NLP For the Win
Unilever win a prestigious I-COM award for data storytelling
This week, I saw the great news that one of my former clients, Unilever, had won the I-COM Global Data Creativity Award in the "Marketing Sciences Data Storytelling" category. I worked with the team that built this internal product; therefore, I'm not surprised they won. Still, something I want to highlight though is related to the category, specifically the word "storytelling".
The product itself is built to capture a massive amount of product feedback and customer ratings, which, given the scale of Unilever's business, is vast. The solution uses machine learning* to make sense of all the data and presents insights in a dashboard that the marketing and product teams can use to continually improve their products.
End User Needs are Vital
What makes this a fantastic solution, however, is that it's built by technical people who understand all of the machine learning and data science requirements, but the output is presented in a way that is easy to digest by the users of that data. (At Dataiku we referred to these personas as Builders and Consumers.)
Imagine if the output was just a table of columns, rows, or basic charts. It would be challenging to engage with and understand, especially at the scale of Unilever's business. Solutions like this must always present the key signals in a way that's crystal clear, enabling users to make decisions confidently.
Unfortunately, I can't share any images of what Unilever built, but the dashboard aspect of the system was prominent and easy for the marketers to understand.
Data Without a Story Doesn't Mean Much
This is the standard that every data project should strive for. I previously wrote about Presenting a Compelling Data Story last December, using some fun examples to illustrate the concept. The bottom line is, you can create the most technically advanced solution, but it's meaningless if users can't access the output simply and easily.
*In case you were wondering, a big part of the solution uses Natural Language Processing, NLP for short. NLP is a branch of artificial intelligence that helps computers understand, interpret, and manipulate human language. A standard algorithm that allows teams to perform tasks like Sentiment Analysis which is a technique of categorising a text string (i.e. sentence or paragraph) as positive or negative. In the context of Unilever's solution, NLP is used to analyse the text-based product feedback and customer ratings, providing valuable insights for the marketing and product teams.
Using generative AI at work still has the ability to cause embarrassment, or worse a large mistake, when we don't check the output.
To prevent that, I've created a Notion document complete:
- Simple checkpoints before using AI.
- A clear process for checking AI output for accuracy and quality.
- Actionable tips on how to add their own valuable insights and polish AI responses.
- Practical examples for common work tasks.
- Essential background info on why AI can make mistakes (like 'hallucinations').
- And much more, all within an easy-to-use, interactive Notion template.
Curated News
Microsoft Introduces 'Tenant Copilot' and 'Agent Factory'
Microsoft is set to unveil "Tenant Copilot," an AI feature designed to act as a digital coworker by accessing and processing organizational data within Microsoft 365. This initiative is part of a broader strategy called the "Agent Factory," aiming to embed AI deeply across Microsoft's products, including LinkedIn and Dynamics. The focus is on managing AI agents alongside human employees, with tools to oversee both human and AI identities.
Workday's Shift Towards AI-Enhanced Enterprise Software
Gerrit Kazmaier, Workday's new President of Product and Technology, discusses the company's move from monolithic systems to an ecosystem approach, integrating AI to improve user experience in HR and finance. The emphasis is on automating mundane tasks and supporting decision-making, while being cautious about AI-generated inaccuracies and biases. Workday's "Everyday AI" initiative encourages innovation across engineering and operations.
Law Firms in Asia-Pacific Embrace Agentic AI Amid Geopolitical Challenges
Law firms like Ashurst and Gilbert + Tobin are adopting generative AI tools to enhance productivity and client service, even as they navigate complex geopolitical challenges in the Asia-Pacific region. These advancements are seen as essential in adapting to a volatile global market, with AI being used to scale capabilities and improve service delivery.
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Thanks for reading, and see you next Friday.
Simon,
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