Predictive Analytics Market by Solutions (Financial Analytics, Risk Analytics, Marketing Analytics, Sales Analytics, Web & Social Media Analytics, Network Analytics), Services, Deployment, organization size and Vertical - Global Forecast to 2022
[163 pages Report] The predictive analytics market size is expected to grow from USD 4.6 billion in 2017 to USD 12.4 billion by 2022, at a Compound Annual Growth Rate (CAGR) of 22.17% during the forecast period. Proliferation of internet and the availability of various means for accessing the internet have led to a massive increase in the data volumes being generated. This will help in the advancement and expansion of high-speed internet services. Globalization and economic growth are also playing major roles in driving greater data generation worldwide. Additionally, with the rise in touchpoint and the need for collecting data to understand consumer behavior, every touch by a consumer has become an important data point that can be processed to reveal user behavior. With the exponential rise in individual and organizational data, businesses are now deploying teams of data scientists and analysts to process the collected data. Another factor accelerating adoption is the revenue generating potential of predictive analytics. This is compelling firms to invest in predictive analytics.
Also, the rise in connected and integrated technologies has provided a platform to predictive analytics software vendors for leveraging this development and the unprecedented growth of the internet. Additionally, the eCommerce sector has modified the traditional shopping behavior of customers. Dedicated email campaigns, online/social media advertising, and cognitive analyzing of customers are the key enablers driving sales and increasing customers’ loyalty. With connected devices coming to the forefront, retailers are focusing on real-time analysis of customers’ shopping behavior and market basket analysis for analyzing consumers’ perception, which can be used for building tailor-made offers to increase customer retention. Similarly, with the rise in the global IoT analytics demand in the retail sector, the market is expected to have unprecedented growth opportunities for predictive analytics.
The exponential growth in data volume is due to the expansion of businesses worldwide, which is driving the rise in data volumes and sources. The accumulation of big data in a single location has rapidly developed the evaluation capabilities of data science experts in every organization. Additionally, companies prefer to provide stand-alone solutions rather than combined solutions. This is eventually resulting in a rise in the number of big data analytics startups, which are driving noteworthy innovations.
The predictive analytics for finance to counter frauds, minimize the risk of non-compliance through regulatory adherence
Predictive analytics leads to ad hoc analysis, which assists companies to have all workable solutions for their business specific questions and forecast past, present, and possible future predictive scenarios. In the current competitive business scenarios, companies need more than accurate predictive statements and reports from its predictive analytics. Companies now need more forward-looking, predictive insights that can help them shape impactful business strategy and improve the day-to-day decision-making in real time. Predictive analytics solution in predictive analytics can assist companies by combining internal predictive information and operational data with external information such as social media, demographics, and customer trading habits which may address critical business questions with unprecedented ease, speed, and accuracy. In addition, predictive analytics helps them to implement BI and analytical tools to derive precise insights from predictive data needed to take business decisions and be more strategic by boosting finance functions and credibility as a strategic partner to the business. IBM, SAP SE, SAS Institute, Inc., and Oracle Corporation are a few analytics leaders who offer predictive analytics to the customers worldwide.
Customer behavior analysis to enhance understanding of purchasing behavior and preference of the customer. Also, helps in tracking customer loyalty fueling the growth of the overall predictive analytics market
Customer analytics is an advanced and systematic analytical process, also known as customer intelligence, in which customer data is used by companies to better understand customer behavior and make strategic business decisions through customer segmentation and predictive analytics. It is a systematic analysis of the customer insights, which assist the organization to identify and target the customers for marketing programs from their behavioral prediction. It helps organizations to retain the existing customers, maximize the customer lifecycle value, and gain customer loyalty. The data optimization is done by the combination of process and technologies, such as behavioral analysis, sentiment analysis over social media, predictive modeling, segmentation, and data visualization and reporting. The analysis of such huge data offers a competitive advantage to an organization.
Cloud deployment model to grow at the highest CAGR during the forecast period
The cloud deployment model provides multiple benefits, such as reduced operational costs, simple deployments, and higher scalability. Due to this, cloud deployment for predictive analytics solution is expected to grow with an increasing awareness of benefits of cloud-based solutions. The predictive analytics solution providers are focusing on the development of robust cloud-based predictive solutions for their clients, as many organizations have migrated to either private or public cloud. Additionally, providers such as IBM Corporation and Qual Metrix are focusing on the development of cloud software that would incorporate on-premises application to the cloud. Moreover, the cloud provides additional flexibility for business operations and real-time deployment ease to the companies that implementing predictive analytics. Cloud solutions make it easy for users in applying the predictive capabilities to the entire organization and helps in maintaining a competitive edge by eliminating the administrative roadblocks of the supporting infrastructure and allow organizations to focus on improving their competencies. The predictive cloud solutions are also significantly gaining traction due to its cost-effective benefits and global availability.
North America to account for the largest market size during the forecast period.
The global predictive analytics market by region covers 5 major geographic regions: North America, Asia Pacific (APAC), Europe, the Middle East and Africa (MEA), and Latin America. North America constitutes the highest market share, owing to the growing adoption of predictive analytics as well as high penetration of predictive analytics in multiple industry verticals, such as retail and ecommerce, BFSI, and government. The US and Canada are 2 two prominent markets in North America that are witnessing healthy adoption of advanced technologies, such as predictive analytics solutions.
Key Market Players
The predictive analytics ecosystem comprises vendors, such as Alteryx, Inc. (US), AgilOne (US), Angoss Software Corporation (Canada), Domino Data Lab (US), Dataiku (US), Exago, Inc. (US), Fair Isaac Corporation (FICO) (US), GoodData Corporation (US), International Business Machines (IBM) Corporation (US), Information Builders (US), Kognitio Ltd. (UK), KNIME.com AG (Switzerland), MicroStrategy, Inc. (US), Microsoft Corporation (US), NTT DATA Corporation (Japan), Oracle Corporation (US), Predixion Software (US), RapidMiner (US), QlikTech International (US), Sisense, Inc. (US), SAP SE (Germany), SAS Institute, Inc. (US), Tableau Software, Inc. (US), TIBCO Software, Inc. (US), and Teradata Corporation (US). These Predictive Analytics Software vendors are rated and listed by us on basis of product quality, reliability and their business strategy. Please visit 360Quadrants to see the vendor listing of Predictive Analytics Software.
Recent Developments:
- July 2017, SAP collaborated with energy and services company Centrica to help their customers in managing assets and energy consumption on insights available through the IoT.
- February 2017, Oracle announced the expansion of its IoT portfolio with the introduction of 4 new cloud solutions to assist businesses to fully utilize the advantages of the digital supply chain. By applying advanced predictive analytics to devise signals, IoT applications can help in automating business processes and operations across the supply chain to enhance customer experience.
- March 2016, the company has extended their strategic partnership to offer combined capabilities of cloud analytics and big data to their users. This will help users to automate and simplify the decisions while attaining greater business insights for smarter business decisions.
Key questions addressed by the report:
- What are the opportunities in the predictive analytics market?
- What is the competitive landscape in the market?
- What are the regulations that will impact the market?
- How are mergers and acquisitions evolving the market?
- What are the dynamics of the market?
Frequently Asked Questions (FAQ):
What is Predictive Analytics?
What are the top companies providing Predictive Analytics?
What are the top industries adopting Predictive Analytics?
What are various trends in Predictive Analytics?
- Driver:
- The rise in touchpoint and the need of collecting consumer data for understanding user behavior
- Continuous development across artificial intelligence and machine learning to improve business performance
- Opportunities:
- Enterprises are aligning their business models towards digital transformation, thereby encouraging predictive analytics adoption
What are various Predictive Analytics techniques?
To speak to our analyst for a discussion on the above findings, click Speak to Analyst
Table of Contents
1 Introduction (Page No. - 16)
1.1 Objectives of the Study
1.2 Market Definition
1.3 Market Scope
1.4 Years Considered for the Study
1.5 Currency
1.6 Stakeholders
2 Research Methodology (Page No. - 19)
2.1 Research Data
2.1.1 Secondary Data
2.1.2 Primary Data
2.1.2.1 Breakdown of Primaries
2.1.2.1.1 Key Industry Insights
2.2 Market Size Estimation
2.3 Microquadrant Methodology
2.3.1 Vendor Inclusion Criteria
2.4 Research Assumptions
2.5 Limitations
3 Executive Summary (Page No. - 27)
4 Premium Insights (Page No. - 32)
4.1 Attractive Opportunities in the Predictive Analytics Market
4.2 Market, By Region
4.3 Market, By Industry Vertical and Region
4.4 Life Cycle Analysis, By Region, 2017
5 Predictive Analytics Market Overview and Industry Trends (Page No. - 36)
5.1 Market Overview
5.1.1 Introduction
5.1.2 Market Dynamics
5.1.2.1 Drivers
5.1.2.1.1 Increasing Adoption of Predictive Analytics for Forecasting Future Market Trends
5.1.2.1.2 Enterprises’ Need for Ensuring Market Competitiveness
5.1.2.1.3 Growing Adoption of Big Data and Other Related Technologies
5.1.2.2 Restraints
5.1.2.2.1 Changing Regional Data Regulations Leading to the Time-Consuming Restructuring of Predictive Models
5.1.2.3 Opportunities
5.1.2.3.1 Increasing Awareness Accelerating the Development of Better Analytics Tools
5.1.2.3.2 Advent of Machine Learning and AI
5.1.2.4 Challenges
5.1.2.4.1 Ownership and Privacy of the Collected Data
5.1.2.4.2 Data Ecosystems and Exchanges
5.2 Industry Trends
5.2.1 Predictive Analytics: Use Cases
5.2.1.1 Use Case #1: Deliver Personalized Interactions
5.2.1.2 Use Case #2: Understand Buying Patterns
5.2.1.3 Use Case #3: Increase Revenue and Decrease Customers’ Business Inefficiencies
5.2.1.4 Use Case #4: Market Basket Analysis
5.3 Predictive Analytics Process
5.4 Regulatory Implications
5.4.1 Sarbanes-Oxley Act of 2002
5.4.2 General Data Protection Regulation
5.4.3 Basel
6 Predictive Analytics Market Analysis, By Type (Page No. - 46)
6.1 Introduction
6.2 Solutions
6.2.1 Financial Analytics
6.2.1.1 Fraud Detection
6.2.1.2 Profitability Management
6.2.1.3 Governance and Compliance Management
6.2.1.4 Others
6.2.2 Risk Analytics
6.2.2.1 Cyber Risk Management
6.2.2.2 Operational Risk Management
6.2.2.3 Credit and Market Risk Management
6.2.2.4 Others
6.2.3 Marketing Analytics
6.2.3.1 Predictive Modelling
6.2.3.2 Yield Management
6.2.3.3 Product and Service Development Strategies
6.2.3.4 Others
6.2.4 Sales Analytics
6.2.4.1 Sales Life Cycle Management
6.2.4.2 Sales Rep Efficiency Management
6.2.4.3 Others
6.2.5 Customer Analytics
6.2.5.1 Customer Segmentation and Clustering
6.2.5.2 Customer Behavior Analysis
6.2.5.3 Monitoring Customer Loyalty and Satisfaction
6.2.5.4 Others
6.2.6 Web and Social Media Analytics
6.2.6.1 Social Media Management
6.2.6.2 Search Engine Optimization
6.2.6.3 Performance Monitoring
6.2.6.4 Competitor Benchmarking
6.2.7 Supply Chain Analytics
6.2.7.1 Distribution and Logistics Optimization
6.2.7.2 Inventory Management
6.2.7.3 Manufacturing Analysis
6.2.7.4 Others
6.2.8 Network Analytics
6.2.8.1 Intelligent Network Optimization
6.2.8.2 Traffic Management
6.2.8.3 Others
6.2.9 Others
6.3 Services
6.3.1 Managed Services
6.3.2 Professional Services
6.3.2.1 Support and Maintenance
6.3.2.2 Consulting
7 Predictive Analytics Market Analysis, By Organization Size (Page No. - 71)
7.1 Introduction
7.2 Small and Medium-Sized Enterprises
7.3 Large Enterprises
8 Predictive Analytics Market Analysis, By Deployment Model (Page No. - 75)
8.1 Introduction
8.2 On-Premises
8.3 Cloud
9 Predictive Analytics Market Analysis, By Industry Vertical (Page No. - 79)
9.1 Introduction
9.2 Banking, Financial Services, and Insurance
9.3 Telecommunications and It
9.4 Retail and Ecommerce
9.5 Healthcare and Life Sciences
9.6 Manufacturing
9.7 Government and Defense
9.8 Energy and Utilities
9.9 Transportation and Logistics
9.10 Others
10 Geographic Analysis (Page No. - 90)
10.1 Introduction
10.2 North America
10.2.1 By Type
10.2.2 By Solution
10.2.3 By Service
10.2.4 By Professional Service
10.2.5 By Deployment Model
10.2.6 By Organization Size
10.2.7 By Industry Vertical
10.2.8 By Country
10.2.8.1 United States
10.2.8.2 Canada
10.3 Europe
10.3.1 By Type
10.3.2 By Solution
10.3.3 By Service
10.3.4 By Professional Service
10.3.5 By Deployment Model
10.3.6 By Organization Size
10.3.7 By Industry Vertical
10.3.8 By Country
10.3.8.1 Germany
10.3.8.2 United Kingdom
10.3.8.3 France
10.3.8.4 Rest of Europe
10.4 Asia Pacific
10.4.1 By Type
10.4.2 By Solution
10.4.3 By Service
10.4.4 By Professional Service
10.4.5 By Deployment Model
10.4.6 By Organization Size
10.4.7 By Industry Vertical
10.4.8 By Country
10.4.8.1 Japan
10.4.8.2 India
10.4.8.3 Singapore
10.4.8.4 Australia
10.5 Middle East and Africa
10.5.1 By Type
10.5.2 By Solution
10.5.3 By Service
10.5.4 By Professional Service
10.5.5 By Deployment Model
10.5.6 By Organization Size
10.5.7 By Industry Vertical
10.6 Latin America
10.6.1 By Type
10.6.2 By Solution
10.6.3 By Service
10.6.4 By Professional Service
10.6.5 By Deployment Model
10.6.6 By Organization Size
10.6.7 By Industry Vertical
10.6.8 By Country
10.6.8.1 Brazil
10.6.8.2 Mexico
11 Competitive Landscape (Page No. - 117)
11.1 Microquadrant Overview
11.1.1 Visionary Leaders
11.1.2 Innovators
11.1.3 Dynamic Differentiators
11.1.4 Emerging Companies
11.1.5 Predictive Analytics Market (Global) Competitive Leadership Mapping, 2017
11.2 Competitive Benchmarking
11.2.1 Strength of Product Portfolio Adopted in the Market
11.2.2 Business Strategy Excellence Adopted in the Market
12 Company Profiles (Page No. - 121)
(Business Overview, Strength of Product Portfolio, Business Strategy Excellence, Recent Developments)*
12.1 International Business Machines (IBM) Corporation
12.2 Oracle Corporation
12.3 SAP SE
12.4 Microsoft Corporation
12.5 SAS Institute, Inc.
12.6 Fair Isaac Corporation (FICO)
12.7 NTT Data Corporation
12.8 Tableau Software, Inc.
12.9 Tibco Software, Inc.
12.10 Rapidminer, Inc.
12.11 Angoss Software Corporation
*Details on Overview, Strength of Product Portfolio, Business Strategy Excellence, Recent Developments Might Not Be Captured in Case of Unlisted Companies.
13 Appendix (Page No. - 156)
13.1 Key Insights From Industry Experts
13.2 Discussion Guide
13.3 Knowledge Store: Marketsandmarkets’ Subscription Portal
13.4 Available Customizations
13.5 Related Reports
13.6 Author Details
List of Tables (82 Tables)
Table 1 United States Dollar Exchange Rate, 2014–2016
Table 2 Evaluation Criteria
Table 3 Predictive Analytics Market Size, By Type, 2015–2022 (USD Million)
Table 4 Solutions: Market Size, By Region, 2015–2022 (USD Million)
Table 5 Market Size, By Solution, 2015–2022 (USD Million)
Table 6 Financial Analytics Market Size, By Region, 2015–2022 (USD Million)
Table 7 Financial Analytics Market Size, By Application, 2015–2022 (USD Million)
Table 8 Risk Analytics Market Size, By Region, 2015–2022 (USD Million)
Table 9 Risk Analytics Market Size, By Application, 2015–2022 (USD Million)
Table 10 Marketing Analytics Market Size, By Region, 2015–2022 (USD Million)
Table 11 Marketing Analytics Market Size, By Application, 2015–2022 (USD Million)
Table 12 Sales Analytics Market Size, By Region, 2015–2022 (USD Million)
Table 13 Sales Analytics Market Size, By Application, 2015–2022 (USD Million)
Table 14 Customer Analytics Market Size, By Region, 2015–2022 (USD Million)
Table 15 Customer Analytics Market Size, By Application, 2015–2022 (USD Million)
Table 16 Web and Social Media Analytics Market Size, By Region, 2015–2022 (USD Million)
Table 17 Web and Social Media Analytics Market Size, By Application, 2015–2022 (USD Million)
Table 18 Supply Chain Analytics Predictive Analytics Market Size, By Region, 2015–2022 (USD Million)
Table 19 Supply Chain Analytics Market Size, By Application, 2015–2022 (USD Million)
Table 20 Network Analytics Market Size, By Region, 2015–2022 (USD Million)
Table 21 Network Analytics Market Size, By Application, 2015–2022 (USD Million)
Table 22 Others: Market Size By Region, 2015–2022 (USD Million)
Table 23 Services: Market Size By Region, 2015–2022 (USD Million)
Table 24 Services: Market Size By Type, 2015–2022 (USD Million)
Table 25 Managed Services Market Size, By Region, 2015–2022 (USD Million)
Table 26 Professional Services Market Size, By Region, 2015–2022 (USD Million)
Table 27 Professional Services Market Size, By Type, 2015-2022 (USD Million)
Table 28 Support and Maintenance Services Market Size, By Region, 2015–2022 (USD Million)
Table 29 Consulting Services Market Size, By Region, 2015–2022 (USD Million)
Table 30 Predictive Analytics Market Size, By Organization Size, 2015–2022 (USD Million)
Table 31 Small and Medium-Sized Enterprises: Market Size By Region, 2015–2022 (USD Million)
Table 32 Large Enterprises: Market Size By Region, 2015–2022 (USD Million)
Table 33 Market Size, By Deployment Model, 2015–2022 (USD Million)
Table 34 On-Premises: Market Size By Region, 2015–2022 (USD Million)
Table 35 Cloud: Market Size By Region, 2015–2022 (USD Million)
Table 36 Market Size, By Industry Vertical, 2015–2022 (USD Million)
Table 37 Banking, Financial Services, and Insurance: Market Size, By Region, 2015–2022 (USD Million)
Table 38 Telecommunications and It: Market Size By Region, 2015–2022 (USD Million)
Table 39 Retail and Ecommerce: Market Size By Region, 2015–2022 (USD Million)
Table 40 Healthcare and Life Sciences: Market Size By Region, 2015–2022 (USD Million)
Table 41 Manufacturing: Market Size By Region, 2015–2022 (USD Million)
Table 42 Government and Defense: Market Size By Region, 2015–2022 (USD Million)
Table 43 Energy and Utilities: Market Size By Region, 2015–2022 (USD Million)
Table 44 Transportation and Logistics: Market Size By Region, 2015–2022 (USD Million)
Table 45 Others: Market Size By Region, 2015–2022 (USD Million)
Table 46 Predictive Analytics Market Size, By Region, 2015–2022 (USD Million)
Table 47 North America: Market Size, By Type, 2015–2022 (USD Million)
Table 48 North America: Market Size, By Solution, 2015–2022 (USD Million)
Table 49 North America: Market Size, By Service, 2015–2022 (USD Million)
Table 50 North America: Market Size, By Professional Service, 2015–2022 (USD Million)
Table 51 North America: Market Size, By Deployment Model, 2015–2022 (USD Million)
Table 52 North America: Market Size, By Organization Size, 2015–2022 (USD Million)
Table 53 North America: Market Size, By Industry Vertical, 2015–2022 (USD Million)
Table 54 Europe: Predictive Analytics Market Size, By Type, 2015–2022 (USD Million)
Table 55 Europe: Market Size By Solution, 2015–2022 (USD Million)
Table 56 Europe: Market Size By Service, 2015–2022 (USD Million)
Table 57 Europe: Market Size By Professional Service, 2015–2022 (USD Million)
Table 58 Europe: Market Size By Deployment Model, 2015–2022 (USD Million)
Table 59 Europe: Market Size By Organization Size, 2015–2022 (USD Million)
Table 60 Europe: Market Size By Industry Vertical, 2015–2022 (USD Million)
Table 61 Asia Pacific: Predictive Analytics Market Size, By Type, 2015–2022 (USD Million)
Table 62 Asia Pacific: Market Size, By Solution, 2015–2022 (USD Million)
Table 63 Asia Pacific: Market Size, By Service, 2015–2022 (USD Million)
Table 64 Asia Pacific: Market Size, By Professional Service, 2015–2022 (USD Million)
Table 65 Asia Pacific: Market Size, By Deployment Model, 2015–2022 (USD Million)
Table 66 Asia Pacific: Market Size, By Organization Size, 2015–2022 (USD Million)
Table 67 Asia Pacific: Predictive Analytics Market Size, By Industry Vertical, 2015–2022 (USD Million)
Table 68 Middle East and Africa: Market Size By Type, 2015–2022 (USD Million)
Table 69 Middle East and Africa: Market Size By Solution, 2015–2022 (USD Million)
Table 70 Middle East and Africa: Market Size By Service, 2015–2022 (USD Million)
Table 71 Middle East and Africa: Market Size By Professional Service, 2015–2022 (USD Million)
Table 72 Middle East and Africa: Market Size By Deployment Model, 2015–2022 (USD Million)
Table 73 Middle East and Africa: Market Size By Organization Size, 2015–2022 (USD Million)
Table 74 Middle East and Africa: Market Size By Industry Vertical, 2015–2022 (USD Million)
Table 75 Latin America: Predictive Analytics Market Size, By Type, 2015–2022 (USD Million)
Table 76 Latin America: Market Size By Solution, 2015–2022 (USD Million)
Table 77 Latin America: Market Size By Service, 2015–2022 (USD Million)
Table 78 Latin America: Market Size By Professional Service, 2015–2022 (USD Million)
Table 79 Latin America: Market Size By Deployment Model, 2015–2022 (USD Million)
Table 80 Latin America: Market Size By Organization Size, 2015–2022 (USD Million)
Table 81 Latin America: Market Size By Industry Vertical, 2015–2022 (USD Million)
Table 82 Market Ranking for the Predictive Analytics Market, 2017
List of Figures (37 Figures)
Figure 1 Predictive Analytics Market Segmentation
Figure 2 Market: Research Design
Figure 3 Breakdown of Primary Interviews: By Company, Designation, and Region
Figure 4 Data Triangulation
Figure 5 Market Size Estimation Methodology: Bottom-Up Approach
Figure 6 Market Size Estimation Methodology: Top-Down Approach
Figure 7 Market: Assumptions
Figure 8 The Market is Expected to Witness Significant Growth During the Forecast Period
Figure 9 Market Snapshot By Type (2017 vs 2022)
Figure 10 Market Snapshot By Service (2017 vs 2022)
Figure 11 Market Snapshot By Solution (2017 vs 2022)
Figure 12 Market Snapshot By Deployment Model (2017 vs 2022)
Figure 13 Increasing Adoption of Predictive Analytics is Driving the Market Growth
Figure 14 North America is Estimated to Have the Largest Market Share in 2017
Figure 15 Banking, Financial Services, and Insurance Industry Vertical, and North America are Estimated to Have the Largest Market Size in 2017
Figure 16 Asia Pacific is Expected to Have the Highest Growth Rate During the Forcast Period
Figure 17 Predictive Analytics Market: Drivers, Restraints, Opportunities, and Challenges
Figure 18 Predictive Analytics Process
Figure 19 Services Segment is Expected to Grow at A Higher CAGR During the Forecast Period
Figure 20 Customer Analytics is Expected to Have the Highest CAGR During the Forecast Period
Figure 21 Managed Services Segment is Expected to Grow at A Higher CAGR During the Forecast Period
Figure 22 Consulting Services Segment is Expected to Grow at A Higher CAGR During the Forecast Period
Figure 23 Small and Medium-Sized Enterprises Segment is Expected to Have A Higher Growth Rate During the Forecast Period
Figure 24 Cloud is Expected to Have A Higher Growth Rate During the Forecast Period
Figure 25 Telecommunication and It Vertical is Expected to Have the Highest Growth Rate During the Forecast Period
Figure 26 Asia Pacific is Estimated to Grow at the Highest CAGR in the Predictive Analytics Market
Figure 27 Asia Pacific is Expected to Have the Highest Growth Rate in the Market
Figure 28 North America: Market Snapshot
Figure 29 Asia Pacific: Market Snapshot
Figure 30 International Business Machines Corporation: Company Snapshot
Figure 31 Oracle Corporation: Company Snapshot
Figure 32 SAP SE: Company Snapshot
Figure 33 Microsoft Corporation: Company Snapshot
Figure 34 SAS Institute, Inc.: Company Snapshot
Figure 35 Fair Isaac Corporation: Company Snapshot
Figure 36 NTT Data Corporation: Company Snapshot
Figure 37 Tableau Software, Inc.: Company Snapshot
The study involved 4 major activities to estimate the current market size for the predictive analytics market. An exhaustive secondary research was done to collect information on the market, the peer market, and the parent market. The next step was to validate these findings, assumptions, and sizing with industry experts across the value chain through primary research. Both top-down and bottom-up approaches were employed to estimate the complete market size. Thereafter, the market breakdown and data triangulation procedures were used to estimate the market size of the segments and sub segments.
Secondary Research
In the secondary research process, various secondary sources, such as Hoovers, Bloomberg Businessweek, and Dun & Bradstreet, have been referred to identify and collect information for this study. These secondary sources included annual reports; press releases and investor presentations of companies; whitepapers, certified publications and articles by recognized authors; gold standard and silver standard websites; predictive analytics technology Research and Development (R&D) organizations; regulatory bodies; and databases.
Primary Research
Various primary sources from both supply and demand sides of the predictive analytics market ecosystem were interviewed to obtain qualitative and quantitative information for this study. The primary sources from the supply-side included industry experts, such as Chief Executive Officers (CEOs), Vice Presidents (VPs), marketing directors, technology and innovation directors, and related key executives from various vendors who provide the predictive analytics software, associated service providers, and system integrators operating in the targeted regions. All possible parameters that affect the market covered in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data.
Following is the breakdown of the primary respondents:
To know about the assumptions considered for the study, download the pdf brochure
Market Size Estimation
For making market estimates and forecasting the predictive analytics market and other dependent submarkets, the top-down and bottom-up approaches were used. The bottom-up procedure was used to arrive at the overall market size of the global predictive analytics market using key companies’ revenues and their offerings in the market. The research methodology used to estimate the market size includes the following:
- The key players in the market have been identified through extensive secondary research.
- The market size, in terms of value, has been determined with the help of the primary and secondary research processes.
- All percentage shares, splits, and breakups have been determined using secondary sources and verified through primary sources.
Data Triangulation
With data triangulation and validation through primary interviews, the exact value of the overall parent market size was determined and confirmed using this study. The overall market size was then used in the top-down procedure to estimate the size of other individual markets via percentage splits of the market segmentation.
Report Objectives
- To define, describe, and forecast the predictive analytics market based on type, deployment mode, organization size, industry verticals, and regions
- To provide detailed information regarding the major factors, such as drivers, restraints, opportunities, and challenges, influencing the growth of the market
- To analyze the market’s sub segments with respect to individual growth trends, prospects, and contributions to the total market
- To analyze the opportunities in the market for stakeholders and provide the competitive landscape of the market
- To forecast the revenue of the market’s segments with respect to 5 major regions, namely, North America, Europe, Asia Pacific (APAC), Middle East and Africa (MEA), and Latin America
- To profile the key players and comprehensively analyze their recent developments and positioning in the predictive analytics market
- To analyze the competitive developments, such as partnerships, collaborations, and acquisitions, new product launches and product enhancements, and new business strategies, in the market
Scope of the Report
|
Report Metrics |
Details |
|
Market size available for years |
2015–2022 |
|
Base year considered |
2016 |
|
Forecast period |
2017–2022 |
|
Forecast units |
Billion (USD) |
|
Segments covered |
Type, Deployment Model, Organization Size, Vertical, and Region |
|
Regions covered |
North America, APAC, Europe, Latin America, and MEA |
|
Companies covered |
Alteryx, Inc. (US), AgilOne (US), Angoss Software Corporation (Canada), Domino Data Lab (US), Dataiku (US), Exago, Inc. (US), Fair Isaac Corporation (FICO) (US), GoodData Corporation (US), International Business Machines (IBM) Corporation (US), Information Builders (US), Kognitio Ltd. (UK), KNIME.com AG (Switzerland), MicroStrategy, Inc. (US), Microsoft Corporation (US), NTT DATA Corporation (Japan), Oracle Corporation (US), Predixion Software (US), RapidMiner (US), QlikTech International (US), Sisense, Inc. (US), SAP SE (Germany), SAS Institute, Inc. (US), Tableau Software, Inc. (US), TIBCO Software, Inc. (US), and Teradata Corporation (US). |
This research report categorizes the predictive analytics market based on type, deployment model, organization size, industry vertical, and region.
Based on type, the predictive analytics market has been segmented as follows:
- Solutions
- Financial Analytics
- Risk Analytics
- Marketing Analytics
- Sales Analytics
- Customer Analytics
- Web and Social Analytics
- Supply Chain Analytics
- Network Analytics
- Others
- Services
- Managed Services
- Professional Services
- Support and Maintenance
- Consulting
Based on deployment model, the market has been segmented as follows:
- On-Premise
- Cloud
Based on organization size, the predictive analytics market has been segmented as follows:
- Small Enterprises
- Large Enterprises
Based on industry verticals, the market has been segmented as follows:
- BFSI
- Telecom and IT
- Retail and Ecommerce
- Healthcare and Life Sciences
- Government and Defenses
- Manufacturing
- Energy and Utilities
- Transportation and Logistics
- Others
Based on regions, the predictive analytics market has been segmented as follows:
- North America
- Europe
- APAC
- Latin America
- MEA
Available Customizations
With the given market data, MarketsandMarkets offers customizations as per the company’s specific needs. The following customization options are available for the report:
Product Analysis
- Product matrix gives a detailed comparison of the product portfolio of each company
Company Information
- Detailed analysis and profiling of additional market players up to 5
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Growth opportunities and latent adjacency in Predictive Analytics Market
According to us, implementing predictive analytics would be a good strategy for an organization: With the increasing volume and variety of business data, due to increasing adoption of emerging technologies such as Artificial Intelligence, Machine Learning, Internet of Things and Mobility, organizations require real-time insights from those datasets for faster and better decision making. Predictive analytics helps industries in understanding the customer perception by providing competitive market edge and an ability to orchestrate business decisions rapidly. It also provides operational excellence by improving productivity and profitability across organizations, and help the organization for achieving financial efficiency, informed decision making, and better data visualization for both structured as well as unstructured data sets. Organizations across industry verticals (including BFSI, Retail, Healthcare, Government, Telecom, and so on) are implementing predictive analytics for multiple business applications to get these benefits and most of them are achieving better results. For example, HSBC recently partnered with an AI start-up Ayasdi to automate anti-money laundering investigations using predictive modelling and they saw the number of investigations by 20% without reducing the number of cases referred for more scrutiny. Vodafone is using CleverTap’s customer analytics solution to engage their users and drive conversions. Using the predictive analytics tool, Vodafone could successfully scale personalized campaigns to double the conversions. Hence, predictive analytics is considered as a new mantra for businesses across industries because it helps organizations achieving varied range of business outcomes, higher customer satisfaction, and efficient operations. It is now widely being used by marketing, sales and finance teams to achieve desirable business performance.
Do you think implementing predictive analysts will be a good strategy? Would it be good with an automation platform?