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Maze VS Plotly

Compare Maze VS Plotly and see what are their differences

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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

Maze logo Maze

Beautiful & actionable analytics for InVision prototypes

Plotly logo Plotly

Low-Code Data Apps
  • Maze Landing page
    Landing page //
    2023-10-10
  • Plotly Landing page
    Landing page //
    2023-07-31

Maze features and specs

  • Ease of Use
    Maze provides an intuitive and user-friendly interface, making it accessible to designers and researchers with varying levels of expertise.
  • Comprehensive Analytics
    The platform offers detailed analytics and actionable insights, helping users make data-driven decisions for improving their designs.
  • Fast Feedback
    Users can quickly obtain feedback from testers thanks to Maze's rapid testing capabilities, which helps accelerate the design iteration process.
  • Integration Capabilities
    Maze seamlessly integrates with tools like Figma, Sketch, and Adobe XD, allowing users to directly import their prototypes for testing.
  • Remote Usability Testing
    The platform supports remote usability testing, enabling teams to gather insights from a wider audience without geographic constraints.
  • Collaborative Features
    Maze includes collaborative features that allow team members to work together, share feedback, and streamline the design process.

Possible disadvantages of Maze

  • Pricing
    Some users may find the pricing model expensive, especially for smaller teams or individual designers.
  • Learning Curve for Advanced Features
    While the basic functions are easy to use, there may be a learning curve associated with mastering the more advanced features and analytics.
  • Limited Free Plan
    The free plan comes with limitations in terms of the number of responses and available features, which may not meet the needs of all users.
  • Internet Dependency
    Since Maze is a cloud-based tool, an uninterrupted internet connection is required, which could be a drawback in areas with unstable connectivity.
  • Customization Limitations
    Some users may find the level of customization for test questions and workflows to be limited compared to other, more advanced UX research tools.

Plotly features and specs

  • Interactivity
    Plotly offers highly interactive plots that allow users to pan, zoom, and hover over data points for more information. This enhances the user experience and provides deeper insights.
  • High-quality visualizations
    It provides aesthetically pleasing and highly customizable charts, making it suitable for publication-quality visuals.
  • Versatility
    Plotly supports multiple chart types including line charts, scatter plots, bar charts, and 3D plots, making it suitable for a wide range of applications.
  • Python integration
    Plotly is well-integrated with Python and works seamlessly with other popular data science libraries like Pandas, NumPy, and Scikit-learn.
  • Web-based
    The plots can be easily embedded in web applications or dashboards, making it ideal for sharing insights over the internet.
  • Open-source
    Plotly offers an open-source version, which allows users to create and share visualizations without any cost.

Possible disadvantages of Plotly

  • Performance
    Rendering very large datasets can sometimes be slow, which may not be suitable for real-time data visualization requirements.
  • Learning curve
    Even though the library is well-documented, the extensive range of features can have a steep learning curve for beginners.
  • Cost for advanced features
    While the basic functionality is free, more advanced features, such as export to certain formats and additional customizable options, require a paid subscription.
  • Dependency management
    Plotly has a number of dependencies that need to be managed properly, which can sometimes complicate the setup process.
  • Complexity
    For simple visualizations, Plotly might be overkill and simpler libraries like Matplotlib or Seaborn could be more appropriate.

Analysis of Plotly

Overall verdict

  • Overall, Plotly is a strong choice for those looking to create dynamic and interactive data visualizations, thanks to its range of features and ease of integration with web technologies.

Why this product is good

  • Plotly is considered good because it offers a comprehensive suite of tools for creating interactive visualizations that can be used in web applications, reports, and dashboards. It supports many different types of plots, is easy to use for both beginners and experienced developers, and integrates well with popular programming languages like Python, R, and JavaScript.

Recommended for

    Plotly is recommended for data scientists, analysts, and developers who need to create interactive and visually appealing data visualizations. It's particularly useful for those who work with Python or R and want the ability to embed their visualizations in web applications or dashboards.

Maze videos

+ Add

The Maze Runner - Movie Review

More videos:

  • Review - Circuit Maze Review - with Tom Vasel
  • Review - Magic Maze Review - with Tom Vasel

Plotly videos

+ Add

Create Real-time Chart with Javascript | Plotly.js Tutorial

More videos:

  • Review - Introducing plotly.py 3.0
  • Review - Is Plotly The Better Matplotlib?
  • Tutorial - Plotly Tutorial 2021
  • Review - Data Visualization as The First and Last Mile of Data Science Plotly Express and Dash | SciPy 2021

Category Popularity

0-100% (relative to Maze and Plotly)

Maze

Plotly

User Experience
100 100%
User Experience
0% 0
Data Visualization
0 0%
Data Visualization
100% 100
Design Tools
100 100%
Design Tools
0% 0
Charting Libraries
0 0%
Charting Libraries
100% 100

User comments

Share your experience with using Maze and Plotly. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Maze and Plotly

Maze Reviews

7 Best Product Discovery Tools for High-Growth B2B SaaS Teams (2026)
Maze is a specialist tool for rapid prototyping and unmoderated user testing. It allows product teams to turn Figma designs into interactive "missions" to collect quantitative data (misclick rates, heatmaps, and completion times) before writing a single line of code.
Source: www.laneapp.co
Crowd vs Maze: A Comprehensive Comparison of User Research Platforms
Thinking of hopping on Maze and a secondary user feedback that might cost you over $150 monthly? Well, think again. With Crowd, you get all of this without breaking the bank. Merge quantitative data (like CSAT and NPS scores) with qualitative insights (user testing feedback) for a comprehensive understanding of user experience and customer sentiment.
Source: blog.crowdapp.io
11 Hotjar alternatives and competitors in 2024
Maze doesnโ€™t yet offer the ability to host fully-integrated moderated tests. The current moderated research solutions include Interview Studies to help you gain insight from users faster. Maze also offers Clips, enabling you to get deeper insights into your testerโ€™s pain points, feelings, and processes without the need for additional resources for a facilitator to be present.
Source: maze.co
Maze vs UXtweak: Which is the better tool?
๐Ÿ‘€ Looking to Switch to UXtweak but Locked into Maze subscription? If youโ€™re currently subscribed to Maze but want to explore what UXtweak has to offer, we have a special deal for you! We will provide free access to UXtweak for the remaining duration of your Maze subscription. No need to worry about extra costs or initiating a new procurement process. Simply reach out to us...
Source: blog.uxtweak.com
5 Best UXtweak Alternatives
Maze is also a cloud-based software and is designed to help businesses test prototypes, marketing campaigns, user feedback, and design ideas.
Source: blog.uxtweak.com

Plotly Reviews

Best 8 Redash Alternatives in 2023 [In Depth Guide]
Plotly is specifically designed for companies who want to build and deploy analytic applications like dashboards using Python, Julia, or R without needing DevOps or Javascript developers.
Source: www.datapad.io
5 Best Python Libraries For Data Visualization in 2023
Plotly is a web-based data visualization toolkit that comes with unique functionalities such as dendrograms, 3D charts, and also contour plots, which is not very common in other libraries. It has a great API offering scatter plots, line charts, bar charts, error bars, box plots, and other visualizations. Plotly can even be accessed from a Python Notebook.
Source: www.technotification.com
Top 8 Python Libraries for Data Visualization
Plotly is a free open-source graphing library that can be used to form data visualizations. Plotly (plotly.py) is built on top of the Plotly JavaScript library (plotly.js) and can be used to create web-based data visualizations that can be displayed in Jupyter notebooks or web applications using Dash or saved as individual HTML files. Plotly provides more than 40 unique...
Source: www.geeksforgeeks.org
5 top picks for JavaScript chart libraries
Plotly is a graphing library thatโ€™s available for various runtime environments, including the browser. It supports many kinds of charts and graphs that we can configure with a variety of options.
Source: blog.logrocket.com

Social recommendations and mentions

Based on our record, Plotly seems to be a lot more popular than Maze. While we know about 34 links to Plotly, we've tracked only 1 mention of Maze. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Maze mentions (1)

Plotly mentions (34)

  • How to Analyze 47 Million Hacker News Posts: A Data Scientist's Dream Dataset Just Got Better
    Let's dive into some practical examples. First, you'll need to set up your environment with the right tools. I recommend using pandas for data manipulation and plotly for visualization. - Source: dev.to / 4 months ago
  • Python for Data Visualization: Best Tools and Practices
    Plotly is perfect for interactive visualizations. You can create interactive charts and graphs that allow users to hover, click, and zoom in. Plotly is also great for web-based visuals, making it easy to share your findings online. - Source: dev.to / over 1 year ago
  • Generative AI Powered QnA & Visualization Chatbot
    Front End: A React application that leverages React-Chatbotify library to easily integrate a chatbot GUI. It also uses the Plotly library to display the charts/visualizations. The generative AI implementation and details are entirely abstracted from the front end. The front-end application depends on a single REST endpoint of the backend application. - Source: dev.to / over 1 year ago
  • Build a Stock Dashboard in less than 40 lines of Python code!๐Ÿค“
    In this tutorial, Mariya Sha will guide you through building a stock value dashboard using Taipy, Plotly, and a dataset from Kaggle. - Source: dev.to / over 1 year ago
  • Essential Deep Learning Checklist: Best Practices Unveiled
    How to Accomplish: Utilize visualization libraries like Matplotlib, Seaborn, or Plotly in Python to create histograms, scatter plots, and bar charts. For image data, use tools that visualize images alongside their labels to check for labeling accuracy. For structured data, correlation matrices and pair plots can be highly informative. - Source: dev.to / about 2 years ago
View more

What are some alternatives?

When comparing Maze and Plotly, you can also consider the following products

UserTesting.com - Usability testing has never been easier. Get videos of real people speaking their thoughts as they use websites, mobile apps, prototypes and more!

D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.

Hotjar - The #1 Leader in Heatmaps, Recordings, Surveys & More. Sign up for a 15-day free trial and start learning from real user behavior today!

RAWGraphs - RAWGraphs is an open source app built with the goal of making the visualization of complex data...

Sprig - Delivering locally-sourced, seasonal, sustainable lunches and dinners.

Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.

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