Achieving your Best Possible Assessment in the Data Science and Machine-Learning Platforms* (DSMLP) Magic Quadrant (MQ)
Getting your company recognized in the DSMLP Magic Quadrant can reap huge rewards for your business and help grow your sales pipeline. But it isn’t easy.
If you can answer yes to any of these questions:
- Are your competitors getting better results — even when their product is inferior?
- Are you struggling to ‘move the dot’ in your MQ?
- Do your references seem to say something different when they talk to you and the analysts?
- Do you want your business or company listed in the next version of this MQ?
We can help you, this is what we specialize in
We are a team of former senior Gartner analysts who’ve written and reviewed hundreds of Magic Quadrants such as the Data Science and Machine-Learning Platforms MQ. We have an in-depth understanding of the factors for Magic Quadrant success and are uniquely placed to give tangible advice that will add value when responding to the DSMLP Magic Quadrant.
Our clients tell us that we really help them in this area.
“Anne provided a great evaluation of our previous year’s submissions to Gartner and provided concrete suggestions on how we could improve it. Anne was also a key member of the team that developed our strategy on how to best craft our submission this year.”
We often hear these challenges and understand that it can be really frustrating
How we help?
- Use our extensive experience as former Gartner analysts to make sure your Data Science and Machine-Learning Platforms Magic Quadrant responses are the best they can possibly be to ensure success. See: Move the dot in the right direction.
- Deliver the best possible submission, by delivering a best-practice-driven survey response, a best ever briefing by delivering a differentiated essential story, backed up by evidence, great references and, as appropriate, a memorable focused demo.
- Make sure your references actually improve the result.
- Get the analyst to see your company/product/service as it is today and not as it was in the past. More: How to improve analyst engagement.
- Clarify and articulate your company’s vision in a way that aligns to the way in which vision is measured by Gartner.
- Get your company into the Magic Quadrant for the first time.
See what some of the companies listed in the latest version of the DSMLP Magic Quadrant are saying about it
Companies listed in the Data Science and Machine-Learning Platforms Magic Quadrant include: Altair, Alteryx, Anaconda, Databricks, Dataiku, DataRobot, Domino, Google, H2O.ai, IBM, KNIME, MathWorks, Microsoft, RapidMiner, SAS, TIBCO Software.
Access the Magic Quadrant document
Magic Quadrant for Data Science and Machine-Learning Platforms
*Before 2017 Gartner evaluated these vendors and solutions under the name of the Magic Quadrant for Advanced Analytics Platforms (AAP). In 2017 the name changed to Data Science Platforms (DSP). In 2018 the term “Machine Learning” was added.