Marketing Reports & Ads Optimization

Creating marketing reports and optimizing ads manually can be inefficient. KaibanJS automates this process with AI agents that extract insights, identify keywords, and generate ad strategies—saving time and improving precision.

The Challenge

Marketing teams often struggle with:

Extracting key insights from website content.
Identifying and structuring effective keywords.
Creating compelling ad copies tailored to the audience.
Managing multiple campaigns while ensuring consistency.

Manual processes can be inconsistent and time-consuming, especially for large-scale campaigns.

The Solution with KaibanJS

KaibanJS automates marketing workflows using AI agents that extract content insights, generate keyword-focused reports, and create optimized ad templates. This ensures efficiency and consistency across multiple campaigns.

The Agentic Solution

KaibanJS utilizes two specialized AI agents:

🕵️Agents

ContentAnalyzer:
- Extracts key themes, keywords, and value propositions from website content.
- Identifies tone, style, and unique selling points.
ReportGenerator:
- Compiles marketing insights into structured reports.
- Generates keyword-focused ad templates with optimized headlines and descriptions.
- Recommends ad optimization strategies, including negative keyword suggestions.

Process Overview

Here’s how KaibanJS automates marketing optimization:

📝Tasks

Content Analysis: The ContentAnalyzer scans the provided URL to extract keywords, tone, and value propositions.
Report Generation: The ReportGenerator structures insights into a marketing report and generates ad templates.
Optimization Suggestions: Includes keyword improvements and performance-enhancing strategies.
Output Compilation: Delivers a complete marketing report with actionable insights and ready-to-use ad copies.

Implementation

Below is an example of how this automation is implemented using KaibanJS:

import { Agent, Task, Team } from 'kaibanjs';
import { Tool } from "@langchain/core/tools";
import { z } from "zod";
import axios from "axios";

// === UrlMarkdown Tool ===
export class UrlMarkdown extends Tool {
  constructor(fields) {
    super(fields);
    this.name = "url_markdown_tool";
    this.description = "Gets content in Markdown format from a URL.";
    this.schema = z.object({
      url: z
        .string()
        .url()
        .describe("The URL from which to extract content in Markdown format."),
    });
  }

  async _call(input) {
    try {
      const requestUrl = `https://r.jina.ai/${encodeURIComponent(input.url)}`;
      const response = await axios.get(requestUrl);
      return response.data;
    } catch (error) {
      return `Error getting content from URL: ${error.message}`;
    }
  }
}

// Tool instance
const urlMarkdownTool = new UrlMarkdown();

// === AGENTS ===

// Content Analysis Agent
const contentAnalyzer = new Agent({
  name: 'ContentAnalyzer',
  role: 'Content Analysis Specialist',
  goal: 'Extract and analyze relevant information from URLs',
  background: 'Expert in web content analysis and key information extraction',
  tools: [urlMarkdownTool]
});

// Report Generator Agent
const reportGenerator = new Agent({
  name: 'ReportGenerator',
  role: 'Marketing Report Specialist',
  goal: 'Generate detailed marketing reports and optimized ads',
  background: 'Specialist in digital marketing and Google Ads generation',
  tools: []
});

// === TASKS ===
const tasks = [
  // Task 1: Content Analysis
  new Task({
    description: `Analyze both the main URL: {url} and the specific landing page: {ad_destination_url} using the url_markdown_tool.

Required information to extract:
1. Website type analysis (identify if it's an ecommerce)
2. Specific analysis for {service_to_promote}:
   - Key features and benefits
   - Pricing information if available
   - Unique selling points
   - Technical specifications
   - Service guarantees or warranties

3. Landing page specific elements ({ad_destination_url}):
   - Main call to action
   - Conversion elements
   - Trust signals
   - Testimonials or social proof
   - Service-specific benefits

4. Generate keywords focused on {service_to_promote}:
   For ecommerce:
   - Transactional keywords specific to the product/service
   - Price-oriented terms for this specific service
   - Product-specific features and specs
   For non-ecommerce:
   - Service-specific benefit keywords
   - Problem-solution keywords
   - Industry-specific terms

5. Generate 10 longtail variations for {service_to_promote}:
   - Include specific features
   - Add location modifiers if relevant
   - Use buying intent modifiers
   - Include pricing terms if applicable

Language: {language}`,
    expectedOutput: `Output in markdown format with titles and lists for easy reading.
- Website Type: [Ecommerce/Non-ecommerce]
- Service Analysis for {service_to_promote}: [Key features and benefits]
- Landing Page Analysis: [Key conversion elements from {ad_destination_url}]
- Primary Keywords: [at least 10 keywords focused on {service_to_promote}]
- Longtail Keywords: [10 variations specific to {service_to_promote}]`,
    agent: contentAnalyzer,
    priority: 1
  }),

  // Task 2: Ad Generation
  new Task({
    description: `Using the analyzed information, generate optimized ads specifically for {service_to_promote}.

Make sure to:
1. Create Service-Specific Ads for {service_to_promote}:
   - Identify and address key pain points:
     * Current frustrations
     * Common challenges
     * Industry problems
     * Time-wasting issues
     * Cost-related concerns
     * Quality concerns
     * Process inefficiencies
   
   - Structure headlines as Problem > Solution:
     * "Tired of [Pain Point]? > Discover [Solution]"
     * "Struggling with [Problem]? > Get [Benefit]"
     * "Fed up with [Issue]? > Try [Solution]"
     * "[Pain Point] Problems? > We Fix That"
   
   - Use description lines to:
     * Acknowledge the pain ("We know [pain point] is frustrating")
     * Present the solution ("Our [service] eliminates [problem]")
     * Show the benefit ("Save [X] time/money")
     * Provide proof ("Join [X] satisfied customers")

   - Pain-focused CTAs:
     * "Stop [Pain Point] Today"
     * "End My [Problem] Now"
     * "Fix My [Issue] Fast"
     * "Solve My [Challenge]"
     * "Free Me From [Pain Point]"

2. Create Problem-Solution Variations:
   ### Pain Point Focus Ad
   - **Headline 1:** [Identify Pain Point]
   - **Headline 2:** [Present Solution]
   - **Description 1:** [Empathize + Solution]
   - **Description 2:** [Benefit + Proof]
   - **CTA:** [Pain Resolution Action]

   ### Solution Focus Ad
   - **Headline 1:** [Solution to Pain]
   - **Headline 2:** [Unique Benefit]
   - **Description 1:** [How We Solve It]
   - **Description 2:** [Success Proof]
   - **CTA:** [Get Solution Now]

   ### Emotional Relief Ad
   - **Headline 1:** [Emotional Pain Point]
   - **Headline 2:** [Emotional Relief]
   - **Description 1:** [Understanding + Solution]
   - **Description 2:** [Transformation Story]
   - **CTA:** [Transform Now]

3. Pain Point Keywords:
   - Include problem-specific terms
   - Use "fix", "solve", "eliminate" modifiers
   - Add "vs", "alternative to" comparisons
   - Include "prevent", "avoid", "stop" variations

4. All ads should:
   - Use headlines that validate customer pain points
   - Show immediate relief or solution
   - Include proof of problem resolution
   - Use empathetic language
   - Demonstrate understanding of the issue
   - Offer clear path to solution

5. Provide specific recommendations for:
   - Best performing ad elements from landing page
   - Keyword insertion opportunities
   - A/B testing variations based on landing page content
   - Quality Score optimization based on landing page relevance

6. Negative keywords specific to {service_to_promote}

Language: {language}`,
    agent: reportGenerator,
    priority: 2,
    expectedOutput: `
[![Nimbox Logo](https://crm.nimboxcrm.cloud/uploads/company/9e85677a40aafa432269e8b241f4ddae.png)](https://nimbox360.com)

# Ad Campaign for {service_to_promote}
*Generated by [Nimbox360](https://nimbox360.com) with KaibanJS*

## Service-Specific Ads
### Primary Ad
- **Headline 1:** [Based on {service_to_promote} USP]
- **Headline 2:** [Feature from landing page]
- **Description 1:** [Benefits from {ad_destination_url}]
- **Description 2:** [CTA matching landing page]
- **Final URL:** {ad_destination_url}

### Secondary Ad
- **Headline 1:** [Alternative {service_to_promote} USP]
- **Headline 2:** [Social proof from landing page]
- **Description 1:** [Different benefit angle]
- **Description 2:** [Alternative CTA]
- **Final URL:** {ad_destination_url}

## Brand Variation Ads
[Similar structure with brand focus]

## Optimization Recommendations
[Based on landing page analysis]`
  }),
];

// === TEAM ===
const team = new Team({
  name: 'Marketing Ads Team',
  agents: [
    contentAnalyzer,
    reportGenerator
  ],
  tasks: tasks,
  inputs: {
    url: 'https://nimbox360.com', // URL to analyze
    company_name: 'Nimbox360', // Company name
    language: 'en', // Options: 'en' for English, 'es' for Spanish
    ad_destination_url: '', // Specific landing page for the ad
    service_to_promote: '', // Specific service or product to promote in the ad
  },
  env: {
    OPENAI_API_KEY: import.meta.env.VITE_OPENAI_API_KEY ?? (() => { throw new Error('OPENAI_API_KEY is required') })(),
    GOOGLE_API_KEY: import.meta.env.GOOGLE_API_KEY || null,
  }
});

export default team;

Outcome

With KaibanJS, teams receive:

Marketing Reports: Structured insights on keywords, messaging, and ad performance recommendations.
Optimized Ad Templates: Ready-to-use headlines, descriptions, and calls-to-action.
Scalable Automation: Repeatable workflows for multiple clients or campaigns.

Expected Benefits

Time Savings: Automates content analysis and report creation.
Higher Performance: Generates data-driven ad strategies with optimized relevance.
Scalability: Easily adapts to various business needs.
Consistency: Ensures uniform quality across all campaigns.

Get Started Today

Ready to streamline your marketing workflows? Explore KaibanJS and elevate your ad campaigns.

🌐 Website: KaibanJS
💻 GitHub Repository: KaibanJS on GitHub
🤝 Discord Community: Join the Community

Special thanks to Aitor Roma for his collaboration

We Value Your Feedback!

Have ideas or suggestions? Join our community or contribute on GitHub. Contribute Now

The Challenge​

The Solution with KaibanJS​

The Agentic Solution​

Process Overview​

Implementation​

Outcome​

Expected Benefits​

Get Started Today​

Special thanks to Aitor Roma for his collaboration​