The 451 Take:
Marketing and service functions are so thoroughly interdependent that it's essential to join forces to map the customer journey experience. Creating an effective conversational experience requires solid integration at technical and operational levels between different parts of the stack. Because the permutations are so varied, vendors must guide business expectations toward the best path to success. It's important to ensure machine-learning (ML) capabilities for a more humanistic interface and experience. The use of artificial intelligence (AI) and machine learning will help identify contexts in which service situations can be turned into offer opportunities, or where brand encounters can be augmented with service data.
Given that 80% of online purchases in 2017 were influenced by mobile devices, and within a decade the average person will have more conversations during a day with bots than humans, organizations that fail to deliver contextually relevant experiences will be passed over for those that do.
For instance, 77.2% of survey respondents in 451 Research's VoCUL Consumer Representative Survey Q3 2017, use their smartphones for SMS/texting on a daily basis, surpassing daily usage of phone calls. In the same survey, daily use for third-party messaging apps is at 43.3%, and use for social networking has reached 67%. Heightened activity of these uses are a reason that early implementations of chatbots have been within Facebook Messenger and similar social platforms and messaging services.
With the explosion in new types of physical, digital and blended experiences, the battleground is quickly evolving with customers expecting intelligent, immersive and pervasive experiences – all personalized to their own changing context. As a result, it's critically important for companies to know their customers, and also to be able to orchestrate their experience across the customer journey to promote engagement across the digital and physical worlds. Success comes not just from knowing when to interact, but also knowing which method a particular consumer prefers, such as web, self-service, mobile chat/text, Facebook Messenger or Twitter.
Conversational experiences across the customer journey
Customer lifestyle changes have facilitated the surge in conversational technologies that create frictionless, on-demand, cross-channel conversational experiences throughout the customer journey, from product discovery and ordering to mobile payments, tracking order status and providing customer service. Part of this concept is conversational commerce.
Conversational experiences are a relatively new set of technologies that nurture relationships across the customer journey, typically using machine learning to trigger contextual responses to a mobile phone at relevant points in the customer lifecycle. Businesses can leverage chatbots to provide automated, personalized selling or VIP support experiences on-demand via messaging apps such as Facebook Messenger, Twitter DM and WhatsApp.
As seen in Figure 1, our Voice of the Connected User Landscape: Mobility and Digital Transformation survey, H2 2017, bears this out. When asked about customer experience technologies, 24.5% of participants anticipate that chatbots and digital assistants will have the highest investment within their organization over the next 12 months. Yet what is most important is that key customer experience technology investments span the customer journey from social engagement, mobile applications and intelligent personalization to collaboration tools and customer loyalty management. All these technologies add up to the growing importance of conversational experiences across the customer journey.
However, we still see adoption of conversational technologies as an important measure that companies can and should take to embrace the larger trend of contextual experiences. For many companies, future success depends on creating user experiences that intelligently leverage data as contextual cues to deliver personalization and make informed responses. Employees in consumer engagement-oriented roles will also benefit as these technologies overlay existing, legacy business systems, or help employees with scale by automating tasks such as lead qualification and nurturing.
For example, AI-powered sales assistants can be responsible for contacting anyone who has expressed some initial interest in the company – such as downloading a white paper, getting a badge scanned at a conference, or requesting additional information on the company website. Or it can proactively engage customers to resolve support situations from simple questions to complex transactions in an automated self-serve channel. Issues can also be seamlessly escalated to a live agent when a self-service environment is not effective.
These conversational commerce tools with ML algorithms can create a personal concierge in a self-service or even assisted-service engagement. For example, users can text or chat restaurant reservation requests, get product information based on contextually relevant data or place an order without adding to a shopping cart. These engagement tools work most effectively when integrated into a transactional e-commerce system. For example, a customer could type or speak 'find me red platform shoes for under $150.' (Additionally, rich media elements can be included, such as a picture of the desired item to trigger product discovery and inventory availability.)
The customer would then get a personalized product recommendation along with express shipping selected, and color and size already accounted for; they can pay and track shipping status all within the confines of a digital mobile conversation. If a service request is needed, depending on the complexity, it can be handled through an automated self-service conversation or automatically escalated to a customer service representative.
By unlocking information that is generated across multiple customer interactions and across several channels and sources, brands can exceed customer expectations. Yesterday's world was about one-way customer interactions; today's is about self-directed, on-demand, two-way engagement anywhere, on any device. Customers want to communicate on their own terms in their preferred channels. Depending on the urgency, nature and overall context of the customer's situation, self-service is one of the most important engagement channels, with many interactions beginning on mobile devices. Conversational experiences are well on their way to being a linchpin in an organization's ability to not only survive but flourish in a competitive, consumer-empowered world.
Chatbots accommodate the anytime, anywhere commerce and service experiences that consumers expect from the businesses they engage with. They serve as a logical and familiar interface that appeals to consumers across generations. In many ways, chatbots are a natural extension of the behaviors consumers are already accustomed to. Additionally, it is the invisible, voice-activated interfaces powering digital assistants like Amazon's Alexa, Apple's Siri or Microsoft's Cortana that are the first wave in a coming evolution of interactions that will remove dependence on a particular device or contact channel.
The number of consumers that now own a mobile device with an embedded digital voice assistant is substantial, with 23.7% of Consumer Representative Survey Q3 2017 respondents using it for a digital assistant daily, and 19.5% using it weekly. Smart speakers have blended hardware, software and services into an intuitive and fluid interface, and it's not surprising to see consumers reacting positively to them. In 451 Research's 2017 ISP & Smart Home Trends report, over half of Amazon Echo owners answered that they use it daily, and respondents in VoCUL's Consumer Trends Representative Survey Q1 2017 said 29.5% of the time they use their Amazon smart speaker to shop on Amazon.com. These data points are early indicators that as voice and chat interfaces grow in usage, businesses will be able to reach and engage their customer wherever they are, whether in cars, living rooms or stores.
The evolving nature of the technologies powering conversational experiences
The success and development of conversational commerce thus far is attributable to advancements in AI, intent analysis with ML, automatic speech recognition and NLP. Chatbots have come into existence as a business tool, and can at the very least have basic conversations with users, due to AI integration. However, since they are emerging technologies based on emerging technologies, the state of chatbots and digital assistants is directly indexed to the evolution of AI, ML and NLP.
Fluid and natural bidirectional conversations and other functionalities are in a stage of infancy and low adoption. What will largely impact the extent to which the technology moves forward is amount and quality of data available. Aggregating data that may be dispersed and siloed, as well as converting that data into a format that can be processed, are clear challenges confronting businesses. However, as AI matures and becomes better understood by IT administrators and organizations, its capabilities will expand and improve.
While some misinterpretations by chatbots are reasonable and forgivable (human communication is also far from perfect), chatbots and digital assistants are notorious for generating illogical responses. Challenges when communicating with these technologies are ultimately an effect of how robust the NLP is. For example, 77% of respondents in our ISP & Smart Home Trends (Leading Indicator) survey April 2017/January 2017 were not very satisfied with the accuracy of Alexa – a percentage that is not lamentable, but should be higher for consumers to be more comfortable and see the value in smartbots.
Facebook has also played a vital role in shaping the state of conversational experiences, especially for service and commerce interactions. But while the Facebook Messenger platform has become one of the initial channels where organizations have implemented chatbots, the business case behind doing so is not totally obvious. Facebook itself will need to continue to adapt to consumer preferences and a dynamic IT landscape, and so too will conversational technologies and how they materialize in customer engagement.
Conversational commerce experiences will also extend into new social platforms, as well as other frequently used channels such as business websites and apps, marketplaces and digital wallets. Businesses thinking about the future of the space should look to WeChat and AliPay as powerful case studies that both underscore the potential of conversational commerce, and demonstrate the requirements for bringing it to life. These applications have unlocked new value for businesses and consumers alike by converging messaging, social engagement, commerce and payments at scale. A coalescence of these ingredients will undoubtedly be required for any businesses looking to capitalize on the conversational commerce opportunity.
Real-world deployments are just getting started
Current-generation chatbot deployments are primarily limited to basic self-service and support functions. However, thanks to integration with digital wallets like PayPal and Masterpass, several food establishments have enlisted chatbots through Facebook Messenger to bring ordering ease to their customers. For companies with a high volume of online orders and a Facebook presence – such as Subway, which released its chatbot service in August 2017 – implementing a Messenger chatbot is a logical move.
Other restaurants that have gravitated toward Messenger for chatbot deployments include The Cheesecake Factory, Starbucks, Taco Bell, Domino's and Pizza Hut. We expect other messaging platforms to see increased attention. For instance, Apple's Business Chat allows businesses to communicate with customers, including performing transactions through Apple Pay, and presents a natural opportunity for conversational commerce use cases.
Several financial institutions have integrated, or are in the process of integrating, chatbots into their online and mobile banking channels. Capital One, for instance, launched Eno in May 2017, which can perform service-related tasks like paying credit card bills and retrieving account balances. Bank of America's forthcoming Erica chatbot is intended to go beyond service and provide contextual financial advice.
Companies may be compelled to adopt conversational technologies because they serve to ease more than just the experience of the consumer. They can also be relevant to employees in roles involving customer engagement – sales, contact centers/support and marketers – by acting as intelligent tools that are to be incorporated and used in conjunction with various employee applications such as CRM. These technologies may manifest as data repositories or mechanisms for lead engagement/qualification or task automation (for example) that help employees gain insight and analytics, and be more efficient.
In the longer term, more use cases and verticals that benefit, especially in regard to how customer experience is orchestrated as a whole, will emerge. There are already instances of chatbot usage to enable personalization and product recommendations for marketing purposes, such as H&M and Sephora's services on messaging platform Kik. But we expect capability enhancements to gain traction and increase the scale of adoption of these functions. In advertising, collected data, insights and analysis could be leveraged to improve targeting, measurement and attribution. Targeted paid outreach through chatbots may materialize as a common customer engagement channel.
A dynamic conversational market
Despite some consolidation in 2017, the list of vendors of bot frameworks is still rather extensive: Kasisto, Conversable, Inbenta, Kore.ai, Passage AI, Flow.ai, ReplyYes, Gupshup, IPSoft, Twilio, Nanorep (acquired), Conversica and Verint are only a portion of this list. Customer-service-specific applications include Salesforce, 7, CafeX, Inbenta and Helpshift, LivePerson AnswerDash, Zendesk and Interactions LLC.
The chatbot landscape has been active and evolving within the past year, similar to our predictions. Some companies have pivoted strategies by offering new or different services. As Figure 2 illustrates, companies of different sizes and verticals have shown interest in chatbots for varying reasons. Many seek to bolster their B2B product portfolios with AI, while others want to improve their own customer experience and other front-office related services.
Figure 2: Recent Conversational Technologies M&A Activity
Conversable, for one, offers a combination of a technology platform and a set of services for designing and managing automated conversations. Privately held IPsoft has been in this sector since 1998, and has a fully developed chatbot platform that may be useful should a larger player want to leap directly into the arena – notwithstanding the potential target's 2,500 employees and potentially high price tag.
Smaller but older providers in the space like LivePerson or Interactions may be targets of larger platform suppliers, or be acquirers themselves as they seek systems that fit into niches, such as Reply.ai. In a similar vein, we've already seen Smartsheet with its Converse.AI buy, and HubSpot with its MotionAI purchase, follow a similar strategy. Other potential acquisition targets are Passage AI, Gupshup, ReplyYes and Flow.ai. As we have already seen, chatbot vendors may decide to dabble in different areas of chatbot usage where they are not currently operating, namely business collaboration and communication use cases, or on the customer engagement, marketing and commerce side.
Keith Dawson is a principal analyst in 451 Research's Customer Experience & Commerce practice, primarily covering marketing technology. Keith has been covering the intersection of communications and enterprise software for 25 years, mainly looking at how to influence and optimize the customer experience.
Jordan McKee is a Principal Analyst leading 451 Research’s coverage of the payments ecosystem. He focuses on digital transformation across the commerce value chain, with an emphasis on the major trends impacting payment networks, issuing and acquiring banks, payment processors and point-of-sale providers.
Sheryl Kingstone leads 451 Research’s coverage for Customer Experience & Commerce, which covers the many aspects of how customer experience is a catalyst for digital transformation.