How Brightcove leveraged generative AI to transform customer support
In a bid to improve efficiency and quality in its customer support, streaming services company Brightcove became an early adopter of Amazon Q, a generative AI–powered assistant for its in-house “Expert Bot.”
When approached by Amazon, Brightcove executives immediately saw the potential to better handle technical queries from its diverse range of global clients that include the SXSW conference, Consumer Technology Association, Cancer Treatment Centers of America and the Academy Awards.
Brightcove support agents field thousands of queries, from simple instructions to reset a password to more complex help like embedding video in a WordPress site that can require significant time.
“In the past, answering this question would require a support agent to manually search through documentation and provide a detailed response,” said Scott Levine, chief product officer at Brightcove.
With the new tool, the company says it is saving time and improving its already highly regarded customer service.
“The starting point for us was ‘Can we make it easier for us to answer every single one of those questions and make ourselves do better?’” Levine said.
Delivering value in the rush to adopt generative AI tools
The Brightcove example reflects a wider trend of organizations adopting generative AI across a range of business functions, showing they can deliver real business value, a 2024 McKinsey survey found.
To gain a genuine competitive advantage, however, businesses should focus on helping people do their current jobs better and lift productivity, according to the research firm.
If generative AI tools improve the way employees provide customer service and support, it can have a real impact on the business, according to some experts.
“How you service and support customers, whether your business offers a product or an interaction, is becoming more of a differentiator,” said Melissa Copeland, founder and principal of Blue Orbit Consulting, which specializes in customer experience design and technology adoption.
The challenge is applying the technology where it delivers a dividend, not just for automation or cost cutting.
“Organizations must find the opportunity to use technology to reduce friction for customers and reduce friction for agents,” Copeland said.
Copeland cites examples of businesses that have seen a minimum 25% to 35% return on investment in the form of decreased handling time or first call resolution when deploying generative AI customer support tools. The gains could expand beyond, too.
“Then there’s thinking about new metrics beyond the traditional ways. That’s what’s really exciting about the possibilities of these tools,” she said.
Build generative AI tools with guardrails to foster trust
To deliver on the promises of generative AI, organizations must ensure the accuracy of the model to build trust, according to McKinsey.
In Brightcove’s case, it took a cautious approach, setting well-defined guardrails around the use of customer information that require permissions, rigorously testing the system, and having in-house technical experts scrutinizing the output.
“It's not one person looking at it; it's 50 people looking at it,” Levine said.
The Amazon team worked closely with Brightcove staff, teaching them how to craft questions to get the most suitable answers and taking time to train the bot on its extensive library of documentation as the source for responses.
“Streaming is complex, and that creates a lot of information about how to do it the best way across thousands of customers,” Levine said.
The bot-generated answers also include citations that link to the Brightcove source information so if the answer doesn’t look right, human experts can verify the response and feed that back to the tool. It adds an important layer of trust and teaches the model to help improve its output as it processes more queries.
“We have a lot of very technical people here at Brightcove, and when we see answers that aren’t right, we call it on it,” he said.
The end result is that the bot provides customer and product support teams with responses to customer questions. Brightcove has found it’s not only reduced the response time but also improved the overall efficiency of the support team.
“It’s about giving our customers the information they need quickly and accurately, and continuously improving that process,” he said.
Avoiding the trap of one-off tools
To maximize the potential of generative AI, McKinsey recommends that organizations avoid one-off solutions and invest the time and resources into tools that will scale.
Copeland cautioned that organizations must think through the longevity of the platform they’ll be working with.
“Use as your base platform a known entity, such as a large outfit that already offers customer experience tools you’re using across the business,” Copeland said.
While organizations might want to experiment, they also need to avoid different internal groups building their own tools independently to ensure widest application of new tools.
“If you get one-off customizations, it’s difficult to pull together, and when things are done in bits and pieces without any kind of central coordination, it becomes a nightmare to centralize and scale,” Copeland said.
In the case of Brightcove, Levine sees ways to expand the company’s use of generative AI to address more complex tasks such as enhancing metadata management on video streams or automating translation services to convert a video into multiple languages.
“Our customers have footprints all around the world, and if we can enable them to translate content on the fly, that's another use case for generative AI,” Levine said.
Above all, Brightcove’s use of Amazon Q is meant to not only improving operational efficiency but also add value to its service for customers.
“Everything we do starts with that mindset and driving business value,” he said.