Predictive Analytics Software Data

Reach companies using
predictive analytics software

Verified predictive analytics contacts for companies using SAS Analytics, IBM SPSS, DataRobot, Alteryx, RapidMiner, predictive modelling, forecasting, data science and machine learning analytics platforms.

  • Verified predictive analytics contacts
  • SAS, IBM SPSS and DataRobot users
  • Data scientist and analytics buyer roles
  • Free 100-record sample list
415k Verified Contacts
95% Accuracy Rate
60+ Countries
45 days Refresh Cycle
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100 verified predictive analytics contacts. Delivered in 24 hours.


predictive analytics software
Overview

What Is Predictive Analytics Software Data? 

  • 30+ CRM platforms covered
  • 95% deliverability guaranteed
  • Direct dials & verified emails
  • Refreshed every 90 days
  • GDPR & CCPA compliant
  • Ready-to-import CSV / CRM
  • Module-level segmentation
  • Free replacement guarantee
  • Verified predictive analytics software data
  • SAS, IBM SPSS, DataRobot & Alteryx contacts
  • ML modelling & forecasting platform data
  • Decision-maker contacts included
  • GDPR & CCPA-conscious B2B data
  • Ready-to-import CSV / CRM
  • Platform-level technographic segmentation
  • Free replacement guarantee
Data Includes

What information is included in the dataset?

Each record in our machine learning analytics platform users list is structured for sales, marketing, CRM, ABM, analytics consulting outreach and market research workflows.

Contact Name

Job Title and Seniority

Verified Business Email

Phone

Company Name and Website Domain

LinkedIn Profile URL

Industry and Business Sector

Revenue and Employee Size

City, State, Country and Region

Platform Used and Analytics Category

Who’s this for?

Built for AI, analytics and data growth teams

If your buyers use predictive analytics, data science, forecasting or machine learning analytics platforms, this dataset gives your team sharper campaign targeting.

  • AI and machine learning vendors
  • Analytics consultants and advisory firms
  • MLOps and AI governance providers
  • Data engineering firms
  • Cloud data and BI platforms
  • SaaS sales and analytics platform teams
  • ABM and demand generation teams
  • Market research and territory planning teams
Predictive Analytics Data Covered

15+ predictive analytics platforms. One database.

Filter by predictive analytics software, machine learning platform, region or company size and pull a clean list in minutes.

Predictive Analytics PlatformVerified ContactsCompaniesCoverageAction
Microsoft Azure Machine LearningPredictive #01
33.6k6.7kGlobalGet sample →
Amazon SageMakerPredictive #02
43.7k8.7kGlobalGet sample →
Google Vertex AIPredictive #03
12k2.4kGlobalGet sample →
SAS ViyaPredictive #04
5.4k1.1kGlobalGet sample →
IBM SPSS ModelerPredictive #05
2.9k575GlobalGet sample →
AlteryxPredictive #06
31.2k6.2kGlobalGet sample →
DataRobotPredictive #07
3k592GlobalGet sample →
DataikuPredictive #08
6k1.2kGlobalGet sample →
Databricks ML + LakehousePredictive #09
97.4k19.5kGlobalGet sample →
H2O.aiPredictive #10
2.5k509GlobalGet sample →
SAP Analytics CloudPredictive #11
15k3kGlobalGet sample →
Oracle Analytics CloudPredictive #12
27.2k5.4kGlobalGet sample →
Altair AI Studio RapidMinerPredictive #13
1.6k329GlobalGet sample →
Tableau Predictive + ML FeaturesPredictive #14
130k26kGlobalGet sample →
ThoughtSpotPredictive #15
4k799GlobalGet sample →
Predictive analytics data includes Microsoft Azure Machine Learning, Amazon SageMaker, Google Vertex AI, SAS Viya, IBM SPSS Modeler, Alteryx, DataRobot, Dataiku, Databricks, H2O.ai and more.
FAQs

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Predictive analytics software data is a verified B2B dataset of companies using predictive modelling, statistical analytics, machine learning analytics, forecasting, data science and advanced analytics platforms. It includes company details, decision-maker contacts, platform usage, industry, location and CRM-ready fields.
Yes. DiscoverMSPs can provide a SAS customers database based on your target industry, geography, company size, job title and campaign objective. This data is useful for analytics consulting, AI governance, model migration, risk analytics and data science campaigns.
Yes. Companies using SAS analytics can be targeted for predictive modelling, risk analytics, forecasting, fraud analytics, customer analytics, data science enablement, migration and cloud analytics campaigns.
Yes. IBM SPSS users list data can help vendors and consultants reach companies using SPSS for statistical analysis, predictive modelling, research analytics, survey data and behavioural insights.
Yes. DataRobot customers database segments can help AI vendors, MLOps providers and analytics consultants target companies using DataRobot for automated machine learning, predictive modelling, model deployment and AI governance.
Yes. Alteryx users contact list data can help vendors reach companies using Alteryx for data preparation, analytics automation, self-service workflows, reporting automation and predictive modelling.
Explore

Find predictive analytics data the way you sell

Switch between tabs to segment companies by analytics platform, machine learning workflow, industry, geography, company size, buyer role or campaign intent.

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12,000+ customers ISO 27001 certified GDPR compliant
The Complete Guide

Best Fit Use Cases for Predictive Analytics Software Data

A practical guide for B2B teams that need platform-specific predictive analytics, data science, machine learning, AI governance and advanced analytics targeting data.

Best fit use cases for predictive analytics data

This dataset is best suited for B2B teams that need platform-specific predictive analytics, data science and machine learning targeting. It helps sales, marketing, ABM and analytics outreach teams reach companies using predictive modelling software, statistical analytics tools, forecasting platforms and advanced analytics environments.

It is especially useful for predictive analytics software lead generation, SAS customers database targeting, companies using SAS analytics outreach, IBM SPSS users list campaigns, DataRobot customers database targeting, Alteryx users contact list outreach and RapidMiner customers database campaigns.

Teams can also use this data for data scientists email list B2B targeting, Chief Analytics Officer contact database outreach, machine learning analytics platform users list enrichment, companies using predictive modeling software targeting, MLOps and AI governance campaigns, analytics migration and modernisation campaigns, data engineering and AI-readiness outreach, partner recruitment, market research and territory planning.

How to use predictive analytics software data

Start by selecting your predictive analytics platform. Choose whether you want to target companies using SAS Analytics, IBM SPSS, DataRobot, Alteryx, RapidMiner, KNIME, H2O.ai, TIBCO Data Science or related predictive analytics platforms.

Next, select the analytics workflow you want to target, such as predictive modelling, statistical analytics, machine learning analytics, forecasting, risk scoring, fraud modelling, customer analytics, data preparation, data science automation or AI governance. Then define buyer roles such as Data Scientist, Chief Analytics Officer, Chief Data Officer, Analytics Manager, Data Science Manager, Machine Learning Engineer, BI Manager or Head of Data.

Finally, apply company filters by industry, employee size, revenue range, geography and company type. Use the final dataset for cold email, calling, LinkedIn outreach, ABM campaigns, partner recruitment, CRM enrichment, predictive analytics campaigns or market research.

Select your analytics platform

Choose the predictive analytics platform that matches your campaign goal, including SAS Analytics, IBM SPSS, DataRobot, Alteryx, RapidMiner, KNIME, H2O.ai, TIBCO Data Science or related advanced analytics software users.

Filter by workflow and buyer role

Narrow your list by analytics workflow such as predictive modelling, statistical analytics, machine learning analytics, forecasting, risk scoring, fraud modelling, customer analytics, data preparation, data science automation or AI governance, then select Data Scientists, Chief Analytics Officers, Chief Data Officers, Analytics Managers, Machine Learning Engineers and BI leaders.

Build and launch targeted outreach

Segment predictive analytics software data by industry, employee size, revenue range, geography and company type, then use the final dataset for cold email, calling, LinkedIn outreach, ABM campaigns, partner recruitment, CRM enrichment, predictive analytics campaigns and market research.

Why Predictive Analytics Platform Data Matters

Buyer Context

Predictive analytics buyers are not general data contacts. They are connected to business forecasting, data science, machine learning, statistical modelling, customer intelligence, risk analytics, operational optimisation and AI readiness.

SAS Users

A company using SAS Analytics may be focused on statistical modelling, enterprise analytics, risk analytics, forecasting, fraud analytics or industry-specific decisioning workflows.

IBM SPSS

A company using IBM SPSS may be managing statistical analysis, research analytics, survey data, predictive modelling and behavioural insights.

DataRobot

A company using DataRobot may be focused on AI model development, automated machine learning, model deployment, governance and predictive decisioning.

Alteryx

A company using Alteryx may be using analytics automation, data preparation, workflow automation and self-service analytics.

RapidMiner

A company using RapidMiner may be focused on machine learning workflows, predictive modelling, data mining and analytics process automation.

Better Outreach

Platform context helps your team align messaging with modelling environments, data science workflows, AI maturity, forecasting needs, model governance requirements, data preparation gaps and machine learning adoption roadmaps.

Questions buyers ask us most

Yes. RapidMiner customers database data can help vendors target companies using RapidMiner for machine learning, predictive modelling, data mining, analytics workflows and AI experimentation.
A data scientists email list B2B includes contacts responsible for predictive modelling, machine learning workflows, statistical analysis, data preparation, model development, analytics automation and AI initiatives.
A Chief Analytics Officer contact database includes senior analytics leaders responsible for analytics strategy, predictive modelling, data science adoption, AI readiness, platform selection, data governance and business decision intelligence.
A machine learning analytics platform users list includes companies using tools such as DataRobot, RapidMiner, SAS, Alteryx, IBM SPSS and related platforms for predictive modelling, machine learning, data mining and analytics automation.
Yes. DiscoverMSPs can help identify companies using predictive modeling software based on platform signals, industry, company size, geography and buyer role.
The data is usually delivered in CSV or Excel format and can be prepared for CRM, email outreach, sales engagement, ABM platforms or marketing automation systems.

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