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Table of Contents

• What is Predictive Analytics Software?
• The benefits of Predictive Analytics Software
• Typical features of Predictive Analytics Software
• The cost of Predictive Analytics Software
• Considerations when buying Predictive Analytics Software

What is Predictive Analytics Software?

Predictive Analytics Software enables businesses to understand customers, products, and best practices for their industry, along with potential opportunities and risks. The software analyzes historical data sets to predict future sales trends and patterns.

Predictive analytics tools allow marketers to identify emerging customer bases, improve lead scoring, customer engagement, and conversions through personalized marketing, and effectively utilize the marketing budget. The tool utilizes different techniques, such as statistical analysis, textual analysis, and machine learning algorithms, that help a data scientist analyze data and predict outcomes.

The benefits of Predictive Analytics Software

Predictive analytics software is being used increasingly by businesses across different industries to grow their sales, enhance customer satisfaction, and gain a competitive advantage. Here are some common benefits of using a predictive analytics solution.

• Facilitates personalized and targeted marketing: A predictive analytics tool enables marketing teams to create customer segments based on different parameters, such as online activity, buying habits, age bracket, and occupation. It also enables them to uncover patterns in consumer behavior and predict customer intent. All these insights allow marketers to understand customer information at a granular level and personalize their marketing strategies accordingly.
• Streamlines inventory management: Poorly managed inventory can often lead to a decline in customer satisfaction, depleted margins, and productivity losses. Predictive analytics software utilizes real-time and historical data to streamline supply chain operations. The cloud-based software forecasts stock levels, consumer demand, inventory distortion, and sales trends. This allows retailers and inventory managers to prevent stock-outs, reduce storage costs, and optimize deliveries.
• Improves decision-making: Predictive analytics solution processes a large volume of data and offers actionable insights into the efficiency of business processes, including sales, marketing, and customer services. By offering detailed information about business data and creating future predictions, the tool enables business owners and department heads to make quick and assertive business decisions and grow their revenue.

Typical features of Predictive Analytics Software

• Artificial intelligence (AI) and machine learning (ML): Uses AI and ML algorithms to analyze big data sets and predict future outcomes.
• Data clustering: Identifies items with similar characteristics in a data set and groups them together to facilitate comparison and prediction.
• Data discovery: Applies advanced analytics techniques, such as statistical analysis, data mining, and sentiment analysis, to gain actionable insights, identify patterns, and gain the most out of the available business data.
• Data visualization: Provide multiple data visualization options, such as graphs, charts, and reports to facilitate interpretation.
• Decision support: Enables businesses to make timely and appropriate decisions based on real-time predictive insights.
• Forecasting: Uses data to predict the possible demand, sales, and financial future outcomes.
• Multiple data sources: Analyzes transactional and customer data derived from a variety of data sources, including internal and external data sources, such as user interactions, campaign histories, and social media channels.
• Trend analysis: Predicts future market and consumer trends based on current and historical data.

The cost of Predictive Analytics Software

Most products in the market are priced on a per-month basis and can be divided into three pricing tiers based on their starting price.

Price ranges:*

• $55–$86
• $87–$450
• $450+

*The pricing included is for the entry-level/lowest-priced offering found on vendor websites on September 27, 2022. These ranges correspond to the 25th, 75th, and 100th percentiles of pricing information gathered from vendor websites of sample products.

The above list summarizes pricing for the base plans of most products. An enterprise or premium product that is priced higher may include additional features such as natural language processing, time series analysis, and workflow management.

Considerations when buying Predictive Analytics Software

Here are some common considerations that you can keep in mind before investing in the best predictive analytics tool for your business.

• Specific business requirements: Predictive analytics tools can be used across varied industries. Before shortlisting predictive data analytics solutions for your business, make sure to understand your specific use cases and the features you would want in an analytics solution. For instance, if you are a retail business owner, you would need a cloud-based data analytics tool that is able to segment customers based on their behavior or demographics, streamline supply chain management, and manage marketing campaigns. For this, you would want the software to have necessary features such as trend analysis, action alerts, and data mining.
• Ability to extract data from multiple sources: Before you invest in a predictive analytics solution, make sure that the software is able to gather and analyze big data from multiple internal and external sources, such as customer surveys, interviews, organization records, polls, and government databases. The ability to compile data from different sources onto a single dashboard will provide you with a complete overview of your business performance.
• Text mining capabilities: Text mining is an important feature that you should look for in a predictive analytics tool. An ideal predictive analytics software solution is capable of transforming unstructured text in documents and databases into structured and understandable data using AI and natural language processing. This will help you analyze data held in spreadsheets, emails, documents, and social media posts.