Generative AI was a theme that defined 2023, and this trend is continuing this year. IBM recently published a series of ‘targeted, research-backed guides to generative AI’. While these guides address a range of topics, we’re going to take a look at the insights related to marketing.
The good news is that IBM believes the advent of generative AI offers marketing an opportunity to excel when it comes to personalisation:
While many marketing organizations are already using generative AI based on public large language models (LLMs) for content creation, few have tapped this game-changing capability for extreme customization by feeding the models their own data. But that will soon change, as more than half (51%) of CMOs say they have plans to build foundation models with proprietary data—the intellectual capital about customers that sits in marketing—before the end of 2024.
This would completely change the way that consumers interact with marketing materials – although there are two sides to the coin, as this would also introduce a new element of risk. In order to mitigate these risks, IBM shares three pointers that every CEO should consider when thinking about AI and marketing:
1. Marketing is the pacesetter for enterprise-wide generative AI
More than one in four (27%) executives expect marketing roles to be automated due to generative AI.
Although this may sound alarming to those working in the marketing industry, Mark Read (CEO of WPP) believes that AI will lead to alternative job prospects. Read says:
“We know what jobs [generative AI] will disrupt, but we don’t know what jobs AI will create. And I’m sure it’ll create many, many jobs. If I look at WPP, probably half the jobs inside the company didn’t exist 20 years ago. We didn’t have social media managers. We didn’t have programmatic media managers. We didn’t have search engine optimizers. I could go on.”
This could change the way that many marketing agencies operate: with some workplaces experiencing a big transformation. IBM suggests the following advice for handling these changes:
- Make the CMO the champion of the customer. Position marketing as the owner of the brand’s customer experience and lifecycle. Give it the responsibility and authority to influence the customer value chain across the enterprise. Recognize and address brand risks while leveraging new engagement opportunities offered by generative AI.
- Emphasize higher-value role creation. Work with the CMO to build marketing teams rooted in the skills needed for the generative AI era. As in customer service, apply lessons learned from marketing’s reinvention to other functions
- Turn apprehension into excitement. Encourage your CMO to execute a purpose-driven, targeted, formal change management approach to help marketers understand and lean into new value propositions for their roles. Lead with openness, transparency, and authentic communication from both the top down and the bottom up.
While many will remain concerned about job security, actioning these steps could help to demonstrate a pragmatic approach to the adoption of AI. If generative AI allows human workers to focus on higher level tasks that are more fulfilling, we could even see an increase in job satisfaction.
2. Content creators are freed from feeding the beast
As generative AI plays a larger role in content creation, teams will be able to spend more time thinking strategically about how messaging can support both business objectives and customer needs—and experimenting with innovative marketing approaches. They can create dynamic journey maps based on what buyers are doing.
Rather than frantically filling the publishing pipeline, they can thoughtfully consider where high-value content should be created based on data inputs and determine which delivery methods will be most effective for each customer. These directives can also fuel product and merchandizing decisions across the organization.
This approach will likely divide creatives, with some excited about the role that generative AI could play in their work, and others some seeing it as a direct threat to the jobs of content creators.
Here’s what IBM recommends doing:
- Say goodbye to writer’s block. Show teams how generative AI can accelerate the content production process. Tap LLMs customized with your organization’s data to help brainstorm topics, headlines, social posts, and variations on messaging that will work for different audiences. Triple check to eliminate bias in any content created by generative AI–or humans
- Close the gap between customer needs and marketing content. Determine where content is needed to prompt desired customer actions and outcomes and use generative AI to produce pieces that will alleviate specific pain points on the customer journey.
- Identify people doing tomorrow’s jobs today. Discover the new roles that generative AI enables by paying close attention to people on the front lines. Those who embrace generative AI from the start will have insights, leading practices, and lessons learned that will help you define the MarOps model of the future.
The ‘triple check’ mentioned in the first point is especially important here, since this will require a real human to do the job. The recurring theme here is that human workers will be needed to implement this type of work: which is why it’s important for marketers to become competent users of AI tools. There is immense value in understanding how new tools work. Staying up to date with new developments can help marketers offer a wider and more valuable skill set.
3. With generative AI, hyper-personalization is no longer a pipe dream
More than two in five (42%) CMOs say scaling hyper-personalization is a marketing priority—and 64% expect to use generative AI for content personalization in the next year or two. But organizations need a consolidated, granular view of customer behaviors and preferences to get there. This takes flawless data integration and management, which has long been marketing’s Achilles heel.
As mentioned above, using AI to its full potential (especially when it comes to hyper-personalisation) will require humans who are able to interpret complex data and implement their findings appropriately. IBM recommends:
- Build multidisciplinary marketing and IT teams. Align CMO and CIO priorities, incentivizing partnership between the two. Stand up the infrastructure, systems, and data integration required for true one-to-one marketing with generative AI.
- Get the full picture of your customers’ needs. Break down functional silos to consolidate data from marketing, sales, and customer service to capture a complete picture of customers’ individual journeys with your business.
- Supercharge open models with customer data. Position your customer data as your best brand differentiator and defense against misinformation. At the same time, leverage the speed and scalability of open and public models to personalize experiences and offerings—while securing sensitive data each step of the way.
Successfully executing an AI-led, hyper-personalised marketing strategy would be something completely new. Although it will take some time to fully measure the extent of the business benefits this could offer, many organisations will want to lead the way in this new advancement.
This truly is a ‘sink or swim’ moment for marketers and creatives everywhere, and at Novagram we’re ready to crest the waves and see what this year will hold. As we stay abreast of the latest AI advancements, we continue to offer our clients outstanding branding, design, and digital development work.
If you’re interested in working with us in 2024, get in touch.
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