How often ChatGPT mentions Vertex AI for predictive analytics software, and how it stacks up against the tools that dominate the answers.
Share of ChatGPT answers naming each tool, same 1 questions.
| # | Tool | Visibility | |
|---|---|---|---|
| 1 | Dataiku | 100% | |
| 2 | SAS Viya | 100% | |
| 3 | Alteryx | 100% | |
| 4 | DataRobot | 100% | |
| 5 | IBM SPSS Modeler | 67% | |
| 6 | Tableau | 67% | |
| 7 | Azure Machine Learning | 67% | |
| 8 | Amazon SageMaker | 67% | |
| 9 | Alteryx One | 67% | |
| 10 | Databricks | 33% | |
| 11 | IBM watsonx.ai | 33% | |
| 12 | Vertex AI ← this tool | 33% |
Free account, see every engine, the trend over time, and which sources to win.
The questions where ChatGPT currently names Vertex AI.
The “best” predictive analytics software depends on your use case (forecasting, customer behavior, fraud detection, marketing, operations, data science, etc.). These are among the strongest options in 2026: G2 G2 Learn Hub
| Software | Best for | Strengths |
|---|---|---|
| sas.com | Large enterprises, regulated industries | Advanced statistical modeling, forecasting, AI governance, explainable models |
| dataiku.com | Data science teams + business users | Collaborative ML workflows, AutoML, model deployment |
| datarobot.com | Automated machine learning | Quickly builds and compares predictive models without deep coding |
| azure.microsoft.com | Enterprise AI/MLOps | Scalable model training, deployment, monitoring |
| cloud.google.com | Cloud-based ML | End-to-end AI platform with forecasting and ML tools |
| aws.amazon.com | AWS environments | Managed ML development, deployment, and forecasting |
| alteryx.com | Analysts and low-code teams | Data preparation, automation, predictive workflows |
| tableau.com | Business intelligence + predictive insights | Strong visualization and analytics sharing |
| ibm.com | Enterprise AI platforms | AI model development, governance, integration |
| sap.com | SAP-centric companies | Planning, forecasting, and enterprise analytics |
G2 Zapier## Quick recommendations
If you tell me your industry, company size, data volume, and whether you need no-code vs. data-scientist tools, I can narrow this to the top 3 choices.