In today’s rapidly evolving business landscape, artificial intelligence (AI) and machine learning (ML) have emerged as powerful tools that not only drive efficiency but also foster creativity and innovation across various industries. For the brands that can get it right, it’s a powerful differentiator.
In this article, we’ll uncover how these technologies offer real-world applications and the benefits of how brands can make AI real. We’ll focus on specific examples that highlight their ability to streamline processes, generate insights, and enhance overall productivity.
Analyzing Massive Video Data in Media Outlets
One remarkable application of AI lies in the ability to analyze massive amounts of unstructured data and make sense out of it swiftly. Imagine a large media outlet utilizing advanced algorithms to understand the emotions portrayed in TV shows, down to individual episodes to uncover various themes based on the dialogue and situation during that scene.
Large language models or LLMs can break down information to match the emotions of a specific TV episode with the emotions of an ad and the needs of the consumer watching the show, ensuring relevance and resonance with the audience to help increase attention. We’ve even seen AI leverage weather data to dynamically match ads against those same emotions of TV shows that I mentioned earlier, creating a personalized and contextually relevant advertising experience to what the specific episode and the local weather outside may be emoting. This is just one example of how AI enhances the efficiency of targeted advertising campaigns, driving higher engagement and revenue for media outlets.
Insights Generation and Data Science
Another significant contribution of AI and ML is in the realm of producing and distributing business insights across the enterprise. Today, this process relies heavily on the usage of dashboards and querying databases using SQL to identify insights across various data sources such as marketing, sales, and service. With the advent of generative AI, this process is going through a revolutionary change where we can use conversation interfaces to efficiently join data tables together, simplifying the often complex and time-consuming task of data integration This alleviates a substantial amount of manpower from data scientists day-to-day, allowing them to focus on more critical and strategic tasks around putting the insights into business actions. Note that generative AI can make mistakes, so ensure that your process has checks in place.
Furthermore, creating intuitive interfaces that enable natural language queries enhances the accessibility of data for non-technical users like Merkle’s GenCX.
For instance, a user can simply ask, “Show me all the sales from the paint department last quarter that only came from new customers.” This natural language processing capability not only saves loads of time, but democratizes data access, giving individuals across an organization (whether it’s marketers to incorporate into campaigns, or sales to best understand prospects they’re targeting) to derive valuable insights fast without the need for specialized technical skills.
Efficiency, Creativity, and Innovation
The integration of AI and ML not only enhances efficiency in routine tasks but also stimulates creativity and innovation. By automating mundane and repetitive processes, organizations can free up human resources to focus on more creative and strategic endeavors. The ability to analyze vast amounts of data in real time opens up new avenues for innovation, allowing businesses to make data-driven decisions promptly.
Creating customer journeys and personalized content is extremely critical in our ability to connect, inspire, and engage consumers. However, creating meaningful content and journey ideas takes time and creativity.
For a recent client, my team and I leveraged generative AI tools to create hundreds of concepts fast that were then used to brainstorm, ideate, and create finalized versions of content throughout various journeys that we laid out. This ability to use the power of prompt engineering and gen AI tools for image creation are game changing and is accelerating our ability to drive true one-to-one personalization faster than ever before.
The boom of AI and ML’s accessibility is reshaping the landscape of efficiency, creativity, and innovation across various industries, but brands need to understand how it can be used for their benefit. From analyzing video data in media outlets to empowering data scientists with Gen AI for insights generation, the applications are vast and promising. Start by testing small in a controlled environment and don’t be afraid to fail.
As organizations continue to leverage these technologies, the future holds the potential for unprecedented advancements and transformative breakthroughs in how we work, create, and innovate.
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