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Product analytics Market to reach USD 30.5 billion by 2027

Product analytics Market to reach USD 30.5 billion by 2027

Product Code: OIRIA-54686600
Publish Date: 11-07-2021
Page: 200

Global Product analytics Market is valued approximately at USD 7.9 billion in 2020 and is anticipated to grow with a healthy growth rate of more than 21.3% over the forecast period 2021-2027. Product analytics is used to find out future possibilities for product developments, identify designs in utilization of products by thriving information from customers chat, E-mail, calls etc. The Product analytics market is being driven by growing demand for advanced analytics tools to ensure market competitiveness, growing adoption of big data and other related technologies. Furthermore, the growing use by financial institutes in reducing the risks by analyzing the real position of client companies with the help of real time cash liquidity view and increasing use of artificial intelligence is boosting the market. For instance, In May 2021, Veritone’s Interaction Analytics solutions was developed by Veritone, which has inbuilt AI solutions for conversational intelligence that can retrieve information from customer interactions such as voice calls, texts, emails, social streams, images, and videos in near-real-time, and can use that information for making smart decisions which help in enhancing customer satisfaction. However, growing concerns over data privacy and security may impede market growth over the forecast period of 2021-2027.

The regional analysis of the Product analytics Market is considered for the key regions such as Asia Pacific, North America, Europe, Latin America, and Rest of the World. Asia Pacific is has emerged as a significant region across the world in terms of market share due to growing awareness towards enhancing the customer experience and use of artificial intelligence in the region. Whereas North America is also anticipated to exhibit the highest CAGR over the forecast period 2021-2027, due to growing number of product analytics key players across the region.

Major market player included in this report are:
Risk Edge Solutions Pvt. Ltd.
Pendo.io, Inc.
Google LLC (NASDAQ: GOOGL)
International Business Machines Corporation (NYSE: IBM)
Oracle Corporation (NYSE: ORCL)
Adobe Inc. (NASDAQ: ADBE)
Salesforce.com, Inc.
Mixpanel Inc.
Piwik PRO
Heap Inc
The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Mode:
Tracking Data
Analysing Data
By Component:
Solutions
Services
By End-Use:
Automotive
Retail and Consumer Goods
Food and Beverage Manufacturing
Machinery and Industrial Equipment Manufacturing
Healthcare and Pharmaceuticals
Energy and Utilities

By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE

Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
Rest of the World

Furthermore, years considered for the study are as follows:

Historical year – 2018, 2019
Base year – 2020
Forecast period – 2021 to 2027.

Target Audience of the Product analytics Market in Market Study:

Key Consulting Companies & Advisors
Large, medium-sized, and small enterprises
Venture capitalists
Value-Added Resellers (VARs)
Third-party knowledge providers
Investment bankers
Investors

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2019-2027 (USD Billion)
1.2.1. Product Analytics Market , by Region, 2019-2027 (USD Billion)
1.2.2. Product Analytics Market , by Mode, 2019-2027 (USD Billion)
1.2.3. Product Analytics Market , by Component , 2019-2027 (USD Billion)
1.2.4. Product Analytics Market , by End-Use, 2019-2027 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Product Analytics Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Product Analytics Market Dynamics
3.1. Product Analytics Market Impact Analysis (2019-2027)
3.1.1. Market Drivers
3.1.1.1. Increasing demand for advanced analytics tools to ensure market competitiveness
3.1.1.2. Growing adoption of big data and other related technologies
3.1.2. Market Restraint
3.1.2.1. Growing concerns over data privacy and security
3.1.3. Market Opportunities
3.1.3.1. Rising demand for real-time analytics solutions
Chapter 4. Global Product Analytics Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.1.6. Futuristic Approach to Porter’s 5 Force Model (2018-2027)
4.2. PEST Analysis
4.2.1. Political
4.2.2. Economical
4.2.3. Social
4.2.4. Technological
4.3. Investment Adoption Model
4.4. Analyst Recommendation & Conclusion
Chapter 5. Global Product Analytics Market , by Mode
5.1. Market Snapshot
5.2. Global Product Analytics Market by Mode, Performance – Potential Analysis
5.3. Global Product Analytics Market Estimates & Forecasts by Mode 2018-2027 (USD Billion)
5.4. Product Analytics Market , Sub Segment Analysis
5.4.1. Tracking Data
5.4.2. Analysing Data
Chapter 6. Global Product Analytics Market , by Component
a. Market Snapshot
6.1. Global Product Analytics Market by Component, Performance – Potential Analysis
6.2. Global Product Analytics Market Estimates & Forecasts by Component 2018-2027 (USD Billion)
6.3. Product Analytics Market , Sub Segment Analysis
6.3.1. Solutions
6.3.2. Services
Chapter 7. Global Product Analytics Market , by End-Use
b. Market Snapshot
7.1. Global Product Analytics Market by End-Use, Performance – Potential Analysis
7.2. Global Product Analytics Market Estimates & Forecasts by End-Use 2018-2027 (USD Billion)
7.3. Product Analytics Market , Sub Segment Analysis
7.3.1. Automotive
7.3.2. Retail and Consumer Goods
7.3.3. Food and Beverage Manufacturing
7.3.4. Machinery and Industrial Equipment Manufacturing
7.3.5. Healthcare and Pharmaceuticals
7.3.6. Energy and Utilities
Chapter 8. Global Product Analytics Market , Regional Analysis
8.1. Product Analytics Market , Regional Market Snapshot
8.2. North America Product Analytics Market
8.2.1. U.S. Product Analytics Market
8.2.1.1. Mode breakdown estimates & forecasts, 2018-2027
8.2.1.2. Component breakdown estimates & forecasts, 2018-2027
8.2.1.3. End-Use breakdown estimates & forecasts, 2018-2027
8.2.2. Canada Product Analytics Market
8.3. Europe Product Analytics Market Snapshot
8.3.1. U.K. Product Analytics Market
8.3.2. Germany Product Analytics Market
8.3.3. France Product Analytics Market
8.3.4. Spain Product Analytics Market
8.3.5. Italy Product Analytics Market
8.3.6. Rest of Europe Product Analytics Market
8.4. Asia-Pacific Product Analytics Market Snapshot
8.4.1. China Product Analytics Market
8.4.2. India Product Analytics Market
8.4.3. Japan Product Analytics Market
8.4.4. Australia Product Analytics Market
8.4.5. South Korea Product Analytics Market
8.4.6. Rest of Asia Pacific Product Analytics Market
8.5. Latin America Product Analytics Market Snapshot
8.5.1. Brazil Product Analytics Market
8.5.2. Mexico Product Analytics Market
8.6. Rest of The World Product Analytics Market
Chapter 9. Competitive Intelligence
9.1. Top Market Strategies
9.2. Company Profiles
9.2.1. Risk Edge Solutions Pvt. Ltd.
9.2.1.1. Key Information
9.2.1.2. Overview
9.2.1.3. Financial (Subject to Data Availability)
9.2.1.4. Product Summary
9.2.1.5. Recent Developments
9.2.2. Pendo.io, Inc.
9.2.3. Google LLC (NASDAQ: GOOGL)
9.2.4. International Business Machines Corporation (NYSE: IBM)
9.2.5. Oracle Corporation (NYSE: ORCL)
9.2.6. Adobe Inc. (NASDAQ: ADBE)
9.2.7. Salesforce.com, Inc.
9.2.8. Mixpanel Inc.
9.2.9. Piwik PRO
9.2.10. Heap Inc

Chapter 10. Research Process
10.1. Research Process
10.1.1. Data Mining
10.1.2. Analysis
10.1.3. Market Estimation
10.1.4. Validation
10.1.5. Publishing
10.2. Research Attributes
10.3. Research Assumption

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Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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