Digital assistants are not at this point a shocking new concept—after all, between Apple’s Siri and Android’s Cortana, most of us have digital assistants in our pockets already. However, taking the DA idea to an enterprise level is a whole other kettle of fish—and requires integration with other online trends, like search-engine based analytics.
Forbes has listed digital assistants as No. 4 in the Top 7 Online Marketing Trends That Will Dominate 2016, noting that marketers will have to make their business information accessible for use by the likes of Siri and Cortana. However, companies are looking to go further than that, and are fomenting the rise of digital employees, powered by intelligent, natural language interaction (NLI) apps.
These employees are the gateway to customer contact centers, sales employees, executive PAs that update systems and the business analysts that have lightening quick insights on markets and trends.
For instance, Shell has used Artificial Intelligence’s Teneo platform to develop virtual assistants called Emma and Ethan to help and advise customers on the technical aspects of Shell’s lubricant products in the U.K. and U.S. markets. Emma and Ethan know the details of more than 3000 Shell products, and understand more than 16,500 different characteristics of those products, providing customers with a wide range of answers to queries and relevant technical information such as product pack availability, physical property details including density or flash points, and product performance benefits.
Emma and Ethan can also help find lubricants for specific equipment by linking customers through to Shell Lubematch, and can recommend the nearest distributors in the U.K. and U.S. This type of in-depth knowledge allows Emma and Ethan to answer a wide range of questions.
In the latest version of Teneo, AI is using machine learning and auto-coding to enable Teneo to learn, predict and proactively recommend improvements to an application. This enables organizations to quickly build and deploy NLI applications that address the majority of customer queries within very short timescales.
For instance, in the Shell example, if the customer doesn’t provide all the information needed, Emma and Ethan ask their own qualifying questions in return to ensure the most appropriate answer is given.
“The key is in the technology that you chose to build your digital employee as it will dictate how fast you can react in the future,” said AI, in a blog. “Delivering natural-language applications to grow with your business requires a platform that is scalable, multi-lingual and device independent; one that can seamlessly integrate with back end systems and third party applications. But equally important is that it needs to be easy to use.”
A caveat: Lengthy development timescales, escalating costs and highly complex computational linguistics is the death knell to many digital assistant projects. So, an enterprise DA platform also needs to deliver artificial intelligence using readily available business information and search-engine analytics. Digital assistants like Siri and Cortana do utilize traditional search engines, but only when necessary to find information. Enterprise DAs should be hooked in all the time, and accessible via mobile devices.
“As devices get smaller, the more we all rely on natural language to communicate our needs,” the company noted. “[The] suggestion that search will eventually be dominated by digital assistants resonates with events already taking place, such as mobile overtaking desktop for Internet access. Ensuring your business is a part of that conversation means aligning your digital employee strategy with future trends – today.”