Côme Billerey's guest appearances

Côme Billerey

Software & Technology by MarketScale

Beyond Technology: The Experience Podcast

MarketScale Technology

Bob Baxley

Dan Miller

David Hill

David Sawyer

John Dudley

Dan Thompson

Eric Anderson

Michael Longoria

Andy Weir

Ben Taylor

John Ryan

Chris Devlin

Matt Wood

Paul Johnson

Ross Perot

OwlTail

Like other industries affected by the growth of the experience economy, restaurants and QSRs are feeling the pressure to make the customer journey as frictionless as possible. Acrelec's digital ordering technology solution helps make the customer experience easy, the kitchen more productive, and ultimately the restaurant more profitable. On this episode of Beyond Technology: The Experience Podcast brought to you by Acrelec, host Daniel Litwin sat down with Côme Billerey, head of products at Acrelec, to discuss how AI is the difference-maker in smart QSR menus. Before digital ordering technology using AI, QSRs were challenged to serve the two basic tenets of food service: speed and food quality. "People were being served fast but the food was already prepared before they arrived in the restaurant," Billerey said. "Now customers expect to have the food prepared as soon as they order and still be served fast. This is where AI can really improve by driving the customers during the ordering process to personalize and also improve on the kitchen side for better production capabilities." Personalization is the key to the customer experience, Billerey said. With AI and tools such as Acrelec's Bridge, the central brain of a restaurant's software, customers can see previous orders and personalized recommendations based on the time of day and other factors that might leverage machine learning to make accurate predictions. Also on this episode, Billerey shared how Acrelec is consulting with UI and UX design companies to ensure the company's digital signage solutions are the most responsive and easiest to use for consumers.

Like other industries affected by the growth of the experience economy, restaurants and QSRs are feeling the pressure to make the customer journey as frictionless as possible. <a href="https://www.acrelec.com/" rel="nofollow" target="_blank">Acrelec's</a> digital ordering technology solution helps make the customer experience easy, the kitchen more productive, and ultimately the restaurant more profitable. On this episode of Beyond Technology: The Experience Podcast brought to you by Acrelec, host Daniel Litwin sat down with <a href="http://marketscale.com/industries/contributors/come-billerey/" rel="nofollow" target="_blank">Côme Billerey</a>, head of products at Acrelec, to discuss how AI is the difference-maker in smart QSR menus. Before digital ordering technology using AI, QSRs were challenged to serve the two basic tenets of food service: speed and food quality. "People were being served fast but the food was already prepared before they arrived in the restaurant," Billerey said. "Now customers expect to have the food prepared as soon as they order and still be served fast. This is where AI can really improve by driving the customers during the ordering process to personalize and also improve on the kitchen side for better production capabilities." Personalization is the key to the customer experience, Billerey said. With AI and tools such as Acrelec's Bridge, the central brain of a restaurant's software, customers can see previous orders and personalized recommendations based on the time of day and other factors that might leverage machine learning to make accurate predictions. Also on this episode, Billerey shared how Acrelec is consulting with UI and UX design companies to ensure the company's digital signage solutions are the most responsive and easiest to use for consumers.

How AI Is Making Digital Ordering More Personalized Than Ever with Côme Billerey

Over the last decade digital technology has spread into quick serve restaurants, typically in the form of digital menu boards. But only until recently have those stores been able to use digital technology to collect, analyze, and predict customer behavior. On this episode of the ____ podcast, Côme Billerey, head of product innovation at Acrelec, shares how machine learning has come to your favorite restaurant.  “We are focusing on how can we improve the customer journey and improve operations thanks to AI,” Billerey said.  This means using machine learning to improve the speed of service, and possibly predict orders so restaurant managers know how to allocate resources to optimize efficiency.  The latest smart displays found in stores can collect data in real-time. With AI, the displays can learn the weather and forecast how many people will be in the store and what they’ll order. Billerey explained that these predictive capabilities have been used by websites like Amazon for some time, but only now are they available to brick and mortar stores.  Although the technology will never achieve 100% accurate trend forecasting, “in the past years we have reached, in certain fields, really great predictive capabilities of 95 to 97%," Billerey said.  Billerey divulged that he worked with McDonalds in leveraging machine learning to time cars in a drive-thru lane. First using sensors in the road and then switching to cameras, he was able to predict bottlenecks so that the restaurants could reorganize staff for better service. The experience gave him a greater appreciation for the human eye which, working with the brain, is capable of visual processing and analysis that cameras and computers just can’t do.  “It should amaze people, or at least, it amazes me," Billerey said.  Currently, he’s working with Intel to create more cost and energy effective solutions to process real-time data. And while AI is not hard to deploy at select sites, many startups have trouble doing so across a network. That’s where he says Acrelec is different.  “We know how to scale technology on many, many different locations," Billerey said.

Over the last decade digital technology has spread into quick serve restaurants, typically in the form of digital menu boards. But only until recently have those stores been able to use digital technology to collect, analyze, and predict customer behavior. On this episode of the ____ podcast, Côme Billerey, head of product innovation at Acrelec, shares how machine learning has come to your favorite restaurant. “We are focusing on how can we improve the customer journey and improve operations thanks to AI,” Billerey said. This means using machine learning to improve the speed of service, and possibly predict orders so restaurant managers know how to allocate resources to optimize efficiency. The latest smart displays found in stores can collect data in real-time. With AI, the displays can learn the weather and forecast how many people will be in the store and what they’ll order. Billerey explained that these predictive capabilities have been used by websites like Amazon for some time, but only now are they available to brick and mortar stores. Although the technology will never achieve 100% accurate trend forecasting, “in the past years we have reached, in certain fields, really great predictive capabilities of 95 to 97%," Billerey said. Billerey divulged that he worked with McDonalds in leveraging machine learning to time cars in a drive-thru lane. First using sensors in the road and then switching to cameras, he was able to predict bottlenecks so that the restaurants could reorganize staff for better service. The experience gave him a greater appreciation for the human eye which, working with the brain, is capable of visual processing and analysis that cameras and computers just can’t do. “It should amaze people, or at least, it amazes me," Billerey said. Currently, he’s working with Intel to create more cost and energy effective solutions to process real-time data. And while AI is not hard to deploy at select sites, many startups have trouble doing so across a network. That’s where he says Acrelec is different. “We know how to scale technology on many, many different locations," Billerey said.

AI, Now Served at Your Favorite Restaurant with Côme Billerey of Acrelec

Over the last decade digital technology has spread into quick serve restaurants, typically in the form of digital menu boards. But only until recently have those stores been able to use digital technology to collect, analyze, and predict customer behavior. On this episode of the ____ podcast, Côme Billerey, head of product innovation at Acrelec, shares how machine learning has come to your favorite restaurant. “We are focusing on how can we improve the customer journey and improve operations thanks to AI,” Billerey said. This means using machine learning to improve the speed of service, and possibly predict orders so restaurant managers know how to allocate resources to optimize efficiency. The latest smart displays found in stores can collect data in real-time. With AI, the displays can learn the weather and forecast how many people will be in the store and what they’ll order. Billerey explained that these predictive capabilities have been used by websites like Amazon for some time, but only now are they available to brick and mortar stores. Although the technology will never achieve 100% accurate trend forecasting, “in the past years we have reached, in certain fields, really great predictive capabilities of 95 to 97%," Billerey said. Billerey divulged that he worked with McDonalds in leveraging machine learning to time cars in a drive-thru lane. First using sensors in the road and then switching to cameras, he was able to predict bottlenecks so that the restaurants could reorganize staff for better service. The experience gave him a greater appreciation for the human eye which, working with the brain, is capable of visual processing and analysis that cameras and computers just can’t do. “It should amaze people, or at least, it amazes me," Billerey said. Currently, he’s working with Intel to create more cost and energy effective solutions to process real-time data. And while AI is not hard to deploy at select sites, many startups have trouble doing so across a network. That’s where he says Acrelec is different. “We know how to scale technology on many, many different locations," Billerey said.

Over the last decade digital technology has spread into quick serve restaurants, typically in the form of digital menu boards. But only until recently have those stores been able to use digital technology to collect, analyze, and predict customer behavior. On this episode of the ____ podcast, <a href="https://marketscale.com/industries/contributors/come-billerey/" rel="nofollow" target="_blank">Côme Billerey</a>, head of product innovation at <a href="https://www.acrelec.com/" rel="nofollow" target="_blank">Acrelec</a>, shares how machine learning has come to your favorite restaurant. “We are focusing on how can we improve the customer journey and improve operations thanks to AI,” Billerey said. This means using machine learning to improve the speed of service, and possibly predict orders so restaurant managers know how to allocate resources to optimize efficiency. The latest smart displays found in stores can collect data in real-time. With AI, the displays can learn the weather and forecast how many people will be in the store and what they’ll order. Billerey explained that these predictive capabilities have been used by websites like Amazon for some time, but only now are they available to brick and mortar stores. Although the technology will never achieve 100% accurate trend forecasting, “in the past years we have reached, in certain fields, really great predictive capabilities of 95 to 97%," Billerey said. Billerey divulged that he worked with McDonalds in leveraging machine learning to time cars in a drive-thru lane. First using sensors in the road and then switching to cameras, he was able to predict bottlenecks so that the restaurants could reorganize staff for better service. The experience gave him a greater appreciation for the human eye which, working with the brain, is capable of visual processing and analysis that cameras and computers just can’t do. “It should amaze people, or at least, it amazes me," Billerey said. Currently, he’s working with Intel to create more cost and energy effective solutions to process real-time data. And while AI is not hard to deploy at select sites, many startups have trouble doing so across a network. That’s where he says Acrelec is different. “We know how to scale technology on many, many different locations," Billerey said.