Streaming platforms to retail stores are finding fascinating use cases for GenAI
Streaming platforms love to make recommendations, based on your viewing habits, hoping that you will stay with the platform. Currently, most of those recommendations are based on genre – if you have watched a horror movie, it will likely recommend other horror movies. But that’s not how we humans are. We are more complex. Generative AI is now beginning to address that complexity.
Sunil Rao, EVP and head of analytics for the Americas at customer experience management company Merkle, s ai d at our webinar last week that for a certain streaming platform, they used GenAI to analyse the platform’s video content at a granular level, understanding the emotions and actions, the themes and tones across a film or episode. This, he said, allowed them to match content and advertisements to viewer preferences with unprecedented precision. “We’re seeing a 21% improvement in ad performance and a 45% improvement in engagement rates,” Sunil said. Which means that AI is not only able to boost business metrics but also able to foster more satisfying viewer experiences.
The intersection of AI and real time data analysis is opening up fascinating new frontiers in retail and customer service. Industry leaders are harnessing these technologies to reimagine customer experiences and create personalised interactions that were once the stuff of science fiction. And in the webinar, the consensus was clear: AI, particularly GenAI, is not just another passing trend but a transformative force in customer engagement.
AI in retail
“I’m very bullish on AI,” said Vineet Mehta, general manager of enterprise technology for Kmart and Target Australia. AI’s true power, he said, lies in its ability to augment existing analytical and digital capabilities, acting as “an extra turbo mode on your engine.”
Kmart Australia has deployed AI powered chatbots for customer service, resulting in 30% of calls being handled without human intervention. AI is also revolutionising product design and inventory management. Vineet described how Kmart is using AI in conjunction with 3D design tools to streamline the creation of their private label products. “We can change the colour on the fly now,” he said, highlighting the agility this brings to the design process.
In physical stores, AI is taking on roles once reserved for human staff. Kmart has introduced robots that roam store aisles, capturing real time inventory data. The company is also exploring AI applications in loss prevention, using image recognition to detect potential theft scenarios in real-time.
Be careful
However, the road to AI integration comes with challenges. Navin Dhananjaya, chief solutions officer at Merkle, stressed on the need for robust governance and ethical considerations in AI deployment. “We definitely need some quantifiable measures,” he said, pointing out the importance of metrics related to bias detection and model observability.
Data privacy and security remain paramount concerns as companies push the boundaries of personalisation. Navin highlighted the risks of “prompt hacking” in large language models, where vulnerabilities could potentially expose sensitive information. Hackers could potentially use carefully crafted prompts to deceive the LLM into performing unintended actions. To mitigate these risks, Merkle has a three-pronged approach involving experimentation, business validation, and legal approval for AI initiatives.
The experts also stressed the importance of data readiness in successfully implementing AI solutions. “Having the right curated data in one place, integrated in a way where we can use that to feed these algorithms in a production capacity, has been a challenge,” Sunil observed. He estimated that even for mature organisations, it could take several months to get their data infrastructure AI-ready.
Vineet cautioned against AI deployment without proper testing, especially in customer-facing applications. “There’s very little margin between winning a customer and losing a customer,” he warned.
Despite these challenges, the potential of AI in enhancing customer experience is undeniable. From creating synthetic customer profiles for more accurate marketing to enabling natural language interactions with complex data sets, AI is opening up new possibilities for businesses to understand and serve their customers better.
India for the world
The impact of these advancements extends beyond individual companies to entire industries and economies. India, with its rich talent pool in data analytics and AI, is positioned to play a significant role in this transformation. Global capability centres (GCCs) in India are seen to be not just supporting but often leading AI initiatives with global impact.
“Most GCCs are doing it end-to end. They are doing thought leadership, they’re driving innovation, they are the talent powerhouse, and they are building solutions,” said Sunil.
Streaming platforms love to make recommendations, based on your viewing habits, hoping that you will stay with the platform. Currently, most of those recommendations are based on genre – if you have watched a horror movie, it will likely recommend other horror movies. But that’s not how we humans are. We are more complex. Generative AI is now beginning to address that complexity.
Sunil Rao, EVP and head of analytics for the Americas at customer experience management company Merkle, s ai d at our webinar last week that for a certain streaming platform, they used GenAI to analyse the platform’s video content at a granular level, understanding the emotions and actions, the themes and tones across a film or episode. This, he said, allowed them to match content and advertisements to viewer preferences with unprecedented precision. “We’re seeing a 21% improvement in ad performance and a 45% improvement in engagement rates,” Sunil said. Which means that AI is not only able to boost business metrics but also able to foster more satisfying viewer experiences.
The intersection of AI and real time data analysis is opening up fascinating new frontiers in retail and customer service. Industry leaders are harnessing these technologies to reimagine customer experiences and create personalised interactions that were once the stuff of science fiction. And in the webinar, the consensus was clear: AI, particularly GenAI, is not just another passing trend but a transformative force in customer engagement.
AI in retail
“I’m very bullish on AI,” said Vineet Mehta, general manager of enterprise technology for Kmart and Target Australia. AI’s true power, he said, lies in its ability to augment existing analytical and digital capabilities, acting as “an extra turbo mode on your engine.”
Kmart Australia has deployed AI powered chatbots for customer service, resulting in 30% of calls being handled without human intervention. AI is also revolutionising product design and inventory management. Vineet described how Kmart is using AI in conjunction with 3D design tools to streamline the creation of their private label products. “We can change the colour on the fly now,” he said, highlighting the agility this brings to the design process.
In physical stores, AI is taking on roles once reserved for human staff. Kmart has introduced robots that roam store aisles, capturing real time inventory data. The company is also exploring AI applications in loss prevention, using image recognition to detect potential theft scenarios in real-time.
Be careful
However, the road to AI integration comes with challenges. Navin Dhananjaya, chief solutions officer at Merkle, stressed on the need for robust governance and ethical considerations in AI deployment. “We definitely need some quantifiable measures,” he said, pointing out the importance of metrics related to bias detection and model observability.
Data privacy and security remain paramount concerns as companies push the boundaries of personalisation. Navin highlighted the risks of “prompt hacking” in large language models, where vulnerabilities could potentially expose sensitive information. Hackers could potentially use carefully crafted prompts to deceive the LLM into performing unintended actions. To mitigate these risks, Merkle has a three-pronged approach involving experimentation, business validation, and legal approval for AI initiatives.
The experts also stressed the importance of data readiness in successfully implementing AI solutions. “Having the right curated data in one place, integrated in a way where we can use that to feed these algorithms in a production capacity, has been a challenge,” Sunil observed. He estimated that even for mature organisations, it could take several months to get their data infrastructure AI-ready.
Vineet cautioned against AI deployment without proper testing, especially in customer-facing applications. “There’s very little margin between winning a customer and losing a customer,” he warned.
Despite these challenges, the potential of AI in enhancing customer experience is undeniable. From creating synthetic customer profiles for more accurate marketing to enabling natural language interactions with complex data sets, AI is opening up new possibilities for businesses to understand and serve their customers better.
India for the world
The impact of these advancements extends beyond individual companies to entire industries and economies. India, with its rich talent pool in data analytics and AI, is positioned to play a significant role in this transformation. Global capability centres (GCCs) in India are seen to be not just supporting but often leading AI initiatives with global impact.
“Most GCCs are doing it end-to end. They are doing thought leadership, they’re driving innovation, they are the talent powerhouse, and they are building solutions,” said Sunil.
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