When it comes to identifying the top emerging technologies that will have the biggest impact on customer experience, it's important that organisations look at the industry rends in general as well as their competition to inform their strategic plans for CX.
Key Aspects
Technology leaders supporting CRM strategy and the customer experience should consider following key recommendations as part of their overall CX investment:
Explore the opportunities represented by the five key emerging technologies (AI, multichannel customer engagement, etc.) by creating three to five business technology scenarios that tell a story that generates enthusiasm.
Discourage short-term focus on financial goals when deploying new tech for CX. Instead, focus on how emerging tech will impact your customers and the ability of your organization to deliver the desired CX.
Model a business moment or an internet-connected thing as a customer for your enterprise to identify how business processes, people and customer experience changes.
Top 5 Emerging Technologies impacting customer experience
Technology is becoming a critical component of customer experience initiatives. As we can see, more than two-thirds of customer experience projects now involve technology. In addition to using mature CRM technologies such as case management, organizations must also follow emerging technologies to determine how they can improve the customer experience. Emerging technologies are disruptive by nature, but the competitive advantage they provide is not yet well known or proven in the market. Leading organizations will be implementing them with the knowledge that financial returns may take years to emerge, even as these technologies impact and improve the CX.
In a recent Gartner survey, exploring which emerging technologies are expected to have the biggest impact on CX projects in next three years. Across the entire sample, artificial intelligence, virtual customer assistants or chatbots, and omnichannel (multichannel) customer engagement were ranked as the top three.
Emerging Technologies Expected to Have Biggest Impact on CX Projects in the Next Three Years
Percentage of Respondents. Sum of Top Three Ranked
Figure 1. Emerging Technologies Expected to Have Biggest Impact on CX Projects in the Next Three Years
When looked at self-reported organizational CX maturity, those at beginner levels ranked omnichannel customer engagement, AI and real-time event-driven application architecture as the top three. Respondents from organizations with higher levels of maturity placed AI, virtual customer assistants, real-time event-driven application architecture and IoT as their top choices.
#1: Artificial Intelligence
Artificial Intelligence applies advanced analysis and logic-based techniques including machine learning to interpret events, to support and automate decisions, and to take actions.
AI is composed of dozens of technologies with varying degrees of intelligence and autonomy. We break AI technologies into three main types:
Systems that engage in a humanlike way. These include computer vision, chatbots and agents, and natural language interfaces.
Systems that operate themselves, make decisions and/or improve themselves with no human in the loop. Examples include self-optimizing smart machines, autonomous vehicles, and detection systems that learn and protect against new threats in real time.
Advanced techniques for generating insight, such as deep neural networks. We might informally call these “analytics on steroids.” They can be used, for example, for prediction, market segmentation, and listening for weak or hidden signals in data, images, and sound.
AI-enabled capabilities are infusing every software category, including CRM and customer analytics. AI-powered natural language recognition makes possible new categories of apps, such as virtual customer assistants, virtual personal assistants (VPAs) with voice interfaces and chatbots with text interfaces. Using AI in physical products is enabling the creation of intelligent things that can interact with customers, such as advanced robots.
Understandably, interest in AI is high given the level of hype surrounding the technology. CX leaders must invest the time to learn and understand the possibilities and risks of these technologies.
Impact on Customer Experience:
Real-time customer insights: What happens when customer interactions and intent continuously come from both human and nonhuman customers? How do you collect, process and act on the intelligence as fast as your customers think you should? Organizations are experiencing an ever-increasing volume and richness of data that’s hard to keep up with. We believe that the speed and precision of AI technologies and analytics, in addition to human insight, will provide the continuous intelligence needed for the customer experience of the future. We also see AI technologies enhancing text, sentiment, voice, interaction, IoT and even traditional survey analysis.
Creating precision customer experiences: Survey respondents ranked personalized experiences as the fourth highest CX project priority, behind CX metrics, voice of the customer and increasing the speed of product/service launch. Combined, these priorities point to a personalized, contextualized experience based on the customer journey, and a possible competitive differentiator. This will require organizations to leverage new types of analysis and data sources. Rather than attempt multiple high-risk initiatives, a marketer or salesperson should leverage existing or new systems driven by AI capabilities to assist with making better decisions with less wasted effort. In the retail industry, online retailer Stitch Fix combines the expertise of human stylists with the insights and efficiency of AI to analyze a variety of trends. It combines public information on fashion trends with personalized information on the customers’ preferences, purchasing history and social media posts. This results in a personalized and curated box of clothing and accessories delivered at scale. Stitch Fix is even using this insight to design its own line of merchandise.
#2: Virtual Customer Assistants and Chatbots
Chatbots and virtual assistants are gaining tremendous interest in the market. Twenty-six percent of CIOs report that chatbots are the main AI-based application in use in their enterprises. The ability to chat through text, or even talk using voice, with applications, services and brands is fueling a wave of innovation in customer experience. Successful virtual customer assistant and chatbot deployments start with identifying use cases that will result in capabilities your customers will want to use.
The difference between chatbots and VCAs is that chatbots are functionally narrow and often highly specialized conversational agents that frequently use, but are not limited to, text chat. In contrast, VCAs in general are more capable conversational agents that can adapt to broader, interactional natural-language conversations of a transactional, rather than purely informational, nature.
Top CRM virtual customer assistant and chatbot use cases are either customer-support-focused, such as exposing a knowledge base, offering account or order management self-service, or customer-engagement-focused, such as enabling product research, marketing or digital commerce capabilities. Chatbots can be for any audience.
Your virtual customer assistant’s ability to converse and improve its conversation capabilities over time is one critical way that will make it unique and successful. VCA and API-based CRM integrations will not differentiate your customer experience if they cannot support the necessary conversation flow along a customer’s journey.
Impact on Customer Experience:
Making the experience more human, not less. Role-based assistants can significantly improve interactions with employees, customers and partners. These assistants can handle many routine information-driven workloads (for example, simple customer or employee service requests). This frees humans to focus on more complex and higher-value tasks that customers value.
Reducing customer effort. VCAs enable better customer experiences on company websites and can be utilized in multiple ways to accomplish different objectives. Connect with and better support B2B buyers through virtual customer assistant use cases such as product discovery and discernment, lead generation, customer service and technical support.
#3: Omnichannel Customer Engagement
Omnichannel (also known as multichannel) customer engagement is a capability arising from the evolution of customer service contact center applications, such as case management. Currently, these applications have shifted to the multichannel customer engagement center. They handle all incoming and outgoing media channels and devices, as well as handling the customer engagement rules, content and workflow. The new capabilities facilitate omnichannel automation of engagements in web, app, and consumer messaging channels, and in community and social engagement with customers on any social channel. The capabilities also facilitate heavier use of personalization, advanced analytics, video chat, co-browsing and mobile support.
The customer engagement center offers new capabilities in addition to those found in traditional contact center applications. These include real-time guidance, predictive customer analytics, and automation of engagements. The result is the potential to provide customer service and support by engaging intelligently — both proactively and reactively — with customers by answering questions, solving problems and giving advice.
Impact on Customer Experience:
Meeting customers when and where they want to be engaged. Customers use many channels when they interact with organizations. It will be impossible to deliver a personalized customer experience without understanding how customers use and experience the different channels by which you communicate. Multichannel customer engagement technologies can provide the foundation for this.
Educating the organization on customer behaviors. Improving customer understanding across the organization is essential to developing a customer-centric culture. Something like a multichannel customer engagement center can provide a single source of truth about customer behaviors. This will help the organization become more fact-based in decision making versus anecdote based.
#4: Real-Time Event-Driven Application Architecture
The basic premise of any digital business application is that it is responsive to new information and the states of the actors involved — that is, customers, staff, stock or processes. It then transforms such responsiveness into competitive benefit through real-time context-aware decision making. Not only does the digital business detect new information — typically provided by “events” — in near real time, but it responds accordingly. It does this through either automated “decisions” or notifications to business users to act.
Some business events, or combinations of events, constitute “business moments.” These are transient opportunities in which people, data, businesses and things work together dynamically to create increased value and increasingly personalized customer experiences. These detected situations call for specific business actions. The most significant business moments have implications for multiple parties. For example, they engage multiple applications, business units or partners.
Event-driven architecture (EDA) is at the very heart of real-time-sensitive digital business. Organizations capture real-world business events in digital form as they happen by “listening” to event sources like IoT devices, mobile applications, ecosystems, and social and business networks; for example, when a customer places an order, an event occurs.
Impact on Customer Experience:
Providing in-the-moment guidance and help to users based on their current situation. Basic functions like the next-best action or location-based recommendations are examples of this. Eventually, we expect increasingly personalized mobile application experiences will drive all forms of customer engagement.
Detecting and discovering business moments. A digital business monitors event streams to stay aware of the current context and thereby make more intelligent decisions. In a competitive market, more intelligent decisions translate into better customer service and greater success for the business. A digital business monitors event streams to be alert to the presence of business moments. Sensing business moments and responding to them in “business real time” is central to a digital business’s commitment to its customers and ecosystem partners.
#5: Internet of Things
We define the Internet of Things as a network of physical objects (things) that contain embedded technology to sense or interact with their internal state or external environment, and that can send and receive data to or from a remote digital platform. The IoT comprises an ecosystem that includes things, communications, applications and data analysis, security, monitoring, and management and professional services. We estimate that there will be 23 billion internet-connected devices by 2022. Many of these endpoints will directly interface with customers. Examples include:
Digital advertising found on purpose-built advertising columns, telephone kiosks, public transport street furniture (such as bus shelters) and garbage bins.
A networked trash bin equipped with sensors to monitor usage, air quality or capacity.
Hand-wash stations used to ensure compliance with regulations regarding hand-washing procedures for medical staff.
Drones that deliver a variety of payloads and monitoring equipment.
Cargo shipping containers that can be tracked in multiple ways, from location to monitoring their contents.
Equipment that orders its necessary parts to ensure continued, reliable performance.
We expect IoT devices will become increasingly intelligent, potentially delivering the power of AI-enabled systems everywhere, including the home and medical facilities. As intelligent things evolve, they’ll start to work together in collaborative swarms. For example, in terms of the order and after-sales service, it is notable how fast predictive maintenance is being enhanced using connected assets coupled with machine learning algorithms. As an example, Pratt & Whitney’s latest engine, the PW1000G, has 40% more sensors than the V2500 brought into service in 2008. Performance data that was previously relayed twice in a flight can now be sent every 2.5 seconds.
Additionally, we believe things will gain the capacity to buy, sell and request service. This will result in new opportunities for revenue, efficiencies and managing customer relationships. It will also present new challenges to data security and privacy. Things with these abilities represent new customers that organizations will be able to sell to and governments can tax. Some “things as customers” have already been enabled by humans to have the ability to negotiate, buy and sell.
Impact on Customer Experience:
Engaging customers through everyday things and places. Internet-connected devices and places, backed up by intelligent systems, will provide additional touchpoints for customers along their journeys to engage and for organizations to learn. Don’t just focus on autonomous vehicles as they become new customer engagement points; think about the home, the workplace, the hospital, the vacation, and where entertainment takes place, and the things used in each of those locations. For example, expect robots to steadily improve and drive engagement in more settings such as retail, healthcare and transportation hubs.
Engaging customers who may not be human. How do you sell to a thing or machine? What will get a machine to buy from you when its decisions are based on algorithms, not emotion? How will your human customer service agents handle requests from millions of machines? What does “customer experience” even mean for a machine? These are key questions that all organizations will need to address as intelligent machines gain the capacity to buy, sell and request service on behalf of their human owners.