Early this year I predicted that there would be a great shakeout in #ArtificialIntelligence, culling the herd of software companies claiming to be AI. As brands and consumers both get comfortable interacting with AI powered technologies, it is time to dig a bit deeper. 2019 will be the year when AI’s true potential will be unleashed and companies will see the real results from investing in the right AI-powered solutions.
In a recent Deloitte survey of 1,100 US executives from companies considered to be early AI adopters, 82 percent report a positive return on their investment. The investment in AI powered solutions will only grow in the coming years because it is no longer an option but an imperative. But investment in any technology without understanding its true potential is not going to yield the right results and this is especially true in #CustomerExperience.
In customer engagement, the key to delivering effortless and memorable customer experience is by truly understanding your customer and their needs. This is where intent is so important, because only by knowing what the customer is trying to do can serve their needs correctly. By using AI to understand a customer’s intent and journey, brands can offer customized and precise information that leads to a personalized, predictive, and effortless customer experience.
Here are some of the trends I foresee for the coming year with respect to AI-driven customer experiences:
- Bot Experimentation will End: 2019 will be the Year of Mainstream Bot Implementation - 2017 and 2018 were the years of chatbot experimentation and early adopters, but in 2019 enterprises will mature into more mainstream chatbot implementations. The C-suite is aware of the importance of CX and executives are involved in making chatbots/virtual agents a key part of their company’s customer experience. According to the Gartner’s 2018 CIO Survey featured in Hype Cycle for Contact Center Infrastructure, 2018, 38% of enterprises are planning or actively exploring chatbots, and as a result we will see more enterprise grade chatbots being deployed. At the same time, many projects will fail as companies are still underestimating the complexity of enterprise chatbots. Companies will become educated on what an “enterprise grade” platform needs to provide, such as: cross-channel capabilities, scalability, security, reliability, ability to integrate with enterprise systems of record and systems of engagement, pre-built industry intent models, and sophisticated tools for optimization.
- Verticalization – Vertical chatbots will gain interest as they bring customized solutions for industries such as Financial Services and Retail; where consumers expect a continuous, convenient and customized customer experience. From the Retail industry trying to bridge the online and offline gaps to Financial Services companies using chatbots to answer, solve, and advise digital customer needs, bots which are purposely created with specific vertical tasks in mind will become more common. Enterprises will find that adopting chatbots with verticalized specialties will help them deploy faster and will result in greater customer adoption and CSAT/NPS scores.
- Enter EmBots - As customer interactions with chatbots grow, so does their expectation from these automated interactions. The Forrester CX Index concluded that brands are struggling to create and sustain a human connection with their customers. The EmBots (for Emotional Bots) could be an answer to this as these are bots powered by Emotional Intelligence, the ability the ability to detect user emotion during interactions, acknowledge that emotion and respond empathetically. The AI models allow the bot to detect customers’ frustration, so it can immediately escalate to a human without letting it turn into a negative customer experience. This Emotional Intelligence capability will continue to grow in importance in the coming year.
- Predictive Analytics in CX- The ultimate frontier of AI for CX will be the ability to use the insights the chatbot gathers from customer interactions, in order to better understand the customer, anticipate outcomes and proactively act upon intent to resolve the issue before escalation. AI has the power to draw detailed insights into a customer’s journey, and to offer proactive action-oriented interactions rather than reactive. This will greatly improve customer experience as it reduces effort by the customer and helps him or her achieve goals faster. Imagine this as Siri reminding you two months before your spouse’s birthday to make the restaurant reservations based on data from your last year’s planning calendar.
- Humans and Chatbots will Engage in Three-way Blending – The blending of humans and AI will remain a key differentiator in creating a successful customer experience, as simulation of human intelligence by machines still requires a lot of support from humans. A critical criterion for digital self-service is to maintain the quality of the interaction and this can be achieved by blending bot and human efforts to augment customer experience. This ensures less waiting time for consumers, thereby increasing overall self-service adoption. Vendors will take steps towards providing deep self-learning bot capabilities making it a three-way blending experience. Deep learning allows enterprises to create predictive models with uncanny accuracy on image, voice, and natural language data that was previously impossible to analyze. The deep-learning model’s ability to predict outcomes and identify patterns can help in use cases like fraud detection, customer churn analysis, and purchase propensity modeling
- Amazon Alexa and Google Home will Continue to be Relegated to Simple Tasks – Gartner predicts that the VPA-enabled wireless speaker market (virtual personal assistants such as Google Home and Amazon Alexa) will reach $3.52 billion by 2021. The coming year will witness VPAs (sometimes referred to as “smart speakers”) continue to gain mindshare and will augment customer interactions with rise of enterprise use cases in the coming year. However, VPAs will continue to be utilized primarily for simple tasks like checking the weather, playing music or checking balances, not for more complex interactions, but for these use cases like playing music, the service providers will start to integrate service into VPAs.
- Welcome Hyper-Personalization – With rising expectations for customer service, the degree of personalization will be a key differentiator in highly competitive markets. AI will be used to personalize experiences based on a single customer journey view. A view into every customer touchpoint throughout the journey is essential for hyper-personalization, and customer journey mapping helps to understand the specific devices, touchpoints, and interactions which are crucial in personalizing in order to create memorable customer experience moments that increase brand affinity. We also foresee the birth of a segmented user conversation model as an aide to personalization. Conversational models optimized for customer characteristics such as age group, language and dialect patterns, education level, geography, etc. will become a more common way to create a personalized experience.
- Messaging is the New Norm – With asynchronous messaging, brands are able to offer continuous conversations, where customers can easily pick up where they left off and never have to repeat themselves. With the ability to integrate interaction platforms to social and native apps like Apple Business Chat and FB Messenger, messaging will continue to grow as a preferred channel for consumers. A recent Forrester survey (Forrester Analytics Consumer Technographics NA Survey, 2018) found that 63% of North American consumers are using an average of at least five social platforms, such as Facebook, Twitter, etc. With Google now joining the messaging party with RCS (the Android version of ABC), we believe the native messaging platforms such as Apple Business Chat will grow faster than enterprise-specific messaging apps, due to ease of use.
- A New Metric for CX Measurement – Companies need to measure all the ways that consumers interact with them. With chatbots and virtual agents and asynchronous messaging becoming part of the mix, Average Handle Time (AHT) becomes a bit archaic. Total Customer Interaction Time (TCIT) is the new metric that measures the time it takes from when a consumer initiates an interaction to when he or she successfully completes that interaction. When a bot is handling all or part of a conversation, the most important measurement becomes NSAT (Net User Satisfaction) and Automation Rate as captured by TCIT. As AI and Deep Learning expand their impact, the most sophisticated, conversational virtual agents can now measure intent and will soon be diving deeper into user sentiment and leveraging that in their models.
- The CMO will become the Orchestrator of CX – As the ultimate arbiter of the total brand promise, the CMO will step up and claim responsibility for synchronizing CX efforts at the company level. I also believe that the CMO is turning into the conductor of customer experience as the advent of AI and other technological innovations affect brand-customer interactions. A recent Forrester report states that marketers' use of AI will multiply and mature in the next five to 10 years. While it won't fundamentally change the purpose of the Marketing function, AI will become CMOs' best friend, enabling Marketing teams to return to the function’s core essence.