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Which data do I need Listed MSPs Why choose us Build a segment Why it is normally slow Is the data good? FAQAI & ANALYTICS · TECHNOLOGY USERS EMAIL LIST
Verified predictive analytics contacts for companies using SAS Analytics, IBM SPSS, DataRobot, Alteryx, RapidMiner, predictive modelling, forecasting, data science and machine learning analytics platforms.
100 verified predictive analytics contacts. Delivered inside two business hours.
THERE IS NO PUBLIC TECHNOLOGY SAMPLE · NAMES, CONTACTS AND YOUR FILTERED COUNT COME WITH THE FREE SAMPLE
Each record in our machine learning analytics platform users list is structured for sales, marketing, CRM, ABM, analytics consulting outreach and market research workflows.
WHY PREDICTIVE ANALYTICS PLATFORM DATA MATTERS
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.
A company using SAS Analytics may be focused on statistical modelling, enterprise analytics, risk analytics, forecasting, fraud analytics or industry-specific decisioning workflows.
A company using IBM SPSS may be managing statistical analysis, research analytics, survey data, predictive modelling and behavioural insights.
A company using DataRobot may be focused on AI model development, automated machine learning, model deployment, governance and predictive decisioning.
A company using Alteryx may be using analytics automation, data preparation, workflow automation and self-service analytics.
A company using RapidMiner may be focused on machine learning workflows, predictive modelling, data mining and analytics process automation.
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.
CUT BY FIELDS ON EVERY RECORD
CUT BY PLATFORMS COVERED
CUT BY BUILT FOR AI, ANALYTICS AND DATA GROWTH TEAMS
FIG. 1 The ways a technology user record can be segmented, as described on this page. Name the cut you need and a data specialist builds it into your free sample.
Filter by predictive analytics software, machine learning platform, region or company size and pull a clean list in minutes.
| Platform | List | Contacts | Companies | Coverage |
|---|---|---|---|---|
| Microsoft Azure Machine Learning | Microsoft Azure Machine Learning Users Email List | 33.6k | 6.7k | Global |
| Amazon SageMaker | Amazon SageMaker Users Email List | 43.7k | 8.7k | Global |
| Google Vertex AI | Google Vertex AI Users Email List | 12k | 2.4k | Global |
| SAS Viya | SAS Viya Users Email List | 5.4k | 1.1k | Global |
| IBM SPSS Modeler | IBM SPSS Modeler Users Email List | 2.9k | 575 | Global |
| Alteryx | Alteryx Users Email List | 31.2k | 6.2k | Global |
| DataRobot | DataRobot Users Email List | 3k | 592 | Global |
| Dataiku | Dataiku Users Email List | 6k | 1.2k | Global |
| Databricks ML + Lakehouse | Databricks ML + Lakehouse Users Email List | 97.4k | 19.5k | Global |
| H2O.ai | H2O.ai Users Email List | 2.5k | 509 | Global |
| SAP Analytics Cloud | SAP Analytics Cloud Users Email List | 15k | 3k | Global |
| Oracle Analytics Cloud | Oracle Analytics Cloud Users Email List | 27.2k | 5.4k | Global |
| Altair AI Studio RapidMiner | Altair AI Studio RapidMiner Users Email List | 1.6k | 329 | Global |
| Tableau Predictive + ML Features | Tableau Predictive + ML Features Users Email List | 130k | 26k | Global |
| ThoughtSpot | ThoughtSpot Users Email List | 4k | 799 | Global |
If your buyers use predictive analytics, data science, forecasting or machine learning analytics platforms, this dataset gives your team sharper campaign targeting.
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.
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
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 ca
A practical guide for B2B teams that need platform-specific predictive analytics, data science, machine learning, AI governance and advanced analytics targeting 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.
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.
Straight answers about how the data is built, checked and delivered.
Predictive analytics software users 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.
Yes. The Azure Machine Learning customers list is a cut of this data, with the people who own predictive models. If the product is niche or legacy, the free 100-record sample shows how many companies we can confirm before you buy anything.
QUESTIONS THAT BRING BUYERS TO THIS PAGE, ANSWERED PLAINLY
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.
Tell us the platform, the industry and the market. We send 100 verified records to judge before you buy.
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