As we enter 2018, it’s clear the expectations of intelligent assistance providers and enterprise practitioners are more in balance than ever before. It’s also clear that the number of “known knowns” is growing rapidly.
As we enter 2018, it’s clear the expectations of intelligent assistance providers and enterprise practitioners are more in balance than ever before. It’s also clear that the number of “known knowns” is growing rapidly.
Here are five examples of how and why we will learn more about the complex workings of conversational commerce in the coming year.
Solution providers have access to a history of FAQs, recordings, call detail records (CDRs), chat transcripts, product literature, CRM records, and even interactive voice response (IVR) scripts to inform IAs on the basic intents of customers in the top vertical categories. Even if you are not Google, Facebook, or another one of the tech giants that benefit from exposure to inconceivably large data sets, it’s possible to access quality insights about your consumers. Big data is no longer required to get started in conversational commerce.
IAs have a near immediate negative impact on operating costs and positive impact on customer satisfaction, but their ability to replace live agents and assistants is vastly overrated. To the contrary, the need to monitor and constantly tune responses to keep them relevant and satisfactory to prospects and customers is growing and will provide a source of new of jobs and permanent employment.
Categorization? √ Understanding? √ Conversation? Nope! Some solution providers are better than others at recognizing context, promoting turn-taking, and allowing customers’ minds to wander and jump around topics, but the game board is still largely governed by statistics and branches on logic trees that can come up empty. When that happens, IAs are no better than poorly designed, frustrating IVR apps. Watch for some real advancements to correct this situation in 2018.
It’s a shame that the branded Big Four (and other heavy hitters in the tech industry) have elected to create separate and unequal “platforms” for messaging bots and voice first agents. Companies would like to see intelligent assistance infrastructure that lets them develop a service once and have it render correctly on all devices and in all modes. Instead, in the short-to-medium term, we are stuck with the same, duplicated efforts that plague mobile apps (iOS versus Android – and a few, lesser others). Separate staffs maintain the code base for Alexa skills versus Google actions, Facebook Messenger bots, and a few, lesser others.
Now that we’ve tackled the “known knowns,” we can expect start-ups and stealthy entrepreneurs to emerge in 2018 to tackle “known unknowns.” They will do this by blending machine learning, natural language processing, knowledge management, and other elements of AI with the human touch. Some might even expose and exploit the “unknown knowns.” Their nature is to be determined, but there is always room for break-through technologies. At the very minimum, solutions will span the traditional lines of demarcation between customer care, marketing, user ID, and authentication and relationship management platforms.
Adoption and use of conversational commerce will accelerate in 2018. Forces are aligning for people to employ conversational technologies at home, in their cars, and in their offices. It’s up to solution providers to manage the complexity of underlying processes to keep it simple for end users and enterprises alike.
This article originally appeared on the Opus Research blog. Copyright 2017.
Dan Miller is founder and lead analyst at Opus Research, a market research firm focused on conversational commerce.
