Edit Content
Bizwit-Logo-Final

Bizwit Research & Consulting LLP is a global provider of business intelligence & consulting services. We have a strong primary base of key industry leaders along with the chain of industry analysts to analyze the market trends and its future impact in order to estimates and forecast different business segments and markets. 

Global Payment Analytics Software Market to reach USD XX million by 2028.

Global Payment Analytics Software Market Size study, By Type (Cloud based, Web based), By Enterprise Size (Large Enterprise, Small and Medium Enterprise), and Regional Forecasts 2022-2028

Product Code: ICTEITS-80301690
Publish Date: 14-08-2022
Page: 200

Global Payment Analytics Software Market is valued approximately USD XX million in 2021 and is anticipated to grow with a healthy growth rate of more than XX % over the forecast period 2022-2028. The Payment Analytics Software utilized for tracking online payments for e-commerce and subscription-based businesses. This type of software consolidates payment data from multiple sources (e.g., Google pay, Paytm, Phone Pay, PayPal, Stripe, etc.) to monitor customer payments. The growing E-commerce Sector and increasing adoption of mobile based transaction services as well as recent product announcements from leading market players are factors that are accelerating the global market demand. For instance, according to UNCTAD estimates – during 2019, Online retail sales in selected countries including Australia, Canada, China, Korea Republic, Singapore, UK, and USA was estimated at USD 2038 billion, and this amount is further increased to USD 2495 billion by 2020. Furthermore, as per India Brand Equity Forum (IBEF)- in 2020, Indian e-commerce market was estimated at USD 46.2 billion, and this number is projected to grow to USD 188 billion by 2025. Furthermore, leading market are coming up with innovative products to capitalize the growing demand for Payment Analytics Software. For instance, in November 2021, USA based -ACI Worldwide a leading provider of real-time digital payment software, launched its new Omni-Commerce Payment Analytics software. This new software is part of ACI Omni-Commerce and enable merchants to access payments data gathered through multiple channels within a merchant’s payment ecosystem. Moreover, in March 2022, India based Paytm Payments Services Limited (PPSL), a wholly owned subsidiary of One97 Communications, new data analysis feature named ‘Payment Analytics’ for online and offline merchants. This new service would be available to all Paytm merchants at no extra cost and would enable merchants with data-driven payment insights. Also, growing penetration of big data analytics technologies and increasing ownership of smartphones in emerging markets are anticipated to act as a catalyzing factor for the market demand during the forecast period. However, a lack of network infrastructure and data privacy concerns impede the growth of the market over the forecast period of 2022-2028.

The key regions considered for the global Payment Analytics Software Market study include Asia Pacific, North America, Europe, Latin America, and the Rest of the World. North America is the leading region across the world in terms of market share owing to the growing adoption of payment Analytics software and presence of leading market players in the region. Whereas, Asia Pacific is anticipated to exhibit a significant growth rate over the forecast period 2022-2028. Factors such as rising big data analytics sector and growing emergence of 5G technology in the region, would create lucrative growth prospects for the global Payment Analytics Software Market across the Asia Pacific region.

Major market players included in this report are:
ProfitWell
BlueSnap
Databox
Payfirma
YapStone
CashNotify
HiPay Intelligence
PaySketch
Revealytics
RJMetrics

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 Type
Cloud based
Web based
By Enterprise Size
Large Enterprise
Small and Medium Enterprise
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, 2020
Base year – 2021
Forecast period – 2022 to 2028

Target Audience of the Global Payment Analytics Software 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, 2020-2028 (USD Million)
1.2.1. Payment Analytics Software Market, by Region, 2020-2028 (USD Million)
1.2.2. Payment Analytics Software Market, by Type, 2020-2028 (USD Million)
1.2.3. Payment Analytics Software Market, by Enterprise Size, 2020-2028 (USD Million)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Payment Analytics Software 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 Payment Analytics Software Market Dynamics
3.1. Payment Analytics Software Market Impact Analysis (2020-2028)
3.1.1. Market Drivers
3.1.1.1. Growing E-commerce Sector.
3.1.1.2. Increasing adoption of mobile based transaction services.
3.1.1.3. Recent product announcements from leading market players.
3.1.2. Market Challenges
3.1.2.1. Lack of network infrastructure.
3.1.2.2. Data privacy concerns.
3.1.3. Market Opportunities
3.1.3.1. Growing penetration of big data analytics technologies.
3.1.3.2. Increasing ownership of smartphones in emerging markets.
Chapter 4. Global Payment Analytics Software 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 (2018-2028)
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
4.5. Top investment opportunity
4.6. Top winning strategies
Chapter 5. Risk Assessment: COVID-19 Impact
5.1.1. Assessment of the overall impact of COVID-19 on the industry
5.1.2. Pre COVID-19 and post COVID-19 Market scenario
Chapter 6. Global Payment Analytics Software Market, by Type
6.1. Market Snapshot
6.2. Global Payment Analytics Software Market by Type, Performance – Potential Analysis
6.3. Global Payment Analytics Software Market Estimates & Forecasts by Type 2018-2028 (USD Million)
6.4. Payment Analytics Software Market, Sub Segment Analysis
6.4.1. Cloud Based
6.4.2. Web Based
Chapter 7. Global Payment Analytics Software Market, by Enterprise Size
7.1. Market Snapshot
7.2. Global Payment Analytics Software Market by Enterprise Size, Performance – Potential Analysis
7.3. Global Payment Analytics Software Market Estimates & Forecasts by Enterprise Size 2018-2028 (USD Million)
7.4. Payment Analytics Software Market, Sub Segment Analysis
7.4.1. Large Enterprise
7.4.2. Small and Medium Enterprise
Chapter 8. Global Payment Analytics Software Market, Regional Analysis
8.1. Payment Analytics Software Market, Regional Market Snapshot
8.2. North America Payment Analytics Software Market
8.2.1. U.S. Payment Analytics Software Market
8.2.1.1. Type estimates & forecasts, 2018-2028
8.2.1.2. Enterprise Size estimates & forecasts, 2018-2028
8.2.2. Canada Payment Analytics Software Market
8.3. Europe Payment Analytics Software Market Snapshot
8.3.1. U.K. Payment Analytics Software Market
8.3.2. Germany Payment Analytics Software Market
8.3.3. France Payment Analytics Software Market
8.3.4. Spain Payment Analytics Software Market
8.3.5. Italy Payment Analytics Software Market
8.3.6. Rest of Europe Payment Analytics Software Market
8.4. Asia-Pacific Payment Analytics Software Market Snapshot
8.4.1. China Payment Analytics Software Market
8.4.2. India Payment Analytics Software Market
8.4.3. Japan Payment Analytics Software Market
8.4.4. Australia Payment Analytics Software Market
8.4.5. South Korea Payment Analytics Software Market
8.4.6. Rest of Asia Pacific Payment Analytics Software Market
8.5. Latin America Payment Analytics Software Market Snapshot
8.5.1. Brazil Payment Analytics Software Market
8.5.2. Mexico Payment Analytics Software Market
8.6. Rest of The World Payment Analytics Software Market

Chapter 9. Competitive Intelligence
9.1. Top Market Strategies
9.2. Company Profiles
9.2.1. ProfitWell
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. BlueSnap
9.2.3. Databox
9.2.4. Payfirma
9.2.5. YapStone
9.2.6. CashNotify
9.2.7. HiPay Intelligence
9.2.8. PaySketch
9.2.9. Revealytics
9.2.10. RJMetrics
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

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
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.

Need Assistance

Contact Person -
Krishant Mennon
Call us @
+ 91 99931 15879
Email: sales@bizwitresearch.com

Checkout

Why Choose Us?

Quality over Quantity

Backed by 60+ paid data sources our reports deliver crisp insights with no compromise quality.

Analyst Support

24x7 Chat Support plus
free analyst hours with every purchase

Flawless Methodology

Our 360-degree approach of market study, our research methods leave stones unturned.

Enquiry Now