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Virtually Speaking

Do Not Pass Go: Deploying IVAs in the Calculated Enterprise

Posted by Shannon Senecal on Mar 17, 2016 5:11:59 PM


At Next IT, we regularly hear from customers who are excited to gain the competitive advantages they associate with conversational interfaces. Their excitement is well founded: well-designed intelligent virtual assistants (IVAs) for customer experience translate into increased profits and customer satisfaction.

In fact, there’s now a massive body of evidence demonstrating that conversational interfaces are becoming necessary tools for engaging end users, in any context. Gartner predicts, for example, that “by 2018, 30% of our interactions with technology will be through ‘conversations’ with smart machines” and that “by 2020 smart agents will facilitate 40% of mobile interactions.”

The problem, of course, is that not all IVAs are created equal. Before businesses and organizations rush to adopt them, they need to appreciate that there is an enormous difference between throwing a one-size-fits-all IVA at a problem and deploying a solution designed to solve a well-defined business challenge.

What do we mean by that? For over a decade, we’ve developed IVAs that are adaptive to the business needs of the enterprise. That tailored approach means the IVA ships with your business’s specific KPIs written into its DNA. The core elements of the IVA, from language and domain models to delivery channels like desktop, mobile and social, all need to work together towards the same goal.

Defining the business realities gives you the ability to design a context-aware user experience that tracks towards your goals. For example, in our work with Amtrak, which you can read about here, we addressed very specific challenges around travel booking and reservations.

Amtrak wanted to find a solution that would provide web visitors with instant access to online self-service. Their goal was to reduce their customers’ need to call or email a representative, while improving the customer experience during booking and reservation changes.

With a clearly defined challenge and measurable goals set, we began to develop Ask Julie to address Amtrak’s specific needs. The results were exciting, including:

  • An 8X return on investment

  • 25% more bookings with Julie than without

  • Saving $1 million in customer-service email costs in a single year

Most importantly, over time, we were able to expand Julie’s role to address other business goals and challenges. Today, Julie drives increased revenue with built-in up-selling and cross-selling capabilities. Customers now spend 30% more per-booking when using Julie. This was all possible because Amtrak’s goals were clearly defined and ranked.

So, as you’re working on your next customer-experience project, don’t start by reviewing available technologies. Start by defining business problems and goals. The path to success is illuminated when everyone knows where they’re starting and where they need to go.

Topics: Conversational interface, Intelligent Virtual Assistants, Natural Language Understanding, Tech