How AI helped Unilever discover 'breakfast for dessert'

The FCMG giant's global head of insight has co-written a book on AI in marketing. But what has Unilever learned and how is it keeping up with the pace of change in tech?

It is often said that the world’s most successful people are voracious readers. Titans of business such as Warren Buffet credit their success to consuming vast amounts of information in order to become the smartest person in the room.

But what if you’re a normal person in marketing who doesn’t have hours every day to read, but still wants to be ahead of the curve and create worthwhile insights for your brand? 

Stan Sthanunathan, the Unilever head of insights credited by the company as its "chief provocateur", believes artificial intelligence could hold the key for marketers to learn more deeply about culture and society in specific and targeted ways. A mechanical engineer by training, Sthanunathan left Coca-Cola after 17 years to join Unilever in 2013 to lead its global insights division from London.

Sthanunathan has co-authored a new book, AI for Marketing and Product Innovation, that presents itself as a hands-on guide for creatives and marketing professionals to learn more about AI through primers and real-life examples.

For an industry that has long felt comfortable dealing in myths such as the creative rock star, leaving AI to dwell within the realm of marketing gimmickry, the book serves as a timely reminder for the New Year that machine-learning technology is here to stay and is only going to get more powerful. The marketing professionals who learn how to best harness its power are going to come out on top.

The authors attempt to outline the resources, skills and metrics needed to make the most of AI and machine learning, even for those with very little knowledge. More knowledgeable readers would likely find themselves skipping through to later chapters for the more in-depth discussions about specific applications for using AI for product innovation, pricing dynamics or customer segmentation. 

Unlocking metaphors with machines

There is a standout passage in the second chapter of the book that explains how the idiosyncratic nature of non-conscious human thought processes – what we think but are unaware that we are thinking it – can be more reliably interpreted by machines:

"One specific, and very important, asset that AI and ML bring to the advertising table is metaphor analysis and implementation. Neuroscientists and linguistic experts agree: metaphors are essential ways in which human beings make sense out of the world around us and express widely shared, non-conscious truisms about life." 

When pressed by Campaign on what specific AI-driven insights he has gained during his six years at Unilever, Sthanunathan reveals how the company’s approach towards AI has been shifted by Bollywood movies, of all places. 

Sthanunathan joined Unilever in 2013

"We started thinking that AI would be used for structured data and the internal mindset was ‘let’s use this for predictive modelling’," Sthanunathan says. "But the big takeaway was: how can it be used for unstructured data? That’s where the richeness in data and the big ‘aha’ moment came for us."

In essence, it’s a concept that is as simple as Buffett getting smarter because he reads a lot of books: give an intelligent mind a lot of inputs rooted in society and culture, and it should be able to start making connections and insights about what makes that society tick.

Having seen how movies have influenced Indian culture for decades by talking to directors about how they understood what was happening in society, Unilever developed a tool that goes "straight to the source of influence: songs, TV and film".

Sthanunathan explains: "The movies we watch, the books we read, all influence our thinking. If you can analyse every single piece of dialogue in a movie or song, we may be able to unearth something meaningful. Consuming all that content is not a mind-numbing experience for a computer. We started mining unstructured data to get metaphors. We can use those same pieces of information to identify emerging trends to see."

And that process led to some surprising insights that have now been embraced by some of Unilever’s biggest brands, such as Ben & Jerry’s, which launched a range of breakfast flavours in 2017.

The link between ice-cream and breakfast came about after Unilever found that there are at least 50 songs in the public domain where the lyrics talk about "ice-cream for breakfast". Meanwhile, a separate research effort into the ice-cream category revealed that there are many businesses in the US that were making ice-cream for breakfast in their local area, and people were going to Dunkin' Donuts for breakfast and taking the treats home.

"The machine-learning algorithm crunches all this data and we’ve now learned there’s an opportunity for going after sweet breakfast items. Two years down the road and our competitors are now doing the same," Sthanunathan exclaims with pride. 

How tech start-ups pitch to Unilever

The book launch comes at a pivotal time for Unilever as chief executive Paul Polman made way for beauty and personal care marketer Alan Jope, who began his new role on 1 January. Keith Weed, Unilever's chief marketing officer, is joining Polman in "retirement" later this year.

Rather than replace creative or strategic thinking by marketers, Sthanunathan is adamant that this technology will enhance their ability to think differently, as well as free up their time to do more. 

Alan Jope: new Unilever CEO

Sthanunathan freely admits that some of the most interesting tech platforms are coming from start-ups rather than large corporations. He excitedly prefaces this point with the flourish of a headline writer: "Tech has democratised marketing!"

"We find them," he says of the start-ups, of which several are currently working directly with Unilever from the US, the UK, China, Israel, Finland and Singapore. 

Sthanunathan explains the process of working with prospective start-ups: "We spend a day, or day-and-a-half, and give them five minutes to make pitch after giving them a brief. We go through a bunch of start-ups and, after that, we pick one to take to a pilot stage, for which we usually spend a four-digit amount – to see whether it works or not." 

Meanwhile, he warns that there has to be a "massive change" in marketers’ job description in terms of embracing quantitative techniques and AI-driven technology.

"I’m not expecting them to be coders, but an appreciation of this is going to be mission critical going forward. Marketing is a blend of art and science, and brands are created on the vision that marketers have."

Indeed, there is likely to be no shortage of marketers and adland folk who will have made New Year’s resolutions to read more in the spirit of personal and professional self-improvement. AI for Marketing and Product Innovation is certainly worth a look, at least until someone invents an AI that can start reading books for you.

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