- Executive Summary
- A seismic shift for marketers
- Generative AI makes it hyper-personal
- Unlocking variety
- Feasting on the possibilities
- An opportunity and a threat
- A market set to boom
- Is an incremental approach best?
- Learnings
Executive summary:
The world of marketing is undergoing a seismic shift due to the arrival of generative AI. Machine learning models such as ChatGPT, Dall-E, and Midjourney can create engaging marketing content instantly, removing wait times and empowering marketers to experiment with greater freedom. It is little surprise, then, that the number of organisations testing its potential is rising fast.
- IBM’s Firefly demonstrates the vast and diverse potential for AI-generated marketing materials
- Phyron AI hyper-personalises car dealership marketing with automatically-generated video materials.
- Nestle partners with AI firm Courage to create a generative marketing campaign for KitKat about the technology itself.
- “AI is both an opportunity and a threat in equal measure,” says Ben Carter, global chief marketing officer at online car marketplace Carwow.
- 39% of marketers in a Salesforce survey indicate they are unsure how to use the technology safely.
- McKinsey: Generative AI could boost marketing productivity by 5-15% of total expenditure, or US$463 billion annually.
Imagine a future where marketing campaigns that once demanded months of meticulous planning and execution can be launched in mere weeks—or even days. While it remains early days, it appears highly likely that in the near future a lot of the marketing we see will come from the algorithm. It may be tempting, then, to jump right in with generative AI, but take it easy: an incremental implementation is the safest course of action.
A seismic shift in marketing
Like many industries before it, the world of marketing is being shaken up by the rise of generative AI. Long a dream for many software engineers, this technology is now empowering marketers to streamline content creation, enhance creativity, and deliver personalised experiences to their target audiences like never before. At the heart of this boom lies a new class of machine learning models that can generate high-quality text, graphics, audio, and videos by analysing existing data patterns. Indeed, generative AI empowers marketers to craft compelling narratives quickly and tailor messaging to specific audience segments with expert precision. The era of content bottlenecks and one-size-fits-all approaches could very well be over.
According to a McKinsey report from June 2023, generative AI could contribute a staggering $4.4 trillion to annual global productivity, with the marketing and sales sectors poised to capture a substantial portion of that value. Furthermore, generative AI could boost marketing productivity by an impressive 5 to 15 per cent of total marketing expenditure, the equivalent of $463 billion annually. The future of generative AI in marketing looks promising, so let’s take a closer look at it in practice. How it is reshaping the ways in which firms build campaigns, and what are some of the most noteworthy examples of its use to date?
Generative AI makes it hyper-personal
The differentiating power of generative AI is its ability to produce high-quality, hyper-personalised content at scale.
There are several ways in which generative AI could potentially revolutionise how marketing firms speak to their target audience. However, the most significant opportunity it creates is the enabling of hyper-personalisation at scale. With a single prompt, a marketing firm can create resonant content for a given demographic, then with an additional prompt, tweak the messaging approach to reach another. Automate this process and your marketing firm may not even have to lift a finger.
It can even be targeted at the individual level. Ultimately, the power of generative AI is achieved through the brute force of analysing vast troves of data—including data pertaining to the customer’s behaviour, online browsing habits, individual tastes, and lived experiences. It can then use this information to generate content that is not only relevant, but also highly engaging, and tailored to the expectations of the individual on the receiving end. This can be written copy, images, or even video content that feels cohesive and well-integrated, rather than disjointed or generic.
Don’t forget that this is a near-instantaneous process. Whereas a human marketing team may labour for weeks or even months on the right approach for a given demographic, the turnover with generative AI is remarkably fast. It can reduce the time and resources needed to design effective marketing campaigns to as little as a few short days. It can even automate the testing of its own marketing materials on the segment in question, and refine its approach based on metrics such as clicks and time spent viewing. This enables marketers to better understand innovation opportunities by simultaneously analyzing and interpreting text, image, and video data. Such granular personalisation was not possible before the advent of Gen AI, and it’s now powering productivity gains across the global economic marketplace.
Unlocking variety
Insights from IBM and automotive marketing firm DriveCentric showcase the potential for hyper-personalisation at scale.
Our examination of the companies trying out generative AI in marketing begins with the legacy technology company IBM, and what it describes as their most ambitious brand initiative in over a decade. The strategic launch of the ‘Let’s Create’ campaign serves two functions simultaneously: to showcase IBM’s capacity to co-create technology solutions, while also demonstrating how AI shakes up the conceptualisation, production, and dissemination of marketing materials.
Leveraging Adobe Firefly, IBM generated an array of over 200 assets and 1,000 marketing variations, resulting in a remarkable 26-fold engagement surge. “We have started leveraging Adobe Firefly to revolutionise client experiences through AI-powered design, while also streamlining our internal creative workflows,” said Billy Seabrook, Global Chief Design Officer, IBM Consulting. “With Firefly, our 1,600 professional designers within the IBM Consulting experience design team can shift their focus from mundane tasks to devising innovative design solutions with AI, surpassing client expectations”.
Meanwhile, in the automotive industry, one of the biggest challenges facing dealerships is personalising marketing to the needs of specific customers and segments. Enter marketing firm Phyron AI, which blends automation with generative AI to create data-driven video advertisements on social media for a dealership’s entire inventory of vehicles. This approach, it asserts, can substantially increase customer engagement while costing “less than the price of a cup of coffee per vehicle.” Some of the technology’s abilities include rendering a 2D vehicle image in 3D with a 40-degree pan. “This software upgrade raises the bar for promotional videos. It brings cars to life in a way never previously possible,” said Jens-Peter Sjoberg, Co-Founder of Phyron AI. “The results speak for themselves.”
“’Have A(I) Break’ connects one of the most enduring brand platforms in advertising to something deeply relevant in culture. It’s shining a light on a simple, universal human truth that it doesn’t matter how much things change, we’re always better when we take a break”.
Joel Holtby, Co-Founder and Chief Commercial Officer, Courage
Feasting on the possibilities
These highlights from the food industry reveal how generative AI can be used to create vibrant and engaging campaigns.
Some organisations are taking a more vibrant approach to generative AI marketing. Take Mcdonald’s, which partnered with AI marketing firm DDB Group to bring in the Chinese New Year in the fast food outlet’s Hong Kong locations. The commercials, which can be viewed across social media, TV and local LED billboards, invite the viewer to the opening of a virtual McDonald’s restaurant, before taking them on a journey through a range of imagined worlds. A range of music stars, including MC Cheung, Panther Chan and Gareth T. join the celebrations, wishing the viewers a happy new year. “We believe the visual interest and impact of AI has added extra flavours to the celebration,” remarks Tina Chao, Chief Marketing Officer for McDonald’s Hong Kong.
Other companies in the food industry are taking a more humorous approach. Nestle partnered with Toronto marketing firm Courage to generate a video marketing campaign, dubbed ‘Take A(I) Break’, which whimsically melds tradition with the cutting-edge. Inspired by recent research from Google DeepMind, it makes the playful suggestion that even AI could benefit from taking a break sometimes. The result: a staggering increase in accuracy, from 30 per cent to a remarkable 60-70 per cent. This unusual campaign has graced screens throughout Canada, but can also be found on KitKat’s official YouTube channel. “[It] connected one of the most enduring brand platforms in advertising to something deeply relevant in culture,” said Joel Holtby, Co-Founder and Chief Commercial Officer, Courage.
An opportunity and a threat
While generative AI can offer numerous benefits to marketers, it’s important to remain vigilant about its current limitations.
When asked to share their views on the use of generative AI in marketing, most experts agree that the technology will have a positive impact on the industry, making it easier for marketers to experiment with new ideas. “If you’re going to make one thing and it takes a long time, you’re not going to take as many risks”, says James Slezak, chief executive officer of consumer research platform Swayable. “But we’ve all had crazy ideas and wondered, ‘Would they fly? Would they lift consumer intent?’ Now there’s a chance to do that more easily”.
Others remain on the fence. “AI is both an opportunity and a threat in equal measure”, says Ben Carter, global chief marketing officer at online car marketplace Carwow. “It is an opportunity because it will deliver significant productivity gains and enable us to deliver even more relevant messages to our audiences. It is a threat, not because it could wipe out humanity (hopefully not), but because there are only a few technologies that could cause real disruption, and this is one of them”.
If you do decide to incorporate generative AI into your marketing strategy, it’s important to ensure that there is always a human in the loop, according to Michael Heaven, co-founder and managing director of digital agency Butterfly 3ffect. “While there is plenty of room for gen AI to improve the workflow of a project, there should be plenty of human guardrails to prevent output that could be harmful to a client being published,” Heaven says.
“AI is both an opportunity and a threat in equal measure”.
Ben Carter, global chief marketing officer at online car marketplace Carwow
A market set to boom
Marketers are finding a wide variety of applications for generative AI—but also indicate their concerns regarding its use.
Statistics reveal that, despite the apparent potential, things remain at a relatively nascent stage for generative AI in marketing. A 2022 study by the MIT Technology Review found that only 5% of marketing organisations considered generative AI critical to their functions, and only 20% were properly deploying it across different advertorial use cases. By 2025, however, this is expected to rise, with 20% of marketing executives polled indicating their intention to make the technology a core part of their department’s function. Numbers from a 2023 Salesforce survey of 1,000 marketers paint a slightly more promising picture: more than half of firms are currently using generative AI, with a further 22% planning to trial the technology in the coming year.
Marketers polled in the Salesforce survey also indicated their concerns with the technology, with 39% stating they are unsure how to use the technology safely. Amongst their concerns were accuracy and quality (31%), trust (20%), skill preparedness (19%), and their own job safety (18%). Nevertheless, it is being deployed across a wide variety of use-cases by those adept in AI. As per market research firm Insider Intelligence, the top five uses for generative AI in marketing in May 2023 were basic content creation and writing copy (both 76%), inspiring creative thinking (71%), analysing market data (71%), and generating asset images (62%).
Further data from Insider Intelligence reveals that, of the marketing firms using AI, 46% have already embraced it as the core of their current and future campaign strategies. Six in 10 highlight improvements to advertising performance as the primary benefit of its integration. Little surprise, then, that the market for generative AI in advertising is expected to skyrocket as the decade continues. According to Inkwood Research, the market was valued at US$11.73bn in 2020 and could exceed US$82.7bn by 2028 at a compound annual growth rate of 26.58%.
Is an incremental approach best?
Bringing in AI should be a gradual process, beginning with off-the-shelf solutions before tailoring and integrating them alongside other digital tools.
There is no shortage of ways in which generative AI can be implemented within a marketing operation. However, it is important to bear in mind the level of experience your team already has with the technology before proceeding. For companies just getting started, or with an IT team only just getting to grips with the technology, it may be preferable to use off-the-shelf solutions. These are the more generic tools such as Midjourney, Casper.ai and ChatGPT that have already been proven effective in a broad sense, while perhaps not being tailored to the acute business needs of your organisation. This may provide incremental boosts to productivity in areas such as content development and messaging.
Once your marketing team is comfortable with using these tools, it may be time to consider tailoring the foundational AI models to your benefit. This could mean leveraging consumer data from inside the organisation and using them as training material for the AI to hyper-personalise content. For example, email and social media-based outreach campaigns could be lightly tweaked to meet the expectations of a specific demographic—and subsequently reviewed by a human—before being shared.
At the more advanced level, your marketing team may be almost entirely hands-off, focussed on higher-level strategic plays and performing little more than scheduled oversight over the general marketing operation. At this level, generative AI is heavily customized to your organisation’s needs and deeply integrated with automation tools and both real and modelled consumer data. Hyper-personalised marketing materials are sent out automatically and targeted not only to the demographic or segment but to the minutiae of the individual consumer’s tastes and preferences. To succeed in this approach, you may wish to expand or reorganise your marketing team with more AI engineers and data scientists. Jumping into the deep end blind may not create the results you are looking for, and could prove a costly mistake.
Learnings:
Generative AI ultimately remains an emerging technology, albeit a highly promising one. As it continues to advance, there could be great potential for its use among brands looking to level up their creativity, streamline content production, and deliver more personalised experiences than were previously possible.
- Generative AI unlocks hyper-personalisation at scale, allowing unprecedented product targeting.
- It can also be used to speed up ideation and quickly generate marketing materials across various creative formats.
- While only a minority of marketing firms have fully embraced generative AI, those who do report substantive boosts to productivity and performance.
- An incremental approach to implementing generative AI may prove most effective, allowing teams to adapt to its presence.
- Another key consideration is to always have a human in the loop to ensure that the AI-generated content aligns with the brand’s values.
As generative AI evolves, key questions remain: How might it reshape marketing norms and consumer expectations? What new creative frontiers could it unlock? And perhaps most importantly, how can marketers harness its power responsibly to build deeper brand-consumer connections? While no answer has yet emerged to any of these questions, it does appear certain that, whatever the future holds for marketing, generative AI is likely to be a big part of it.
