The next revolution in marketing has begun courtesy Gen AI

Other tech giants are working on similar solutions for developers that not only enable them to create hyper-personalised content but also enable publishing entities to target them to the right audience.

It has been ten months since ChatGPT’s release and subsequent sensation. There have been many debates, since then, about Gen AI’s applications, impact on jobs, need for regulations and policy, and of course, the ubiquitous question, will AI go rogue and how?

Almost a year in, we can agree that there are many unknowns than knowns, although one of the applications that experts can agree on is Gen AI’s ability to hyper-personalise marketing content. By analysing data on user behaviour, preferences, and demographics Gen AI technologies can adapt marketing content dynamically resulting in increased engagement from the users.

Excitement About Gen AI’s Capabilities

To be fair, hyper-personalisation was the theme for many Chief Marketing Officers in 2021 even before the advent of the Gen AI possibility. However, prompt-based image/video generation that is now possible has made the idea of hyper-personalisation even more personal than one could have imagined in the pre-ChatGPT era.

Prompt-generated marketing copies, along with predictive AI targeting to deliver hyper-personalised content to relevant users, are expected to change the game of marketing. At the Cannes Lions Festival this June, the marketing industry’s marquee event of the year, Google and Meta
showcased some of the personalisation solutions they have been working on.

In a demo, a Google icon was uploaded and it immediately output Google-branded 3D high-quality images of many objects including a dog cartoon and a glass of rose, apt for the occasion. Meta also talked about its AI sandbox as part of many tools for advertisers, in which you can use a few text prompts to come up with a marketing copy.

Other tech giants are working on similar solutions for developers that not only enable them to create hyper-personalised content but also enable publishing entities to target them to the right audience. Some customers have already started piloting by generating personalised marketing videos.

Custom AI Generated Videos, Better Targeting

For example, Carvana created 1.3M+ unique AI-generated videos for its customers. They are taking each customer on a “Carvana joyride” from the day they bought their car with an AI-generated video, tailored to their car-buying experience.

Carvana’s blog lists the example of a customer named Holly who bought a Carvana Corvette on September 29, 2019. September 29 is National Coffee Day, and everyone was also talking about the ending of Game of Thrones that day. Carvana’s system combined these elements with the purchase information available on file to create a custom video.

Custom content, video, and/or images, can help catch a potential customer’s attention, but it is also important to target this personalised content to the relevant audience. Although predictive targeting through machine learning was already widely used, these technologies combined with generative hyper-personalisation could unlock more value.

Microsoft recently launched Predictive Targeting, an AI-powered advertising tool. Predictive Targeting analyses signals from advertisers’ existing ads and landing pages and Microsoft’s audience data to identify potential new audiences and claims to improve conversion by an average of 46 percent.

AI algorithms can readjust behavioural data incrementally based on each new interaction, making marketing campaigns progressively smarter as they roll out across more customers and channels.

Customer Acquisition Struggles

These possibilities are particularly relevant today when brands, retailers, and marketers are struggling with user acquisition. In a low-rate environment, acquisition dollars were easier to come by. But with the latest Fed rate hike in July, we are in the highest interest rate period in the past couple of decades, making the availability of funds for acquisition without proven profitability, much more expensive.

In the meantime, the cost of customer acquisition has steadily increased over the last decade. According to ProfitWell, customer acquisition costs (CAC)  for companies increased by approximately 60 percent between 2014 and 2019, but the pandemic made it even worse.

There are many factors at play here. Firstly, many brands have moved online and are competing with each other for ad inventory which has grown at a slower pace than the demand. Secondly, regulations around online privacy such as deprecating cookies, Central Consumer Protection Authority (CCPA) and General Data Protection Regulation (GDPR), and iOS 14.5 privacy norms have made ad-targeting more difficult.

Performance of some paid channels has reduced significantly and marketers have resorted to broader, less efficient advertising and pulled away from channels where they have low confidence in targeting abilities.

Therefore for many businesses, the focus has moved to retaining the already acquired, rather costly, users. Privacy laws are expected to continue to evolve in lockstep with AI advancements and will play a key role in shaping how hyper-personalisation technology is implemented.

The Gen AI Opportunity

Hence the gen AI hyper-personalisation disruption has arrived at a very opportune time. With increasing digital advertising spend, the upward pressure on keywords is expected to continue to increase. Therefore customer acquisition cost will only reduce if the net impact from improved conversion due to hyper-personalisation offsets the inflationary pressures.

Critics will argue that the verdict will only be known once the solutions currently under the works are optimised and production-sized at scale across the advertising ecosystem from marketers to publishers.

However, it can be agreed that this is a transformative time for the industry and these technologies have the power to revolutionise the marketing and advertising landscape as we know it.

Sneha Mathew is a Strategy and Operations expert in the tech industry leading Scaled Partnerships Strategy at Google Play. Views are personal, and do not represent the stand of this publication.