The Virtual Assistant is the Future of Business

April 23 2018

Businesses need smarter, more intuitive tools to gain real-time insights from their data. But the conventional dashboard—displaying a dizzying array of charts and graphs with multiple data points—isn’t the answer. The virtual assistant is.

What makes a good user experience (UX)? Many factors come into play, including the user’s work habits, environment and goals. An exceptional UX must meet the customer’s precise needs, applying elegance and simplicity to deliver seamless interaction. As noted by Nielsen Norman Group, a leading UX consultancy, one first must draw a distinction between UX and the user interface (UI). Using the example of movie review website, firm co-founders Don Norman and Jacob Nielsen write: “Even if the UI for finding a film is perfect, the UX will be poor for a user who wants information about a small independent release if the underlying database only contains movies from the major studios.”

This analogy applies as well to the world of application performance management (APM) software, where the conventional UI—the aforementioned dashboard—is optimized to meet the needs of the IT professional, who can drill down to explore technical issues in greater depth. Often, however, this presentation is visual overkill for the mobile-toting business user seeking a far narrower range of insights.

For business customers, simpler is almost always better, and that’s why conversational UX is the superior choice for extracting real-time business insights from vast and varied sources of data. According to a recent study by CapTech, an IT management consulting firm, businesses are rapidly adopting conversational UX-based virtual assistants, such as chatbots, Amazon Alexa, Apple Siri and Google Assistant. While conversational UX is beginning to appear in some APM solutions too, it has targeted the IT user and not the business. At AppDynamics we are beginning to experiment with this focus on the business user, beginning with some prototypes of an “intelligent bot,” a smart virtual assistant that employs proactive reporting, on-demand interaction, and automated task execution—all combined with machine learning—to extend the capabilities of APM far beyond its traditional IT roots.

Needed: Simpler Data Analysis

Business users today favor popular, mobile-based social platforms—think Slack, Skype, Facebook Messenger and Cisco WebEx—for workplace interaction. At the same time, self-service analytics is a growing trend in the enterprise, one requiring intuitive tools that enable the user to glean insights from company data without assistance from IT or a data scientist. This self-serve approach can bring analytics “to the masses” via a familiar, intuitive UI, often on a mobile device.

The dashboard isn’t the answer here, particularly when business users want to be alerted only when key metrics are impacted. A conversational UX, voice or text, can revolutionize business by providing intelligent automation that enables users to see in real time how technology is impacting their operations and customers. By empowering companies to measure and baseline everything, conversational UX becomes a central nervous system for the entire organization. The key benefit here is proactive visibility, such as real-time alerts on sudden changes in company sales, revenue or customer churn.

A Smarter Virtual Assistant

The conversational assistant can deliver value to a much broader user base—not just IT—by providing deeper, more automated and proactive business monitoring. Think of it as a concierge service for monitoring and optimization. By sending alerts for key metrics, the virtual assistant frees users from having to log into a dashboard to view their KPIs, since their assistant does it for them.

What kinds of business services could this assistant deliver? Some examples:

    • Real-time proactive reporting: users are alerted to KPIs they care about, such as a sudden drop-off in sales or revenue.
    • On-demand interaction: The ability to make natural language queries such as “What were total sales in the past hour?” Or, “How did this customer segment perform over the past two hours?”
    • Context-driven recommendation and task execution: The assistant might ask the user, “Total sales have declined 25% in the past hour, what would you like to do?” Suggested actions could include “Provide more information,” “Notify IT,” “Snooze alert for 30 minutes,” or other options.
    • Customer segment monitoring: When a user requests the customer journey for a particular service or application, the assistant could provide a graphical representation revealing bottlenecks or critical metrics (such as a drop in the number of conversions) that must be addressed immediately.

The true benefit of the business-focused virtual assistant is its ability to provide proactive reporting, on-demand interaction and automated task execution—all without the need for pesky logins or dashboards. It could also deliver key metrics, such as high-level KPIs, via an easy-to-use UI available on a variety of platforms, including mobile.

By incorporating machine learning capabilities, the virtual assistant could also deliver prescriptive insights that help businesses detect and prevent fraud in real-time, improve retail forecasts, create more accurate pricing models, and much more. More than simply a conversational UX, this cognitive helper would become a powerful recommendation engine enabling a natural conversation channel for business users to engage with their APM software.

The intelligent virtual assistant is smart automation that will change the way business operates. Rather than analyzing massive data sets long after they’ve gone cold, business users will soon be able to access real-time information—uncovering insights that enable them to see trends and changes as they happen. Here at AppDynamics, we are seeing promising results with virtual assistant prototypes, and we’re starting to work with customers on early use cases.

Harish Doddala
Harish Doddala is leading product growth and adoption initiatives of Business iQ at AppDynamics. He has over 10 years of Product Management and Software Engineering experience delivering results for AppDynamics/Cisco, VMware and Oracle. Harish is a Fellow at Massachusetts Institute of Technology, System Design and Management and has published in international speech and audio conferences. Harish has filed two patents: one for querying machine learning models and one to uncover root cause analysis.

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