A single insight that drives a single brand proposition inevitably creates marginalised groups that we don’t market to. Despite our best intentions, as marketers, we are typically biased in our thinking and outlook. Marginalisation comes in all forms, and it’s not all about gender, ethnicity or location. On the contrary, marginalisation within marketing is much more pervasive, a derivative of segmentation.

The problem may be in the fundamental way marketers approach audiences. Are we perhaps too focused on what we call our ‘core’ audiences?

Even before taking a glimpse at a brief, it’s very rare a marketer does not already have an idea or image of who the campaign intends to target and immediately starts to pigeonhole their thinking. Preconceived ideas, or even ‘imagination’, kick in to give the supposed audience an age group, an attitude, and a way of behaving in media. This idea is then cemented in the recommendations as they are validated by the vast amounts of audience data available today to produce a single insight that drives a single brand proposition or message.

This is especially true for luxury and premium brands, which rightfully need to narrow how they define their audiences. But this is also as true for any brand that has written in its campaign briefs ‘Who is this for?’

It is not being suggested that all brands should target the masses and ‘go broad’ to market to the marginalised. No, that is not the only alternative. Then how do we push marketing to the marginalisation to be more than cliché, featuring of diverse models in an ad? We can do this by taking a more human approach to understanding people – understanding their deep motivations.

Why customer motivations aren’t the correct focus

Understanding an audience’s deep motivations goes beyond simply the functional reasons for buying. It’s not something you can observe simply by tracking what people do and buy, but it is discovered by asking the question of ‘why’ behind the ‘what’ people do. It’s really all about relevancy rather than loyalty.

For example, the ‘what’ is using digital signals to identify who’s configuring the new Range Rover online, or analysing CRM data to understand who purchased the Omega Seamaster 007 Edition. This means we can cluster other people who do the same action as one audience segment. Audience segmentation is explained by Mailchimp. But segmentation is not personalisation. This is the beauty of today’s marketing world and our capability to navigate the overflowing amounts of data to be the driver of success. But despite having more data than we know what to do with it on what people do, there is so much human truth which is lost when we only understand the ‘what’.

Understanding motivations helps us overcome this loss. It allows us to see behind the identical behaviour of different people buying or doing something new to understand there are diverse instinctive drivers (the ‘why’) influencing people to do what they do. An understanding that some are driven by the motivation to be seen better than others (accomplishment), some to fit into a group of friends (status), some by to complete a collection of dream cars (possession), or some to fulfil their mother’s life-long dream of seeing the Northern Lights (affection).

People are individuals and not convenient capable to be lumped together

This is not about putting a heartfelt twist on audience understanding, but this difference between designing campaigns on the ‘why’ versus the ‘what’ has an immense impact on marketing to them.

When we start with the ‘what’, audience understanding is limited to socio-demographic segmentation and basic attitudes of existing and predictable potential buyers. This naturally creates campaigns that never speak to certain groups, and when this is repeated across the industry for years on years the reputation of marketing being a driver of marginalised groups is inevitable.

On the other hand, the beauty of using motivations to understand people is that anyone can be part of an audience defined by motivations, no matter if it’s a 45-year-old Chinese entrepreneur or a 15-year-old boy in Toronto, or even a 68-year-old retiree with a bucket-list road trip planned with new friends.

This does not mean brands can only design campaigns for a broad audience of ages 15 to 68. Using a combination of niche motivations can still lead to brands targeting tight audiences that deliver on-brand campaign success metrics or sales. But at the same time, by reflecting a common motivation rather than the colour of the skin or age bracket, diverse representation in marketing can stop playing to stereotypes and instead deliver a brand message that resonates across socio-demographics.

Planning on motivations is not the sole answer to all the shortcomings we face in marketing to the marginalised. We most certainly need to go beyond and continue making an active effort to fight our unconscious biases and stereotypes. But we are sure we’re not alone among marketers finding their media creativity often suppressed under endless checklists of potentially antiquated best practices, principles, brand guidelines and a more recently added line item on portraying diversity.

Imagine then being able to uniquely personalise the product selection content in every email to every individual on your database, at any hour of the day, taking your products into the frontal lobe of your customer’s consciousness, rather than waiting and hoping your customer comes to you. And this without you ever needing to spend a minute of your time on it. Instead of an autonomous solution for hyper-personalisation, this is AI machine learning software at its finest.

This perpetually watches the buying and browsing habits of each of your consumers. AI machine learning predictive analytics program ranks every SKU in order of the greatest buying propensity for each customer. It sends them emails to generate more purchases, being so accurate and showing them what has been established they want.

This complements traditional ESP software.  Naturally, it nurtures their loyalty too. Sites with high traffic, not adding a facility such as this to their mix, will still be experiencing a higher churn, lower basket values and a higher rate at which goods are returned, and could easily be eliminated.