#Qlipper #LLM Optimization #Media Analysis

Qlipper Unveils Enhanced Media Analysis Features

In a significant update, Qlipper, a leading PR measurement service developed by Todonada Inc., has added powerful new filtering functionalities to its media analysis feature. This enhancement allows public relations professionals to sort media outlets based on their permission status for LLM crawlers, as well as their crawl priority. With the rise of Generative AI technologies such as ChatGPT, this new feature is designed to provide PR teams with an essential tool in navigating the evolving media landscape.

Understanding the Shift Towards LLMs

The way consumers access information is shifting from traditional search engines to Large Language Models (LLMs). The presence of a brand in these models largely hinges on whether its information is included in their training datasets. This concept is often referred to as LLM Optimization (LLMO), highlighting the importance of brand exposure in journalistic content as part of PR activities.

However, no matter how many articles are published, if media outlets block LLM crawlers, the content will not contribute to the training data. Determining if a media outlet permits crawling by LLMs has traditionally been a tedious task for PR professionals, as it requires researching each outlet individually.

New Filtering Capabilities

With Qlipper's enhanced media analysis feature, PR professionals can now select media outlets based on two critical criteria:

1. LLM Crawler Permission Status (robots.txt)
- Analysts will now be able to examine the robots.txt file of various outlets, determining permissions for different AI vendors such as OpenAI, Google, Apple, and more. The system categorizes these permissions into three main types:
- Learning: Access for the purpose of gathering data for LLM training.
- RAG: Access aimed at retrieving information during AI searches or answer generation.
- Fetch: Access used for URL referencing in chat applications.
- Media details will display a badge indicating the permission status for each vendor, allowing users to filter down to outlets that only permit learning crawlers, thereby optimizing outreach efforts.

2. Crawl Priority
- Based on backlink structures across the web graph, each outlet’s ease of being crawled by LLMs is categorized into three levels: High, Medium, and Low. Media with high crawl priority are deemed more likely to successfully convey articles to the LLM's data collection pipeline. PR teams can now focus their efforts on outlets categorized as having high priority to boost the chances of reaching LLMs effectively.

Integrating with Digidigi for Comprehensive PR Strategy

Todonada Inc. also offers a tool named Digidigi, which measures brand awareness and hallucination effects within LLMs. By combining Qlipper’s media exposure capabilities with Digidigi’s analytical insights, brands can effectively implement a robust PDCA (Plan-Do-Check-Act) cycle for optimizing their PR strategies. This integration enables PR teams to measure the impact of their media outreach on LLM visibility and brand recognition.

Access to New Features

All existing Qlipper customers can access these new features at no additional cost, further enhancing their media analysis functions. Qlipper is designed as a comprehensive PR measurement service, automatically collecting news articles based on keywords and providing unique metrics like virtual PV, Ad equivalent value, positive-negative scores, and risk scores to support the effectiveness of PR campaigns.

Company Overview

Company Name: Todonada Inc.
CEO: Yasuyuki Matsumoto
Location: 302 Yahiko Building, 7-11-13 Ueno, Taito-ku, Tokyo, 110-0005
Business Focus: Development and operation of cloud services for corporations, system consulting, and employee training.
Services Offered: PR measurement service