AiThority Interview with Luke Damian, Chief Growth Officer for Applause

Please tell us a little bit about your role and responsibilities in your current company.

I am the Chief Growth Officer for Applause. I’m responsible for driving the go-to-market strategy for the company – which spans organizations like product strategy, marketing and sales operations and enablement. At the end of the day, my primary responsibility is to develop and maintain a deep understanding of what our clients need, and rally our Applause teams around those needs to forge long-term partnerships grounded in trust.

How does Applause fit into the modern AI landscape?

Applause is a software testing and digital quality company. We have always embraced innovation and for nearly 15 years have worked with our clients to help set the standard for digital quality.

As with all emerging technologies, AI is changing and evolving all the time – including its real-world applications. Companies that are successful in developing accurate and truly useful AI-driven experiences are committed to quality throughout the development process – from data collection through training and testing. However, since Applause has been training and testing AI for many years now, we know how difficult it is for companies to source the right high-quality, unbiased data they need at the scale and speed required to bring their products to market. Recently, we’ve all seen this lack of data play out in situations where AI has had less than stellar performance.

Applause provides a proven solution to quickly and efficiently source large volumes of high quality training data to feed AI algorithms and help them learn. In addition, our skilled testers evaluate the outputs to verify that the models are working as intended and are unbiased. There’s no substitute to having real people test digital experiences – especially the very nuanced and personalized responses users expect from AI.

Due to the size and breadth of our community of over a million digital testers, we can test AI experiences across geographies, languages and on a huge variety of devices including voice assistants, wearables, voice activated devices, smart home devices, in-car systems and in-store experiences.

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What are the major benefits of investing in AI for customer experience? How can customers improve the way their AI tools interact with end-users?

When the technology works as intended, AI quickly provides very personalized, highly relevant interactions, eliminating the need for users to make calls for assistance, or to have to sort through layers of information to find what they are looking for. However, getting it wrong can erode a brand’s reputation and relationship with its customers. To ensure great experiences, it’s crucial to work with the correct data sets that reflect a brand’s end users, and then to test the outcomes with people who represent the real behaviors, languages and dialects, and other relevant characteristics of the intended user profile. This must be an iterative process, to ensure the algorithms are continuing to learn and meet customers’ expectations.

ChatGPT3 and 4 have become the staple of every data scientist and AI engineering teams in the recent weeks. Could you shed some light on the progress GPTs could make in the next 2 months?

As companies developing GPTs continue to learn from real-world results and make necessary improvements, we’ll see that technology advance and become more widely used. GPTs can provide greater efficiencies and time savings, especially in cases where resources are limited or lacking, such as with the shortage of software developers we are currently facing. We’ll see companies try to utilize the new models in both customer-facing applications and to improve productivity within their own organizations. But we have to keep in mind – the algorithms are only as good as their data sets. We recommend, as we do with all new innovations, that testing is baked into the full lifecycle of development.

Could we soon have voice-to-code platforms for testing and software development?

These platforms already exist, and can be really helpful in saving developers and testers time with more simple or repetitive tasks, freeing up resources for more complex and interesting work. However, not all software testing can be automated. It is still vital for humans to be involved in software development and testing, especially when trying to understand the full customer experience.

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What’s the AI roadmap in your current organization?

Over the years, Applause has raced to keep pace with the rapid rate of technology advancements and has always met our customers’ testing needs for bringing their innovative products to market – including AR/VR, crypto currency, IOT, and metaverse experiences. In regards to AI, we will continue to partner with our customers to deliver on current and next generation data collection requirements, training and testing insights, so that they can release high-quality AI applications. We will also continue to explore and incorporate new ways that our internal teams can use AI to support our customers and community.

Please tell us more about your recently published report on AI-powered chatbots and voice assistants.

This is the second year that we reached out to our community of testing experts with our AI and Voice Applications survey to understand their experiences with chatbots, IVR, Chat GPT and other voice applications. Primarily, we were looking to gauge the sentiment around the technologies and interest in using them, and also to understand the causes of poor experiences and dissatisfaction.

For a second year in-a-row, thousands of survey respondents shared their frustration with current chatbot interactions. Their major complaints were inaccuracy of answers and failing to understand language variations and phrasing of questions. However, one-third of the respondents said they would use chatbots more often if they responded more accurately to questions and voice commands.

It was also interesting to see that while 74% of survey respondents said they had positive interactions with ChatGPT and the vast majority said it would be helpful to complete work-related tasks, 86% still expressed concern about potential for inherent bias in AI-driven technology.

As we rely on AI technology more heavily for mission-critical business functions, including software development and testing, it is essential for companies developing the technology to focus on quality and eliminating bias. As dictated by the scope of the project, companies should commit to collecting the appropriate amounts of diverse data, training the algorithm to use the data for specific use cases, and then testing the outcomes in real situations with real people – and by as diverse a group of people as possible. You can’t get the insights needed by testing in house or in the lab. There are just too many nuances to consider.

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Your take on the future of AI-powered apps for customer experience and customer support across industries:

As users become more and more accustomed to and satisfied with the results when interacting with AI-powered customer support, there’s no reason why it shouldn’t become more widely used. However, as our AI and Voice Applications survey showed this year, 48% of respondents said they would prefer to wait for a human agent during service calls. Clearly, there are opportunities for improvement before relying more heavily on that technology. Companies that are committed to meeting their customers’ high expectations should take that seriously.

Thank you, Luke! That was fun and we hope to see you back on AiThority.com soon.

[To share your insights with us, please write to sghosh@martechseries.com]