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How Unilever leverages ChatGPT to deliver business value

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2023-04-11 21:34:02987browse

How Unilever leverages ChatGPT to deliver business value

Over the past few years, consumer packaged goods (CPG) companies have faced many challenges. The epidemic has led to changes in consumer channel preferences, supply chain tensions and cost pressures. CPG giant Unilever has been using analytics and artificial intelligence to address this challenge.

Unilever, headquartered in London, has a history of 93 years and is the world's largest soap manufacturer. Its offline products include food and condiments, toothpaste, beauty products, etc., and its brands include Dove, Hermann's, Ben & Jerry's ice cream, etc.

Alessandro Ventura, chief information officer and vice president of analytics and business services at Unilever North America, has spent years helping the company bring artificial intelligence to the forefront of its business. While initially just in the IT director role, he has since added analytics and people services to his portfolio. This includes everything from facilities management, fleet management, employee and facility services, and personnel data.

Unilever believes that artificial intelligence is not a future technology. It has been widely used in all walks of life, and all industries need to adapt to it.

In recent months, Unilever has developed a number of new technology applications to help its business units position themselves in future markets. The most important of them is "Alex", short for Alexander the Great. Powered by ChatGPT, Alex filters emails at Unilever's Consumer Engagement Center, sorting spam from real consumer messages. For legitimate messages, it recommends a response to Unilever's customer service staff.

Ventura said, "Although Alex is very good at this job, he may still lack a little personal touch, while our customer service staff in the consumer engagement center have a lot of personal touch. So, we let They decide whether to respond to our consumers like Alex suggested or add some personal suggestions; if Alex gives an answer that's wrong or doesn't have an answer, they can flag it so Alex can learn from it next time."

Application of Generative AI

Alex was created using a neural network system and uses ChatGPT to achieve content generation. Ventura said the tool can understand consumer requests and even capture tone of voice. It can then store answers and sentiment in Salesforce. What’s more, the tool can take care of these tedious tasks, giving customer service staff more time to focus on what they do best. To date, Alex has helped Unilever reduce the time it takes customer service staff to draft answers by more than 90%.

Homer, another tool from Unilever, also uses ChatGPT to generate content. It is a neural network that takes some details about a product and generates an Amazon product listing with short and long descriptions that match the tone of the brand.

Ventura explained, "We want to make sure we capture the voice of the brand. For example, we want to differentiate between TRESemmé and Dove shampoo, and this system can definitely do that."

United Another AI-based tool launched by Lever during the week of Thanksgiving in the U.S. supports Hellmann's mayonnaise brand. The aim is to reduce food waste. It connects to Hermann's recipe management system so people can go into the refrigerator, select two or three ingredients in the refrigerator, and then exchange those ingredients for a recipe.

In the first week, the tool gained 80,000 likes from users.

For Ventura, this is the magic of analytics and artificial intelligence in CPG: it enables personalization at scale. He said, “In the CPG space, we are relying more and more on analytics and artificial intelligence to do different things. Consumers are becoming more specific about what they want. It’s a bit cliché, but they do want personality. ified products and experiences. Analytics can help CPG companies understand the context in which they browse and what consumers want, and then, through artificial intelligence, we can expand one-to-one relationships across the many consumers we have."

Co-creation is key to AI success

In addition to consumer relationships, analytics and AI are also key to making CPG companies more sustainable. Ventura cited examples such as ingredient traceability and using machine learning to automate predictions, which in turn helps companies minimize waste. Unilever is also applying analytics and artificial intelligence to logistics, including tracking inventory and optimizing routes.

Ventura said of operations after the inflation crisis, “We threw away the old interpretation of elasticity. We had to come up with new calculations because the traditional calculations gave a different picture than what we had on the shelf The picture is very different. Going forward, we will continue to see pressure from a variety of different challenges from geopolitical situations around the world."

To support its innovation in analytics and artificial intelligence, Unilever has adopted a hybrid model. It has a global center of excellence and also has a number of data scientists joining the business units.

Ventura explained, "It's basically a 'two-gear' system. The local team can ingest the data very quickly and then work with the business units to create statistical models and analytical models. Then, if the model can be leveraged and extended, we pass it to the global team so they can move the dataset around the global data lake that we have and start creating and maintaining that model globally."

Ventura believes that co-creation and co-ownership of analytics and AI capabilities with business capabilities is the key to success.

He said, "Whether it's machine learning for automated predictions or Alex in the consumer engagement center, if we take a black box and say, 'Hey, do what the machine tells you,' it will It will take a long time, and machines may never be 100% trusted. By co-creating and co-owning, I feel we can start from the right starting point, where humans and machines can work side by side as co-workers. Plus, you end up with a less biased systems because you are able to introduce a more diverse perspective into your algorithms, both from a business perspective and from a technical perspective."

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