Emotional branding in the era of generative AI

Apple, Nike, and Starbucks. What’s the first thought that comes to your mind when you read these names or see their logos? Ambition, persistence, comfort?

Regardless of what the exact words are, what’s more important is that, when we come across such iconic brands, we don’t jump to think of their latest products or services. Instead, we think of the emotion the brands evoke.

According to a study by Mars, marketers have just about two seconds to capture consumers’ attention in the digital realm. Unless a customer is already a brand enthusiast, they are unlikely to remember the unique value proposition (UVP) of a product. Therefore, marketers must ensure that their marketing campaigns not only emphasise the UVP but also instantly hook the audience by striking the right emotions.

This works from a financial perspective as well. Harvard Business Review found that fully emotionally connected consumers, on an average, are 52% more valuable to a brand.

To achieve this, brands must defer to the work of renowned psychologist Dr Robert Plutchik, who, in 1980, proposed the wheel of emotions. There are eight primary human emotions: fear, anticipation, joy, trust, sadness, disgust, anger and surprise. Within marketing, anger, sadness and disgust can be disregarded. Fear is an interesting one, which is now replaced with FOMO or the fear of missing out.

Evolving challenges

Before the age of digitisation, emotional branding was tougher, as it relied heavily on physical interactions and limited communication channels. Consequently, it was challenging to reach and emotionally connect with a wide audience in a personalised and scalable way.

Today, marketers face the opposite challenge—oversaturation. Psychologist Dr Gloria Mark studied people’s interaction with computers for more than two decades and identified 47 seconds as the average 21st-century attention span on a screen. This has dropped from 2½ minutes in 2004.

This means that the amount of time marketers have to hook you before you can swipe the notification away is shorter than ever. This has resulted in a slew of ‘clickbaity’ headlines—all in the pursuit of maximising clickthrough rates (CTR).

Enter generative AI

First, a brief primer on Generative AI.

AI that generates original content resembling human-created data using algorithms and learned patterns. It creates new data, images, or text, either entirely from scratch or by modifying existing content.

~ ChatGPT 3.0

Generative AI can revolutionise marketing by enabling brands to create more personalised and emotionally resonant campaigns. Large language models (LLMs) such as ChatGPT push the boundaries of marketing beyond anything that’s come before. GPT-4’s multimodal capabilities mean that marketers can utilise it not only for personalised text messages but also for creating multimedia assets tailored to specific campaigns with respect to palette, theme, and tonality.

For marketers trying to maximise CTRs, the key is to publish content that users cannot help but click on. This requires an in-depth understanding of the industry their brand operates within, what emotions readers resonate with the most, and whether or not the copy/creative aligns with this emotion. Keeping track of these variables is undeniably hectic for marketers. But introducing AI into the workflow helps speed things up.

How would it work?

Using LLMs, campaign texts can be converted into numerical representations that measure the relation between the text and the aforementioned wheel of emotions. In tandem with a generative AI powered content assistant, these copies can be analysed and tweaked to boost certain emotions.

For example, our data finds that FOMO-dominant messaging is the most common type within the retail fashion industry. But surprise-dominant messaging drives up to 10% higher CTRs. Armed with this insight, fashion marketers can ask their AI content assistant to raise the surprise quotient within their copy in a bid to maximise the campaign’s CTR.

With further advancements in the field, this kind of customisation could be brought down to the individual user level—where the notification you receive could be entirely unique based on how you emotionally connect with certain words or phrases.

The future is now

Mainstream names such as Adobe have entered the fray with integrated features such as Generative AI Fill, allowing users to create a selection around the desired area and type in appropriate edits into a textbox.

The Firefly creative engine then steps in and edits the piece in accordance with the prompt and the broader context it can glean. Not only this, the Firefly creative engine is also capable of creating vivid images out of abstract text prompts, thus lowering the technical bar required to tell emotionally compelling stories.

A few years ago, this would have seemed like a pipedream. But it has come to fruition a lot quicker than most anticipated.

Embracing generative AI as the ‘next big thing’ in martech will elevate marketers from the rest—taking them to the ‘10x marketer’ status. By understanding and leveraging the inner-workings of generative AI, they can unlock a new world of possibilities. Age-old martech conundrums such as scaling hyper-personalised content will be potentially solved by those who manage to successfully integrate generative AI into diverse and even siloed workflows.

With generative AI on their side, marketers can elevate brands to new heights and shape the future of marketing. The time to embrace generative AI is now, and those who do not risk falling off the wayside amidst a revolution in marketing excellence.

(The author is Vice President - Data Science, CleverTap.)