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Best Predictive Analytics Software in 2024

What is Predictive Analytics Software?

Predictive analytics software is a tool that uses statistical algorithms and machine learning techniques to analyze historical data and make predictions about future events. It helps businesses and organizations identify patterns and trends in their data, and use them to make decisions about their operations, marketing strategies, and customer inte... Read Buyer’s Guideimg

Best Predictive Analytics Software

(Showing 1 - 10 of 20 products)

Most PopularNewest FirstTop Rated Products
Apigee

Apigee

Brand: Google

4.6img

4.6 out of 5

(0 user reviews)

Apigee is a world-class API management and predictive analytics software. It is an innovative software powered by Google for seamless and efficient opera... Read More About Apigee img

$20

Unifers AI

Unifers AI

Brand: Unifers

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Unifers AI is designed to streamline marketing processes and enhance customer engagement through intelligent automation and personalized communication stra... Read More About Unifers AI read review arrow

Price On Request

Duetto GameChanger

Duetto GameChanger

Brand: Duetto

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Duetto GameChanger is a cloud-based revenue management tool for hotels, casinos, and resorts, using real-time data and predictive analytics to optimize pri... Read More About Duetto GameChanger read review arrow

Price On Request

Attention Insight

Attention Insight

Brand: Attention Insight

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Attention Insight is a predictive analytics software that uses AI to analyze and predict user attention to digital content, helping businesses optimize the... Read More About Attention Insight read review arrow

$31 /Month

Pecan AI

Pecan AI

Brand: Pecan

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Pecan AI is a data science platform specializing in predictive analytics software, offering tools for advanced data analysis and modeling to derive insight... Read More About Pecan AI read review arrow

$950 /Month

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DataStories

DataStories

Brand: DataStories

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DataStories is a predictive analytics software that uses augmented analytics to create explainable insights and transform complex data into interactive sto... Read More About DataStories read review arrow

€267 /User/Month

Plat AI

Plat AI

Brand: Plat AI

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Plat AI is a data science platform that integrates predictive analytics software, offering robust data analysis and modeling tools to derive insights and e... Read More About Plat AI read review arrow

Price On Request

Conative AI

Conative AI

Brand: ConativeAI

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Conative AI is designed for e-commerce teams that connect inventory systems with marketing channels, enabling real-time management and optimization of inve... Read More About Conative AI read review arrow

$999 /Month

Runecast Analyzer

Runecast Analyzer

Brand: Runecast Solutions

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Runecast Analyzer is a complete Predictive Analytics Software designed to serve Startups, SMBs, SMEs and Agencies. This Predictive Analytics Software for... Read More About Runecast Analyzer img

Price On Request

Termus BRIDGE

Termus BRIDGE

Brand: ACCA

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With the help of TheBriNA (Thermal Bridges Numerical Analysis), users can quickly get the total calculation of a thermal bridge from a single drawing. It... Read More About Termus BRIDGE img

Price On Request

Last Updated on : 19 Dec, 2024

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Best Predictive Analytics Software FAQ’s

Software questions,
answered

SAP Predictive Analytics, Qlik Sense, Adobe Analytics and IBM Watson Studio are some noteworthy software solutions for predictive analytics.

The top predictive analytics software for marketing professionals are Improvado, Sisense, Looker, Tableau and Dataiku.

The purpose of predictive analytics tools is to examine historical data and analyze it to make predictions about future trends or outcomes.

Yes, SAP provides multiple predictive analytics tools that use statistical algorithms and machine learning to help companies in analyzing data and make accurate predictions about future events.

Yes, you can use Excel to do basic predictive analytics with the help of its built-in features like data analysis tool, pivot tables and regression analysis tool.

The three most common techniques used for predictive analytics are neural networks, regression and decision trees.

Buyer's Guide for Top Predictive Analytics Software

Found our list of Predictive Analytics Software helpful? We’re here to help you make the right choice and automate your business processes. Let’s discover some of the essential factors that you must consider to make a smarter decision!

  • What is Predictive Analytics Tool?
  • How Does Predictive Analytics Software Work?
  • Who Uses Predictive Analytics Software?
  • Why Use Predictive Analytics Software?
  • Key Features of Predictive Analytics Software
  • Benefits of Predictive Analytics Software
  • Latest Predictive Analytics Software Trends
  • Factors to Consider When Buying Predictive Analytics Software

What is Predictive Analytics Tool?

Predictive analytics is an additional category of advanced analytics that makes predictions about future events using historical data and statistical modeling. This analytics approach is used by numerous organizations for assessing risk, identifying opportunities, and forecasting business trends. They utilize predictive analytics software to analyze historical facts and current data for a much better understanding of their products and customers.

This extremely powerful tool makes analysis more accessible and easier for organizations plus it can even standardize or automate some repeated procedures like data preparation, data exploration, model validation, model training, and more. Moreover, thanks to an intelligent analytics engine, business or technical analysts might find it easier to conduct ad hoc analysis or other data research procedures.

How Does Predictive Analytics Software Work?

Predictive analytics software uses historical data to find out patterns and trends. Then the software uses this information to forecast future outcomes. Here are some basic steps involved in this entire process:

  • Collection of data: In the first step, the software collects all the relevant data. This information might come from a wide range of sources like sales data, customer data, social media data, and more.
  • Data cleaning & preparation: The next stage is to clean and prepare data for analysis. It might involve the removal of missing values, data formatting, and handling irregularities.
  • Data research: Once data preparation is complete, in the next stage you have to carefully analyze it to identify any trends and patterns. This process may involve visualizing data, doing statistical analysis, and finding relationships between different variables with the help of the machine learning method.
  • Model building: Then in the next step, you have to create a predictive model. In order to do this, you can choose a suitable algorithm and use historical data for model training.
  • Model authentication: After the model-building process, it is critical to properly validate it to ensure its accuracy and reliability. This could entail evaluating the model's overall performance using cross-validation procedures or testing it against fresh data.
  • Deployment: The predictive model can finally be utilized for creating predictions as per fresh data. This might involve integrating it with an application or larger system, such as a customer relationship system and e-commerce platform.

Who Uses Predictive Analytics Software?

Predictive analytics software is utilized by numerous organizations and industries like manufacturing, finance, healthcare, and more for gaining insights from collected data and making well-informed decisions.

  • Finance: This software is used in financial institutions for fraud detection, identifying risks, and monitoring customer behavior. It is also helpful in developing investment strategies and assessing creditworthiness.
  • Business & Marketing: Organizations use predictive analytics software to forecast sales, find potential clients and improve marketing initiatives. In order to stay ahead of the competition, it helps companies in identifying trends, customer preferences and opportunities.
  • Manufacturing: Predictive analytics software is utilized in the manufacturing sector for enhancing supply chain management, optimizing production schedules, and predicting equipment failures. It aids manufacturers in maximizing resource usage and locating production snags.
  • Healthcare: In the healthcare industry, this software is used for analyzing patient data, lower readmission rates, enhancing treatment protocols, and improving clinical outcomes. This software assists healthcare experts in the effective allocation of resources, managing chronic conditions and spotting high-risk patients.

Why Use Predictive Analytics Software?

Predictive analytics software is used for risk management, improving operations, boosting efficiency, and promoting personalized interactions with consumers.

  • Better decision-making: Software for predictive analytics will help your organization in making more informed decisions by offering critical insights about upcoming trends and consequences. You can improve your judgment about risk management, strategic planning, and resource allocation by using data to predict future events.
  • Improved efficiency: By using this software, your organization can improve operations, eliminate waste, boost efficiency, and enhance the overall process. It may lead to cost savings, increased profitability, and client satisfaction.
  • Personalized interaction: With the help of predictive analytics software, you can personalize your interactions with clients, boosting engagement and loyalty. After analyzing customer data, your organization can find out individual preferences that enable you to modify your sales and marketing strategies accordingly.
  • Risk management: Predictive analysis system can help you in identifying and mitigating risks before they turn into serious a problem. You can analyze the data to take proactive steps and reduce the likelihood of risks.

Key Features of Predictive Analytics Software

A few noteworthy features of predictive analytics software are scalability, ease of use, automatic procedures and many more. Let’s look at these features in more detail.

Let’s look at some noteworthy features of predictive analytics software

  • Unified Platform: Predictive analytics tools let you converge the capabilities of numerous tools into one single platform. It empowers you to remove obstacles to enterprise-wide data analysis and insights.
  • Easy to Use: Faster data preparation, analysis, blending, and interpretation using thousands of no-code and low-code analytical components.
  • Scalable: This software allows you to scale data preparation and automated analytical procedures across hybrid, cloud, and on-premises sources.
  • Automate procedures: Some predictive analytics tools allow you to automate all analytical steps that include predictive analytics, data science, reporting, blending, and data preparation.
  • Enterprise Grade: The latest analytics software uses the most recent security certifications and standards to minimize risk and guarantee complete data protection. You can connect to your applications as well as data via open API standards.
  • Time-saving: Manual analysis is a time-consuming task, but in predictive analytics software you just have to perform a handful of actions to get the desired results at a lightning-fast speed.
  • Easy to use: There must be numerous users who are not familiar with different algorithms and models. Such users can also utilize predictive analytics tools to know about their business's future and make changes as per requirement.

Benefits of Predictive Analytics Software

Predictive Analytics Software offers a plethora of benefits, some of the key advantages include:

  • Competitive benefit: Using a predictive analytics tool empowers you to stay ahead of the latest trends and understand your customers’ requirements. It gives your business a competitive advantage, produces better goods & services, runs more successful sales & marketing efforts, and expands the market share.
  • Innovation: The predictive analytics tool can assist your businesses in finding newer chances for expansion and development. By analyzing data and understanding market trends, you can create cutting-edge products and services that fulfill the shifting requirements of your customers.
  • Predictive Maintenance: Companies in asset-based industries can use this software for forecasting and budgeting for maintenance purposes. This is accomplished by collecting and analyzing data produced by equipment, allowing you to decrease the unnecessary expenses for preventive maintenance, avert downtime and increase the lifespan of your products. 
  • Determine profitable customers: It is critical for your company to determine the customers who spend the maximum amount, which results in long term profits in the business. This high level of insights is only possible with the help of predictive analytics, enabling your business to maximize the marketing budget and concentrate all the efforts on attracting consumers who'll generate the most profit and will ultimately have the best lifetime values.
  • Fraud detection: You can use predictive analytics tools to identify patterns to spot and prevent illegal activities. It helps in the identification of abnormalities that could lead to cyberattacks and other vulnerabilities. This assists your business in putting adequate policies in place to protect critical data and information from fraud and various online threats.

Latest Predictive Analytics Software Trends

Numerous trends are currently shaping the predictive analytics industry. Some of the prominent trends in this domain are:

  • Artificial Intelligence: Many businesses have been revolutionized by new age technologies such as artificial intelligence, machine learning, automation, robotics, and so on. Data analytics is growing at a rapid rate with AI and it is unlocking new business opportunities by forecasting customer demand. AI is also improving inventory stocking levels along with the improvement in the transit process. In recent times, we have seen a big boost in the growth of scalable and clever ML and AI techniques that are fully capable of handling small data sets, unlike conventional techniques.
  • Data democratization: Regardless of your technical expertise, data democratization can be used to empower you to comfortably interact with data and make better business decisions. Thanks to data democratization, even non-technical users can gather and analyze their data without any assistance from system administrators, data stewards, or IT staff. Owing to prompt access to data and its effective comprehension, your team can take much faster decisions. Moreover, when it comes to handling big data and utilizing its potential, a democratized data environment is of utmost importance.
  • Data-as-a-Service (DaaS): Data-as-a-service or DAAS is a cloud-based tool that can be used for analyzing and managing data. It offers business intelligence as well as data warehouses that can be used from anywhere in the world. It is estimated that DaaS will witness rapid growth and reach as an industry in the coming years. The usage of DaaS will make it easier for analysts to review bulk data and allow its seamless sharing across multiple departments and industries. Soon, DaaS will become a more common and significant method for managing, analyzing, integrating, and storing data.

Factors to Consider When Buying Predictive Analytics Software

Let's look at the four key considerations to look for while investing in predictive analytics software for your business:

  • Quality: While using predictive analytics, it is difficult to be 100% accurate all the time. The quality of predictive analytics will be the main difference between accurate and inconsistent predictions. If you want to build a precise and reliable learning model, then you should look for vendors that have put their time and effort into ensuring the sustainability of their machine-learning algorithms. They must also have an excellent track record with clients in similar industries as yours.
  • Application: When you have a better understanding of the application for your predictive analytics tool, it'll give you a clear understanding of which solution provider can best suit your requirements. You must ask providers about their expertise in this domain and how they have assisted their customers with preventive maintenance systems. If the software requires the maximum number of existing programs to be reworked, then you must consider if it's worth the investment or not.
  • Integration: Integration is one of the key factors when choosing a predictive analytics tool for your business. You should look for a solution that can easily integrate with future technological add-ons as well as simpler upgrade paths. As technological advancements are happening at a rapid rate, being ready for any upcoming technology should be your utmost priority.
  • Cost: Lastly, the price of your software will always play a crucial role in choosing the perfect solution. The actual cost of the software, additional costs, insurance, and subscriptions, all these factors need to be analyzed with your budget. Comparing different predictive analytics tools will give you a clear picture of what you can expect from your current budget and it will also allow you to adjust your budget and expectations accordingly. Moreover, you should also not rule out the idea of spending more money on a comprehensive software system.

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