6 Best Predictive Analytics Tools (2023)

Struggling to generate sales? Want to get a better return on ad spend? Here are the best platforms to forecast business outcomes to optimize your performance.

Everyone says data is king. 

But they’re wrong.

Data alone isn’t enough to help businesses move forward.

It’s understanding the data and knowing how to use it that help businesses grow.

Predictive analytics tools are essential to understanding and using your business data to help you see what the future holds.

This type of software helps you leverage the power of historical (and current) data to understand trends, forecast incoming revenue, and optimize marketing strategies.

In this guide, we’ll break down the six best predictive analytics platforms on the market today so you can decide on the right one for you and your business goals.

What are predictive analytics tools?

Before we break down the different tools, let’s look at predictive analytics and its impact on marketing and business growth strategy.

Predictive analytics is the practice of using present and past data to predict business outcomes.

The process of predictive analytics combines a variety of methods, including statistical techniques and advanced analytics, in order to forecast marketing performance, forecast demand, optimize campaigns, retain customers, cross-sell products, and more.

Keep in mind — predictive analytics tools aren’t prophetic. They can’t offer guaranteed outcomes. What they can do is offer reliable probabilities of results.

As a single part of the greater advanced analytics game, predictive analytics uses statistics and machine learning to forecast a specific event’s likelihood. 

While mathematics and data science are the building blocks of predictive analytics, many modern predictive analytics platforms like Pecan AI don’t require users to be data scientists. 

Most predictive analytics tools are both advanced enough that data scientists can get the most out of them and simple enough that business people without a data background can understand the predictions to make effective business decisions.

Advantages of using a predictive analytics tool

Did you know that experts think the predictive analytics market will reach $67.66 billion by 2030? The global market is growing at a compound annual growth rate (CAGR) of 24.4 percent.

There’s no doubt this type of prediction software is becoming an increasingly important part of business strategy.

The question is: What are the benefits of leveraging predictive analytics software?

1. Understand customer behavior

To grow your business, you need to reach your target market effectively. But if you don’t know your audience, your competitors who do know them will win them over.

One of the biggest benefits of using predictive analytics software is that you’ll understand your customers better. By leveraging historical data through a platform, you’ll gain insights into your customers’ behaviors and how those behaviors change throughout the customer journey.

With that knowledge, you’ll be better able to spot potential roadblocks and objections to your marketing and customer engagement efforts so you can improve your strategy.

2. Unlock opportunities to increase sales

By leveraging historical data, a predictive analytics platform can help you identify products and services your customers have bought from you in the past to help predict what they’ll need in the future.

Understanding past purchase behavior can help you see which customers are most likely to be interested in upsell and cross-sell offers to provide more value, generate repeat purchases, and improve average order value.

3. Optimized lead segmentation

Predictive analytics software isn’t just about understanding your customers to get more out of them. It’s also about gaining insight into prospects and leads so you can convert more of them into customers.

Business teams can use a predictive analytics platform to identify leads more likely to convert based on past data. This can help them optimize strategy and resource allocation for the best possible results.

4. Improved ROI

Predictive analytics tools can be a great way to convert more leads into customers, encourage repeat purchases, and increase average order value. You can also use them to reduce your churn rate so customers stay customers longer.

Ultimately, one of the key objectives of using predictive analytics is to improve the lifetime value (LTV) of customers. Since you can use predictive analytics to get customers to spend more during their time with you, it can give you a greater return on investment (ROI) on your investment in acquiring customers and retaining them.

5. Improved operations

Leveraging predictive analytics software doesn’t just have monetary benefits like improved revenue, ROI, and profitability. It’s also a great way to improve your operational efficiency.

By integrating predictive analytics into your day-to-day business processes, you’ll be able to make better decisions to prioritize the actions that will yield the best outcome. The result is that your organization will be focused on high-impact actions, improving your team’s overall productivity.

6 best predictive analytics tools

This section will look at six of the best predictive analytics platforms you can use to kickstart or upgrade your predictive analytics journey.  

We’ll describe what each predictive analytics software can do for its users, the key features and integrations, and the pros, cons, and pricing so you can find the software that’s right for you.

Tool #1: Pecan

Pecan is an AI-driven predictive analytics platform that helps marketing, sales, and operations teams predict business outcomes. Founded in 2018, the low-code predictive analytics and data science platform enables organizations to leverage the full power of AI and predictive modeling without requiring a data scientist.

Pecan.ai dashboard for optimizing marketing spend.

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Why Pecan AI: Pecan is the leading low-code predictive analytics solution. While most predictive analytics platforms require a development team to allow them to function, Pecan enables non-techies to forecast business outcomes with ease.

Pecan AI features include predictive return on advertising spend (ROAS), AI-driven predictive analytics, automated data prep, predictive model building, model monitoring, and actionable predictions for specific business goals, as well as customizable templates for predictive models like conversion, LTV, and customer churn.

Pecan AI integrations include Salesforce, Oracle, Snowflake, Amazon S3, IBM Db2, Singular, AppsFlyer, Firebase, Adjust, Google BigQuery, PostgreSQL, and Microsoft SQL Server.

Pricing: From $50 per month with a 14-day free trial.

What it’s great at:

  • Fast modeling and data integration
  • AI automates several predictive analytics processes
  • Low-code interface is great for non-techies or small teams
  • Easy predictive model implementation
  • Automated data prep, model building, deployment, feature engineering, and model monitoring
  • No need for an in-house data scientist
  • Customizable model templates
  • Hyper-specific predictions for goals

Areas of limitation:

  • Dashboard can take some getting used to
  • Higher starting price point

Tool #2: Qlik Sense

Qlik Sense is a data science tool that’s also great for predictive analytics. Founded in 1993, the software can quickly generate machine learning models and explore several “what-if” scenarios with its code-free user interface.

Qlik Sense operations

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Why Qlik Sense: Qlik is a great tool for anyone who doesn’t have any coding experience. Small business owners and enterprise organizations can use it to conduct experiments and mine data to identify key drivers in your models. 

Qlik Sense features include augmented analytics, advanced AI modeling, smart visualization, a mobile app, flexible APIs, self-service analysis creation, and alerts for data changes.

Qlik Sense integrations include Databricks, MongoDB, RowShare, Smartsheet, Snowflake, SysAid, Amazon Web Services, and TOPdesk.

Pricing: From $20/month with a 30-day free trial.

What it’s great at:

  • Interface is easy to use
  • Plenty of customization options
  • Quick to implement
  • Enterprise option available
  • Industry-specific solutions

Areas of limitation:

  • Data modeling is limited
  • Navigation could be improved

Tool #3: SAS Advanced Analytics

SAS is a global software company founded in 1976. Headquartered in North Carolina, the company offers a variety of predictive analytics tools, including SAS Advanced Analytics. This software generates models for future probabilities of outcomes.

SAS Advanced Anaytics

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Why SAS Advanced Analytics: The tool offers marketing leaders and data scientists a robust infrastructure of analytics features to run quick simulations and get quick results. The platform offers coding and no-code predictive analytics, depending on your level of expertise. It’s great for new organizations and those scaling that need an option that grows with them.

SAS Advanced Analytics features include data mining, data analysis, data interactions, scripting tools, data governance that tracks data and model lineage for simple data retraining, data visualizations, knowledge base, and report generation.

SAS Advanced Analytics integrations include open-source integrations via various APIs, allowing you to align the software with your current technology setup.

Pricing: Upon request, with a 14-day free trial.

What it’s great at:

  • Can process large amounts of data
  • Great for data exploration
  • Can build machine learning algorithms
  • Easy to use once set up

Areas of limitation:

  • Quite expensive
  • Can take some time to set up

Tool #4: Oracle Crystal Ball

Oracle is one of the biggest software companies in the world, known for its wide array of products. The software conglomerate’s predictive analytics solution is called “Crystal Ball” and is great for simulating spreadsheet models.

Oracle Crystal Ball

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Why Oracle Crystal Ball: If you like spreadsheets, then you’ll love Crystal Ball. Oracle designed it to be an exhaustive spreadsheet app for forecasting, optimization, and simulation. The tool is excellent for helping marketing leaders predict campaign outcomes through various spreadsheets.

Oracle Crystal Ball features include data visualizations, OptQuest developer kit, data unification, data interactions, report generation, time series forecasting, optimization, and Monte Carlo simulations. 

Oracle Crystal Ball integrations include Excel.

Pricing: Single purchase of $1,100 ($410 for students or faculty) with a free trial.

What it’s great at:

  • Great for spreadsheet users
  • Variety of templates available
  • Classroom edition for the academic community
  • User-friendly interface
  • Low barrier to entry
  • Easy-to-read data visualization

Areas of limitation:

  • Excel version crashes occasionally
  • UI looks a bit outdated for some users

Tool #5: Alteryx

Alteryx is an all-in-one, self-service predictive analytics platform with robust forecasting and automation features. Founded in 1997, the predictive analytics solution serves thousands of customers worldwide, including Netflix, Salesforce, P&G, and Nestle.

Alteryx dashboard.

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Why Alteryx: Alteryx delivers end-to-end automated analytics, data science processes, and machine learning to help businesses unlock hidden business and marketing insights to build reliable predictions. The platform is great at pulling data from multiple sources and tools to give teams business insights without needing coding experience.

Alteryx features include automated machine learning model creation, advanced analytics with built-in Python integration, visual text mining, NLP capabilities, drag-and-drop data prep, code-free automation building blocks, cleaning and blending data, and data extraction from structured and unstructured sources. Some of these features require additional paid upgrades and are not included in the core Alteryx Designer software.

Alteryx integrations include Amazon S3, Google BigQuery, Snowflake, Shopify, Salesforce, JSON, Excel, Google Analytics, HubSpot, Facebook Ads, and Mailchimp.

Pricing: From $4,950/user/year for the Designer version with a 30-day free trial.

What it’s great at:

  • Over 80 native integrations
  • No coding experience necessary
  • Easy to use
  • Variety of macros to automate processes
  • Active Alteryx support community

Areas of limitation:

  • Very expensive compared to other tools
  • Requires manual data cleansing for best results
  • Not the best data visualization
  • Some bugs

Tool #6: Tableau

In 2003, Stanford researchers created Tableau as a result of a computer science project. The web and cloud-based predictive analytics tool is designed to offer data-driven experiences and insights to help you optimize your strategy through data visualization.

Tableau dashboard.

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Why Tableau: Tableau is a data visualization solution for a variety of users — from freelancers to enterprise organizations. It also includes some predictive analytics capabilities, drawing on parent company Salesforce’s Einstein AI. 

Tableau features include data visualization and interpretation, big data services, collaboration tools, automated modeling, data discovery, desktop tools, cloud tools, reports interface and dashboard, and on-premises servers.

Tableau integrations include Amazon Redshift, Vertica, PostgreSQL, Splunk, Salesforce, Snowflake, Google Analytics, Amazon Athena, Google BigQuery, and Hive.

Pricing: From $15/month with a 14-day free trial.

What it’s great at:

  • Visual data is easy to understand
  • Easily accessible through any device
  • Easy drag-and-drop builder
  • Quick insights

Areas of limitation:

  • Steep learning curve
  • Mobile app has limited features

Leverage AI to take your predictive analytics to the next level

If you’re struggling to optimize critical business outcomes in marketing, supply chain, sales, or elsewhere in your organization, predictive analytics can be a game changer.

Predictive analytics tools help you understand your audience and your business activities better so you can determine what actions are bringing the most value to your audience and your organization.

By understanding what’s to come through predictive analytics, you can optimize your marketing campaigns, better allocate resources, and improve your overall performance.

While we discussed the top tools available today, it’s crucial your chosen software is compatible with your goals, budget, and data infrastructure.

If you’re looking for an AI-driven predictive analytics platform that doesn’t require data scientists or developers, then you’ll want to check out Pecan AI.

Marketing leaders can leverage Pecan for marketing mix modeling and predictions to forecast customer churn, foresee customer lifetime value, and optimize marketing campaigns to maximize revenue. With Pecan, you can quickly build AI models to foresee your customers’ future actions so you can proactively plan out campaigns.

Sign up for a 14-day free trial of Pecan today.