
Retail Analytics Market Report and Forecast 2025-2034
Description
The global retail analytics market reached a value of about USD 10.68 Billion in 2024 . The industry is further expected to grow at a CAGR of about 23.70% in the forecast period of 2025-2034 to reach a value of around USD 89.59 Billion by 2034 .
Retail Analytics Market Growth
Retail analytics is the intelligence solution that focuses on providing analytical modelling on various crucial processes in the retail industry. It aids in the decision-making process of the retailers by providing consumer insights and scope of product marketing and procurement. The increase in the number of social media users enables retailers to understand the demographic data and design their promotional and market growth strategies.
The increasing adoption of digitalisation, online shopping, and the proliferation of smartphones are major factors driving the retail analytics market expansion. The rise of e-commerce and social commerce has led to the generation of vast amounts of customer data, which retailers are leveraging to gain meaningful business insights and improve their operations. Retailers are increasingly adopting advanced technologies like artificial intelligence, machine learning, and big data analytics to extract insights, automate decision-making, enhance customer experiences, and optimise inventory and supply chain management. Additionally, the growing focus on improving customer relationships through personalised marketing, loyalty programs, and targeted promotions is further propelling the demand for retail analytics solutions.
Key Trends and Developments
Adoption of AI and ML in retail analytics, focus on shelf space allocation, and shift towards data-driven decision making have resulted in retail analytics market development
April 2024
The Estée Lauder Companies (ELC) and Microsoft are expanding their global strategic relationship by creating an AI Innovation Lab. Microsoft's generative AI tools and expertise will help ELC leverage its data to create more personalised experiences, faster insights, and better consumer connections.
April 2024
Oracle Corporation Japan plans to invest over USD 8 billion in cloud computing and AI infrastructure in Japan over the next decade. This strategic move underscores Oracle's commitment to meeting the evolving demands of the Japanese market and strengthening its position in cloud computing services.
January 2024
IBM and SAP partnered to create innovative AI solutions for the FMCG and retail industries, focusing on supply chain, finance, sales, and services enhancements using generative AI. This collaboration integrates IBM WatsonX and AI assistants into SAP solutions for product portfolio management.
November 2023
IBM collaborated with AWS to introduce a new cloud database offering, merging IBM Db2 database with Amazon RDS. This collaboration aims to assist businesses in managing data with flexibility, security, and scalability to optimise data management for AI workloads.
Integration of artificial intelligence and machine learning
By using AI and ML, retailers can analyse the vast amounts of data generated by them. This integration enables retailers to gain deeper insights into customer behaviour, optimise operations, personalise marketing campaigns, and enhance the overall customer experience.
Focus on product inventory management and shelf space allocation
Retail analytics tools are being utilised to ensure that products are placed strategically, in the right quantity, and at the right location to meet customer demand effectively. This trend aids retailers in minimising inventory costs, reducing out-of-stock situations, and optimising store layouts.
Increased adoption of industry 4.0 technologies
The adoption of Industry 4.0 technologies, such as Internet of Things (IoT) and automation, in the retail sector is a notable trend shaping the global retail analytics market outlook. A leading retailer, IKEA, has implemented IoT-enabled smart shelves to monitor inventory levels and optimise stock replenishment in its stores.
Rising demand for personalised marketing campaigns
Retailers are increasingly leveraging retail analytics to create personalised marketing campaigns based on customer preferences and behaviour patterns. A popular e-commerce platform, Amazon, uses AI-powered algorithms to offer product recommendations to its customers based on their purchasing history.
Retail Analytics Market Trends
Trends like efficient inventory management and shelf space allocation contribute to better profit margins and enhanced customer satisfaction. A leading fashion retailer, Zara, uses data analytics to optimise its inventory levels and shelf space allocation, allowing it to quickly respond to changing fashion trends.
The adoption of AI and ML in retail analytics is expected to drive retail analytics market growth by improving decision-making processes and operational efficiency. Walmart, a leading retail giant, has successfully implemented AI-powered chatbots to improve customer service and reduce wait times in its stores. Similarly, Target, another prominent retailer, has leveraged AI-driven analytics to optimise its inventory management and reduce stockouts.
Moreover, by utilising data analytics, retailers can identify customers interested in specific products, tailor marketing strategies accordingly, and enhance customer engagement. A leading beauty retailer, Sephora, uses data analytics to create personalised product recommendations and loyalty programs, resulting in increased customer loyalty and sales.
Retail Analytics Industry Segmentation
The EMR’s report titled “Retail Analytics Market Report and Forecast 2025-2034” offers a detailed analysis of the market based on the following segments:
Market Breakup by Solution
Cloud models are high in demand due to its capacity of storing large amount of data and records
Cloud deployment models simplify scalability, allowing businesses to quickly increase the number of servers they use, thereby enhancing future growth and simplifying data organisation, cleanup, and analysis. The availability of cloud solutions for mass users is likely to create significant opportunities for retail analytics market growth, especially in regions where cloud adoption is on the rise.
In contrast, on-premises solutions offer organisations more flexibility and control over customising their IT infrastructure, reducing dependency on the internet, and safeguarding critical company data from theft and fraud. This solution is preferred by organisations in the BFSI industry due to increased concerns about frauds like new account fraud and account takeovers, as on-premises solutions are less vulnerable to such frauds.
Customer management segment leads the market as retail analytics help determine customer preferences and enhance revenue
Customer management is expected to capture the maximum share in retail analytics market as retailers are increasingly implementing analytical tools to understand customer preferences and market trends, which is a key to driving sales and revenue. Such software helps measure customer loyalty, identify purchasing patterns, forecast demand, and optimise store layouts.
Retailers are using data analytics in supply chain management to examine the efficiency of marketing campaigns, better manage inventories, and enhance customer service. Analytical platforms offer meaningful insights and interactive dashboards, which can help retailers improve on-ground fleet management and logistics through route and network optimisation.
Leading Companies in the Retail Analytics Market
Market players are focused on expanding their market presence through partnerships and are investing in the development of innovative retail analytics solutions to gain a competitive edge
SAP SE
SAP SE, founded in 1972 and headquartered in Baden-Württemberg, Germany, is a multinational enterprise software company. SAP offers cloud-based retail analytics tools, which enable retailers to manage their operations, inventory, and customer relationships more effectively.
Oracle Corporation
Oracle Corporation, founded in 1977 and headquartered in Texas, United States, is a leading provider of database software and enterprise software solutions. Its offerings help retailers optimise their pricing strategies and improve inventory management through personalised marketing campaigns.
Microsoft Corporation
Microsoft Corporation, founded in 1975 and headquartered in Washington, United States, is known for its software, consumer electronics, and personal computers. Microsoft's retail analytics solutions, integrated with its cloud computing platform, Azure, enable retailers to leverage data-driven insights to improve decision-making.
MicroStrategy Incorporated
MicroStrategy Incorporated was founded in 1989. The company is headquartered in Virginia, United States. The company provides business intelligence (BI), mobile software, and cloud-based services, including artificial intelligence-powered enterprise analytics software and services.
Other key players in the global retail analytics market include QlikTech International A.B., RetailNext, Inc., Solvoyo, Altair Engineering Inc., SAS Institute Inc., and Teledyne Flir LLC, among others.
Retail Analytics Market Analysis by Region
North America to significantly boost the market growth due to its extensive deployment of cloud-based data analytics
The North American region accounts for a major share in the market owing to the large investments made by huge enterprises to deploy advanced technologies and gain a competitive edge in the market. The early adoption of analytical and cloud-based solutions by large enterprises across the region has significantly contributed to the industry growth.
The Asia Pacific region is experiencing significant growth in the retail analytics market share, driven by the rise in the penetration of social media, growth in e-commerce, and the presence of developing and emerging economies offering substantial opportunities for retail stores and technology advancement. The region’s growth is further fuelled by the increasing demand for retail analytics in inventory management, strategic planning, and customer behavior analysis.
Retail Analytics Market Growth
Retail analytics is the intelligence solution that focuses on providing analytical modelling on various crucial processes in the retail industry. It aids in the decision-making process of the retailers by providing consumer insights and scope of product marketing and procurement. The increase in the number of social media users enables retailers to understand the demographic data and design their promotional and market growth strategies.
The increasing adoption of digitalisation, online shopping, and the proliferation of smartphones are major factors driving the retail analytics market expansion. The rise of e-commerce and social commerce has led to the generation of vast amounts of customer data, which retailers are leveraging to gain meaningful business insights and improve their operations. Retailers are increasingly adopting advanced technologies like artificial intelligence, machine learning, and big data analytics to extract insights, automate decision-making, enhance customer experiences, and optimise inventory and supply chain management. Additionally, the growing focus on improving customer relationships through personalised marketing, loyalty programs, and targeted promotions is further propelling the demand for retail analytics solutions.
Key Trends and Developments
Adoption of AI and ML in retail analytics, focus on shelf space allocation, and shift towards data-driven decision making have resulted in retail analytics market development
April 2024
The Estée Lauder Companies (ELC) and Microsoft are expanding their global strategic relationship by creating an AI Innovation Lab. Microsoft's generative AI tools and expertise will help ELC leverage its data to create more personalised experiences, faster insights, and better consumer connections.
April 2024
Oracle Corporation Japan plans to invest over USD 8 billion in cloud computing and AI infrastructure in Japan over the next decade. This strategic move underscores Oracle's commitment to meeting the evolving demands of the Japanese market and strengthening its position in cloud computing services.
January 2024
IBM and SAP partnered to create innovative AI solutions for the FMCG and retail industries, focusing on supply chain, finance, sales, and services enhancements using generative AI. This collaboration integrates IBM WatsonX and AI assistants into SAP solutions for product portfolio management.
November 2023
IBM collaborated with AWS to introduce a new cloud database offering, merging IBM Db2 database with Amazon RDS. This collaboration aims to assist businesses in managing data with flexibility, security, and scalability to optimise data management for AI workloads.
Integration of artificial intelligence and machine learning
By using AI and ML, retailers can analyse the vast amounts of data generated by them. This integration enables retailers to gain deeper insights into customer behaviour, optimise operations, personalise marketing campaigns, and enhance the overall customer experience.
Focus on product inventory management and shelf space allocation
Retail analytics tools are being utilised to ensure that products are placed strategically, in the right quantity, and at the right location to meet customer demand effectively. This trend aids retailers in minimising inventory costs, reducing out-of-stock situations, and optimising store layouts.
Increased adoption of industry 4.0 technologies
The adoption of Industry 4.0 technologies, such as Internet of Things (IoT) and automation, in the retail sector is a notable trend shaping the global retail analytics market outlook. A leading retailer, IKEA, has implemented IoT-enabled smart shelves to monitor inventory levels and optimise stock replenishment in its stores.
Rising demand for personalised marketing campaigns
Retailers are increasingly leveraging retail analytics to create personalised marketing campaigns based on customer preferences and behaviour patterns. A popular e-commerce platform, Amazon, uses AI-powered algorithms to offer product recommendations to its customers based on their purchasing history.
Retail Analytics Market Trends
Trends like efficient inventory management and shelf space allocation contribute to better profit margins and enhanced customer satisfaction. A leading fashion retailer, Zara, uses data analytics to optimise its inventory levels and shelf space allocation, allowing it to quickly respond to changing fashion trends.
The adoption of AI and ML in retail analytics is expected to drive retail analytics market growth by improving decision-making processes and operational efficiency. Walmart, a leading retail giant, has successfully implemented AI-powered chatbots to improve customer service and reduce wait times in its stores. Similarly, Target, another prominent retailer, has leveraged AI-driven analytics to optimise its inventory management and reduce stockouts.
Moreover, by utilising data analytics, retailers can identify customers interested in specific products, tailor marketing strategies accordingly, and enhance customer engagement. A leading beauty retailer, Sephora, uses data analytics to create personalised product recommendations and loyalty programs, resulting in increased customer loyalty and sales.
Retail Analytics Industry Segmentation
The EMR’s report titled “Retail Analytics Market Report and Forecast 2025-2034” offers a detailed analysis of the market based on the following segments:
Market Breakup by Solution
- Software
- Service
- Cloud
- On-Premise
- Customer Management
- Supply Chain Management
- In-Store Operation
- Marketing and Merchandising
- Others
- North America
- Europe
- Asia Pacific
- Latin America
- Middle East and Africa
Cloud models are high in demand due to its capacity of storing large amount of data and records
Cloud deployment models simplify scalability, allowing businesses to quickly increase the number of servers they use, thereby enhancing future growth and simplifying data organisation, cleanup, and analysis. The availability of cloud solutions for mass users is likely to create significant opportunities for retail analytics market growth, especially in regions where cloud adoption is on the rise.
In contrast, on-premises solutions offer organisations more flexibility and control over customising their IT infrastructure, reducing dependency on the internet, and safeguarding critical company data from theft and fraud. This solution is preferred by organisations in the BFSI industry due to increased concerns about frauds like new account fraud and account takeovers, as on-premises solutions are less vulnerable to such frauds.
Customer management segment leads the market as retail analytics help determine customer preferences and enhance revenue
Customer management is expected to capture the maximum share in retail analytics market as retailers are increasingly implementing analytical tools to understand customer preferences and market trends, which is a key to driving sales and revenue. Such software helps measure customer loyalty, identify purchasing patterns, forecast demand, and optimise store layouts.
Retailers are using data analytics in supply chain management to examine the efficiency of marketing campaigns, better manage inventories, and enhance customer service. Analytical platforms offer meaningful insights and interactive dashboards, which can help retailers improve on-ground fleet management and logistics through route and network optimisation.
Leading Companies in the Retail Analytics Market
Market players are focused on expanding their market presence through partnerships and are investing in the development of innovative retail analytics solutions to gain a competitive edge
SAP SE
SAP SE, founded in 1972 and headquartered in Baden-Württemberg, Germany, is a multinational enterprise software company. SAP offers cloud-based retail analytics tools, which enable retailers to manage their operations, inventory, and customer relationships more effectively.
Oracle Corporation
Oracle Corporation, founded in 1977 and headquartered in Texas, United States, is a leading provider of database software and enterprise software solutions. Its offerings help retailers optimise their pricing strategies and improve inventory management through personalised marketing campaigns.
Microsoft Corporation
Microsoft Corporation, founded in 1975 and headquartered in Washington, United States, is known for its software, consumer electronics, and personal computers. Microsoft's retail analytics solutions, integrated with its cloud computing platform, Azure, enable retailers to leverage data-driven insights to improve decision-making.
MicroStrategy Incorporated
MicroStrategy Incorporated was founded in 1989. The company is headquartered in Virginia, United States. The company provides business intelligence (BI), mobile software, and cloud-based services, including artificial intelligence-powered enterprise analytics software and services.
Other key players in the global retail analytics market include QlikTech International A.B., RetailNext, Inc., Solvoyo, Altair Engineering Inc., SAS Institute Inc., and Teledyne Flir LLC, among others.
Retail Analytics Market Analysis by Region
North America to significantly boost the market growth due to its extensive deployment of cloud-based data analytics
The North American region accounts for a major share in the market owing to the large investments made by huge enterprises to deploy advanced technologies and gain a competitive edge in the market. The early adoption of analytical and cloud-based solutions by large enterprises across the region has significantly contributed to the industry growth.
The Asia Pacific region is experiencing significant growth in the retail analytics market share, driven by the rise in the penetration of social media, growth in e-commerce, and the presence of developing and emerging economies offering substantial opportunities for retail stores and technology advancement. The region’s growth is further fuelled by the increasing demand for retail analytics in inventory management, strategic planning, and customer behavior analysis.
Table of Contents
153 Pages
- 1 Executive Summary
- 1.1 Market Size 2024-2025
- 1.2 Market Growth 2025(F)-2034(F)
- 1.3 Key Demand Drivers
- 1.4 Key Players and Competitive Structure
- 1.5 Industry Best Practices
- 1.6 Recent Trends and Developments
- 1.7 Industry Outlook
- 2 Market Overview and Stakeholder Insights
- 2.1 Market Trends
- 2.2 Key Verticals
- 2.3 Key Regions
- 2.4 Supplier Power
- 2.5 Buyer Power
- 2.6 Key Market Opportunities and Risks
- 2.7 Key Initiatives by Stakeholders
- 3 Economic Summary
- 3.1 GDP Outlook
- 3.2 GDP Per Capita Growth
- 3.3 Inflation Trends
- 3.4 Democracy Index
- 3.5 Gross Public Debt Ratios
- 3.6 Balance of Payment (BoP) Position
- 3.7 Population Outlook
- 3.8 Urbanisation Trends
- 4 Country Risk Profiles
- 4.1 Country Risk
- 4.2 Business Climate
- 5 Global Retail Analytics Market Analysis
- 5.1 Key Industry Highlights
- 5.2 Global Retail Analytics Historical Market (2018-2024)
- 5.3 Global Retail Analytics Market Forecast (2025-2034)
- 5.4 Global Retail Analytics Market by Solution
- 5.4.1 Software
- 5.4.1.1 Historical Trend (2018-2024)
- 5.4.1.2 Forecast Trend (2025-2034)
- 5.4.2 Service
- 5.4.2.1 Historical Trend (2018-2024)
- 5.4.2.2 Forecast Trend (2025-2034)
- 5.5 Global Retail Analytics Market by Deployment Mode
- 5.5.1 Cloud
- 5.5.1.1 Historical Trend (2018-2024)
- 5.5.1.2 Forecast Trend (2025-2034)
- 5.5.2 On-Premise
- 5.5.2.1 Historical Trend (2018-2024)
- 5.5.2.2 Forecast Trend (2025-2034)
- 5.6 Global Retail Analytics Market by Function
- 5.6.1 Customer Management
- 5.6.1.1 Historical Trend (2018-2024)
- 5.6.1.2 Forecast Trend (2025-2034)
- 5.6.2 In-store Operation
- 5.6.2.1 Historical Trend (2018-2024)
- 5.6.2.2 Forecast Trend (2025-2034)
- 5.6.3 Supply Chain Management
- 5.6.3.1 Historical Trend (2018-2024)
- 5.6.3.2 Forecast Trend (2025-2034)
- 5.6.4 Marketing and Merchandising
- 5.6.4.1 Historical Trend (2018-2024)
- 5.6.4.2 Forecast Trend (2025-2034)
- 5.6.5 Others
- 5.7 Global Retail Analytics Market by Region
- 5.7.1 North America
- 5.7.1.1 Historical Trend (2018-2024)
- 5.7.1.2 Forecast Trend (2025-2034)
- 5.7.1.3 Breakup by Solution
- 5.7.1.4 Breakup by Deployment Mode
- 5.7.1.5 Breakup by Function
- 5.7.2 Europe
- 5.7.2.1 Historical Trend (2018-2024)
- 5.7.2.2 Forecast Trend (2025-2034)
- 5.7.2.3 Breakup by Solution
- 5.7.2.4 Breakup by Deployment Mode
- 5.7.2.5 Breakup by Function
- 5.7.3 Asia Pacific
- 5.7.3.1 Historical Trend (2018-2024)
- 5.7.3.2 Forecast Trend (2025-2034)
- 5.7.3.3 Breakup by Solution
- 5.7.3.4 Breakup by Deployment Mode
- 5.7.3.5 Breakup by Function
- 5.7.4 Latin America
- 5.7.4.1 Historical Trend (2018-2024)
- 5.7.4.2 Forecast Trend (2025-2034)
- 5.7.4.3 Breakup by Solution
- 5.7.4.4 Breakup by Deployment Mode
- 5.7.4.5 Breakup by Function
- 5.7.5 Middle East and Africa
- 5.7.5.1 Historical Trend (2018-2024)
- 5.7.5.2 Forecast Trend (2025-2034)
- 5.7.5.3 Breakup by Solution
- 5.7.5.4 Breakup by Deployment Mode
- 5.7.5.5 Breakup by Function
- 6 North America Retail Analytics Market Analysis
- 6.1 United States of America
- 6.1.1 Historical Trend (2018-2024)
- 6.1.2 Forecast Trend (2025-2034)
- 6.2 Canada
- 6.2.1 Historical Trend (2018-2024)
- 6.2.2 Forecast Trend (2025-2034)
- 7 Europe Retail Analytics Market Analysis
- 7.1 United Kingdom
- 7.1.1 Historical Trend (2018-2024)
- 7.1.2 Forecast Trend (2025-2034)
- 7.2 Germany
- 7.2.1 Historical Trend (2018-2024)
- 7.2.2 Forecast Trend (2025-2034)
- 7.3 France
- 7.3.1 Historical Trend (2018-2024)
- 7.3.2 Forecast Trend (2025-2034)
- 7.4 Italy
- 7.4.1 Historical Trend (2018-2024)
- 7.4.2 Forecast Trend (2025-2034)
- 7.5 Others
- 8 Asia Pacific Retail Analytics Market Analysis
- 8.1 China
- 8.1.1 Historical Trend (2018-2024)
- 8.1.2 Forecast Trend (2025-2034)
- 8.2 Japan
- 8.2.1 Historical Trend (2018-2024)
- 8.2.2 Forecast Trend (2025-2034)
- 8.3 India
- 8.3.1 Historical Trend (2018-2024)
- 8.3.2 Forecast Trend (2025-2034)
- 8.4 ASEAN
- 8.4.1 Historical Trend (2018-2024)
- 8.4.2 Forecast Trend (2025-2034)
- 8.5 Australia
- 8.5.1 Historical Trend (2018-2024)
- 8.5.2 Forecast Trend (2025-2034)
- 8.6 Others
- 9 Latin America Retail Analytics Market Analysis
- 9.1 Brazil
- 9.1.1 Historical Trend (2018-2024)
- 9.1.2 Forecast Trend (2025-2034)
- 9.2 Argentina
- 9.2.1 Historical Trend (2018-2024)
- 9.2.2 Forecast Trend (2025-2034)
- 9.3 Mexico
- 9.3.1 Historical Trend (2018-2024)
- 9.3.2 Forecast Trend (2025-2034)
- 9.4 Others
- 10 Middle East and Africa Retail Analytics Market Analysis
- 10.1 Saudi Arabia
- 10.1.1 Historical Trend (2018-2024)
- 10.1.2 Forecast Trend (2025-2034)
- 10.2 United Arab Emirates
- 10.2.1 Historical Trend (2018-2024)
- 10.2.2 Forecast Trend (2025-2034)
- 10.3 Nigeria
- 10.3.1 Historical Trend (2018-2024)
- 10.3.2 Forecast Trend (2025-2034)
- 10.4 South Africa
- 10.4.1 Historical Trend (2018-2024)
- 10.4.2 Forecast Trend (2025-2034)
- 10.5 Others
- 11 Market Dynamics
- 11.1 SWOT Analysis
- 11.1.1 Strengths
- 11.1.2 Weaknesses
- 11.1.3 Opportunities
- 11.1.4 Threats
- 11.2 Porter’s Five Forces Analysis
- 11.2.1 Supplier’s Power
- 11.2.2 Buyer’s Power
- 11.2.3 Threat of New Entrants
- 11.2.4 Degree of Rivalry
- 11.2.5 Threat of Substitutes
- 11.3 Key Indicators for Demand
- 11.4 Key Indicators for Price
- 12 Competitive Landscape
- 12.1 Supplier Selection
- 12.2 Key Global Players
- 12.3 Key Regional Players
- 12.4 Key Player Strategies
- 12.5 Company Profiles
- 12.5.1 Microsoft Corp.
- 12.5.1.1 Company Overview
- 12.5.1.2 Product Portfolio
- 12.5.1.3 Demographic Reach and Achievements
- 12.5.1.4 Certifications
- 12.5.2 SAP SE
- 12.5.2.1 Company Overview
- 12.5.2.2 Product Portfolio
- 12.5.2.3 Demographic Reach and Achievements
- 12.5.2.4 Certifications
- 12.5.3 Oracle Corp.
- 12.5.3.1 Company Overview
- 12.5.3.2 Product Portfolio
- 12.5.3.3 Demographic Reach and Achievements
- 12.5.3.4 Certifications
- 12.5.4 Teledyne FLIR LLC
- 12.5.4.1 Company Overview
- 12.5.4.2 Product Portfolio
- 12.5.4.3 Demographic Reach and Achievements
- 12.5.4.4 Certifications
- 12.5.5 MicroStrategy Incorporated
- 12.5.5.1 Company Overview
- 12.5.5.2 Product Portfolio
- 12.5.5.3 Demographic Reach and Achievements
- 12.5.5.4 Certifications
- 12.5.6 SAS Institute Inc.
- 12.5.6.1 Company Overview
- 12.5.6.2 Product Portfolio
- 12.5.6.3 Demographic Reach and Achievements
- 12.5.6.4 Certifications
- 12.5.7 QlikTech International A.B.
- 12.5.7.1 Company Overview
- 12.5.7.2 Product Portfolio
- 12.5.7.3 Demographic Reach and Achievements
- 12.5.7.4 Certifications
- 12.5.8 RetailNext, Inc.
- 12.5.8.1 Company Overview
- 12.5.8.2 Product Portfolio
- 12.5.8.3 Demographic Reach and Achievements
- 12.5.8.4 Certifications
- 12.5.9 Altair Engineering Inc.
- 12.5.9.1 Company Overview
- 12.5.9.2 Product Portfolio
- 12.5.9.3 Demographic Reach and Achievements
- 12.5.9.4 Certifications
- 12.5.10 Solvoyo
- 12.5.10.1 Company Overview
- 12.5.10.2 Product Portfolio
- 12.5.10.3 Demographic Reach and Achievements
- 12.5.10.4 Certifications
- 12.5.11 Others
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