Tag: AI

Fueling the Gig Economy: How AI Can Help Fintech Companies Serve this Booming Workforce

Written by Amy Wallace  on   May 11, 2022

In light of rising inflation, pandemic-era job losses and the work-life balance mindset, a growing number of individuals have embraced gig economy work. A 2022 Gig Payments Report pointed out that, in 2021, there were about 23.9 million independent workers in the United States, an increase from 12.9 million in 2017. Moreover, the number of freelancers across the country is projected to grow to 86.5 million by 2027. The study also found that 85% of respondents have recently increased their gig work or plan to increase it, with 58% citing inflation as their primary reason for doing so.

Traditional financial services, however, are not tailored for the needs of gig workers, both because many banks are more often heavily focused on more premium and higher-income customers, and they also lack access to data about the financial behaviors of gig workers, who often have to keep their financial activity unregistered. Additionally, with jobs coming and going, their paycheques often fluctuate from one month to the next. This lack of a steady income means that these workers struggle to access investment accounts, loans, insurance and other financial products, which also means they are likely to face difficulties when paying for unexpected emergencies, such as costly medical treatments.

For fintech companies, an opportunity awaits. Rising up to address the gaps in this market, many fintech ventures have come to recognize gig workers as potential customers who are underserved by the traditional banks, and are now playing a key role in powering the gig economy. For instance, Nigerian fintech startup ImaliPay allows eRide hailing drivers and gig workers to power their gigs with services such as buy now, pay later (BNPL), insurance and savings (the opportunities for workers in this region are booming, with the African gig economy likely to have over 80 million workers by 2030)!

Read more about how fintechs can provide a stellar customer experience across the board in our ebook, How Conversational AI Is Rewriting the Rules for Fintech Customer Experience!

AI + Fintech Companies = The Ultimate CX for Gig Economy Workers

According to the Gig Payments Report, when it comes to receiving payments, many gig workers prioritize speed of service. Nearly 70% of these workers prefer to receive their pay within the same day they work, 39% prefer immediately after each job and 29% at the end of each day. What’s more, with rising inflation impacting both work and personal expenses for 57% of respondents, having access to funds in a timely manner is crucial to meet financial needs.

With a burgeoning gig economy workforce looking to fintechs to manage their finances, there is bound to be support-related queries that follow. How can the support teams of fintech companies rise up to offer the necessary support, especially support that aligns with the expectations and preferences of their customers today? Herein lies the opportunity for these companies to incorporate modern AI-powered support systems into their technology stacks to provide immediate resolutions to customer issues.

Providing Swift and Immediate Resolutions

Redefining the customer support landscape, AI-powered chatbots for customer service have greatly improved efficiency by delivering personalized resolutions immediately and automatically, for a truly effortless experience. AI can automate resolutions to high-volume, repeatable tickets, such as resetting passwords and paying monthly bills, freeing up human agents to focus on the more complex issues, and decreasing resolution times. The result? Faster and more consistent support for customers, and less fielding of common and repetitive issues for support agents. For instance, if a customer is inquiring about the loan application process, a chatbot could easily serve up a hyper-relevant article from a company’s knowledge base that covers this topic in detail, or if connected to the right backend systems, can even provide the real-time status on an application.

AI-powered solutions enable fintech companies to better support their customers’ needs at more touch points along their journey, which includes access to 24/7 support outside of standard working hours when support teams are unavailable to respond to queries. This also reduces the actual cost of keeping a human support team on standby in case of an unexpected spike in tickets. This type of always-on support is ideal for those gig workers who work irregular hours and schedules but still need access to support from their financial institution.

Providing Personalized and Contextual Responses

Able to tailor interactions based on customer profile and behavior, an advanced AI assistant can show that it understands past interactions and customer preferences – noting, for instance, that a customer had previously inquired about financing options. The chatbots can then respond on an individual level, providing meaningful interactions, and responses that are more personalized and contextualized. Additionally, by integrating data stored in customer relationship management systems (CRMs) with chatbots, conversational AI can engage in more well-informed conversations, and support teams have more context on each customer. For example, here is Sarah, a freelance visual designer who has also been working as a DoorDash delivery courier for the past year, earns approximately $8,000 per month and is seriously considering applying for a loan. Which options would be best for her? What could the terms of her loan be?

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

Meeting Customers Where They Are

Not bound to any one location, gig economy workers are constantly on the move. AI-powered solutions offer resolution across channels – email, chat, messaging, SMS and voice – for support when they need it most.

Moreover, gig workers are busy, and for many, gig work is solely a side hustle to supplement their income (Branch and Marqeta’s report found that only 27% rely on gig work as their primary source of income). By leveraging AI, fintech companies can offer customer service that is proactive – addressing a customer’s issue prior to when they encounter one, by detecting or anticipating the issue in advance, and extending the necessary support needed to resolve it. Sample use cases include warning a customer that a bill is soon due, reminding them to transfer balances from one account to another, or alerting them that there may be a better savings account option for them than their current plan. Such proactive, predictive and preemptive support is ideal for this hustling workforce.

How Conversational AI Is Rewriting the Rules for Gig Workers

As the gig economy continues to boom worldwide, and more and more fintech companies develop financial products and services for this market, AI-powered solutions power proactive, instantaneous and always-on customer service. In turn, fintech companies can focus on creating better customer relationships, and scaling their own growth.

7 Ways AI Customer Experience Can Enhance Your CX

Written by Emily Cummins  on   Feb 15, 2021

AI customer experience is emerging as one of the dominant trends in customer service – this article will explore what it is and why so many companies are adopting AI to improve their CX. Good customer experiences help people feel good about a purchase and a brand. This positive experience influences them to come back in the future. The more efficient and personalized the experience is, the more likely companies can turn a first-time customer into a long-term loyalist and advocate. 

Traditional businesses are now competing against innovative, digital-native upstarts that have grown customer bases by prioritizing the customer experience (CX). Good CX is no longer an option: 2/3 of companies compete on CX, up from just 36% in 20101. Consumer-facing companies across industries are using Artificial Intelligence (AI) to enhance user experience.

  1. What Is AI Customer Experience?
  2. How AI CX Works?
  3. How Does AI Improve the Customer Experience?
  4. 7 Examples of How AI Transforms Customer Experience
  5. The Final Word

What Is AI Customer Experience?

AI customer experience is a holistic view of how customer experience is augmented by artificial intelligence. AI CX leverages technology like machine learning (ML), deep learning, and natural language understanding (NLU) to automate all the little interactions that make up a user’s experience. The key difference between “AI customer experience” and “AI customer service” is that the former is not limited to rapid resolutions to customer questions and issues.

How AI CX Works?

One example of how AI augments customer experience is via an AI-powered chatbot. An AI chatbot can function digitally through messaging platforms like WeChat and Facebook Messenger, email, and on voice assistants like Alexa and Google Assistant. Chatbot statistics show that the biggest benefits of AI customer support chatbots are eliminating wait times historically present with human-only support, helping customer service reps work more efficiently and automating mundane tasks so human agents can focus on complex issues. Companies using chatbots for customer service create happier customers who turn into long-term loyalists and reduced customer service costs. 

Our webinar with Freshworks, Practical AI to Transform Customer Service,
is a great intro to learn how AI can work inside your existing CX.

How Does AI Improve the Customer Experience?

AI can enhance CX in many ways. It streamlines processes and improves automated support to simplify everyday tasks. According to Gartner, “58% of consumers will use AI to save time, and 56% said they’d use it to save money. The more time they save, the more likely they are to purchase a product, and the more money they save, they’re likely to return to your business to buy again.2” 

Using AI to enhance the CX pays off in many ways:

  • Customers who rate a company as delivering a “good” experience are 34% more likely to purchase more and 37% more likely to recommend3
  • Companies with a CX mindset drive revenue 4-8% higher than the rest of their industry4
  • Companies that lead in CX outperform laggards by nearly 80%5

7 Examples of How AI Transforms Customer Experience

Companies are deploying AI to create much better user experiences in these seven key ways.

  1. Create Hyper-relevant Digital Ads
  2. Power Personalized Search
  3. Help Customers Find The Best Price
  4. Provide Immediate Answers To Questions
  5. Anticipate And Prevent Issues
  6. Empower 24/7 Support Across Every Channel
  7. Eliminate The Hassle Of Returns

1. AI customer experience creates hyper-relevant digital ads

According to Joanna Coles, the former chief content officer of Hearst Magazines, “People hate advertising.” This is because, according to Marc Pritchard, the chief brand officer at Procter & Gamble, ads are often irrelevant and sometimes “just silly, ridiculous or stupid.6“

Advertisements are not going anywhere, but the experience is ripe for change: 

  1. 91% of people say ads are more intrusive today than 2-3 years ago7
  2. 83% of people agree with the statement: “Not all ads are bad, but I want to filter out the really obnoxious ones”7
  3. 25.8% of internet users were blocking advertising8

To address the challenges with digital ads and make them less intrusive, brands are harnessing AI to show hyper-relevant ads. Machine learning helps companies anticipate if a person is likely to click on an ad – based on online behavior, customer profiling, and audience segmentation.

For instance, predictive targeting allows companies to adapt ads to an individual customer and recommend products in an ad based on thousands of signals. These algorithms improve over time to provide increasingly personal ads. 

2. AI customer experience powers personalized search

AI is being used to help customers discover the most relevant products and streamline the online user experience. This is driven by the fact that 80% of consumers are more likely to purchase from a brand that provides personalized experiences9. 

Personalized search is typified by Netflix. The streaming company has rights to 13,612 titles10. To help customers more quickly find something they want to watch, Netflix’s AI crunches huge amounts of data to present a different home screen to each viewer. The recommendations are based on past viewing behavior and granular audience segmentation.

The streaming wars are brutal. Your CX must be stellar.
Improve it with our streaming video customer service eBook.

Online shopping is another example of personalized search enhancing the customer experience. eCommerce companies are using AI to surface highly relevant products from expansive online catalogs. Wayfair, for instance, has 37,173 coffee mugs.  AI-powered search provides a better user experience by eliminating the need for people to scroll through multiple pages to see the few products they might be interested in. AI-powered personalized search will only become more pervasive as 71% of consumers feel frustrated when a shopping experience is impersonal11. 

Download a copy of our full Retail and CPG Customer Service Benchmark Report!

3. AI customer experience helps customers find the best price

AI is also helping customers find the best prices so they can be confident that they are getting the best possible price based on predictive intelligence around price fluctuations. For example, Hopper is a highly-regarded startup in the travel space that heavily relies on AI to provide an exceptional CX. The company “offers travelers flight recommendations based on highly accurate pricing predictions, uncovering price drops and exclusive deals relevant for the traveler.” Another way to improve to customer experience is through an AI travel chatbot to quickly answer questions and resolve solutions. 

4. AI customer experience provides immediate answers to customer questions

Netomi offers AI for customer service, providing instant resolutions to simple everyday queries like order or flight status, refund policy and requests, and other FAQs. Advanced customer service AI platforms can integrate with back-end systems like CRM and shipping platforms to provide personalized resolutions to an infinite number of customers at the same time. This frees up customer service reps to focus efforts on high-impact, complex customer situations – providing better customer satisfaction (CSAT) across the board. 

5. AI customer experience anticipates and prevents issues

Companies are also using AI for proactive customer service, which allows them to anticipate and solve problems and issues before customers are even aware. Examples include alerting a customer when a package will be arriving late due to weather delays, offering early check-in to a customer whose flight arrived early or proactively educating a person on how to care for a product. For instance, HP lets a customer know when their printer ink is about to run low and provides a frictionless way to repurchase compatible ink. This eliminates user frustration – improving customer effort score and the responses submitted during customer satisfaction surveys – and the need for a customer to reach out themselves to a company to resolve an issue.

6. AI customer experience empowers customers to get 24/7 support across every channel

There’s an increasing number of channels where customers expect to receive customer support. Human-only agent teams are expensive and hard to staff to manage multiple channels, around-the-clock. AI helps companies scale support across email, chat, voice, messaging, SMS and voice platforms. This allows customers to get the support they need on their preferred channels. Without AI, it would be cost-prohibitive to have a truly omnichannel experience that customers expect i.e., immediate, personalized, meaningful. 

7. AI customer experience eliminates the hassle of returns

Retail customer service is crucial, and returns are a huge part of the online shopping experience. Over 30% of all online purchases are returned. Although retailers have made efforts to make the return process as seamless as possible over the last few years, returning an item is still frustrating. AI helps improve the CX by anticipating when a return is likely based on items in a shopping cart or user behavior. For instance, if a person has multiple sizes of the item or has checked the size guide and return policy within the same session, it could indicate that a person is unsure of what size to buy. AI-powered chatbot tools are preemptively intervening to help the customer find the best possible selection to avoid frustrating and costly returns.

The Final Word

AI is drastically improving CX, delighting customers across the customer journey. And the result of adopting AI for CX is not just happier customers, but also a better topline: 84% of companies that work to improve their customer experience report an increase in their revenue12.

Would you like to learn more about AI and customer experience tools? Our CX experts would love to chat about our chatbot platform.

Request a meeting today.

To learn more about improving the customer experience, visit:

References

  1. https://www.gartner.com/en/marketing/insights/articles/key-findings-from-the-gartner-customer-experience-survey
  2. https://www.gartner.com/en/newsroom/press-releases/2018-09-12-gartner-survey-finds-consumers-would-use-ai-to-save-time-and-money 
  3. https://www.qualtrics.com/xm-institute/roi-of-customer-experience-2019 
  4. http://www2.bain.com/infographics/five-disciplines/ 
  5. https://www.qualtrics.com/blog/forrester-economic-impact-of-experience-management/ 
  6. https://www.nytimes.com/2019/10/28/business/media/advertising-industry-research.html 
  7. https://www.vieodesign.com/blog/new-data-why-people-hate-ads 
  8. https://www.statista.com/statistics/804008/ad-blocking-reach-usage-us/ 
  9. https://us.epsilon.com/pressroom/new-epsilon-research-indicates-80-of-consumers-are-more-likely-to-make-a-purchase-when-brands-offer-personalized-experiences 
  10. https://cordcutting.com/blog/how-many-titles-are-available-on-netflix-in-your-country/ 
  11. https://www.forbes.com/sites/blakemorgan/2020/02/18/50-stats-showing-the-power-of-personalization/ 
  12. https://www.forbes.com/sites/blakemorgan/2019/09/24/50-stats-that-prove-the-value-of-customer-experience/

7 Ways eCommerce is Using AI on Black Friday and Cyber Monday

Written by Emily Cummins  on   Nov 17, 2020

The holiday shopping season has officially begun. Even with the headwinds of economic uncertainty from COVID-19, analysts expect a 35% increase in seasonal online sales this holiday season1. With gift-buying expected to be healthy, analysts also predict a shift back towards traditional gifts from past years’ experience-gifting. This will create a ripe opportunity for eCommerce companies. 

Contrary to popular belief, an eCommerce chatbot is just the tip of the iceberg when it comes to how AI can propel companies to a new level of service. This holiday season, retailers are adopting AI to enjoy greater operational efficiency, provide a better customer experience (CX), reduce costs, and unlock new revenue. Here are some of the most exciting and new ways that eCommerce companies are using AI during this prime holiday shopping season and beyond to beat top-notch eCommerce benchmarks. 

7 AI Use Cases for eCommerce Companies 

1. Virtual Try-Ons and Fitting Rooms: While virtual try-ons have been popular for beauty and cosmetics brands over the years, many traditional retailers and eCommerce companies are rolling out virtual fitting rooms. Whether it’s due to retailers never reopening their physical dressing rooms even as in-person shopping came back during COVID-19, or consumer thirst for new experiences, companies like Macy’s, Adidas and Modcloth are now leveraging AI to power these new virtual experiences. With virtual fitting rooms, shoppers either upload their picture to an app or website, or simply add in their dimensions to create a custom avatar. They can then select products to “try-on” from the safety and comfort of their home. This caters to the 21% of Americans who plan to shop for themselves on Black Friday and 18% on Cyber Monday2.

2. Visual Product Search: A preference for visuals is hard-wired into us: the human brain processes images 60,000 times faster than text, and 90 percent of information transmitted to the brain is visual3. Visual search is a fast-growing area with billions of searches per month across social, search and shopping platforms. There are over 600 million visual searches on Pinterest every month4.

To help shoppers find gifts similar to what they’ve seen, numerous retailers like ASOS5, Walmart’s Hayneedle brand6, Uniqlo7 and IKEA8 are rolling out visual product search. Visual product search uses AI to help customers find stylistically similar products to those in an image that they show the AI. Consumers are rapidly adopting visual product discovery: in one study, 62% of Millennials reported a desire to visually search over any other new technology9. The results for eCommerce companies are significant: visual search results in 50% faster checkouts10, compared to keyword search. Visual search also results in a 20 – 30% increase in conversion. Gartner predicts that by 2021, early adopter brands that redesign their websites to support visual and voice search will increase digital commerce revenue by 30%11. 

Visual search built in collaboration between Hayneedle and Walmart Labs

3. Targeted, Contextual and Personalized Search: Retailers like Wayfair, Etsy Inc. and Pinterest are harnessing their sea of customer data to build predictive, AI-powered recommendation engines and provide unique product discovery search results12. By feeding historical data into these algorithms, retailers can anticipate which products will resonate best with a particular customer based on search and browse history, web behavior (time spent on specific product page) and purchase history. By using AI to recommend products from gigantic online catalogs —  Wayfair, for instance, has 37,173 coffee mugs — retailers see a 50% jump in the success rate of in shopping cart additions. For example, when a customer finds an item is out-of-stock.  AI can now analyze product color, size, pattern, price, style and other attributes to suggest similar items. AI-powered personalized product recommendations are increasing conversion rates by 915% and average order values by 3%13. This AI-driven personalization will boost profitability by 59% by 203514. 

4. Conversational Shopping and Gift Finding: A weariness of shopping in store as a result of COVID-19, has led to 63% of consumers say they are avoiding stores and buying more online this year. In an effort to replicate the knowledgeable store associate, retailers are deploying conversational AI chatbots to act as personal shoppers. Chatbots help people find products and gifts based on who a customer is shopping for, as well as customers’ interests and preferences. These virtual shopping assistants are guiding people to discover products based on a variety of factors – replicating the in-store associate experience of asking a helpful store worker. Consumers are receptive to these conversational AI chatbots: one in every five consumers are willing to purchase goods or services from a chatbot15.

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

5. Automatically Resolve Customer Service Tickets: With ticket volume increasing 42% on average for retailers during the holiday shopping season, AI-powered customer support chatbots are helping retailers scale up support operations. AI chatbots automatically resolve common, everyday customer service queries. Mattress retailer Zinus, for instance, is using a Netomi-powered AI chatbot to instantly respond to product questions, order management, cancellations, warranties and more. This gives customers faster responses and eliminates the need to talk to a human agent for most questions (they can still do so if the retail bot doesn’t have the answer to a complex question). Leveraging AI chatbots to resolve customer service issues increases customer satisfaction (CSAT), reduces costs and boosts live agent productivity. 

6. Preventing and seamlessly managing returns: Following the lucrative holiday shopping season, comes the sobering season of returns. Typically, returns spikes right after Christmas until late January. This year’s “return season” is expected to have more volume and last longer. This is because companies are having longer “Black Friday” season sales and seeing record volumes of online shopping due to COVID-19 as people shun indoor shopping. 

According to reports, online shoppers return 15% to 30% of online purchases, compared to 13% for bricks-and-mortar purchases16. Last year, customers returned $41.6 billion worth of merchandise bought online during November and December alone17. Retailers are using AI to help mitigate returns and maintain customer satisfaction during the process in two key ways:

  • Mitigating Returns Pre-Sale: Predictive analytics can help identify when a return is likely based on online behavior (i.e., checking size guide) or shopping cart (similar items; same item in multiple sizes). When there’s a signal that a return is likely based, a conversational AI agent can help the person make the best decision from the onset. If concluded from the conversation that an eventual return is intended, and the size of the purchase or the potential lost value of returned items in the cart make it worthwhile, retailers can leverage an AI chatbot to provide an incentive to limit the purchase to one selection. 
  • Increase Customer Satisfaction During the Return Process: Even if predictive analytics is deployed during the pre-sale process, returns are inevitable. Retailers are leveraging AI to keep customers satisfied throughout the process through automated updates of when a returned item is received and when a refund is issued. This matches customer expectations; 56% of people say they want notifications about a refund status and 50% want to know the status of their return package18. Beyond automated messages, AI agents can cross-sell alternatives to returned items to recover lost profits. 

7. Optimized Inventory Management: Currently, retailers are losing nearly $1 trillion in sales because they don’t have on hand what customers want to buy19. To address this, eCommerce companies are tapping into AI to anticipate inventory needs and make smarter product purchase decisions. historic sales, anticipated changes in demand, supply-related issues ,and trend forecasting data are being fed into algorithms to help retailers know which products are likely to sell and how to adjust inventory to ensure the most in-demand products are in stock. For instance, to “…better stock individual stores with merchandise local clientele desires, H&M is using big data and AI to analyze returns, receipts and loyalty card data to tailor the merchandise for each store20.” 

Retail and eCommerce Adoption of AI is Booming Across Many Use Cases this Black Friday and Cyber Monday

In this post, we’ve outlined seven of the top ways retailers and eCommerce companies are using AI this holiday season and beyond.  As competition increases from traditional and nimble online-only players, eCommerce companies must leverage AI to provide an exceptional customer experience, drive efficiency with operations and planning, and reduce costs. 

With Black Friday and Cyber Monday only two weeks away, retailers need to ensure their operations and customer experience won’t be impacted negatively by an increase in demand.  It’s not too late for eCommerce companies to adopt AI to get out ahead of seasonal strain.

Continue Reading: Find out about the current state of retail email support in our Customer Service Benchmark Report. Download a copy today. 

References 

  1. CNBC: https://www.cnbc.com/2020/09/15/deloitte-estimates-2020-holiday-retail-sales-will-rise-1-to-1point5percent-.html 
  2. Today.You.Gov: https://today.yougov.com/topics/consumer/articles-reports/2019/11/12/them-or-me-why-black-friday-sometimes-about-gifts 
  3. T-Sciences: http://www.t-sciences.com/news/humans-process-visual-data-better 
  4. Pinterest: https://newsroom.pinterest.com/en/post/celebrating-one-year-of-pinterest-lens 
  5. enGadget: https://www.engadget.com/2018/03/09/asos-visual-search-tool-available-all-shoppers/ 
  6. TechCrunch: https://techcrunch.com/2018/12/18/walmart-is-testing-its-own-in-house-visual-search-technology-on-hayneedle/ 
  7. PSFK: https://www.psfk.com/2020/05/uniqlo-stylehint-personalized-social-commerce.html 
  8. Reuters: https://www.reuters.com/article/us-ikea-ab-apps-exclusive-idUSKCN1SX1DV 
  9. Businesswire – ViSenze: https://www.businesswire.com/news/home/20180829005092/en/New-Research-from-ViSenze-Finds-62-Percent-of-Generation-Z-and-Millennial-Consumers-Want-Visual-Search-Capabilities-More-Than-Any-Other-New-Technology
  10. Shopify: https://www.shopify.com/retail/what-is-visual-search 
  11.  Gartner: https://www.gartner.com/smarterwithgartner/gartner-top-strategic-predictions-for-2018-and-beyond/ 
  12.  WSJ: https://www.wsj.com/articles/retailers-use-ai-to-improve-online-recommendations-for-shoppers-11604330308 
  13.  Personalization.com: https://www.perzonalization.com/blog/personalized-product-recommendations-in-eCommerce/ 
  14.  Big Commerce: https://www.bigcommerce.com/blog/eCommerce-ai/#the-future-of-ai-retail-and-roi 
  15.  Medium: https://medium.com/@Countants/how-artificial-intelligence-is-transforming-the-e-commerce-industry-countants-scalable-custom-73ae06836d35 
  16. CNBC: https://www.cnbc.com/2019/12/19/online-returns-this-holiday-season-to-hit-record-41point6-billion.html 
  17.  CBRE: https://www.cbre.us/about/media-center/cbre-reverse-logistics-2019
  18.  Navar: https://see.narvar.com/rs/249-TEC-877/images/Consumer-Report-Returns-2018-4.3.pdf  
  19.  Retail Dive: https://www.retaildive.com/news/out-of-stocks-could-be-costing-retailers-1t/526327/  
  20.  Forbes: https://www.forbes.com/sites/bernardmarr/2018/08/10/how-fashion-retailer-hm-is-betting-on-artificial-intelligence-and-big-data-to-regain-profitability/?sh=9fe938e5b00a

New eBook: Transforming Customer Support with AI

Written by Can Ozdoruk  on   Jul 31, 2019

Welcome to the Relationship Economy. 

Doing business today is a lot different than it was a few years ago.  Customer service is now just as important as price, quality and brand name in determining where people spend their money and build long-term relationships. Customers have quick-rising expectations for personalized, convenient and immediate support on their channels of choice, and swiftly take their business elsewhere if they are not satisfied. 

In our latest eBook, Transforming Customer Service with AI, we explore this new era of doing business, the challenges that companies face and how helpdesk AI can accelerate a customer support organization into a customer relationship powerhouse. You’ll learn: 

  • What customers expect from companies when they have an issue 
  • How AI can impact the customer service function of businesses of all sizes 
  • Best practices to follow when implementing AI within your business 
  • How to create a continuous-learning AI that improves over time

Customer service now has a direct impact on consumer buying habits, either posing a great risk or presenting an incredible opportunity. Customer service can no longer be an after-thought; it must become a core part of the overall customer experience strategy and business focus moving forward. 

Get your free copy of your eBook here. 

For more information on customer service, visit:

With AI in Customer Service, the Biggest Payback Could Be Time

Written by Emily Cummins  on   May 7, 2019

When it comes to understanding the helpdesk AI benefits to customer service, William Penn eloquently nails it. “Time is what we want most, but what we use worst.”

Time is a commodity that we all need more of. Something that we all hate to waste – especially if it’s spent doing something like contacting a company to resolve an issue that’s been frustrating enough to encounter in the first place. When we hear stats like we spend 43 days on hold for customer service in our lifetime and 86% of customers have to contact customer service multiple times for the same reason, it’s clear that the status quo is ripe for disruption.

“Time is not the main thing. It’s the only thing.” – Miles Davis 

Customers Are Valuing Their Time More Than Ever

Modern customers are used to instantaneous gratification. They walk around with supercomputers in their pockets that can tell them breaking news from around the world, how to avoid a traffic accident that happened one minute before, or let them share a picture of the innovative cocktail the bartender concocted for them with friends and see likes tick up in a matter of seconds. They expect quick. Anything outside of instantaneous is jarring.

Imagine sending a company a question on Facebook and having to wait over 12 hours for a response (which is the average response time). This is unacceptable in your customers’ minds. According to Forrester, 66% of US online adults said that valuing their time is the most important thing a company can do to provide them with good online customer experience. Time, not necessarily a favorable outcome or a pleasant representative (both, of course, are also important). But it’s getting time back to go back to whatever it was they were doing before that is the driving factor to what is considered good service.  

Looking to maximize your CX? Discover what platform may be best for you in our comparison of Intercom vs. Zendesk.

Customer Service Agents, Too, Are Desperate For Time

It’s not just customers who need time back. Agents, too, are inundated with tickets they need to manage and lack the necessary customer service tools and real-time information to adequately address many tickets. Agents report that they often have many windows open simultaneously, yet still more than half almost never or only occasionally have the context they need to most effectively and efficiently solve issues [Microsoft]. This results in rerouting customers to other agents with the right context (which leads to 83% of consumers having to repeat the same information to multiple agents), delayed resolutions and diminished CSAT which weighs negatively on employee satisfaction and morale.

How AI Benefits Time By Giving Back To Both Customers And Agents 

The AI benefits of giving back time are multifaceted:

  • AI can be deployed to respond immediately (i.e. less than one second)  to the everyday customer support tickets, providing customers with the instant gratification that they crave for over 50% of their queries.
  • Automated customer service integrations, such as Zoho chatbot, save agents time from managing mundane, repeatable issues, and focus on more high-touch customer needs. 
  • For agent-managed issues, AI pulls relevant information from business systems and clarifies information with the customer before an agent ever gets involved. Agents no longer have to open multiple windows to gather information from other databases which delay the resolution but rather can quickly review and act on the data provided from an AI.

Are you ready to give time back to your customers and agents using a chatbot platform? Let’s chat. 

For more information on AI and customer service, visit:

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.

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.

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