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Conversational AI: Lesson 4 – Plan for the Future

Erin Abler
Publication Date
19 December 2019

Conversational AI: Lesson 4 – Plan for the Future

What can you do to uncover great use cases for voice? So far in this series, I’ve recommended three steps:

  1. Start with what you know 
  2. Find a meaningful opportunity
  3. Determine your scope

For this last installment, we’ll explore why it’s important to plan for the future.

Soon after your voice skill has made it out into the world, you’ll start to see opportunities to build on the depth and quality of your initial use case. Emerging platform capabilities and glossy new competitor offerings might even land some new “fast-follow” aspirations in your product backlog. As you keep abreast of these advancements, remember that user needs and business goals should remain the key drivers of your overall strategy. You can balance the shiny and the strategic by being purposeful in your planning. Envisioning life after launch will position you better to weigh your options, strive for continued improvement, and jump at the right opportunity for change.

Mind Your Metrics

Once you’ve published your skill, you can start pulling down data about how people are using it. Most Conversational AI platforms have evolved to include analytics as part of a standard dashboard. Those metrics can be an important guide to creating an even better experience for your customers.   

Some key usage patterns to consider include:

  • Session numbers. How many total sessions has the skill received within a certain time period? Were there spikes in traffic? If so, can you identify why? 
  • Retention. How often do customers return after their first use? Is your skill intended to be used regularly, as with a habit-building skill, or periodically, as you might expect for a transactional feature?
  • Interaction paths. Once someone enters the experience, what steps are they most likely to take? Is this the most efficient route available?
  • Intents. What intents or skill features are invoked most commonly? How many different intents tend to be invoked in a single session?
  • Utterances. How many times does the average user speak in a session? How well are users’ utterances–the words they use to indicate what they want–mapping to intents?

As the questions above suggest, it’s best to keep these numbers in context. Combining these metrics with qualitative insights from ongoing prototyping and usability testing will add value to your observations, and can help you avoid confusing correlation with causation.

For example, while heavy use of a particular intent tells you that it’s a more popular functionality, it doesn’t necessarily tell you why. Is it because that intent is without a doubt the most valuable to your audience, or is it partly because it’s the only feature that’s easy to find? Digging into the data more thoroughly will help you discover unexpected insights.

Review and Improve Your Key Benefits

Beyond analyzing UX metrics, lean into the key benefits of the voice skill you've launched. How is the skill enhancing perception of your brand? How is it educating customers on topics related to your brand and your products or services? How does it support ongoing engagement with your customers? As you look to the future, consider how new or enhanced features can extend those benefits.

Wrapping Up: the Four Steps to Finding Good Use Cases

I hope these four lessons will provide you with a framework for finding viable use cases for voice and other conversational experiences. As you move through your program or introduce new ones, think about how you can apply these steps to uncover great use cases for conversational AI. Do you have ideas to add to these lessons? What have your experiences taught you? If you have questions or comments, let us know

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