Marketing AI Agent 'Mazrica Engage' Launches AI Scoring Feature to Visualize Customer 'Buying Intent'
Mazrica Inc. has launched a new 'AI Scoring' feature for its marketing AI agent 'Mazrica Engage.' This feature uses AI to dynamically analyze customer document viewing history and chat content to visualize interest levels, supporting precise sales outreach.
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- 📰 Published: April 23, 2026 at 20:00
- 🔍 Collected: April 23, 2026 at 11:31
- 🤖 AI Analyzed: April 24, 2026 at 01:49 (14h 17m after Collected)
Mazrica Inc. (Headquarters: Chuo-ku, Tokyo; Representative Director & CEO: Eiji Kurosa; hereinafter referred to as 'the Company') is pleased to announce the launch of a new 'AI Scoring' feature in its marketing AI agent 'Mazrica Engage.' This feature visualizes customer buying intent based on document viewing history and chat content.
### Development Background
In recent years, with the increase in lead volume and the diversification of customer touchpoints in sales and marketing, the challenge of 'identifying which customers to prioritize' has become prominent.
Traditional MA (Marketing Automation) tools typically add scores based on human-defined rules, such as document downloads or page views. However, this approach had several issues:
- Difficulty in capturing the 'quality' and context of customer interest.
- Difficulty in reflecting changes in interest over time (temperature decay).
- Scoring logic tends to be subjective and dependent on individuals.
In response, the Company developed this feature to achieve visualization of buying intent that is more aligned with reality. It analyzes natural language communication in AI chats in addition to behavioral data, allowing the AI itself to dynamically generate and update scoring logic.
### Overview of the AI Scoring Feature
This feature comprehensively analyzes factors such as customer document viewing history, content engagement data, utterances in AI chats (natural language), interaction frequency, and the passage of time to visualize buying intent as a score.
Unlike traditional fixed point-addition methods, the AI continuously learns and optimizes the scoring criteria themselves, making it possible to capture the customer's consideration status with higher precision.
### Main Features
1. **AI-Generated and Optimized Scoring Logic**: Instead of manual rules, the AI automatically generates scoring logic based on customer behavior and dialogue data, continuously learning for more realistic evaluations.
2. **Multidimensional Understanding via Natural Language x Behavioral Data**: In addition to action data like content viewing history, it analyzes the content of chat utterances and the specificity of considerations to visualize interest levels and consideration phases that numerical data alone cannot capture.
3. **Time-Axis Based Scoring**: Reflects changes in interest over time based on the frequency and recency of customer actions. It captures not just past actions but 'how much the consideration is progressing right now.'
4. **Optimization of Sales Actions**: By prioritizing outreach to high-score customers, it contributes to improved calling efficiency for inside sales and maximization of business opportunities.
### Usage Image
For example, a customer who frequently views documents and mentions specific implementation considerations or challenges in the chat is determined to have a high score. Conversely, if there are no actions for a certain period, the score naturally decreases, allowing sales representatives to prioritize following up with customers who 'need to move right now.'
### Future Outlook
The Company will continue to support sophisticated decision-making and productivity improvement in the sales and marketing fields through product development utilizing AI and data. Furthermore, centering on 'Mazrica Engage,' we will continue to enhance features as an AI agent aimed at deepening customer understanding and realizing optimal communication.
### About the Marketing AI Agent 'Mazrica Engage'
'Mazrica Engage' is an AI agent that delivers the most suitable information to each customer at touchpoints such as websites and sales/marketing documents, maximizing lead generation and business opportunities. Customers gain an information-gathering experience where they can 'quickly reach the information they want to know,' while companies can visualize customer interests and concerns in the process.
### Company Profile
- **Company Name**: Mazrica Inc. (https://mazrica.com)
- **Headquarters**: 6F Frontier Higashi-Nihonbashi, 2-7-1 Higashi-Nihonbashi, Chuo-ku, Tokyo
- **Representative**: Eiji Kurosa, Representative Director & CEO
- **Established**: April 30, 2015
- **Business Description**: Development and provision of AI solutions
### Development Background
In recent years, with the increase in lead volume and the diversification of customer touchpoints in sales and marketing, the challenge of 'identifying which customers to prioritize' has become prominent.
Traditional MA (Marketing Automation) tools typically add scores based on human-defined rules, such as document downloads or page views. However, this approach had several issues:
- Difficulty in capturing the 'quality' and context of customer interest.
- Difficulty in reflecting changes in interest over time (temperature decay).
- Scoring logic tends to be subjective and dependent on individuals.
In response, the Company developed this feature to achieve visualization of buying intent that is more aligned with reality. It analyzes natural language communication in AI chats in addition to behavioral data, allowing the AI itself to dynamically generate and update scoring logic.
### Overview of the AI Scoring Feature
This feature comprehensively analyzes factors such as customer document viewing history, content engagement data, utterances in AI chats (natural language), interaction frequency, and the passage of time to visualize buying intent as a score.
Unlike traditional fixed point-addition methods, the AI continuously learns and optimizes the scoring criteria themselves, making it possible to capture the customer's consideration status with higher precision.
### Main Features
1. **AI-Generated and Optimized Scoring Logic**: Instead of manual rules, the AI automatically generates scoring logic based on customer behavior and dialogue data, continuously learning for more realistic evaluations.
2. **Multidimensional Understanding via Natural Language x Behavioral Data**: In addition to action data like content viewing history, it analyzes the content of chat utterances and the specificity of considerations to visualize interest levels and consideration phases that numerical data alone cannot capture.
3. **Time-Axis Based Scoring**: Reflects changes in interest over time based on the frequency and recency of customer actions. It captures not just past actions but 'how much the consideration is progressing right now.'
4. **Optimization of Sales Actions**: By prioritizing outreach to high-score customers, it contributes to improved calling efficiency for inside sales and maximization of business opportunities.
### Usage Image
For example, a customer who frequently views documents and mentions specific implementation considerations or challenges in the chat is determined to have a high score. Conversely, if there are no actions for a certain period, the score naturally decreases, allowing sales representatives to prioritize following up with customers who 'need to move right now.'
### Future Outlook
The Company will continue to support sophisticated decision-making and productivity improvement in the sales and marketing fields through product development utilizing AI and data. Furthermore, centering on 'Mazrica Engage,' we will continue to enhance features as an AI agent aimed at deepening customer understanding and realizing optimal communication.
### About the Marketing AI Agent 'Mazrica Engage'
'Mazrica Engage' is an AI agent that delivers the most suitable information to each customer at touchpoints such as websites and sales/marketing documents, maximizing lead generation and business opportunities. Customers gain an information-gathering experience where they can 'quickly reach the information they want to know,' while companies can visualize customer interests and concerns in the process.
### Company Profile
- **Company Name**: Mazrica Inc. (https://mazrica.com)
- **Headquarters**: 6F Frontier Higashi-Nihonbashi, 2-7-1 Higashi-Nihonbashi, Chuo-ku, Tokyo
- **Representative**: Eiji Kurosa, Representative Director & CEO
- **Established**: April 30, 2015
- **Business Description**: Development and provision of AI solutions