Software Alternatives, Accelerators & Startups

Salesforce Maps VS Plotly

Compare Salesforce Maps VS Plotly and see what are their differences

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Salesforce Maps logo Salesforce Maps

Salesforce Maps is a tool that helps companies in finding nearby customers, maximize their selling time with optimal routes, and focus on their sales territories.

Plotly logo Plotly

Low-Code Data Apps
  • Salesforce Maps Landing page
    Landing page //
    2023-08-23
  • Plotly Landing page
    Landing page //
    2023-07-31

Salesforce Maps features and specs

  • Improved Sales Productivity
    Salesforce Maps helps in optimizing sales routes and territories, which can lead to more efficient field operations and increased sales productivity.
  • Enhanced Customer Engagement
    By visualizing customer locations and data geographically, sales representatives can prioritize and engage with high-value clients more effectively.
  • Effective Territory Management
    The tool allows for the efficient management and optimization of sales territories, ensuring balanced workloads and coverage.
  • Integration with Salesforce
    Being a Salesforce product, Salesforce Maps integrates seamlessly with other Salesforce tools and data, enhancing overall CRM capabilities.
  • Mobile Accessibility
    Field teams can access Salesforce Maps on mobile devices, ensuring they have timely and relevant information while on the go.
  • Data Visualization
    The platform provides powerful data visualization capabilities, making it easier to identify trends, patterns, and opportunities.

Possible disadvantages of Salesforce Maps

  • Cost
    Salesforce Maps can be expensive, especially for small to medium-sized businesses, as it may require additional licensing or upgrades.
  • Complexity
    The platform can have a steep learning curve for new users, requiring time and training to fully utilize its capabilities.
  • Dependency on Internet Connectivity
    Since Salesforce Maps relies heavily on real-time data syncing, poor internet connectivity can affect its performance and usability.
  • Data Privacy Concerns
    Managing and visualizing customer data geographically can raise concerns about data privacy and compliance with regulations like GDPR.
  • Limited Offline Functionality
    While it has mobile accessibility, its functionality may be limited when offline, which can be a drawback for field teams operating in areas with poor connectivity.
  • Customization Challenges
    Customizing and scaling the platform to fit specific business needs can sometimes be challenging and may require additional investment in resources and expertise.

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 Salesforce Maps

Overall verdict

  • Salesforce Maps is generally regarded as a good tool for businesses seeking to leverage location-based insights within the Salesforce ecosystem. Its comprehensive feature set, ease of integration, and ability to enhance field operations make it a valuable asset for companies that require geographic visualization and planning capabilities.

Why this product is good

  • Salesforce Maps, formerly known as MapAnything, is considered a robust geolocation solution that integrates seamlessly with Salesforce. It offers advanced features such as route optimization, territory planning, and live tracking, which help businesses increase productivity, optimize sales processes, and improve customer relationships. The ability to visualize data geographically allows for better strategic decision-making and enhances field service efficiency.

Recommended for

  • Sales teams looking to optimize route planning and improve efficiency in the field.
  • Organizations that need to manage and plan territories effectively.
  • Businesses aiming to gain geographic insights from their Salesforce data.
  • Field service operations desiring better resource allocation and live tracking of assets.

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.

Salesforce Maps videos

Salesforce Maps Territory Planning Demo

More videos:

  • Review - Salesforce Maps Jump Start (Success)
  • Demo - Quick Demo - Youreka and Salesforce Maps

Plotly videos

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 Salesforce Maps and Plotly)
Maps
100 100%
0% 0
Data Visualization
0 0%
100% 100
Mapping And GIS
100 100%
0% 0
Data Dashboard
0 0%
100% 100

User comments

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Reviews

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

Salesforce Maps Reviews

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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.
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...
5 top picks for JavaScript chart libraries
Plotly is a graphing library that’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.

Social recommendations and mentions

Based on our record, Plotly seems to be more popular. It has been mentiond 33 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.

Salesforce Maps mentions (0)

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

Plotly mentions (33)

  • 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 / 3 months 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 / 5 months ago
  • Build a Stock Dashboard in less than 40 lines of Python code!🤓
    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 / 7 months 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 1 year ago
  • Python equivalent to power bi/power query?
    For dashboards: - https://plotly.com/ is probably my favourite, but there are others like streamlit, voila and others... Source: over 1 year ago
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What are some alternatives?

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

Geopointe - Geopointe enables Salesforce users to gain spatial insights via maps and apply geography to business processes.

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.

Esri ArcGIS - ArcGIS provides contextual tools for mapping and spatial reasoning so you can explore data & share location-based insights. ArcGIS is the heart of the Esri Geospatial Cloud. Try ArcGIS for free with 21-day trial.

Chart.js - Easy, object oriented client side graphs for designers and developers.

Maptitude - Maptitude is a mapping software that is fitted with GIS features that avail maps and other forms of data regarding the surrounding geographical areas. Read more about Maptitude.

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