#Japan #Tokyo #Merchandising-On #M-Data #TV Metadata

Overview

In a significant move aimed at enhancing service capabilities within the TV and retail sectors, Merchandising-On Co., Ltd., headquartered in Shinjuku, Tokyo, has officially announced a strategic partnership with M-Data Co., Ltd., renowned for its comprehensive TV metadata services. This collaboration marks the beginning of a new phase of integrated data management, allowing both companies to jointly develop improved services for their users.

Partnership Highlights

The partnership will leverage Merchandising-On's Retail Data Service (RDS), which specializes in Point of Sale (POS) data, and M-Data's extensive TV metadata, which provides detailed text-based records of TV programs and commercials. By fusing these datasets, Merchandising-On aims to offer a new service that can analyze the impact of product exposure on sales metrics derived from TV shows and commercials.

Previously, RDS provided sales estimates with a two-day delay; however, with the integration of TV metadata, users will benefit from enhanced service delivery that accelerates data availability and insights.

Furthermore, M-Data will incorporate Merchandising-On's product master data into its TV metadata, creating a unique inventory that categorizes items featured in various media formats—be it food, beverages, or household goods. This integration is anticipated to drive better utilization of TV metadata within retail contexts, thus enhancing efficiency and convenience for businesses.

Enhanced Services through Data Integration

The overall aim of this partnership is not only to strengthen services through data sharing but also to pave the way for the development of joint service offerings that can effectively tackle market challenges. Specific objectives include:

• - Product Demand Forecasting: Utilization of combined datasets to predict product demands accurately, optimizing supply chain operations.
• - Retail Support and Management: Implementing strategies based on real-time data to enhance retail media performance and management.
• - Waste Reduction and Trend Forecasting: Using combined insights to prevent food waste and better forecast market trends, leading to improved purchasing strategies.
• - Financial Data Utilization: The collaboration is also set to promote data usage within the financial sector, establishing alternative datasets that may act as leading indicators for stock market applications.

Case Examples of Data Utilization

General Applications

• - Performing correlation analysis between product exposure in TV programs and sales performance across various distribution chains.
• - Utilizing TV campaign data for strategic marketing initiatives, including PR planning for products featured in television entertainment.
• - Integrating sales data from POS with TV exposure metrics to estimate performance and leverage alternative data as stock indicators.

Retail Development Applications

• - Optimizing product supply strategies by forecasting demand balances and identifying potential hit products.
• - Streamlining operations through generative AI for customer service and data-backed advertising efforts.
• - Executing promotional strategies across entire product categories based on centralized data analysis.

About Merchandising-On

Created in April 1999, Merchandising-On is a leading force in providing services that support sales strategy development and store management in the retail sector. Their expertise encompasses software development focusing on POS analysis, trade area examination, and create-value consultancy tailored for retail businesses.

About M-Data

Founded in January 2006, M-Data specializes in extracting and compiling comprehensive TV metadata which serves as an essential database for advertising performance. With strategic ties to primary broadcast networks, they offer vital services including data distribution and market research analytics that empower clients to interpret data trends effectively.

This partnership, initiated with the goal of integrating data management practices, promises to further enrich the landscape of retail and media data analytics, ultimately contributing to a more insightful understanding of market dynamics.