Richard Snow's Analyst Perspectives

IBM Watson Engagement Advisor for Smarter Customer Service

Posted by Richard Snow on May 25, 2013 10:55:01 PM

Recently my colleague Mark Smith wrote about the IBM Watson platform. Mark is our expert on technically complex subjects like IBM Watson and‎ cognitive computing and VR_2012_TechAward_Winner_Logothe value it can provide to organizations and wrote an educational white paper on the topic. In fact IBM Watson was awarded the 2012 Ventana Research Technology Innovation Award. I focus on the customer and the customer experience, but I became engaged with the launch of the IBM Watson Engagement Advisor, which uncannily brings the two together.

I conclude from my research into customer experience management and discussions around the customer experience that consumers want three related things from companies: to recognize them as individuals, to handle any interaction within the context of their overall relationship and previous interactions, and to provide answers that are personalized to their individual needs. Furthermore, as I described in my recent blog about the 2.0 customer, they are increasingly likely to interact with companies through smart mobile devices. Added up these requirements present a major challenge for companies, and the solution lies in data. Organizations have ever increasing volumes of customer data, found in records in CRM, ERP and other business applications, letters, forms, email, call recordings, scripts collected during Web and chat sessions, text messages, video recordings and now social media posts. These all add up to what we call big data, and it comes in structured, semistructured and unstructured forms. To provide a personalized, in-context response to any interaction, companies have to make sense of all this data and build applications that follow typical customer interactions (for example, a request for information, a billing inquiry, a sales inquiry or a complaint) and use it as the interaction is taking place.

This is the context in which IBM Watson Engagement Advisor debuts. It uses the Watson platform to analyze all available data, make sense of it and provide information back to the application the consumer is using to interact with the organization. Its built-in natural-language processing engine allows it to extract relevant words and phrases and combinations of both from text-based input and to search for relevant data in customer records, documents and other relevant sources. To use IBM’s favorite word, Watson is smart, so once it has followed a process, it learns from that and can improve how it carries out the process in the future. The consumer can thus interact using natural language and receive answers that are personalized and in context, and which should improve in both senses over time and experience.

I recognize that companies may have difficulty understanding this new approach to customer experience management. To engage them IBM has announced an early customer adoption program in which it will provide support and guidance on what interactions are appropriate to automate in this way and how to configure the technology and gain access to the data sources; the target of the program is to have an initial system running in six weeks. My recommendation here is the same as I made last year when several vendors announced tools that help companies build mobile customer service apps: Think of the customer first and build apps to match what they want, not what you think will improve the efficiency of your interaction-handling.

It is often said that customer service is the only true differentiator in competitive markets. The challenge I see is that the boundaries between marketing, sales and customer service are blurring, and what consumers want is answers, and they want them immediately during every interaction. As data volumes and types grow, finding answers is like looking for the proverbial needle in a haystack. Watson may be a platform capable of matching up to this challenge. I recommend that companies looking to improve the customer experience take a close look at the IBM Watson Engagement Advisor.


Richard J. Snow

VP & Research Director

Topics: Social Media, Customer Analytics, Customer Experience, Operational Performance Management (OPM), Social CRM, Mobile Apps, Self-service, Cloud Computing, Customer Service, IBM, Business Performance Management (BPM), Call Center, Cognitive Computing, Contact Center, Contact Center Analytics, CRM, Customer Performance Management (CPM), IBM Watson, Text Analytics

Richard Snow

Written by Richard Snow

Richard leads Ventana Research’s Customer and Contact Center Performance Management research practice, which is dedicated to helping organizations improve the efficiency and effectiveness of managing their customers, throughout their lifetime and across all touch points, including the contact center. He conducts research exploring the people, process, information and technology issues behind customer operations management, contact center management, and customer experience management. He also works with senior business operations and IT managers to ensure that companies get the best performance from today’s highly complex application products. Richard has worked in management and consulting leadership positions in the technology industry including with Price Waterhouse, Sema Group and Valors. In his work, he has been involved with all aspects of delivering highly complex IT solutions to a variety of clients in the telecommunications, financial services and public sectors. Richard has specialized in delivering customer care and billing solutions for telecommunications operators, and several multi-channel contact centers for organizations in both the public and private sectors.