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How does AI support creativity? A marketing perspective

Braze has released its annual Global Customer Engagement Review, covering three trends for customer engagement in 2024. It’s the first trend we will look at here – creativity and strategy work better together with AI.

Some might argue that creativity and AI only go together because leveraging AI for routine work paves the way to being more creative. But it’s not as simple as that. AI can play a strategic role in creativity, and James Manderson, SVP of Customer Success at Braze, helps explain how.

Let’s take a minute and define creativity as it relates to this study. According to Manderson, creativity,

At Braze, we think of creativity as the ability to generate new, original, and valuable ideas and come up with innovative solutions to problems that consumers regularly have. And maybe it’s not always solving problems, but creating moments of joy by helping consumers feel seen and connected with a brand through unique experiences. It’s about using technology and data to amplify and accelerate creative ideas, rather than seeing them as obstacles pitted against one another.

Creativity and strategy work is better with AI

According to this study, marketers are struggling with creativity:

  • 42% said there’s too much emphasis on KPIs
  • 42% said they spend too much time on “business as usual” execution and tasks. 

Other challenges included not being able to demonstrate the ROI impact of creativity and a lack of technology to execute creative ideas.

Here’s a question, though. One of the issues holding marketers back from being more creative and strategic is the need to focus on KPIs – but we are constantly hearing that marketers need to be more data-driven. How do marketers support both? Is it possible? Manderson says yes, they can do both because the two are not mutually exclusive – they complement each other:

Data-driven marketing is about using insights derived from data analysis to inform strategy and decision-making. It helps marketers understand their audience better, identify trends, and measure the effectiveness of their campaigns. This, in turn, can guide creative efforts by providing a clear picture of what works and what doesn’t.

On the other hand, creativity is what allows marketers to come up with more innovative ideas and strategies that can capture the audience’s attention and drive long-term customer lifetime value. It’s about finding new ways to deliver a brand’s message.”

Manderson says that KPIs serve as a guide for creative efforts if used correctly. The key is that marketers can’t focus all their efforts on meeting KPIs; they need to also include time for innovative thinking.

How exactly does AI support creativity?

Manderson offers several ways creativity and strategy work better together with AI, most of which have to do with its ability to analyze vast amounts of data:

AI can process large volumes of data, providing valuable insights into customer behavior, preferences, and trends. These insights can guide creative decisions, ensuring they are both targeted and relevant. For instance, AI can determine which content types are most appealing to different customer segments, leading to the creation of more effective marketing campaigns.

He also explains that AI can help scale content personalization, run A/B tests and quickly analyze results, predict future trends and behaviors, and automate routine tasks such as customer segmentation, personalized email delivery, and journey optimization:

AI can also identify patterns and connections that might be missed by humans, leading to the generation of new creative ideas. For example, AI could analyze data from various industries to identify trends or strategies that could be applied in new ways.

But for all AI can do, marketers still struggle to take advantage of it. 

The challenges mostly lie in marketers being overwhelmed by all of the solutions in front of them, along with all of the breadth of use case possibilities they present. Many brands have yet to utilize it in revolutionary ways. To truly harness the potential of this advanced technology, it should be viewed not merely as a tool to ease the workload of marketers, but rather as a collaborator. It can function as an advisor of sorts, working in tandem with customer engagement teams to facilitate innovative, strategic, and creative endeavors.

Here’s how marketers want to explore the full potential of AI (according to the study):

  • Generate creative ideas – 48%
  • Automate repetitive tasks – 47%
  • Optimize strategies in real-time – 47%
  • Enhance data analytics – 47%
  • Power predictive analytics – 45%
  • Personalize campaign – 44%

How can marketers use AI more strategically?

We’ve been playing with some types of AI (e.g., generative AI) for over a year now, but AI and NLP have also been key capabilities of engagement platforms (like Braze) and other marketing platforms, for a while now. So, it is time to get serious about how these capabilities are leveraged. Manderson says his team always recommends collaborative experimentation when introducing something new:

You can start by creating a list of capabilities you have with various AI solutions in your tech stack and make it a point to assign specific tasks to each solution. You could also reverse the thinking and start with what you want to do that takes too much time or just doesn’t get prioritized in your team’s workday and shop for solutions in your tech stack (or new solutions) that can execute. 

Either way, you start with a list, plan an experimentation schedule that fits what you have and what you want to do, and socialize the results once each experiment concludes. From there, it should be easy to see where AI can make the biggest impact, rally colleagues to see the value of AI, and begin to solidify it as part of their daily work.”

My take

Today’s marketer needs to have an eye on how their tools use AI (and if they don’t, why not). The magic of AI is in its ability to consume and analyze large amounts of data. It makes sense that it can help marketers be more creative by surfacing trends and pointing out things we can’t see that are hidden in the data. I always go back to AI’s ability to support personalization at scale because it can track a customer across all types of channels and interactions and recommend (and even activate) relevant next steps. 

I also agree with Manderson’s recommendation of collaborative experimentation. Be strategic about what you are trying. Don’t try a ton of experiments at once; instead, be selective on things that you think will have an impact. And it doesn’t need to be a huge impact. Sometimes, the little things have huge results and open the door to new ideas on how to leverage AI.

Originally Appeared Here

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Early Bird