Braze published its annual report Global Customer Engagement Reviewcovering three trends in customer engagement in 2024. This is the first trend we’ll look at here: creativity and strategy work better with AI.
Some might argue that creativity and AI only go hand in hand because leveraging AI for routine work paves the way for greater creativity. But it’s not that simple. AI can play a strategic role in creativity, and James Manderson, SVP of Customer Success at Braze, explains how.
Let’s take a minute and define creativity for the purposes of this study. According to Manderson, creativity,
At Braze, we view creativity as the ability to generate new, original and valuable ideas and provide innovative solutions to problems that consumers regularly encounter. And maybe it’s not always about solving problems, but about creating moments of joy by helping consumers feel seen and connected to a brand through unique experiences. It’s about using technology and data to amplify and accelerate creative ideas, rather than seeing them as obstacles opposing each other.
Creativity and strategy work is better with AI
According to this study, marketers struggle to be creative:
- 42% said there was too much emphasis on KPIs
- 42% said they were spending too much time on “business as usual” execution and tasks.
Other challenges included the inability to demonstrate the impact of creativity on ROI and the lack of technology to execute creative ideas.
Here is 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 constantly hear 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 involves using insights derived from data analysis to inform strategy and decision-making. It helps marketers better understand their audience, 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 generate long-term value for the customer. It’s about finding new ways to convey a brand’s message.
Manderson says KPIs serve as a guide for creative efforts if used correctly. The key is that marketers cannot focus all their efforts on meeting KPIs; they must also allow time for innovative thinking.
How exactly does AI support creativity?
Manderson offers several ways creativity and strategy work better with AI, most of which relate to its ability to analyze large amounts of data:
AI can process large volumes of data, providing valuable insights into customer behavior, preferences and trends. This information can guide creative decisions, ensuring they are both focused and relevant. For example, AI can determine which types of content 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 like segmentation customers, delivery of personalized emails and optimization of journeys:
AI can also identify patterns and connections that humans might miss, 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 despite everything AI can do, marketers still struggle to take advantage of it.
The challenges primarily lie in marketers being overwhelmed by all the solutions in front of them, as well as the breadth of use case possibilities they present. Many brands are not yet using it in revolutionary ways. To truly harness the potential of this advanced technology, it must be viewed not just 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 efforts.
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%
- Improve data analysis – 47%
- Powerful predictive analytics – 45%
- Personalize the 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 are also key capabilities in engagement platforms (like Braze) and others marketing platforms, for some time now. So it’s time to think seriously 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 technology stack and make sure to assign specific tasks to each solution. You can also reverse the thinking and start with what you want to do that takes too long or is simply not a priority in your team’s workday and look for solutions in your technology stack (or new solutions) which can be executed.
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 after each experiment is completed. From there, it should be easy to see where AI can have the biggest impact, convince colleagues to understand the value of AI, and start solidifying it as part of their daily work.
My opinion
Today’s marketers need to monitor how their tools use AI (and if they don’t, why not). The magic of AI lies in its ability to consume and analyze large amounts of data. It makes sense that this could help marketers be more creative in surfacing trends and highlighting things we can’t see that are hidden in the data. I always come back to AI’s ability to support personalization at scale, as it can track a customer across all types of channels and interactions and recommend (and even enable) relevant next steps.
I also agree with Manderson’s recommendation for collaborative experimentation. Be strategic about what you try. Don’t try a ton of experiments at once; instead, be selective about the things you think will have an impact. And it doesn’t have to have a huge impact. Sometimes small things yield huge results and open the door to new ideas on how to leverage AI.
