Though the predictive analytics market in Latin America is still at a nascent stage, it is expected to grow significantly during the forecast period. Countries such as Brazil, Colombia, Argentina, Chile, and Peru have good market opportunities. Many countries are struggling in this market due to the lack of advanced technologies and budget constraints. Companies in this region are planning to invest heavily in cost-effective analytics solutions and services. This would help predictive analytics providers to create revenue increasing opportunities for themselves. With organizations in this region planning to invest heavily in cost-effective analytics solutions, the predictive analytics market has a huge scope for development. This has opened opportunities for North American companies to expand their presence in this region. Brazil, Mexico, and Chile are the countries, where the penetration of solutions is high, in comparison to the other countries of the region. In Brazil, the increasing income levels, particularly among the younger population, demonstrate the growing socio-economic strata of the people in the country. Brazil is among the countries that have an enormous dependence on the manufacturing sector and is witnessing the increasing internet adoption as well. With organizations in Latin America planning to invest heavily in cost-effective analytics solutions and services, the predictive analytics market has a huge scope for development. However, the lack of skilled workforce to support technologies is expected to hinder the market growth to some extent.

Frequently Asked Questions

  • How will the Predictive Analytics Market perform in near future?
    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.
  • What are the opportunities in the predictive analytics market?
    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.
  • What is the competitive landscape in the market?
    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). 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.
  • What are the regulations that will impact the market?
    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.
  • How are mergers and acquisitions evolving the market?
    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.
  • What are the dynamics of the market?
    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. 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.

Predictive Analytics Software in Latin America

Comparing 168 vendors in Predictive Analytics Software across 193 criteria.
2 Experts are advising 99 Predictive Analytics Software buyers
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SPSS Modeler reduces the complexities involved in the transformation of data by providing easy-to-use models. SPSS Modeler is extensively used across various languages to analyze data from multiple databases. It majorly helps in analyzing data to predict customer churn rates and data sets. The application can be used across various industry verticles.
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Rapid Miner Studio enables users to create complex predictive models by using a drag and drop visual interface. It has a library of 1500+ machine learning algorithms and functions that can be used to build models specific to any situation. It also offers templates for common cases such as prediction of customer churn, fraud detection, predictive maintenance, etc. It provides proactive recommendations at each step for guidance. Rapidminer helps increase productivity across teams.
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SAP Predictive Analytics software enables users to create, deploy and maintain various predictive models. These on-premise tools can help users anticipate future behavior and outcomes and better guide the decision-making ability to help grow the business. SAP Predictive Analytics Cloud works alongside the BI and planning tools to visualize, plan and predict context. The tool uses in-memory technology and machine learning to uncover relevant predictive insights in real-time.
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ORACLE Analytics Cloud’s Database Platform allows the use of seamless predictive analytics software within the platform, giving it an edge over other vendors. ORACLE Analytics Cloud helps mine various data types, eradicate movement of data, and deliver actionable insights. Application developers deploy this analytics model along with SQL and R functions. ORACLE Analytics Cloud helps predict the behavior of customers, the gap between the demand and supply, and make better marketing strategies.
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SAS Advanced Analytics provides users with better response time and faster insights provided by its in-memory analytics. SAS Advanced Predictive Analytics software helps organize data in a structured manner, making it easy to understand and present. It enables the user to analyze past, present, and future models using quality-tested algorithms. Automation of large-scale forecasts is also possible without the need for high levels of technical knowledge.
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Use the full potential of information to unleash the capability of the human resources of an organization.
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GoodData is a cloud-based platform with high SLA availability and maintenance. It allows for easy incorporation of already existing data warehouses. It allows the platform to be integrated into web or mobile applications. It is one of the most dominant cloud data warehouse that meets most versatile analytics platform requirements.
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Extensive set of cloud services that enables associations to address business problems, construct, oversee, and convey applications on a massive, worldwide system utilizing various tools and frameworks. Microsoft Azure ML Studio can be used to prepare and manage the data they need for machine learning. It can improve productivity through its powerful capabilities that can integrate the current model cycle with that of the app lifecycle.
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NTT Data offers effective solutions that supplement the decision-making process in an organization. This is possible across multiple business platforms and across different development and deployment capabilities. With the help of a comprehensive analytics and business insight methodology, NTT Analytics Solutions can change a client organization into an information-driven pioneer.
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Teradata predictive analytics software provides “Flip the Switch” analytics which allows on-the-fly switching of best campaign users from reverse modeling to forward prediction. Teradata Analytics for Enterprise Applications eradicates the complexity of enterprise application integration, delivers real-time access to integrated data from ERP and other enterprise applications, as well as provides transparency and visibility into business and customer insights.
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Qlik helps enterprises around the globe move quicker, work smarter, and provide a start-to-finish answer to get an incentive out of information. QlikView helps users compare different sets of data from multiple sources and locations to deliver the most value. Its main features include, interactive participation in session-sharing is possible across different groups which enables users to share their insights formally or informally. It is also possible to access and load data from different locations and from different deployment modes – cloud, on-premise, or big data sources.
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