Original subtitles

- Campaign management is another area

where agent AI is perfect and can help the campaign manager.

The campaign can be an email campaign

or social media campaign,

or a B2B campaign using events or a workshop.

In any campaign, traditionally, the campaign is set up

with a set of outreach to customers

using some creatives and copy.

The customer segment to target for the campaign is selected

using traditional AI to build out customer segments,

and the next best click is predicted

and a channel is selected to send out the campaign.

The campaign response data is studied

to decide on the next step of engagement

or a new segment of customers.

Can you see how agent AI will break down

this task into steps?

Well, agent AI can do each of these steps

and reason to decide on the success of each campaign

and optimize the copy, creative, and channel

by iterative testing for customer response

to arrive at the optimal combination

that meets the campaign goals

in the most cost-effective way.

The third example I want to share in marketing is

about personalization.

Personalization is based on customer data,

and in traditional AI, this data is used

to build recommender systems with collaborative filtering.

Can you imagine how personalization can be done by agent AI?

Post a video and write your ideas in the notepad.

Personalization is about collecting and analyzing user data

and using the insights to drive the choice of what selection

of products or experiences a user is presented on a website.

So an agent AI can be tasked to achieve this.

It will break it down to multiple steps

and use tools to collect and analyze data,

then use reasoning to make decisions

on what is the optimal set

of product recommendations for the user.

Can you imagine what kind of agent AI can be used

to achieve results with this use case?

Also, the agent AI can tap into other services

and data sets as tools to optimize its decisions.

Multiple agents can come together to run a task

and debate with each other using the reasoning power of LLM

to arrive at the optimal personalization for the user.

Fascinating, isn't it?

We have gone from a single agent doing a set of single tasks

to multiple agents negotiating towards a common goal.

This comes with ethical responsibilities

and the amazing power of agent AI.

We learn about the different reasoning approaches

and ethical considerations in future lessons.