Put AI in its PLACE: How Zeta is Harnessing Generative AI to Help Marketers Succeed

By Roman Gun, VP Product Management

Our kids’ history books will likely bill 2023 as the ‘AI gold rush’. The introduction of ChatGPT and hundreds of LLMs that followed began to fundamentally change how work gets done. Now that the dust has settled (at least a bit) it’s clear that generative AI is here to stay.

A recent report from The Conference Board explains that 87% of marketers have used AI or experimented with AI tools for at least one application, and 68% are now using AI at least “sometimes” in their daily work. However, marketers remain tepid regarding how AI will impact creativity, work quality, and job availability.

Instead of hoping that the AI storm will just blow over, we need to embrace this seismic shift and figure out how to best harness this new technology to make our lives better and easier, and in turn, make our customers’ lives better and easier.

Another Tool in the Toolbox

When Photoshop was first released in 1990, a whole cohort of designers thought they were going to be put out of jobs. Instead, Photoshop became an indispensable tool to enhance, not replace human ability. It eliminated countless hours of tedious work spent layering, shading, and cropping, and enabled more precision, efficiency, and creativity. Today, Photoshop is a household name inextricably linked with the design industry.

The advent of generative AI is similar. It’s not going to replace marketers, but it will change how we do our jobs, arguably for the better. It’s another tool i that gives us access to powerful analytical and processing capabilities, helping us make strides toward the holy grail of truly individualized customer experiences.
In this post we’ll examine some of the fundamentals of generative AI, what it is, how it works, and how it will benefit marketers. We’ll also introduce and explain the PLACE framework, which Zeta has developed to help marketers compartmentalize different capabilities of AI and apply it to specific areas of their work.

What is Generative AI?

If you’ve been living under a rock for the past 18 months, here’s a crash course on generative AI. Generative AI refers to a type of AI that uses advanced machine learning techniques, especially deep learning models, to create outputs like text, images, music, speech, and even code. Compared to earlier iterations of marketing AI, generative AI represents a significant step forward. 

Earlier AI, like send-time and A/B/n optimization, was limited to processing existing data and returning simple results. Generative AI can create entirely new content based on existing data which yields a much wider variety of creative outputs.

While generative AI is a useful tool, its outputs (e.g., a blog post, email, or campaign) tend to be too rudimentary to be public facing. Some amount of human intervention is still needed to steward your unique brand voice. It’s also important to keep in mind that the AI output is only as good as the inputs and sources it uses to build content, which is why working with clean, up-to-date datasets is essential.

How Generative AI Will Benefit Marketers

As the conversation around generative AI evolves, we need to move beyond the hypothetical and focus on practical applications that can be used today. Below are a few concrete ways that generative AI is making a significant impact on the day-to-day success of marketers.

Increased Efficiency

By doing the legwork quickly churning outideas, blog posts, and graphics, marketers can apply the time saved on creation toinstead focus on fine tuning. Unlike searching Google for answers or ideas, generative AI’s natural language processing (NLP) capabilities allow it to understand the nuances of prompts, leading to more accurate and relevant responses. This means that marketers can get direct and specific answers to their questions without sifting through multiple articles on a given topic.

Greater Creative Capacity

Marketers are under constant pressure to deliver high-value creative output. This can lead to creative fatigue or writer’s block. With the help of generative AI, marketers can eliminate the grunt work and boost their creativity. Think of generative AI as press that keeps the creative juices flowing, and the momentum on a project moving forward. 

Optimized Targeting and Segmentation

Generative AI can spot patterns and trends by analyzing massive amounts of customer, purchase, and behavioral data, allowing you to develop hyper-accurate audience segments.Generative Instead of simply matching audience traits, generative segmentation tools can automatically create net-new audience segments based on previous and predicted behavior. 

Improved ROI

Generative AI can boost marketing ROI by saving time and resources. It shifts focus from routine tasks to strategic projects, creates precise audience segments for better engagement and conversions, and enhances service delivery for increased customer satisfaction and retention.

The Nuts and Bolts of Generative AI

Before we dive into the PLACE framework, it’s important to understand what AI Agents are, how they work together to solve complex problems, and how Zeta is leveraging them within the ZMP.

Agents

A generative AI Agent is a model built for a specific task. Think of an Agent as a subject matter expert (SME) in a particular topic that acts as your assistant.

For example, you might have one Agent that has been specifically tuned to write email subject lines, another that can generate images, and another that creates custom campaign reports. Each Agent works independently to help the marketer do their job more effectively.

Agent Library

Agents can accomplish many different tasks, but learning how to use them can be a bit daunting. That’s why in the coming months Zeta will be rolling out a library of pre-built AI agents that marketers can easily use within the ZMP. The goal is to give marketers the ability to leverage AI more easily in their day-to-day work, and demystify generative AI in general.

The PLACE Framework: Putting Generative AI in Every Marketer’s Pocket

In addition to our library of shelved agents, Zeta has developed the PLACE framework— a structured approach that helps marketers build their own custom AI Agents that are tailored to their specific needs and business cases. Instead of forcing marketers to adapt to a one-size-fits-all AI assistant, Zeta allows for complete customization so marketers can apply generative AI according to their specific use cases.

PLACE, which stands for Part, Landscape, Assignment, Course, and Example, guides marketers through a systematic process of defining the role, context, tasks, actions, and expected outcomes for their AI Agents. By inputting these details into the framework, Zeta helps marketers build custom Agents that can help them do their job more effectively. 

1. Part

First the marketer will define the role of the AI Agent within the marketing team. This could be data analysis, content creation, customer interaction, or any other specific marketing function. The clearer the role, the more effectively the Agent can be programmed to perform its duties.

2. Landscape

Next you need to outline the operating environment or context in which the AI Agent will function. This might include things like market factors, target audience, competition, or specific products. Information can also be pulled from the Zeta Data Cloud to augment first-party data for more targeted results. By understanding the landscape, the AI Agent will be better equipped to make informed decisions and adapt to changes in the environment.

3. Assignment

Now it’s time to specify the tasks that the AI Agent will perform. This could range from analyzing customer data, managing social media accounts, or conducting market research, all the way to creating and executing full marketing campaigns. The key is to detail these tasks as clearly as possible so that the AI Agent knows exactly what it needs to do.

4. Course

Next, define the actions that the AI Agent will take to accomplish its tasks. This involves setting parameters around what the agent can and should do in certain situations, such as when to access internal or external APIs.

5. Example

The final step is to provide examples of the desired output. This could be in the form of reports, insights, customer engagement metrics, or any other tangible results that the marketer expects from the Agent. Providing examples helps to fine tune performance and ensure the Agent delivers on its objectives.

Make AI a Part of Your Day-to-Day Workflow

The PLACE framework is a bold new approach that gives marketers the ability to harness the full potential of AI in their day-to-day work. Our goal is to make generative AI accessible, and to reposition it as a helpful tool, instead of a potential adversary. By embracing generative AI, marketers can displace repetitive, time-consuming tasks with creating impactful experiences for their customers.