Understanding purpose: Humans and AI

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Brand purpose is foundational. Yet, it is also one of the most misunderstood and misused business buzzwords today.

Purpose-led companies can make a tremendous difference in the world, and people increasingly expect such organisations to use this power for good. In Kantar’s 2020 Global Monitor survey, 66% of respondents said it is important to them that the brands they buy are committed to making our society better.

When brand purpose impacts brand choice, it follows that purpose impacts brand growth. Kantar’s BrandZ data shows that, from 2006 to 2018, brands with a stronger purpose grew their value by 175%, more than double compared with those with a weak purpose.

It is clear; brands with a purpose have always been more impactful – so, what has changed?

A higher purpose

The pandemic, along with the social justice movements of the past year, seems to have cemented, and even expanded, the importance of purpose. Concurrently, consumers are more discerning. Brand purpose must be relevant to the brand and feel genuine to the consumer – not bolted on. In this environment, finding the right expression of purpose can be challenging.

Many brands have found a way to do this with impact and authenticity. Nike is an excellent example, with its recent ‘Just Do It’ relaunch. Firmly grounded in emotion, it champions minorities and challenges female stereotypes in sport. Other examples have drawn equal attention for all the wrong reasons – from overly simplistic portrayals of complex societal issues to using charitable donations as some sort of game of chance.

Moreover, once ‘purpose’ becomes part of a brand’s marketing mix, a new set of expectations arise. Fail to deliver on that, and people are likely to perceive a brand as co-opting a cause to help promote and sell things for their benefit – not for the greater good.

How can brands avoid the pitfalls of a badly aligned and poorly expressed brand purpose? To really understand people, we turn to their stories. Human stories bring empathy, understanding and connection. In the context of brand purpose, therefore, it makes sense to look for ways to access people’s human stories on a larger scale.

Conversational artificial intelligence (AI) offers a way to have rich, engaging one-on-one chatbot conversations, with people like you and me, at scale, with the power to uncover what we did not know, getting to the heart of people’s stories, their passions and motivations, needs and expectations.

Conversational AI leverages messenger platforms – such as Facebook Messenger or WeChat – that feel personal and familiar to people; where they can share their stories on their terms, through a guided, adaptive conversation that encourages these to unfold as naturally as possible. Such human-like conversations give researchers access to qualitative depth at a quantitative scale, exploring people’s evolving needs and expectations, and identifying where and how brands can – and do – make a positive difference.

Advances in AI

Advances in text-based AI are playing a critical role in establishing conversational AI as the primary source of human-centric insight, to underpin and activate meaningful, purpose-driven strategies.

On one side, this gives us the power to leverage and embed what we already know into conversational AI and into the conversations we have. Consider here the unique knowledge assets you have: your understanding of your clients or specific markets; your expertise in a particular domain, such as brand purpose.

The extent to which we get this right directly impacts the conversations we have. To elicit depth and step beyond the rational first layer of responses, a bot that is built to establish a deeper understanding – not just resolve a query – must be able to probe when it matters most. To do this, it must know when to probe. Natural language understanding (NLU) is used to trigger intelligent probing powered by implicit data assets on what we already know is important.

For the research industry to fully leverage advances in AI to better understand people, it becomes imperative to externalise our implicit knowledge into the machines, to power NLU that delivers the richness and nuance we are after.

On the other hand, it is about how we find things we don’t know we don’t know. Here, we can turn to natural language processing (NLP) to surface and make sense of the way in which people talk about what matters to them, across thousands and thousands of rows of data.

A best-in-class approach to NLP should leverage your implicit expertise to detect patterns in the conversational data that are meaningful within your domain.

NLP is further boosted by human-in-the-loop (HITL) as a branch of AI that combines the best of human and machine intelligence. This means that, throughout – when we bring together raw, unstructured conversational data with our own implicit expertise – we also involve human experts to train, test, tune and validate AI models. In other areas, such as trend forecasting, this is referred to as the more balanced future brain, where analytics is combined with human experts to synthesise and contextualise, to deliver truly meaningful insights and recommendations.

Bringing together intelligent conversations at scale with the ability to surface meaningful patterns in such data, leveraging implicit expertise, we can create a holistic, integrated, intelligent approach to conversational AI – a closed-loop data ecosystem.

For conversational AI, a radically new way of understanding people in a still largely traditional research industry, a robust AI-powered framework denotes credibility, scalability, repeatability, and – perhaps most importantly – validity.

When human stories and AI combine

Human stories collected at scale help us to understand people. Knowing what genuinely matters to them empowers brands to explore different ways to manifest their purpose with meaning.

For global brands, this is particularly important, as it offers direction to know how to express a global purpose-driven strategy in a nuanced, locally relevant way. The former chief executive of PepsiCo referred to this as “freedom within a frame”, the need for global brands to allow for a measure of freedom for each market to tailor a globally defined strategy in context.

This is where human stories and AI spark together to deliver deeper, locally nuanced insight into brand purpose that underpins clear, relevant, and powerful activation strategies that are grounded in context and immersed in emotion. It is this spark that helps brands express their purpose in a way that will truly matter to consumers and make a positive difference in their world today.

Ansie Lombaard is global innovation director at Kantar

THIS ARTICLE WAS FIRST PUBLISHED IN THE JANUARY 2022 ISSUE OF IMPACT.