Intelligent Marketing Voice Assistant: Patent Distribution, Market Trend, And Opportunity Analysis (Pre-order)

As IT technologies such as human-machine interface, natural language processing, and machine learning solutions have advanced over the years, online retailers, offline retailers, and information technology companies have been actively thinking how to utilize new technologies to enhance consumer shopping intentions and tap their needs with a more initiative and convenient approach. For this reason, intelligent marketing voice assistants have been developed to recommend consumers during shopping process to achieve effective marketing. This report provides key pointsintelligent marketing voice assistant technologies, examines patent distribution of several brands in this area such as Amazon, Google, Microsoft, IBM, Apple, Walmart, and identifies key fields and technologies with regards to intelligent marketing voice assistant patents.

Table of Contents
1.Technology Introduction
2.Patent Analysis
2.1 Patent Mining
2.2 Patent Analysis
2.2.1 Analysis by Patent Field and Patent Application Year
2.2.2 Analysis by Patent Field and Country
2.2.3 Analysis by Patent Field and Assignee
2.2.4 Analysis by Patent Technology and Patent Application Year
2.2.5 Analysis by Patent Technology and Country
2.2.6 Analysis by Patent Technology and Assignee
3.MIC Perspective
Appendix
Glossary of Terms
List of Companies
List of Tables
Table 1 Matrix Analysis of US Intelligent Marketing Voice Assistant Patent Counts by Patent Field and Patent Application Year
Table 2 Matrix Analysis of US Intelligent Marketing Voice Assistant Patent Counts by Patent Field and Country
Table 3 Matrix Analysis of US Intelligent Marketing Voice Assistant Patent Counts by Patent Field and Assignee
Table 4 Matrix Analysis of US Intelligent Marketing Voice Assistant Patent Counts by Patent Technology and Patent Application Year
Table 5 Matrix Analysis of US Intelligent Marketing Voice Assistant Patent Counts by Patent Technology and Country
Table 6 Matrix Analysis of US Intelligent Marketing Voice Assistant Patent Counts by Patent Technology and Assignee
List of Figures
Figure 1 Illustration of Intelligent Marketing Voice Assistants Launched by Amazon, Google, and Microsoft

Research Methodology

SECONDARY RESEARCH
Secondary Research Information is collected from a number of publicly available as well as paid databases. Public sources involve publications by different associations and governments, annual reports and statements of companies, white papers and research publications by recognized industry experts and renowned academia etc. Paid data sources include third party authentic industry databases.

PRIMARY RESEARCH
Once data collection is done through secondary research, primary interviews are conducted with different stakeholders across the value chain like manufacturers, distributors, ingredient/input suppliers, end customers and other key opinion leaders of the industry. Primary research is used both to validate the data points obtained from secondary research and to fill in the data gaps after secondary research.

MARKET ENGINEERING
The market engineering phase involves analysing the data collected, market breakdown and forecasting. Macroeconomic indicators and bottom-up and top-down approaches are used to arrive at a complete set of data points that give way to valuable qualitative and quantitative insights. Each data point is verified by the process of data triangulation to validate the numbers and arrive at close estimates.

EXPERT VALIDATION
The market engineered data is verified and validated by a number of experts, both in-house and external.

REPORT WRITING/ PRESENTATION
After the data is curated by the mentioned highly sophisticated process, the analysts begin to write the report. Garnering insights from data and forecasts, insights are drawn to visualize the entire ecosystem in a single report.