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Can we quantify desire? Under the hood of M&C Saatchi’s brand desire engine


By Sam Anderson | Network Editor

July 18, 2022 | 8 min read

Data-backed marketers have made serious strides in the last couple of decades in figuring out what people desire (and why, and how much). We sat down with two people who claim to be further along on that quest than most: the team behind M&C Saatchi’s ‘brand desire engine.’

A dog staring covetously at a piece of chicken

What we want and why we want it is a mystery – a mystery savvy marketers are trying to solve / Guillermo Latorre via Unsplash

No prizes for this level of insight, but marketing is about getting people to buy (or in some cases do) stuff. Between the messaging and the action is the mysterious realm of wanting: desire.

If you could know what desire is, what makes it tick and how to measure it, that’d be a useful tool. That’s why brands and agencies are willing to pump so many resources into human understanding labs, psychometric research and a raft of qualitative and quantitative techniques to peel back the musty curtain that obscures the reality of want.

Earlier this year, M&C Saatchi unveiled its tentpole desire play: the ‘brand desire engine.’ Working at the confluence of eight artificial intelligence (AI) platforms, using psycholinguistics and machine learning (ML), and a billion (and growing) rows of data, the pitch is that it will allow chief marketers to pinpoint how desire for its brand shifts, and in response to what.

But what does that really mean? How, really, can anyone demystify desire? We spent some time with two leaders from the M&C agencies behind the engine: Rhonda Hiatt, chief strategy officer at strategy arm Clear; and Tim Spencer, chief exec at data specialists Fluency.

The greatest survey

Clear has published brand desire rankings for years; in the past, those rankings were decided by a consumer survey. While that methodology was, according to Hiatt, “robust” and “sophisticated,” its replacement tells an interesting story about big data’s power in the modern marketing industry. Clients, she says, were starting to glean insights about the desirability of their brands from large data sources, but those sources weren’t joined up and might even tell conflicting stories. The brand desire engine is built around the goal of metabolizing all that data into a clear understanding of desire.

“We thought, there has to be a better way than just surveying a lot of people,” says Hiatt. “We’re not saying surveying isn’t a great tool. It’s absolutely part of our methodology here; it’s still hugely helpful and insightful. But we wanted to broaden that perspective and be more diligent with the data.”

The survey is a hundred-year-old methodology but, says Spencer, “the brand in 2022 is in a very different position to where we were in 1920 ... We have huge datasets wrapping around the entire world, which we are codifying for the first time. We don’t have to ask someone what they think or feel; we can go on to Twitter, we can look on search engines, we can get a strong point of view from review sites. All of this data is out there telling us what that brand is like, what it’s about, what's good about it, what’s not so good about it. The problem is it’s not being tapped; it’s not being derived properly.”

Those data streams are many: M&C, they tell us, buys in almost £1m of data off-the-shelf from the likes of YouGov, Kantar and Google; it also feeds in reams of publicly-available data, and clients can add first-party data of their own. Set up at launch to spit out results for 200 top brands, and aiming to grow to map out “all brands that we can get good sizeable data on” (perhaps 5,000), they can feed in those data sources for other clients as they come along.

The output, says Spencer, shows “how much money is on the table for them to make; and what brand desire drivers they need to lean on harder to make that new money.” Following that, they offer more traditional brand consultancy from Clear, albeit backed up by this deeper data insight – Hiatt likens that difference to going from being able to hand clients a map to giving them live GPS data.

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The universal drivers of desire

The engine works on the basis that, as Hiatt says, “there is a universal set of drivers of desire that do exist out there. We’ve done all the work to understand what they are universally. However, the way they’re interpreted, managed and optimized is incredibly different by brand.”

Take one of those drivers: status. “In the old days, we would have had an attribute or a sentiment statement that said, ‘I feel proud when I wear this brand.’ Now, we’re actually seeing what they are posting on Twitter, what they are searching for on Google, what they are putting out on social media.”

Hiatt describes this whole process as “removing the leaps of faith” that brands would traditionally make between (even well-founded) insights and action to address those insights. The opportunities, Spencer says, are exciting: “When you look at all of this data as a consultant, it’s a bit like a sweetie box, because you’re able to see the full picture of a market and say, ‘how do we take a brand that’s incredibly famous for these characteristics, and make it more valuable while retaining its core, but developing its potential?’ You’re in a dreamland.”

Good for strategists, and good for chief marketers, is the dream. As Spencer says, “in the modern world decision-makers need evidence, they need to be able to point to value and they need to be prepared to be taken seriously at a board level.”

M&C is serious about putting this degree of data-backed insight at the core of its brand consultancy; Hiatt says that she hopes the brand desire engine will become the “central intelligence of the business,” helping brands to de-risk decision-making in any area where they can find good data. “It’s not de-risking to the point of zero,” she says, “but it is de-risking some of that by having much more informed and competent data behind it.”

Marketing Brand Strategy Business Leadership

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