Here are the trends that  should inform enterprise investment and deployment of Conversational AI, Cloud-based Contact Centers and Intelligent Assistance in the coming year.

Conversational Clouds Replace Contact Centers

The writing is on the wall. Contact Center as a Service (CCaaS), and its close cousin Unified Communications as a Service (UCaaS) are dead. The jury is out on Communications Platforms as a Service (CPaaS) with Twilio and Vonage duking it out with 8×8, RingCentral and a few other global players (think Ribbon Communications) with a legacy in what’s now thought of as communications plumbing. Replacing Contact Centers is the Conversational Cloud, which is a product of coupling of call-processing, speech processing (both automated speech recognition and text-to-speech rendering), speech and text analytics, and multiple flavors of cognitive resources. All of these resources are hosted in the server farms that comprise the clouds operated by the companies that dominate e-commerce (Amazon/AWS), enterprise computing (Microsoft/Azure), CRM (Salesforce/Service Cloud) and search (Google Cloud).

IT Service Management (ITSM-exemplified by ServiceNow) and the cadre of companies specializing in robotic process automation (RPA-UIPath, AutomationAnywhere, Kofax and a few others) have a role to play, as well. The signal event was the half-billion-plus dollar investment by a consortium that is led by the venture wings of Salesforce and ServiceNow (along with Zoom Video Communications). At base, they are ensuring the future of an excellent go to market partner; however they are really putting a fine point on the fact that the distinction between a contact center, video collaboration platform and pure automation platform is fuzzy once it gets into the cloud. The most promising way to frame the opportunities involved is to think of specific applications and use cases that are made possible by the intermingling of AI- and data-infused resources in The Cloud.

Smart Search Replaces Knowledge Management

AI infusion is riding the wings of automation and one of the major points of entry is in the area of search and, more specifically, discovery. Computing giant IBM has known this for some time as evidenced by the success enterprises have had using Watson Discovery to discover patterns in the queries launched by customers and employees and organizing responses accordingly. Smaller firms, like Talkmap have, likewise, shown how its systems can ingest, analyze and categorize voluminous amounts of call recordings and chat transcripts in ways that are not humanly possible.

From a C2B (customer to business) perspective, “bot” platforms from the likes of Nuance, Creative Virtual, Amelia, Verint and other Conversational AI specialists are able to understand intents from natural language input (conversations) and find responses from within documents, regardless of whether they are product manuals (PDFs), spreadsheets (XLS), customer records or elsewhere. In the past, great attention had been paid to data hygiene and the labor intensive processes involved in extracting, organizing and converting data. Ideally, in 2022, enterprises will finally answer the question “was this trip necessary?” with the money-saving answer “no”.

Conversational Intelligence Reflects the Real Voice of the Customer

Customer Satisfaction (CSAT) scores are constructed on the clay feet of post-contact surveys or worse. Most often, a self-selecting group of customers choose to respond to a short set of questions that share a scale with popular ride sharing programs (“one is the lowest and five is the highest”). The results are distilled into another number (between 1-100) that has become the benchmark for reporting customer satisfaction, although the relationship between CSAT scores and actual customer satisfaction is only made manifest if there is a decline or increase in other so-called Key Performance Indicators (KPIs). This includes customer retention or the response to the simple question “would you recommend this company to a friend”… a question to which a “yes” answer has a direct, positive impact on a company’s Net Promoter Score (NPS).

In 2022, brands can capture 100% of the conversations they have with customers over both text and voice channels. They can also employ advanced analytics to detect customer sentiment, often while the conversations are taking place. The same speech and text analytics technology that can recognize intent can be applied to detect patterns and context in the words that are typed or spoken that indicate distress or dissatisfaction. It is a lot more than a word-spotting technology tuned to see or hear the name of a competitor of the tell-tale indicators of the intention to change vendors. Or more recently, CI specialists like Marchex and Invoca have employed the philosophy of listening better to help accelerate sales efforts or recover lost sales.

Intelligent Authentication Focuses on Customer Experience

In 2021, “Customer Identification and Access Management” (CIAM) became a “thing” as solution providers added ease-of-use features to old-guard methods for logging on to enterprise networks and services. The leaders in single-sign approaches to multiple services (like Facebook, Google and Ping Identity) played important roles in defining CIAM, joining specialists in enterprise access management like Microsoft and Okta. All operated under the handicap of trying to fit the square peg of legacy IAM, which is meant to make it hard to gain access, into the round hole of customer experience, which tries to keep things simple. As we will learn in 2022, in the CX world, convenience always wins.

Enter the community of solution providers that “get” Intelligent Authentication. From both a CX and security perspective, they support passive or frictionless, yet strong authentication by introducing biometrics (voice, face, fingerprints, behavioral). They employ Deep Neural Network- (DNN-) based analytics to detect the sort of anomalous behaviors or characteristics that indicate the presence of an imposter. They use these technologies to derive a risk-score that can be applied to an individual and that individual’s activity to ensure sufficient confidence from the banks, telecom companies, retailers and others that they are protecting the identity and privacy of their customers in the course of conversations over messaging channels and mobile phones.

Cloud-based “Conversational AI” Becomes a Commodity

Commodities, in the form of affordable APIs for the entire alphabet of technology offerings: ASR/TTS, NLU/NLP, analytics and cognitive services, are the basic building material for developers to construct the robust chatbots, voicebots and agent assistants that define conversational commerce. They fuel automation of repetitive tasks, training of digital employees, increasing productivity of live employees and, increasingly, the acceleration of sales efforts and application of marketing efforts with direct impact on revenues. When taken collectively, the result is a very positive return on investment (ROI) from spending on AI-infused resources in the Conversational Cloud.

Categories: Conversational Intelligence, Intelligent Assistants, Intelligent Authentication, Articles