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AppFollow VS Matplotlib

Compare AppFollow VS Matplotlib and see what are their differences

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

AppFollow logo AppFollow

AppFollow is an integrated solution that makes monitoring, analyzing, and elevating your app's reputation easy.

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • AppFollow Organic dashboard
    Organic dashboard //
    2024-04-25
  • AppFollow AI replies
    AI replies //
    2024-04-25
  • AppFollow Reply to reviews
    Reply to reviews //
    2024-04-25
  • AppFollow Agent Performance
    Agent Performance //
    2024-04-25
  • AppFollow Semantic analysis
    Semantic analysis //
    2024-04-25

Your app's reputation determines success. Apps with 4+ stars capture 80% of market revenue and get conversion rates that make competitors jealous. We built AppFollow as the reputation management platform that turns user feedback into measurable results.

AppFollow filters reviews for app teams who need to improve their product and increase sales. Better feedback management improves app ratings, better ratings boost conversion rates and trust, which then means more downloads and revenue. This loop is your competitive advantage.

Our AI suite does the heavy work: with its help, you can tag feedback by topic, summarize insights across thousands of reviews, translate languages, generate unique responses that sound human, and assist your team with complex cases. Automate routine replies and flag issues that need human attention.

Get the reporting you need. Executive reports deliver full summaries for leadership with granular analytics showing which keywords generate downloads. Reveal how competitors attract your users, identify which marketing channels work best, set up Slack alerts for critical feedback, and optimize the time your team spends on reputation management.

Track ASO performance and organic visibility. Monitor reviews across all app stores. See what drives rankings and conversion rates.

Major companies trust AppFollow to maintain their competitive edge. Easy Brain, Wargaming, Lazada, G5, Gameloft, Indeed, Standard Bank, and Opera rely on our platform. We integrate with App Store Connect, Google Play Console, Trustpilot, and all major app marketplaces, with platforms like Steam joining the list soon. We also connect with your existing tools like Zendesk and Slack.

Turn user feedback into business advantage.

  • Matplotlib Landing page
    Landing page //
    2023-06-14

AppFollow

Website
appfollow.io
Pricing URL
Official AppFollow Pricing
$ Details
freemium
Release Date
2015 January
Startup details
Country
Finland
State
Southern Finland
City
Helsinki
Founder(s)
Anatoly Sharifulin
Employees
50 - 99
Edit details

Matplotlib

Website
matplotlib.org
Pricing URL
-
$ Details
Release Date
-
Edit details

AppFollow features and specs

  • Comprehensive Analytics
    AppFollow provides extensive app performance metrics and detailed analytics, which can help users understand their appโ€™s performance and user reviews in depth.
  • Review Management
    The platform offers robust review management tools, allowing users to monitor, analyze, and respond to user feedback directly from the dashboard, making customer interaction more streamlined.
  • Keyword Tracking
    AppFollow includes keyword tracking features that help users improve their app's visibility by identifying the most effective keywords for their appโ€™s ASO strategy.
  • Competitor Analysis
    Users can track competitors' apps and get insights into their performance and strategies. This helps in making informed decisions to stay ahead in the market.
  • Integrations
    AppFollow supports integration with various tools and platforms like Slack, Zendesk, and others, facilitating smoother workflow and collaboration.

Possible disadvantages of AppFollow

  • Pricing
    The service can be quite expensive, especially for startups and small businesses that might find the cost prohibitive.
  • Complexity
    The platform can be complex to navigate for new users, with a steep learning curve that might require additional time and resources to fully utilize.
  • Customization Limitations
    Some users have noted that there are limitations in customizing reports and dashboards, which might not cater to all specific business needs.
  • Limited Free Plan
    The free plan offers very limited functionalities, which may not be sufficient for users who need more comprehensive features and insights.
  • Support Response Time
    There have been instances where users reported slower response times from customer support, which can be a drawback in time-sensitive situations.

Matplotlib features and specs

  • Versatility
    Matplotlib can generate a wide variety of plots, ranging from simple line plots to complex 3D plots. This versatility makes it a go-to library for many scientific and technical visualizations.
  • Customization
    It offers extensive customization options for virtually every element of a plot, including colors, labels, line styles, and more, allowing users to tailor plots to meet specific needs.
  • Integrations
    Matplotlib integrates well with other Python libraries such as NumPy, Pandas, and SciPy, making it easier to plot data directly from these sources.
  • Community and Documentation
    It has a large, active community and comprehensive documentation that includes tutorials, examples, and detailed references, which can help users solve problems and improve their plot-making skills.
  • Interactivity
    Matplotlib supports interactive plots, which can be embedded in Jupyter notebooks and GUIs, allowing for dynamic data exploration and presentation.
  • Publication-Quality
    The library is capable of producing high-quality, publication-ready graphics that meet the stringent requirements of academic journals and professional presentations.

Possible disadvantages of Matplotlib

  • Complexity
    While Matplotlib offers extensive customization, it can be complex and sometimes unintuitive for beginners, requiring a steep learning curve to master all its functionality.
  • Performance
    Rendering a large number of plots or handling very large datasets can be slow, making Matplotlib less suitable for real-time data visualization.
  • Modern Aesthetics
    Out-of-the-box plots from Matplotlib can look somewhat dated compared to those from newer plotting libraries like Seaborn or Plotly, requiring additional customization to achieve a modern look.
  • 3D Plots
    Although Matplotlib supports 3D plotting, its capabilities are relatively limited and less sophisticated compared to specialized 3D plotting libraries.
  • Size and Structure
    The package is relatively large and can be slow to import. Its extensive structure can make finding specific functions and understanding the overall architecture challenging.

Analysis of AppFollow

Overall verdict

  • Overall, AppFollow is highly regarded, especially by app developers and marketing teams looking for a centralized solution to manage app performance and user feedback. It offers a broad range of tools that cater to various facets of app development and marketing, making it a versatile choice for those in need of detailed analytics and effective review management.

Why this product is good

  • AppFollow is considered a valuable tool for app developers and marketers because it provides comprehensive app tracking, analytics, and review management. It helps users monitor app store performance, gather user feedback, and optimize app visibility with features like keyword tracking and ASO tools. Users appreciate its user-friendly interface and integration capabilities with platforms such as Slack, Zendesk, and others.

Recommended for

  • Mobile app developers
  • Product managers
  • Marketing teams
  • ASO specialists
  • Customer support teams focusing on app feedback

Analysis of Matplotlib

Overall verdict

  • Yes, Matplotlib is a good library for data visualization, particularly for users who require a versatile and powerful plotting solution in Python.

Why this product is good

  • Matplotlib is highly regarded due to its extensive customization options, versatility in creating a wide range of static, animated, and interactive plots, and its large user community and support. It integrates well with other scientific libraries in Python, making it a staple for data visualization. The library is also open-source and frequently updated, ensuring it remains a reliable choice for users.

Recommended for

  • Data scientists and analysts needing to create detailed, customized visual representations of their data.
  • Researchers and engineers looking for a comprehensive plotting library that supports scientific and engineering formats.
  • Python developers who require integration with other scientific computing libraries like NumPy and Pandas.

AppFollow videos

+ Add

ASO Tool for Keyword Research (AppFollow Review)

More videos:

  • Review - Intro to AppFollow Review Management Tools
  • Review - AppFollow and Slack Integration for App Review Management

Matplotlib videos

+ Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to AppFollow and Matplotlib)

AppFollow

Matplotlib

App Reviews
100 100%
App Reviews
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Analytics
100 100%
Analytics
0% 0
Technical Computing
0 0%
Technical Computing
100% 100

Questions & Answers

As answered by people managing AppFollow and Matplotlib.

What makes your product unique?

AppFollow's answer

AppFollow uniquely combines AI-powered review analysis, reply automation, and app store optimization into one platform. We help mobile-first teams understand user feedback at scale and turn ratings and reviews into a real growth lever โ€” not just a support task.

Why should a person choose your product over its competitors?

AppFollow's answer

AppFollow is built for teams that care about outcomes, not just data. Customers choose us because we:

  • Save time with smart automation

  • Reveal product and UX insights hidden in reviews

  • Help improve ratings faster with data-backed actions

In short: fewer tools, clearer decisions, better ratings.

What's the story behind your product?

AppFollow's answer

AppFollow started with a simple problem: mobile teams were drowning in user feedback but couldnโ€™t act on it fast enough. What began as a way to track and respond to app store reviews quickly evolved into a full platform helping teams turn user voice into a competitive advantage.

Which are the primary technologies used for building your product?

AppFollow's answer

AppFollow is built using modern cloud infrastructure and scalable web technologies, with a strong focus on AI/ML for text analysis, automation, and secure data processing. The platform is designed to handle large volumes of app store data reliably and in real time.

Who are some of the biggest customers of your product?

AppFollow's answer

  • Easy Brain
  • Wargaming
  • Lazada
  • G5
  • Gameloft
  • Indeed
  • Standard Bank
  • Opera

How would you describe the primary audience of your product?

AppFollow's answer

The platform is built for product managers, growth and ASO marketers, customer experience leaders, and app teams who manage large volumes of user feedback across app stores, regions, and languages. These teams rely on AppFollow to filter signal from noise, identify reputation risks early, and turn user feedback into faster product improvements and measurable business results.

AppFollow is especially valuable for organizations where:

  • A small change in star rating creates outsized financial impact

  • Review volume makes manual analysis impossible

  • Speed matters when bugs, crashes, or UX issues affect ratings

  • Reputation management must scale without increasing headcount

From fast-growing app publishers to international brands managing apps across dozens of markets, AppFollow serves teams that view reputation management as a growth engine, not a support task.

User comments

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Reviews

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

AppFollow Reviews

We have no reviews of AppFollow yet.
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Matplotlib Reviews

25 Python Frameworks to Master
Matplotlib is a widely used tool for data visualization in Python. It provides an object-oriented API for embedding plots into applications.
Source: kinsta.com
5 Best Python Libraries For Data Visualization in 2023
You can use this library for multiple purposes such as generating plots, bar charts, histograms, power spectra, stemplots, pie charts, and more. The best thing about Matplotlib is you just have to write a few lines of code and it handles the rest by itself. Metaplotilib focuses on static images for publication along with interactive figures using toolkits like Qt and GTK.
Source: www.technotification.com
15 data science tools to consider using in 2021
Matplotlib is an open source Python plotting library that's used to read, import and visualize data in analytics applications. Data scientists and other users can create static, animated and interactive data visualizations with Matplotlib, using it in Python scripts, the Python and IPython shells, Jupyter Notebook, web application servers and various GUI toolkits.
Source: searchbusinessanalytics.techtarget.com
Top Python Libraries For Image Processing In 2021
Matplotlib is primarily used for 2D visualizations such as scatter plots, bar graphs, histograms, and many more, but we can also use it for image processing. It is effective to get information out of an image. It doesnโ€™t support all file formats.
Source: www.analyticsvidhya.com
Top 8 Python Libraries for Data Visualization
Matplotlib is a data visualization library and 2-D plotting library of Python It was initially released in 2003 and it is the most popular and widely-used plotting library in the Python community. It comes with an interactive environment across multiple platforms. Matplotlib can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application...
Source: www.geeksforgeeks.org

Social recommendations and mentions

Based on our record, Matplotlib seems to be more popular. It has been mentiond 114 times since March 2021. 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.

AppFollow mentions (0)

We have not tracked any mentions of AppFollow yet. Tracking of AppFollow recommendations started around Mar 2021.

Matplotlib mentions (114)

  • The soul file
    In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib โ€” the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review. Nothing unusual. - Source: dev.to / 5 months ago
  • How to Analyze CSV Files with Python and Pandas
    Numbers are useful, but sometimes itโ€™s easier to spot patterns when you can actually see your data. Pandas works seamlessly with Matplotlib, a popular Python library for creating visualizations. Together, they make it easy to turn raw numbers into clear charts. - Source: dev.to / 8 months ago
  • libmalloc, jemalloc, tcmalloc, mimalloc - Exploring Different Memory Allocators
    We are storing the results in JSON files, which we combine, analyze and visualize using matplotlib in Python. Here's the structure of a benchmark result file:. - Source: dev.to / 9 months ago
  • Building an AI Scoring Agent: Step-By-Step
    NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 10 months ago
  • Top 5 GitHub Repositories for Data Science in 2026
    The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโ€ฆ. - Source: dev.to / 11 months ago
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What are some alternatives?

When comparing AppFollow and Matplotlib, you can also consider the following products

appfigures - Cross-platform app store analytics for all of your mobile apps.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

AppTweak - The most comprehensive ASO & Apple Search Ads platform to optimize your apps' organic and paid performance in the app stores

NumPy - NumPy is the fundamental package for scientific computing with Python

Appbot - AI-powered sentiment analysis & text mining for app reviews and customer feedback. Appbot helps Product, Marketing & Support teams improve faster.

Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.

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