CUSTOMER SUCCESS
Bespoken helps companies like yours, deliver amazing Voice Experiences.
Our automated testing solutions are the fastest way to improve speech recognition, guarantee the quality of your Voice Apps, improve rating, and keep your customers coming back for more.
Explore our customer success stories below and learn how your team can start leveraging automated testing for Voice, today!
What Our Customers are Saying
We have helped Mercedes Benz R&D deliver exceptional quality for its connected car voice interaction experiences – quality which is synonymous with the Mercedes-Benz name.
Bespoken brings the best practices of automated testing. Together, we have created a streamlined development process that assures higher quality and provides a high degree of test automation.
The Mars Agency cut down errors in the speech recognition of their voice app by more than 80% before launching thanks to our software and tech support. Learn how we did it
I cannot reiterate enough how helpful this has been. Our confidence going into this launch is significantly higher because of Usability Performance Testing.
Bespoken and Deako collaborated to establish best practices for automated testing and monitoring of Home Automation devices controlled via voice. The process is innovative but also easy to implement.
The tools from Bespoken have made things easy. We were able to get setup quickly – we got an initial integration done in less than an hour, and it took less than a week implement what we consider to be best practices for testing our devices. The testing and continuous monitoring has reduced downtime and helped improve quality.
In this case study you can learn how improving your skill’s understanding and comprehension will give you more and happier users, and a better positioning on the skill store.
There are very few tools available for handling this. What we are typically left with when we make adjustments to our interaction model is submitting a new version of the skill, and then closely monitoring the reviews for issues reported by users. It’s a user-unfriendly and unreliable way to diagnose speech recognition problems.