March 26, 2019

Marketing Executive’s Guide to AI Assistants and Conversational UIs

As the world of marketing and customer service becomes increasingly automated, AI assistants (driven by artificial intelligence) and conversational UIs (user interfaces that mimic human interaction) are becoming more pertinent to small, mid-sized, and enterprise businesses.

Automated assistants, which began as extremely rudimentary versions of a phone tree, – “Press 1 for your balance, or press 2 to speak to a banking representative” – are a excellent example of early automation in the customer service arena. As artificial intelligence began to drive automation, a new kind of assistant was created: one that could interact with consumers in a human-like way.

As channels opened up in response to mobile device usage and the introduction of “kiosk” based customer service & sales, AI assistants were able to expand into complex user interfaces. The ability to be “conversational” is key to consumer acceptance of AI interfaces. The race is on to develop AIs capable of learning from past interactions and apply that learning to predict future conversations.

There are four main levels of AI assistants/ conversational user interfaces in use today. Choosing the best type to help you achieve your goals is the first step moving you towards automation that can increase productivity, enhance consumer satisfaction, improve ROI, and free up human employees to complete more complex tasks.

Do you have questions about Enterprise-class Conversational AI?

AI Assistants for Notifications

The first level of automated assistant is one-way. It is triggered by an event, which can be designated according to a calendar plugged into a database. For example, a home insurance carrier or agent might have an automated assistant that sends a text message or a Facebook message when a policy is coming up for renewal, on the date 30 days before policy expiration.

Benefit from a marketing perspective

A notification with a link to renew their policy can increase the chances of client retention, by making it easy for the customer to renew for another year. The renewal message can also carry a short communication about new coverage available to increase the likelihood of upgraded coverage.

AI Assistants for FAQs

Question/ response AI assistants are one of the most common types of assistants currently in use, often in chatbot form. Users can ask simple questions and the chatbot can respond with the appropriate answer. In more advanced versions of an FAQ bot, a basic dialogue can be initiated with a request for clarification from the bot and additional input from the user.

Benefit from a marketing perspective

A typical use for a FAQ chatbot in the marketing funnel is to answer customer queries immediately with the best information possible, regardless of whether the chatbot is hosted on a company website or deployed using Facebook Messenger or WhatsApp.

Learn how to launch your Conversational AI pilot in less than 30 days.

Conversational UIs for Contextual Interactions

AI assistants that have been programmed with a broader range of knowledge and the ability to navigate “if/then” scenarios can be used to deliver more intensive customer service by asking questions and analyzing the answers given by the user.

For example, a quote can be derived and a purchase made of service or a product based on customer input. In the case of a gift basket delivery, a basket can be built, items added, the address provided, and shipping calculated through interaction with a conversational UI that provides a human-like experience.

Benefit from a marketing perspective

Sales can be made “hands-free” even if customization is desired. Upsell and cross-sell opportunities can also be explored based on customer input as details about the buyer of the product or service are derived from the context of the conversation.

Do you have questions about Enterprise-class Conversational AI?

AI Assistants and Conversational UIs for Personalized Service

The world of AI assistants and conversational UIs can merge to provide exceptional personalized service. The massive amounts of data available to businesses can now be analyzed and micro-segmented down to individual consumers building highly accurate profiles of buyer history, wants and needs.

For example, a banking customer who recently purchased a home and whose transaction records show baby-related purchases can be targeted to sell life insurance in anticipation of a growing family.

Benefit from a marketing perspective

Consumer behavior and requests can be accurately predicted, and next best actions calculated and deployed in real time to guide consumers in the desired direction, increasing customer acquisition, reducing churn, and improving customer lifetime value (CLV).

As artificial intelligence shifts away from mere “data in, data out” scenarios, deep learning allows conversational UIs to be built drawing on and extrapolating from massive data sets. The result –  predictive analysis with over 90% accuracy. Companies that implement omnichannel communications with consumers see a 5%-10% increase in customer satisfaction.

By utilizing AI assistants and conversational UIs the world of marketing gains a powerful set of new tools to aid in reaching objectives, meeting both short- and long-term company goals.