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Is 2017 The Year AI Revolutionizes Customer Service?


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DISCLAIMER: This is NOT my content. You can see owner of content in deck.

A great overview of how machine learning is already impacting business and cX. So much more to come!

Published in: Data & Analytics
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Is 2017 The Year AI Revolutionizes Customer Service?

  1. 1. Is 2017 The Year AI Revolutionizes Customer Service?
  2. 2. Perspectives Gained From Decades of Experience Eric is a tested startup leader and team builder, with experience launching, developing and inspiring customer support teams. His most recent positions were at Dropcam (now part of Nest Labs/Google) & Zoosk. Eric Hallquist Senior Consultant, Customer Service Lab Sophie Conti CEO, Customer Service Lab Mahesh Ram is the founding CEO at Solvvy, an intelligent self-service platform for customer service. Mahesh is a serial entrepreneur, most recently serving as CEO of GlobalEnglish Corporation (acquired by Pearson PLC in 2012). Mahesh Ram CEO at Solvvy Savvy Customer Service professionals know artificial intelligence and machine learning have the potential to make support interactions easy and effective. But some emerging AI products, like chatbots, failed to live up to their promise last year. Now the question on everyone’s mind is “Will 2017 Be The Year AI Revolutionizes Customer Service?” Solvvy partnered with Customer Service Lab to produce the content in this e- book. Join us in exploring practical CS applications of artificial intelligence and machine learning. Sophie is the founder of Customer Service Lab, and she has spent her career working with startups in customer support with some of the most innovative companies like Leap Motion, Tile, Moo, Etsy, Indiegogo, Teespring and more.
  3. 3. 3 An Introduction To Terminology ARTIFICIAL INTELLIGENCE Teaching machines to think the way that humans think. MACHINE LEARNING DEEP LEARNING 1950’s 1980’s 2010’s Artificial Intelligence is a 60 year-old term, but new AI technologies just started coming to market in the last few years. Machine Learning was popularized by a computer chess program that learned from its mistakes to become a more formidable opponent over time. Deep Learning is an iteration of machine learning. It is machine learning algorithms that run on multiple layers. Also important is Natural Language Processing. NLP is the ability for a computer program to understand human speech, regardless of slang or dialect. Algorithms that mimic the brain’s neural networks to learn without human supervision. The ability for machines to learn without being explicitly programmed.
  4. 4. Customer Service organizations are under pressure from triple demands of increasing volume of support requests, rising expectations of customers and the need to contain costs.
  5. 5. 5 Are Chatbots The Answer? Chatbots are Highly engineered to work with constraints and controls. Fragile and likely to break around edge-case contacts. Bots need to learn how to talk with humans, not vice versa. How AI/ML Impacts Customer Service Today Handles Basic, Repetitive Tasks Boring questions are being automated, making customer service jobs more engaging and interesting. Identifies and Predicts Patterns ML programs identify trends in user behavior that humans can’t easily see. AI is already playing a major role in Customer Service today. Right now, chatbots are highly effective in a narrow set of scenarios, but when you start conversing with a chatbot, it fails. Most bots on the market today do not learn from prior agent interactions. They are hard-wired to work. Chatbots are difficult to maintain and hard to update because they do not sufficiently leverage NLP. The Truth About Chatbots Today when a chatbot runs into an unknown scenario, it is prone to creating terrible experiences and negatively impacting CSAT. The technology is not there yet to support a fully adaptive conversation, but it could be possible in the not-so-distant future. Automates Customer Contact By effectively understanding customer behavior and needs, AI automates interactions.
  6. 6. Advanced technologies like artificial intelligence and machine learning create a more robust self-service offering for your customers. AI and ML offer four competitive advantages: AI / ML is the secret sauce for self-service.Your Customers Prefer Self-Service Support IT IS FAST IT IS EASY Self-service adoption is on the rise. Nearly 9 out of 10 adults have used self-service support in the past 12 months. IT IS CONVENIENT Customers want to get their issue resolved at any point. Virtual agent use jumped from 28% in 2012 to 58% in 2015. Your customers look for the least amount of friction when contacting your support. Data: Forrester Trends 2016, The Future of Customer Service Precise Answers Contextual Experience Immediate Resolutions Smart Responses Customers say valuing their time is the most important thing a company can do for good customer ser vice.
  7. 7. 7 How To Use AI/ML In Customer Service CUSTOMER FACING Improving customer facing interactions is not a new idea, but recent tools leveraging AI/ML have improved its efficiency. Examples of a front-end approach are guided or contextual self-service, improving knowledge base navigation functionality and surfacing the right content to your users at the right time. AGENT FACING Back-End Approach Makes agents more efficient Quickly locate the best answer and then deliver it through any channel. Customer appreciate quick responses from agents and it drives higher CSAT. Examples of a back-end approach are learning from past interaction data to surface the most successful answer and intelligent routing of incoming tickets. Front-End Approach Provides faster resolution
  8. 8. We can show efficiency in areas such as support or risk operations, where we don’t want to grow a really large people organization. It behooves us to lean in on things like machine learning, even AI to make our business very efficient. - Square CFO, Sarah Friar 2016 Q4 Earnings Call
  9. 9. 9 Making AI/ML Work For Your Company Build Approach Technology is core to business Dedicated ML team working on customized solutions Expected >$1M annual budget Buy Approach Specialized, domain-specific need Buying decision made by team (ex: support team buys for self-service) Expected <$75K annual spend All companies can use commercial solutions to immediately gain automation benefits.
  10. 10. TRUSTED BY THE WORLD’S SMARTEST COMPANIES Effortless Self- Service Delivered by Advanced AI and Machine Learning
  11. 11. 11 We help companies improve customer satisfaction with intelligent self-service 21 3 4 5 Rapid Deployment Fast Case Resolutions Reduced Ticket Volume Improved Knowledge Base Continuous Learning Learn more at
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