About this Agent

The Email Campaign Personalization Agent is an AI-driven solution designed to automatically generate personalized email content for digital marketing launch campaigns. By utilizing customer segmentation data, this AI agent crafts tailored email messages that resonate with specific audience segments, enhancing engagement and driving campaign success. It focuses on understanding the audience's preferences, brand alignment, and key messaging to create impactful email communications.

Accuracy
TBD

Speed
TBD

Input Data Set

Sample of data set required for Email Campaign Personalization Agent:

Input

kind	audience	brand	key_message	age_group	location	interests
Launch	New Customers	Swadeshi	Join us for the grand launch of our exciting new fitness app!	18-28	India	Fitness, Sustainable Living
Promotional	Returning Customers	HealthPlus	Discover health tips and products tailored for your lifestyle.	55+	India	Health, Technology
Informational	Potential Leads	TechBharat	Discover health tips and products tailored for your lifestyle.	55+	India	Travel, Eco-friendly products

Deliverable Example

Sample output delivered by the Email Campaign Personalization Agent:

Subject: Join Us for the Grand Launch of Our New Fitness App at Swadeshi!

Dear New Customers,

We are thrilled to invite you to the grand launch of our exciting new fitness app at Swadeshi! 🎉

As a valued customer, your experience matters to us. This app is designed to cater to your fitness journey and promote a sustainable lifestyle. We know you'll love the features we’ve tailored with your interests in mind: Fitness, Sustainable Living.

Launch Event Details:

- Date: This Weekend

- Time: 10:00 AM - 5:00 PM

- Location: Available online and at selected stores across India.

Be among the first to explore the innovative features of our app and enjoy exclusive launch-day offers! Don't miss this opportunity!

Best wishes,

The Swadeshi Team

ZBrain credits and their usage

A credit is a unit of usage on ZBrain. Credits are consumed whenever you perform actions such as embedding documents or querying an app. Here’s how credits are utilized:

Document Embedding:

When you upload a document, it is processed and embedded to create a searchable vector representation. This step consumes credits based on the size of the document and the embedding model used.

Input Processing:

When you ask a question, the relevant context is retrieved from the embeddings and processed by the Large Language Model (LLM). This step incurs a credit cost based on the model and the number of input tokens.

Generating Output

The LLM then generates a response based on the processed input, consuming additional credits based on the number of output tokens.

The cost in credits for various models and processes is detailed below:

Models and Credit Consumption:

Model	Input Cost	Output Cost
GPT-4o	2,500 credits / 1M tokens	7,500 credits / 1M tokens
GPT-4	15,000 credits / 1M tokens	30,000 credits / 1M tokens
GPT-4-32k	30,000 credits / 1M tokens	60,000 credits / 1M tokens
GPT-3.5 Turbo	250 credits / 1M tokens	750 credits / 1M tokens

Embedding Models:

Model	Input Cost
text-embedding-3-small	20 credits / 1M tokens
text-embedding-3-large	130 credits / 1M tokens
ada v2	100 credits / 1M tokens

When you create a knowledge base or query an app, credits are deducted based on the embedding, input, and output token usage. This ensures you only pay for what you use while leveraging the full power of advanced AI models.

Email Campaign Personalization Agent

About this Agent

Input Data Set

Deliverable Example

Subject: Join Us for the Grand Launch of Our New Fitness App at Swadeshi!

Launch Event Details:

Company

Product

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In this personalized demo, you will:

Explore ZBrain Platform

Discover Workflow Integrations

Engage in Q&A Session