What is AI Marketing? Examples and Experiences

Updated: by Heysho

What is AI Marketing?

Today, I'd like to revisit the topic of digital marketing after quite some time. (And no, this article wasn't written by AI.)

  • What exactly is AI marketing and what can it actually accomplish?
  • What benefits come from implementing it?
  • Which tools should you choose?

I'll be discussing "AI marketing," a topic that's been generating significant buzz lately, for those with these questions.

Since December 2022, I've been integrating AI into various aspects of my work, and I've noticed a dramatic improvement in my capabilities as a professional.

To illustrate, I used to tackle challenging tasks through solo trial and error, but now it feels like I'm collaborating with exceptional, lightning-fast consultants, programmers, and data scientists.

In this article, I'll share practical examples, recommended applications, and useful tools based on my personal experiences.

Table of Contents

1. What is AI Marketing?

AI marketing is a relatively new concept that I define as "leveraging generative AI to streamline and enhance marketing activities."

Specifically, it can be applied to areas such as content creation, business automation, and data analysis.

Key Applications

  • Market Research: Harness AI's vast information processing capabilities to conduct competitor analysis and consumer trend research in a fraction of the time.
  • Content Creation: AI assists with drafting articles, social media posts, and ad copy, while also providing quality-improving proofreading.
  • User Insight Extraction: AI analyzes thousands of customer reviews and inquiries to identify valuable patterns and emotional tendencies.

2. Why is AI Marketing Gaining Traction?

According to research by Horizon Grand View Research, the global AI marketing market is projected to grow at an astonishing rate.

While specific data on Japan's AI marketing market wasn't available, the overall AI market forecast for Japan is as follows:

Alongside this rapid market expansion, a serious shortage of AI talent is anticipated.

The Importance of Early Adoption

Currently, AI adoption in the marketing industry remains in its early stages.

Investing in AI marketing now can provide a significant competitive advantage over your rivals.

I believe that establishing your company's AI marketing infrastructure before the market matures and competition for talent intensifies will be crucial for future success.

3. Implementation Examples (From My Experience)

Here are some real-world AI marketing applications I've implemented in my work.

Customer Survey Analysis

  • Challenge: Processing massive amounts of unstructured data.
    • I was tasked with analyzing approximately 7,000 customer survey responses.
    • Since all answers were in free-form text, traditional methods would have required an estimated 200+ hours to classify and aggregate the data.
  • Solution: By using text analysis to automatically categorize and aggregate data, we could determine issue priorities efficiently.
    • Processing time dropped from approximately 200 hours to just 10 hours, and costs were reduced from several thousand dollars in labor to approximately $100 in API fees.
    • Technology used: Python + ChatGPT API (GPT-3.5-turbo)
    • In 2023, the API cost about $100, but thanks to AI model evolution, the same analysis now costs less than $1.
  • Remarks: This was my first AI automation project, and I still vividly remember being shocked by its dramatic impact.

SEO Keyword Classification

  • Challenge: In SEO strategy, it's standard practice to analyze "branded keywords" (containing the brand name) separately from "generic keywords" (without the brand name). Traditionally, this classification required manual work, creating a significant burden and inefficiency.
  • Solution: We developed an automatic classification script using Python and GPT-4.1-mini. The cost to classify approximately 10,000 keywords is less than $0.10, and the process takes only about 20 minutes—a dramatic efficiency improvement over manual classification.
  • Remarks
    • Generative AI excels at text data analysis, dramatically improving both efficiency and accuracy.
    • This example demonstrates a basic application of generative AI in SEO data analysis, but the approach can be extended to classification by various categories like products or topics.

Enhanced KPI Reports with AI-Powered Market Research

  • Challenge
    • When managing a brand website, SEO performance is heavily influenced by fluctuations in branded search volume.
    • During report presentations, I'm frequently asked, "Why did branded keyword search volume increase or decrease?" Identifying the cause is challenging due to multiple contributing factors.
  • Solution: I use ChatGPT's deep research capability with prompts like "Investigate why search volume for the [brand name] increased significantly in [month]."
  • Result
    • The output provides detailed analysis, organizing factors that contributed to the fluctuation—such as brand initiatives, influencer activity, and competitor movements.
    • Including this analysis in KPI reports helps the team understand specifically "which actions drive branded keyword search volume," improving overall SEO performance.

Content Creation at Scale

  • Challenge
    • I was tasked with optimizing on-page SEO for 2,000 category pages on an e-commerce site.
    • Improving meta descriptions and adding lead text was extremely time-consuming. When I requested a quote from an SEO vendor, they charged $500 per page—totaling $1 million for all pages, making the project financially unfeasible.
  • Solution
    • We built an automation system combining Python, LangChain, and generative AI APIs, reducing the production cost to less than $0.01 per page.
    • As a result, search traffic from generic keywords increased by 80% year-over-year.
  • Remarks
    • To mitigate risks, we implemented several safeguards:
      • Using multiple AI models with sophisticated prompts
      • Deploying updates gradually in batches of 50 pages
    • Note that updating numerous pages simultaneously with basic models and simple prompts carries significant risks.

Data Analysis and Data Science Applications

  • Challenge
    • I began learning Python and data science in 2023, but initially lacked confidence in my coding skills, making practical implementation time-consuming.
    • Previously, data science projects often struggled to demonstrate clear business value, making it difficult to secure resources or budget approval.
  • Solution
    • With ChatGPT's assistance, I can now independently perform advanced data analysis quickly and efficiently.
    • Key projects I've completed include:
      • SEO traffic forecasting using machine learning
      • Analyzing advertising impact on organic search traffic
      • Automated KPI report generation
      • Various other Python-based data analyses
  • Insights
    • Given that I achieved these results with limited data science experience, I predict that marketers themselves will increasingly leverage data science in the future.
    • When marketers use AI for data analysis, it helps foster a "data-driven culture" throughout the organization.

Creating AI Tools for Operational Support and Customer Acquisition

As a personal project rather than a company initiative, I've developed AI tools that enhance business efficiency.

For example, my "Email Reply Tool" automatically generates polite, professional responses simply by pasting the original message and entering "polite response" as a keyword. While ChatGPT offers similar functionality, my tool operates faster and produces text with more refined tone.

By making this tool publicly available, we're also attracting potential customers through Google search.

When we released another tool, a "Rap Generator," it ranked highly for keywords like "rap generation," driving approximately 2,000 monthly visitors.

4. Recommended Tools

There are countless AI tools available, but I recommend focusing initially on the ChatGPT Plus paid plan and automation using AI model APIs with Python or Dify, rather than experimenting with too many different tools.

Following AI influencers can provide valuable insights—but remember that subscribing to numerous paid tools doesn't necessarily improve your skills and may waste both time and money.

Here's my shortlist of essential AI tools:

ChatGPT Plus ($20 monthly subscription)

ChatGPT Plus offers diverse functionality that covers approximately 70% of daily tasks.

After testing other major models (Gemini, Claude), I chose ChatGPT Plus for its overall performance and reliability.

Key applications and recommended models include:

  • Coding Assistance: GPT-4o or GPT-4o-mini
  • Business Consultation: GPT-4o
  • Web Search: GPT-4o / GPT-4o-mini (superior)
  • Dictation/Meeting Notes: Voice Mode
  • Proofreading/Translation: GPT-4o-mini (superior)
  • Market Research: Deep Research feature

Claude

While ChatGPT Plus is sufficient for most needs, I also use Claude when I need to enhance text quality for web publication.

  • Model: Claude-3.7 Sonnet (available in the free plan)
  • Primary Uses:
    • Content requiring natural-sounding writing (website copy, etc.)
    • Business image generation (creates infographics in editable SVG format)

Claude excels at producing natural-sounding text with improved readability, enhancing overall content quality.

Python / LangChain

LangChain is a Python library that functions as a platform for combining various AI models into automated workflows.

It's particularly useful for batch processing simple tasks like translating thousands of sentences or classifying customer reviews. For API models, I typically use cost-effective options like Gemini-flash-2.0 and GPT-4.1-mini.

Python / LangGraph

LangGraph, an advanced version of LangChain, enables the construction of complex workflows with parallel or branching prompt sequences.

For example, when automating requirements document creation, you can:

  1. Generate five fictional personas
  2. Conduct simulated interviews with these personas
  3. Evaluate information sufficiency
  4. If adequate, summarize findings and generate a requirements document

This entire process can be executed with a single command, ideal for completing complex tasks consistently and with high quality.

Dify

I rarely use Dify because I mainly call APIs directly via Python, but Dify is an excellent tool for those who want to experiment with various AI models and workflows without programming knowledge.

Personally, I occasionally use Dify when working with Claude's high-end models.

Napkin AI

Napkin AI is a free tool that allows you to quickly create infographics. You can easily generate illustrations that can be immediately incorporated into reports and presentation materials.

Perplexity, Genspark, Felo

Perplexity, Genspark, and Felo are web search tools that I use as supplements for deep research purposes.

While I primarily use ChatGPT, I turn to these three tools as alternatives when I reach usage limits.

5. Information Gathering

These are my main sources for staying updated on AI marketing developments:

  • Iketomo (YouTube): Provides weekly summaries of the latest AI developments.
  • Satoshi Nakajima (Email Newsletter / Voicy): Offers in-depth explanations from a programmer's perspective. While Voicy is no longer updated, past episodes remain valuable for understanding AI and LLM fundamentals.
  • Sam Altman Interviews (YouTube): I watch these as reliable primary sources when making AI future predictions.
  • LangChain Official Channel: Introduces sample code and practical business automation use cases. LangChain is particularly attractive because it can be implemented with minimal API costs.

Additionally, I regularly follow posts from international AI professionals on LinkedIn.

6. Summary

Thank you for reading this article.

Though I'm still learning, I'd be delighted to connect with anyone interested in transforming their business using AI.

If you're currently working on an AI-related project or would like to collaborate on an interesting challenge, please don't hesitate to reach out.

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