Crayon Data

What is Crayon Data?

Crayon Data is a global leader in B2B AI solutions, offering a full-stack, AI-native platform known as maya.ai. The company focuses on accelerating revenue growth and leveraging data value through expertise in external data and machine learning. With a strong international presence and a deep understanding of regional markets, Crayon Data provides personalized AI solutions tailored to individual business needs. Their platform is designed to be flexible, scalable, and secure, enabling businesses of all levels of maturity to implement AI solutions effectively. Overall, Crayon Data's cutting-edge technology and AI expertise have transformed how enterprises compete in the digital era.

Who created Crayon Data?

Crayon Data was founded by Suresh Shankar, who is a second-time entrepreneur with a focus on big data, analytics, and digital personalization. Suresh previously founded RedPill Analytics, which was later acquired by IBM. The company's co-founders include Aarti Ramakrishnan, who has extensive experience in marketing and analytics, especially in the BFSI domain, and Vijaya Kumar Ivaturi (IVK), a prominent expert in innovation management and advanced technologies incubation.

Who is Crayon Data for?

• Data Analyst
• Marketing Manager
• Business strategist
• Sales manager
• Product Manager
• Financial Analyst
• Customer Experience Manager
• IT Consultant
• Operations Manager
• Project Manager

How to use Crayon Data?

Here is a comprehensive step-by-step guide on how to use Crayon Data:

1. Data Studio: Start by visiting the Data Studio page on the Crayon Data website. This is where you can ingest, transform, and enrich your data to unlock its maximum value.

2. AI Studio: Explore the AI Studio section next. Here, you can build powerful AI use cases specifically designed for customer lifecycle management. This is a crucial step for leveraging AI capabilities within your data analysis.

3. Analytics Studio: Move on to the Analytics Studio area. In this section, you can create robust and fast analytics using ready-made metrics and visualization tools provided by Crayon Data. This step allows you to gain valuable insights from your data efficiently.

4. Implementation: After familiarizing yourself with the different studio sections, determine which studio best fits your current needs and objectives in data analysis and management.

5. Utilization: Once you have chosen the appropriate studio, start utilizing the tools and features provided within that studio to work with your data effectively.

6. Integration: Explore how the different studio components can integrate and complement each other to enhance your data processing and analysis capabilities further.

7. Optimization: Continuously optimize your usage of the Crayon Data tools by exploring new features, staying updated on best practices, and seeking support from the Crayon Data community if needed.

8. Feedback and Iteration: Provide feedback to Crayon Data on your user experience and suggest any improvements or additional features you would like to see. Iterate on your data analysis processes based on the insights gained through using the Crayon Data tools.

By following these steps, you can effectively utilize Crayon Data's suite of tools to enhance your data management and analysis capabilities.