SHINKA Co., Ltd. to Launch "The LLMO Marketing and Sales Textbook for Stores and Salons" on April 30th – Redesigning Customer Acquisition with Large Language Model Optimization
SHINKA Corporation announced the April 30th release of "The LLMO Marketing and Sales Textbook for Stores and Salons," authored by its director, Saya Tanaka. This practical guide introduces "LLMO" (Large Language Model Optimization), a new customer acquisition method for the generative AI era, helping businesses become "chosen" by AI.
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- 📰 Published: April 28, 2026 at 20:00
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## Press Release Information
Title: Create "Chosen Stores" with LLMO (Large Language Model Optimization) – A Practical Guide to Redesigning Customer Acquisition to be Released on April 30th
Subtitle:
Company Name:
Industry:
Main Body (first 8000 characters): "The LLMO Marketing and Sales Textbook for Stores and Salons: Start from Scratch and Achieve Results! An LLMO Introduction and Utilization Guide" by Saya Tanaka. Available on Amazon and at bookstores nationwide.
SHINKA Co., Ltd. (Headquarters: Yokohama City, Kanagawa Prefecture; Representative Director: Yukie Oda) will release "The LLMO Marketing and Sales Textbook for Stores and Salons: Start from Scratch and Achieve Results! An LLMO Introduction and Utilization Guide," authored by its director, Saya Tanaka, on April 30, 2026.
This book is a practical guide that systematically explains how store and salon operators should design their customer acquisition strategies in the era of generative AI, focusing on "LLMO (Large Language Model Optimization)." It is a single volume for redesigning how businesses are "chosen" in the AI era.
## Background of Publication: Changes in Search Behavior and the Redefinition of "Being Chosen"
Until now, store customer acquisition primarily focused on optimizing each channel, such as SEO, MEO, social media, and advertising.
However, with the widespread adoption of generative AI, including ChatGPT, user information gathering behavior has significantly changed.
Instead of comparing multiple pieces of information on search engines, the decision-making process of directly asking AI and choosing from its answers is becoming common.
This change is not merely an addition of customer acquisition methods but signifies a shift from "how to be found" to "how to be chosen."
As a result, new perspectives are now required for stores and salons, such as:
- Is information correctly recognized by AI?
- Are they in a state where they will be chosen when compared to competitors?
## Why This Book Now?
Amidst these changes, the field is seeing an increase in voices such as:
- I don't know what to communicate.
- Anxiety that traditional customer acquisition measures will no longer be effective.
- I can't decide what to tackle first in the AI era.
On the other hand, even valuable services and products, if not properly designed for information, may not reach AI or users and could be overlooked without being chosen.
This book was planned to reduce such "invisible opportunity losses."
## Reasons to Adopt LLMO
LLMO (Large Language Model Optimization) is a concept for optimizing information design and dissemination in the AI-driven search environment.
While traditional SEO focused on optimization for search engines, LLMO requires design based on "how to be understood by AI."
However, in practice, many challenges are observed:
- The concept of LLMO itself is not yet widely understood.
- I don't know where to start.
- It's difficult to understand the difference from existing customer acquisition measures.
This book aims to bridge these gaps and explain LLMO in a way that store and salon operators can implement.
## What This Book Aims to Achieve
This book is not just about providing know-how; its goal is to "create a state where valuable services are correctly chosen."
In stores and salons, there is indeed technology, passion, and value for customers.
However, if it is not communicated properly, it is as if it does not exist.
LLMO is the concept for transforming that value into a "communicable form."
Released on April 30, '26
## Book Features
This book explains LLMO from basics to advanced applications in stages.
- Basic design that can be understood without specialized knowledge.
- Concrete examples applied to store businesses.
- Methods for integrating with existing social media, advertising, and LINE measures.
Its characteristic is that it goes beyond mere theory, detailing "what to change starting tomorrow."
Furthermore, by re-evaluating the design of information dissemination, it aims to create a "chosen state" that works for AI search, traditional search, and social media.
## Value This Book Brings
Through this book, store and salon operators will be able to:
- Organize the priorities of customer acquisition measures.
- Construct information design suited to their own stores.
- Understand new customer acquisition channels in the AI era.
- Build information design that leads to sales.
This is not just a marketing method; it is also about acquiring the "ability to articulate reasons for being chosen" in the upcoming AI search era.
## Table of Contents
The structure is designed to allow step-by-step understanding of LLMO from basics to practice, and future prospects.
- CHAPTER 0 Why LLMO Customer Acquisition Now?
- CHAPTER 1 Understanding the Basics of LLMO
- CHAPTER 2 Understanding the Mechanism of LLMO Customer Acquisition
- CHAPTER 3 Media Strong in LLMO Countermeasures
- CHAPTER 4 How to Think About Content Liked by AI
- CHAPTER 5
Title: Create "Chosen Stores" with LLMO (Large Language Model Optimization) – A Practical Guide to Redesigning Customer Acquisition to be Released on April 30th
Subtitle:
Company Name:
Industry:
Main Body (first 8000 characters): "The LLMO Marketing and Sales Textbook for Stores and Salons: Start from Scratch and Achieve Results! An LLMO Introduction and Utilization Guide" by Saya Tanaka. Available on Amazon and at bookstores nationwide.
SHINKA Co., Ltd. (Headquarters: Yokohama City, Kanagawa Prefecture; Representative Director: Yukie Oda) will release "The LLMO Marketing and Sales Textbook for Stores and Salons: Start from Scratch and Achieve Results! An LLMO Introduction and Utilization Guide," authored by its director, Saya Tanaka, on April 30, 2026.
This book is a practical guide that systematically explains how store and salon operators should design their customer acquisition strategies in the era of generative AI, focusing on "LLMO (Large Language Model Optimization)." It is a single volume for redesigning how businesses are "chosen" in the AI era.
## Background of Publication: Changes in Search Behavior and the Redefinition of "Being Chosen"
Until now, store customer acquisition primarily focused on optimizing each channel, such as SEO, MEO, social media, and advertising.
However, with the widespread adoption of generative AI, including ChatGPT, user information gathering behavior has significantly changed.
Instead of comparing multiple pieces of information on search engines, the decision-making process of directly asking AI and choosing from its answers is becoming common.
This change is not merely an addition of customer acquisition methods but signifies a shift from "how to be found" to "how to be chosen."
As a result, new perspectives are now required for stores and salons, such as:
- Is information correctly recognized by AI?
- Are they in a state where they will be chosen when compared to competitors?
## Why This Book Now?
Amidst these changes, the field is seeing an increase in voices such as:
- I don't know what to communicate.
- Anxiety that traditional customer acquisition measures will no longer be effective.
- I can't decide what to tackle first in the AI era.
On the other hand, even valuable services and products, if not properly designed for information, may not reach AI or users and could be overlooked without being chosen.
This book was planned to reduce such "invisible opportunity losses."
## Reasons to Adopt LLMO
LLMO (Large Language Model Optimization) is a concept for optimizing information design and dissemination in the AI-driven search environment.
While traditional SEO focused on optimization for search engines, LLMO requires design based on "how to be understood by AI."
However, in practice, many challenges are observed:
- The concept of LLMO itself is not yet widely understood.
- I don't know where to start.
- It's difficult to understand the difference from existing customer acquisition measures.
This book aims to bridge these gaps and explain LLMO in a way that store and salon operators can implement.
## What This Book Aims to Achieve
This book is not just about providing know-how; its goal is to "create a state where valuable services are correctly chosen."
In stores and salons, there is indeed technology, passion, and value for customers.
However, if it is not communicated properly, it is as if it does not exist.
LLMO is the concept for transforming that value into a "communicable form."
Released on April 30, '26
## Book Features
This book explains LLMO from basics to advanced applications in stages.
- Basic design that can be understood without specialized knowledge.
- Concrete examples applied to store businesses.
- Methods for integrating with existing social media, advertising, and LINE measures.
Its characteristic is that it goes beyond mere theory, detailing "what to change starting tomorrow."
Furthermore, by re-evaluating the design of information dissemination, it aims to create a "chosen state" that works for AI search, traditional search, and social media.
## Value This Book Brings
Through this book, store and salon operators will be able to:
- Organize the priorities of customer acquisition measures.
- Construct information design suited to their own stores.
- Understand new customer acquisition channels in the AI era.
- Build information design that leads to sales.
This is not just a marketing method; it is also about acquiring the "ability to articulate reasons for being chosen" in the upcoming AI search era.
## Table of Contents
The structure is designed to allow step-by-step understanding of LLMO from basics to practice, and future prospects.
- CHAPTER 0 Why LLMO Customer Acquisition Now?
- CHAPTER 1 Understanding the Basics of LLMO
- CHAPTER 2 Understanding the Mechanism of LLMO Customer Acquisition
- CHAPTER 3 Media Strong in LLMO Countermeasures
- CHAPTER 4 How to Think About Content Liked by AI
- CHAPTER 5