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Supermarket Customer Behavior Detection Technology: Patent Distribution, Brand Strength, and Market Opportunity Analysis
Published Date: March 2019
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Report Code: MICR-Cons-37
Home | Market Reports | Business & Industrial | Retail Trade
Supermarket Customer Behavior Detection Technology Patent Distribution Brand Strength and Market

Supermarket Customer Behavior Detection Technology: Patent Distribution, Brand Strength, and Market Opportunity Analysis

Code: MICR-Cons-37
Report
March 2019
26 Pages
Market Intelligence and Consulting Institute
Region: Global,
Description
Table of Content
Tables & Figures

With the growing popularity of e-commerce, online shopping has become a popular shopping method. Despite so, consumers still have a huge demand to shop at physical stores for items such as groceries, frozen food, and beverages. In recent years, the O2O (Online to Offline) commerce is also growing as many online retailers employ the online-to-offline business strategy by offering in-store pick-up services for items purchased online while some large-scale physical retail stores adopt the offline-to-online strategy by allowing customers to place orders online while in stores. The adoption of supermarket customer behavior detection technology will help open a new era for retail businesses and make click-and-mortar retail a reality. This report provides an analysis of supermarket customer behavior detection patent distribution by country and field in terms of patent counts, patent citations, and relative R&D intensity; discovers opportunities and challenges of major assignees such as IBM, Walmart, and Amazon; examines key and relevant technologies pertaining to supermarket customer behavior detection.

Table of Contents
1. Patent Mining
2.Patent Analysis
2.1 Analysis of Trends
2.1.1 Patent Distribution by Country
2.1.2 Patent Distribution by Field
2.1.3 Patent Distribution by Key Technology
2.1.4 Patent Distribution by Relevant Technology
2.1.5 Cross Analysis between Key Technology and Relevant Technology
2.2 R&D Readiness Analysis
2.2.1 Relative R&D Intensity
3. Trend Analysis
3.1 Key Patent Assignees
3.1.1 Analysis of Trends by Key Technology
3.1.2 Analysis of Trends by Relevant Technology
4. MIC Perspectives
Appendix
Glossary of Terms
List of Companies
List of Tables
Table 1 Supermarket Customer Behavior Detection Patents' Key Technology/ Relevant Technology Matrix Analysis
Table 2: Supermarket Customer Behavior Detection Patent Assignees and Their Relative R&D Intensity
Table 3: Patent Distribution Share of Supermarket Customer Behavior Detection by Key Technology: Major Assignees
Table 4: Patent Distribution Share of Supermarket Customer Behavior Detection by Relevant Technology: Major Assignees
List of Figures
Figure 1: Supermarket Customer Behavior Detection Patent Counts by Country
Figure 2: Supermarket Customer Behavior Detection Patent Distribution Share by Field
Figure 3: Supermarket Customer Behavior Detection Patent Distribution Share by Key Technologies: Image Recognition Detection
Figure 4: Supermarket Customer Behavior Detection Distribution Share by Key Technologies: Electronic Devices Positioning Detection
Figure 5: Supermarket Customer Behavior Detection Distribution Share by Key Technologies: AI-Related
Figure 6: Supermarket Customer Behavior Detection Patent Distribution Share by Relevant Technologies

List of Topics:-

Analysis of 505 patents pertaining to supermarket customer behavior detection technology and includes patent counts by technology field and sector using the data mining technique; The detailed profile of top 20 assignees and their relative R&D intensity ranking Trend analysis of the supermarket customer behavior detection technology by country, by field, by sector, by key and relevant technology Analysis of the developments of major players, including IBM, Walmart, and Amazon Detailed analysis of patent count/assignee matrix, sorted by key technologies such as Image Recognition Detection, Electronic Devices Positioning Detection, and AI and, by a number of relevant technologies

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