often, leave the consumer more frustrated than they would have been waiting on hold.

Most commonly, AI agents have failed to understand what a person needs or has not had the authority to take action, and simply pinch hits to a human (who has often had a repetitive exchange with the customer). But just because they haven’t met expectations yet, doesn’t mean it’s time to walk away. As the saying goes….Rome wasn’t built in a day, right?

AI holds so much promise to completely transform customer support, and when done correctly, will enable consumers to get issues resolved quickly, on their terms, 24/7. So what will make AI-powered automation work?

  • Deep Learning: First and foremost, AI needs to learn from real exchanges, like historic emails and call center logs (in addition to FAQs and other explicitly trained scenarios). This will ensure the AI is able to understand the range of which people ask about a single issue or topic, and how an agent has responded in the past. The proper response can even be determined based on various contextual factors, like a person’s loyalty level or size of a wallet, to provide the most appropriate response every time.  Deep learning also enables AI to continuously learn and improve over time.
  • Authority to Resolve:  AIs need to be able to resolve issues. The first step is to accurately understand what a person needs (see point above), the second step is to close out tickets doing things like issuing a return, rebooking a missed flight or upgrading a seat or hotel room. Certain scenarios are more sensitive than others (i.e. a complaint about an issue with another passenger on a flight) and therefore require human intervention, so AI should be used to automate the closure of the low-risk repeatable tickets leaving high-touch queries to humans.
  • Empowered Human Agents: When a conversation is elevated to a human agent, the AI must pass along the specific information that will help the agent provide fast, accurate support, otherwise known as conversational AI. This involves both picking out the specific content from the AI and customer exchange, as well as the information from a CRM, OMS or other systems relevant to this exact need. This will ensure that the human agent does not re-ask questions (causing frustration and increasing the resolution time).
  • Proactive Support:  AI can also help companies move from reactive to proactive support. For instance, the AI would notice a delay in the inventory management system and automate a notification to the customers who are currently awaiting the item. This will enable a company to reach the customers before they have to send an email or make a call themselves. Without AI, this would be entirely too expensive and complex to handle with human agents.

Give your customers instant answers to up to 85% of customer service issues with our Zoho chatbot


AI will usher in a new era of customer support that is proactive, personal and accurate. With research suggesting that the customer experience will become more important than price and product by 2020, and there are currently over 1B customer service tickets created daily, companies must leverage AI for customer support in order to provide the experience that customers expect. An AI agent can’t just respond, though, it must offer a high-quality resolution to deliver on the true promise of AI.

For more information on AI and customer service, discover how to provide brilliant AI-powered salesforce chatbot solutions to every customer, every time.

To read more on customer service, visit: