Osborne  Durgan

Osborne Durgan

1594925580

Analysis and Applications of Multi-Scale CNN Feature Maps

Abstract

In this blog post, we present a formal treatment of receptive fields of convolution layers and characterizations of multi-scale convolutional feature maps using a derived mathematical framework. Using the developed mathematical framework, we compute the receptive fields and spatial scales of feature maps under different convolutional and pooling operations. We show the significance of pooling operations to ensure the exponential growth of spatial scale of feature maps as a function of layer depths. Also, we observe that without pooling operations embedded into CNNs, feature map spatial scales only grow linearly as layer depth increase. We introduce spatial scale profile as the layer-wise spatial scale characterization of CNNs which could be used to assess the compatibility of feature maps with histograms of object dimensions in training datasets. This use case is illustrated by computing the spatial scale profile of ResNet-50. Also, we explain how feature pyramid module generates multi-scale feature maps enriched with augmented semantic representations. Finally, it is shown while dilated convolutional filters preserve the spatial dimensions of feature maps, they maintain greater exponential growth rate of spatial scales compared to their regular convolutional filter counterparts.

_Reading this blogpost, you will have a deeper insight into the intuitions behind the use cases of multi-scale convolutional feature maps in the recent proposed CNN architectures for variety of vision tasks. Therefore, this blogpost can be treated as a tutorial to learn more about how different types of layers impact the spatial scales and receptive fields of feature maps. Also, this blogpost is for those engineers and researchers that are involved in designing CNN architectures and are tired of blind trial and error of which feature maps to choose from a CNN backbone to improve the performance of their models, and instead, prefer from the early steps of design process, to match the spatial scale profiles of feature maps with the object dimensions in training datasets. To facilitate such use cases, we have made our code base publicly available at _https://github.com/rezasanatkar/cnn_spatial_scale.

Introduction

It is a general assumption and understanding that feature maps generated by the early convolutional layers of CNNs encode basic semantic representations such as edges and corners, whereas deeper convolutional layers encode more complex semantic representations such as complicated geometric shapes in their output feature maps. Such a characteristic of CNNs to generate feature maps with multi semantic levels is resultant of their hierarchical representational learning ability which is based on multi-layer deep structures. Feature maps with different semantic levels are critical for CNNs because of the two following reasons: (1) complex semantics feature maps are built on top of basic semantic feature maps as their building blocks (2) a number of vision tasks like instance and semantic segmentation benefit from both basic and complex semantic feature maps. A vision CNN-based architecture takes an image as input, and passes it through several convolutional layers with the goal of generating semantic representations corresponding to the input image. In particular, each convolution layer outputs a feature map, where the extent of the encoded semantics in that feature map depends on both the representational learning ability of that convolutional layer as well as its previous convolutional layers.

CNN Feature Maps are Spatial Variance

One important characteristic of CNN feature maps is that they are spatial variance, meaning that CNN feature maps have spatial dimensions, and a feature encoded by a given feature map might only become active for a subset of spatial regions of the feature map. In order to better understand the spatial variance property of CNN feature maps, first, we need to understand why the feature maps generated by fully connected layers are not spatial variance. The feature maps generated by fully connected layers (you can thinks of the activations of neurons of a given fully connected layer as its output feature map) do not have spatial dimensions since every neuron of a fully connected layer is connected to all the input units of the fully connected layer. Therefore, it is not possible to define and consider a spatial aspect for a neuron activation output.

On the other hand, every activation of a CNN feature map is only connected to a few input units, which are in each other spatial neighborhood. This property of CNN feature maps gives rise to their spatial variance characteristic, and is resultant from the spatial local structure of convolution filters and their spatially limited receptive fields. The differences between fully connected layers and convolutional layers which result in spatial invariance for one and spatial variance for the other one is illustrated in the below image where the input image is denoted by the green rectangle, and the brown rectangle denotes a convolutional feature map. Also, a fully connected layer with two output neurons is denoted by two blue and grey circles. As you can see, each neuron of the fully connected layer is impacted by all the image pixels whereas each entry of feature map is only impacted by a local neighborhood of input pixels.

Image for post

This figure illustrates why the features generated by fully connected layers are not spatial variance while convolutional layers generate spatial variance feature maps. The green rectangle denotes the input image and the brown rectangle denotes a feature map with dimension 5 x 7 x 1 generated by a convolution layer of a CNN. On the other hand, the two blue and grey circles denote activation outputs of a fully connected layer with two output neurons. Let assume the blue neuron (feature) of the fully connected layer will become active if there is a bicycle in the input image while its grey neuron (feature) will become active if there is car in the input image. In other words, the blue neuron is the bicycle feature while the grey neuron is the car feature. Because of the nature of fully connected layers which each neuron’s output is impacted by all the input image pixels, the fully connected layers’ generated features cannot encode any localization information out-of-the-box in order to tell us where in the input image the bicycle is located if there is a bicycle in input image. On the other hand, the feature maps generated by convolutional layers are spatial variance and therefore, they encode the localization information in addition to the existence information of objects. In particular, a generated feature map of dimension W x H x C by a convolutional layer, contains information of existence of C different features (each channel, the third dimension of the feature map, encode existence information of a unique feature) where the spatial dimension W x H of features tell us for which location of the input image, the feature is activated. In this example, the brown convolutional feature map only encodes one feature since it has only one channel (its third dimension is equal to one). Assuming this brown feature map is the bicycle feature map, then an entry of this feature map becomes active only if there is a bicycle in the receptive field of that entry in input image. In other words, this entry does not become active if there is a bicycle in the input image but not in its specific receptive field. Such property of convolutional feature maps enable them not only to encode information about the existence of objects in input images, but also to encode localization information of objects.

#convolutional-network #dilated-convolution #receptive-field #feature-pyramid-network #neural networks

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Analysis and Applications of Multi-Scale CNN Feature Maps
Adaline  Kulas

Adaline Kulas

1594162500

Multi-cloud Spending: 8 Tips To Lower Cost

A multi-cloud approach is nothing but leveraging two or more cloud platforms for meeting the various business requirements of an enterprise. The multi-cloud IT environment incorporates different clouds from multiple vendors and negates the dependence on a single public cloud service provider. Thus enterprises can choose specific services from multiple public clouds and reap the benefits of each.

Given its affordability and agility, most enterprises opt for a multi-cloud approach in cloud computing now. A 2018 survey on the public cloud services market points out that 81% of the respondents use services from two or more providers. Subsequently, the cloud computing services market has reported incredible growth in recent times. The worldwide public cloud services market is all set to reach $500 billion in the next four years, according to IDC.

By choosing multi-cloud solutions strategically, enterprises can optimize the benefits of cloud computing and aim for some key competitive advantages. They can avoid the lengthy and cumbersome processes involved in buying, installing and testing high-priced systems. The IaaS and PaaS solutions have become a windfall for the enterprise’s budget as it does not incur huge up-front capital expenditure.

However, cost optimization is still a challenge while facilitating a multi-cloud environment and a large number of enterprises end up overpaying with or without realizing it. The below-mentioned tips would help you ensure the money is spent wisely on cloud computing services.

  • Deactivate underused or unattached resources

Most organizations tend to get wrong with simple things which turn out to be the root cause for needless spending and resource wastage. The first step to cost optimization in your cloud strategy is to identify underutilized resources that you have been paying for.

Enterprises often continue to pay for resources that have been purchased earlier but are no longer useful. Identifying such unused and unattached resources and deactivating it on a regular basis brings you one step closer to cost optimization. If needed, you can deploy automated cloud management tools that are largely helpful in providing the analytics needed to optimize the cloud spending and cut costs on an ongoing basis.

  • Figure out idle instances

Another key cost optimization strategy is to identify the idle computing instances and consolidate them into fewer instances. An idle computing instance may require a CPU utilization level of 1-5%, but you may be billed by the service provider for 100% for the same instance.

Every enterprise will have such non-production instances that constitute unnecessary storage space and lead to overpaying. Re-evaluating your resource allocations regularly and removing unnecessary storage may help you save money significantly. Resource allocation is not only a matter of CPU and memory but also it is linked to the storage, network, and various other factors.

  • Deploy monitoring mechanisms

The key to efficient cost reduction in cloud computing technology lies in proactive monitoring. A comprehensive view of the cloud usage helps enterprises to monitor and minimize unnecessary spending. You can make use of various mechanisms for monitoring computing demand.

For instance, you can use a heatmap to understand the highs and lows in computing visually. This heat map indicates the start and stop times which in turn lead to reduced costs. You can also deploy automated tools that help organizations to schedule instances to start and stop. By following a heatmap, you can understand whether it is safe to shut down servers on holidays or weekends.

#cloud computing services #all #hybrid cloud #cloud #multi-cloud strategy #cloud spend #multi-cloud spending #multi cloud adoption #why multi cloud #multi cloud trends #multi cloud companies #multi cloud research #multi cloud market

Osborne  Durgan

Osborne Durgan

1594925580

Analysis and Applications of Multi-Scale CNN Feature Maps

Abstract

In this blog post, we present a formal treatment of receptive fields of convolution layers and characterizations of multi-scale convolutional feature maps using a derived mathematical framework. Using the developed mathematical framework, we compute the receptive fields and spatial scales of feature maps under different convolutional and pooling operations. We show the significance of pooling operations to ensure the exponential growth of spatial scale of feature maps as a function of layer depths. Also, we observe that without pooling operations embedded into CNNs, feature map spatial scales only grow linearly as layer depth increase. We introduce spatial scale profile as the layer-wise spatial scale characterization of CNNs which could be used to assess the compatibility of feature maps with histograms of object dimensions in training datasets. This use case is illustrated by computing the spatial scale profile of ResNet-50. Also, we explain how feature pyramid module generates multi-scale feature maps enriched with augmented semantic representations. Finally, it is shown while dilated convolutional filters preserve the spatial dimensions of feature maps, they maintain greater exponential growth rate of spatial scales compared to their regular convolutional filter counterparts.

_Reading this blogpost, you will have a deeper insight into the intuitions behind the use cases of multi-scale convolutional feature maps in the recent proposed CNN architectures for variety of vision tasks. Therefore, this blogpost can be treated as a tutorial to learn more about how different types of layers impact the spatial scales and receptive fields of feature maps. Also, this blogpost is for those engineers and researchers that are involved in designing CNN architectures and are tired of blind trial and error of which feature maps to choose from a CNN backbone to improve the performance of their models, and instead, prefer from the early steps of design process, to match the spatial scale profiles of feature maps with the object dimensions in training datasets. To facilitate such use cases, we have made our code base publicly available at _https://github.com/rezasanatkar/cnn_spatial_scale.

Introduction

It is a general assumption and understanding that feature maps generated by the early convolutional layers of CNNs encode basic semantic representations such as edges and corners, whereas deeper convolutional layers encode more complex semantic representations such as complicated geometric shapes in their output feature maps. Such a characteristic of CNNs to generate feature maps with multi semantic levels is resultant of their hierarchical representational learning ability which is based on multi-layer deep structures. Feature maps with different semantic levels are critical for CNNs because of the two following reasons: (1) complex semantics feature maps are built on top of basic semantic feature maps as their building blocks (2) a number of vision tasks like instance and semantic segmentation benefit from both basic and complex semantic feature maps. A vision CNN-based architecture takes an image as input, and passes it through several convolutional layers with the goal of generating semantic representations corresponding to the input image. In particular, each convolution layer outputs a feature map, where the extent of the encoded semantics in that feature map depends on both the representational learning ability of that convolutional layer as well as its previous convolutional layers.

CNN Feature Maps are Spatial Variance

One important characteristic of CNN feature maps is that they are spatial variance, meaning that CNN feature maps have spatial dimensions, and a feature encoded by a given feature map might only become active for a subset of spatial regions of the feature map. In order to better understand the spatial variance property of CNN feature maps, first, we need to understand why the feature maps generated by fully connected layers are not spatial variance. The feature maps generated by fully connected layers (you can thinks of the activations of neurons of a given fully connected layer as its output feature map) do not have spatial dimensions since every neuron of a fully connected layer is connected to all the input units of the fully connected layer. Therefore, it is not possible to define and consider a spatial aspect for a neuron activation output.

On the other hand, every activation of a CNN feature map is only connected to a few input units, which are in each other spatial neighborhood. This property of CNN feature maps gives rise to their spatial variance characteristic, and is resultant from the spatial local structure of convolution filters and their spatially limited receptive fields. The differences between fully connected layers and convolutional layers which result in spatial invariance for one and spatial variance for the other one is illustrated in the below image where the input image is denoted by the green rectangle, and the brown rectangle denotes a convolutional feature map. Also, a fully connected layer with two output neurons is denoted by two blue and grey circles. As you can see, each neuron of the fully connected layer is impacted by all the image pixels whereas each entry of feature map is only impacted by a local neighborhood of input pixels.

Image for post

This figure illustrates why the features generated by fully connected layers are not spatial variance while convolutional layers generate spatial variance feature maps. The green rectangle denotes the input image and the brown rectangle denotes a feature map with dimension 5 x 7 x 1 generated by a convolution layer of a CNN. On the other hand, the two blue and grey circles denote activation outputs of a fully connected layer with two output neurons. Let assume the blue neuron (feature) of the fully connected layer will become active if there is a bicycle in the input image while its grey neuron (feature) will become active if there is car in the input image. In other words, the blue neuron is the bicycle feature while the grey neuron is the car feature. Because of the nature of fully connected layers which each neuron’s output is impacted by all the input image pixels, the fully connected layers’ generated features cannot encode any localization information out-of-the-box in order to tell us where in the input image the bicycle is located if there is a bicycle in input image. On the other hand, the feature maps generated by convolutional layers are spatial variance and therefore, they encode the localization information in addition to the existence information of objects. In particular, a generated feature map of dimension W x H x C by a convolutional layer, contains information of existence of C different features (each channel, the third dimension of the feature map, encode existence information of a unique feature) where the spatial dimension W x H of features tell us for which location of the input image, the feature is activated. In this example, the brown convolutional feature map only encodes one feature since it has only one channel (its third dimension is equal to one). Assuming this brown feature map is the bicycle feature map, then an entry of this feature map becomes active only if there is a bicycle in the receptive field of that entry in input image. In other words, this entry does not become active if there is a bicycle in the input image but not in its specific receptive field. Such property of convolutional feature maps enable them not only to encode information about the existence of objects in input images, but also to encode localization information of objects.

#convolutional-network #dilated-convolution #receptive-field #feature-pyramid-network #neural networks

Bhakti Rane

1625482158

Heat Maps in Dynamics 365 CRM | Regional sales Analysis | Map Data Analytics

#Heat Map Visualization in Dynamics 365 CRM

Maplytics integrates Dynamic 365 CRM with Bing Maps opening up vast opportunity for the Dynamics CRM users, peers and Partners to analyze graphic data using Heat Map. Heat Map brings forth comparative study of records by studying their density over a region. You can also visualize Heat map within Dynamics 365 CRM in context to boundary, no-boundary, Pie-chart and Column-chart.

#heat maps in dynamics 365 #heat map dynamics crm #sales heat map dynamics 365 #heatmap analytics dynamics 365 #map dynamics 365 data analysis

Ramya M

1608022599

10 Best Multi vendor Marketplace Platforms (2021) - Features & Cost

Great evolution has happened in the buying and selling process due to the advent of ecommerce. There is exponential growth in the field of online business and selling and buying happens at the doorstep. The multi vendor marketplace platform has become the next level in the ecommerce niche.

The multi vendor marketplace platform like Amazon, Flipkart, and eBay have already succeeded in the industry and have set a milestone on sales and revenue.

This fact has inspired many aspiring entrepreneurs and has made them transfer their brick and mortar stores to multi vendor platform.

What is Online Multi vendor Marketplace?

Multi vendor marketplace platform is connect a multiple sellere or vendors to display and sell their products through the platform by agreeing with the terms mentioned by the admin of the platform. They can have their way of promoting their products.

For every sale they make, they need to pay the commission amount to the admin of the marketplace platform if they have agreed with the terms. Else they can have other sources of profit-sharing with the admin and both will be mutually benefited.

Types of Multi vendor Marketplace Platform

There are several types of multi vendor marketplace software in the market. One needs to understand all the types and should know to identify which type of marketplace platform suits his business well.

  • Vertical marketplace – this type of multi vendor marketplace platform concentrates only on one particular service and you cannot find a wide range of services in these platforms. Etsy is a good example of a vertical marketplace where the platform sells handmade crafts alone.
  • Horizontal marketplace – this platform is opposite to a vertical marketplace where you can find several types of services under one roof. Amazon is a perfect example of this type of marketplace.
  • Product-based marketplace – you can find a wide range of products in this marketplace. The products can be physical goods or even digital goods. Amazon and Flipkart are the product-based marketplaces.
  • Service-based marketplace – service providers will list their services like plumbing, personal care, pest control, and many more. Upwork and Fiverr are service-based marketplaces.

Here is a list of Top 10 Best Turnkey Multi vendor Marketplace Platforms:

Now that you have a better understanding of the key features for Multi vendor marketplace, let’s compare ten of the top Multi vendor providers.

1. Zielcommerce – A Powerful & Ready-to-go Multi vendor eCommerce Marketplace Platform

This is image title
Zielcommerce is a white label enabled enterprise grade online marketplace software. The multi vendor platform comes with a one time payment option and it is completely customizable and also scalable. 

Platform Highlights

  • The feature-rich UI and UX have never missed attracting the users towards the multi vendor ecommerce.
  • The platform is user-friendly and it is a perfect device compatible.
  • It’s a convenient marketplace solution that provides all round service required for a perfect multi vendor marketplace platform.
  • This also supports easy brand recognition and you can get more visitors to your ecommerce platform.

Zielcommerce provides its users with a secured environment through its SSL certified marketplace software and gains the trust of the users. You can be easily promoted online with this SEO-optimized platform. Stay connected with your customers all the time with the in-build communication channels.

The pleasing features of this multi vendor marketplacce solution

  • Multilingual and multiple currency support
  • Multiple payment options to facilitate buyers
  • Real-time tracking feature to track orders online
  • Wide delivery option for buyers’ convenience
  • A dedicated mobile application that will suit your business demands
  • Review and rating system to enhance the performance of the platform
  • 24/7 technical support from our end.

Best Use Cases

  • Grocery Ecommerce Platform
  • Fashion & Lifestyle ecommerce Store
  • Electronics Ecommerce Platform
  • Furniture Ecommerce Platform
  • Handcraft Ecommerce Software
  • Health Care & Pharmacy Platform

Client’s Rating

  • Ease of use: 4.5/5
  • Customer service – 4.7/5
  • Overall: 4.6/5

Explore Zielcommerce Multi vendor Ecommerce Platform

2. X-cart – a well-known multi vendor marketplace platform solution

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X-cart is a standalone online marketplace solution for your online business needs. You can get the complete comprehensive features within this multi vendor marketplace software that can meet the customers’ expectations. A genuine approach is maintained and the users trust X-cart for its outstanding functionalities that satisfy the multi vendor market demands.

Platform Highlights

  • Xcart stands alone in the market by providing best multi vendor marketplace solutions that will facilitate users to increase their online credibility.
  • If you prefer to build a multi vendor marketplace platform like amazon or eBay then Xcart is the perfect choice.

It has gained the trust of thousands of users and people who use Xcart as their online multi vendor marketplace software has given the best review about the product.

The salient features of this multi vendor ecommerce platform solution

  • One-time payment to purchase the marketplace software
  • In-built marketing and promotion tools to promote the multi vendor marketplace software
  • Trusted payment gateways integrated with the website
  • Reliable order management system.
  • On-time delivery management

Best Use Cases

  • Hyperlocal Ecommerce Platform
  • Jewellery e-commerce Store
  • Electronics Ecommerce Platform
  • Furniture Ecommerce Platform

Client’s Rating:

  • Ease of use : 3.5/5
  • Customer service – 3.4/5
  • Overall : 3.5/5

Explore Xcart Multi vendor Marketplace Software

3. Cs cart – a perfect multi vendor marketplace solution

This is image title

CS-Cart has never disappointed its users and it comes with the complete ecommerce marketplace solution for all your business demands. You can gain perfect control over the online multi vendor marketplace platform and can personalize the platform to suit your business needs. You will get higher visibility and can easily attract your target audience with the CS-Cart marketplace solution.

Platform Highlights

  • CS-cart is the most reliable multi vendor marketplace platform that gives a user-friendly platform for the user.
  • The interface is easily understandable and no technical knowledge is needed to maintain the multi vendor marketplace software.

You can gain the attention of global audiences through its multilingual support and can take your brand all over the world and build a strong branding with the help of CS cart.

The key features of this multi vendor ecommerce website solution

  • SEO- friendly platform that will help you to get top ranking in all search engines.
  • Mobile –friendly and will get you more mobile users as your customers
  • Get genuine customer care support
  • Well-integrated with all third-party software.
  • The online multi vendor ecommerce platform will have social media logins

Best use cases

Client’s Rating :

  • Ease of use : 4.1/5
  • Customer service – 4.3/5
  • Overall :4.2/5

[Explore Cscart Online Marketplace Software](https://www.cs-cart.com “Explore Cscart Online Marketplace Software”)

4. Arcadier – Superlative Multi vendor marketplace platform

This is image title

Arcadier is the SaaS (Software-as-a-Service) provider that allows businesses, SMEs, local communities, government agencies and entrepreneurs to manage their online multi vendor marketplace platform more efficiently and affectionately. Arcadier has many attractive features that can grab the attention of vendors.

Platform Highlights

  • When you have multiple vendors only then you can call your platform as a multi vendor marketplace platform.
  • This is quite easy when you go for Arcadier.
  • The genuine support that you get with this online multi vendor enterprise marketplace platform will retain your vendors and also your buyers and provides better multi vendor marketplace software to your business needs.

Apart from other SaaS online marketplace platforms on the market that offer a temporary solution for all purposes, Arcadier allows users to choose between multiple options in buying and selling products or services to rental spaces and other business models.

**The Prominent features of this online multi vendor marketplace software solution

  • The seller can manage to add variations to each listing, and also placing images and surcharges on each and every variant.
  • User-friendly platform to get the top ranking in all search engines.
  • Manually configure specific dates and hours of your ads on the calendar.
  • A Complete customer support assistance

Best Use Case

  • Clothing and accessories multivendor ecommerce platform
  • Handicrafts Online marketplace platform
  • On demand music online store
  • On demand movies online marketplace platform

**Client’s Rating: **

  • Ease of use : 3.2/5
  • Customer service – 3/5
  • Overall : 3.1/5

Explore Arcadier Multi vendor Marketplace Platform

5. Bigcommerce - Exquisite Multi Vendor Marketplace Software

Multi vendor Marketplace that converts your single admin online store into Multi vendor Marketplace. It provides of adding vendors and maintain the track record of their order and sales. Apart from vendor features, Bigcommerce gives best buyer features that will impress buyers and make them decide on buying products in your online multi vendor ecommerce platform.

Platform Highlights

  • Offers and discount features are available that will delight buyers and will make them refer more customers to your multi vendor marketplace platform.
  • You can also easily retain your customers by keeping them about new arrivals and offers.
  • As a store admin, you have background access and control and manage the products, orders, vendors and their products.

It comes with an option which, without the approval of the vendor admin the product would not be visible in the forefront. This online multi vendor marketplace platform is excellent features and creating various plans for vendors, a payment management system for vendors.

Impressing features of this online multi vendor marketplace software solution

  • Flexible Functionality Product approval
  • An admin can have full access to the seller’s profile, products, manage
  • Synchronizing products and orders from the “Bigcommerce store” to the "market.
  • Without any issue, the admin can create a “Payment” for the seller, once a product is out of stock.

Best Use Case

  • Handmade products online multi vendor ecommerce platform
  • Educational books online marketplace platform
  • Food delivery multi vendor marketplace platform
  • Fashion and clothing ecommerce platform

Explore Bigcommerce Multi vendor Ecommerce Platform

6. IXXO - Ideal Multi Vendor marketplace software

This is image title
Ixxo is an ideal marketplace solution for those who want to open and manage a high-volume marketplace as IXXO online Multi Vendor ecommerce platform offers unlimited product and unlimited vendor capacity. The marketplace owners can configure vendor privileges purely based on vendors. this help the multi vendor marketplace software owner to provide the basic vendor features, where the vendors dont have much ecommerce experience and privileges.

Platform Highlights

This will ensure that the delivery is taking place in the right way. If there is any delay then through a proper messaging system the buyer will get intimation regarding the delay. This feature impresses the customer and makes the platform the best one.

Splendid features of this Multi vendor marketplace platform solution

  • Simple Checkout Process
  • A wide range of payment options
  • Responds promptly and friendlily.
  • Feature-rich provider dashboard.

Best Use Cases

  • Ticket booking multi vendor ecommerce platform
  • On-demand cab booking online marketplace platform
  • Electronics multi vendor marketplace platform
  • Clothing ecommerce platform

**Client’s Rating: **

  • Ease of use : 4.1/5
  • Customer service – 4.3/5
  • Overall :4.2/5

Explore IXXO cart Online Multi vendor Marketplace Platform

7. Sharetribe - Structured Multi vendor marketplace solutions

Sharetribe is one of the excellent SaaS platforms for building and launching a online multi vendor marketplace software. Easy setting changes to your color theme and photos, instantly.

Platform Highlights

  • It is merged with a integration process, the marketplace allows users to sell products or services online without any technical support.
  • Sharetribe has all in-built marketing tools that will easily promote your brand globally with less effort.

This online multi vendor marketplace platform gives a perfect shopping experience to customers and also satisfied selling experience to vendors. Users can trust sharetribe for their business requirement and can get a trustworthy marketplace solution that will leverage their business to greater levels.

Core features of this multi vendor marketplace platform

  • It is a comprehensive tool for customizing your marketplace.
  • Responsive Design for users, optimized for every screen.
  • More conversions rate and decrease in bounce rate.
  • A comprehensive content management system to maintain an active market with visual content.

Best Use Cases

  • Travel and stay multi vendor ecommerce platform
  • Educational training online marketplace platform
  • Healthcare ecommerce platform
  • Food supply ecommerce platform

**Client’s Rating:**

  • Ease of use : 3.9/5
  • Customer service – 3.7/5
  • Overall :3.8/5

Explore Sharetribe Multi vendor Marketplace Software

8. Appdupe - Intuitive Multi vendor marketplace software

A online Multi vendor marketplace platform is an online marketplace where many sellers can sign up, create their profiles and add products and sell when they want. One of the best examples of multi vendor platforms right now is Amazon, and so on. Well, the multi vendor marketplace platform has multiple benefits for its users and vendors.

Platform Highlights

  • Appdupe gives customers to share their reviews and give ratings for the product they have purchased.
  • Vendors can also read the reviews written by their customers and this will help them to enhance their online multi vendor marketplace platform in a better way.
  • Appdupe also supports multiple revenue models and users can select the one that perfectly suits their business and can get better returns with minimum investment.

Impressing feature of this Multi vendor marketplace platform

  • It provides a hassle-free process
  • Easily download and handle their products in a simple way.
  • Separate dashboard for seller and buyer data formatting may go all the way.
  • Analysis and enhanced the ROI

Best Use Cases

9. Miva - Outbreaking Multi vendor marketplace platform

Is a flexible multi vendor marketplace platform that can be easily modified as their business evolves with more conversions rate, better integrations, with complete solutions for all aspects of online sales, This online multi vendor marketplace software help them generate revenue and increasing the average order value and with less operating costs.

Platform Highlights

Miva suits to any business model and business size. This online multi vendor marketplace platform is very cost-effective and even a startup who plans to start an online store with minimum investment can easily go for Miva.

The online multi vendor marketplace platform looks like it has been built from scratch. It inherits all essential features that are needed to run a multi vendor marketplace platform successfully. All you need is to buy the platform and launch the marketplace and can start earning instantly.

Intuitive feature of this Multi vendor marketplace platform

  • Admin can control and manage the review and approval of new products
  • Flexible commissions for every vendor sale based on subscription plans
  • Separate dashboard for a vendor to manage their own product listing
  • The separate seller has a unique profile on the marketplace and products limits based on membership plans

Best Use Cases

**Client’s Rating: **

  • Ease of use:4/5
  • Customer service – 3.7/5
  • Overall: 3.9/5

10. Quick eSelling – A Proven Multi vendor Marketpalce platform

Quick eSelling is a popular multi vendor online marketplace platform with upgrade features and a more comfortable platform for global merchants and seller to start their own online store. Quick eSelling is an online store feature for Customer Engagement and Retention. This platform has been designed to help you significantly increase your sales and save time.

Platform Highlights

  • Quick e-selling marketplace platform allows you to set commission plan for every individual vendor.
  • You can easily analyze their performance through proper analytics and reports.
  • You can boost the poor performing vendor by providing less commission percentage and boost their sale.

his will satisfy vendors and will make them stay with your multi vendor marketplace platform for a long time. You can get complete support from the technical team round the clock. Whenever customization needed the technical team will guide you in designing your own online multi vendor marketplace platform.

The essential feature of this Multi vendor marketplace software

  • SEO-friendly for ecommerce web development and essential to ensure high traffic
  • Vendors can check sales trends through graphs and data information inputs for building strategies
  • A secured platform for merchants and customers’ transitional communication.
  • It makes it easy for you to launch your online business effectively

Best Use Cases

  • Fashion and accessories marketplace platform
  • E-Book marketplace software
  • Food and beverages ecommerce platform
  • Jewellery online multi vendor ecommerce platform.

Client’s Rating:

  • Ease of use : 3.5/5
  • Customerservice – 3.3/5
  • Overall :3.4/5

Start a multi vendor marketplace Platform with the Best Ecommerce Software Provider

The million-dollar question that has arisen in the minds of every budding entrepreneur is how to start a online multi vendor ecommerce platform. Full attention is needed while building a multi vendor marketplace platform. It is not as simple as you think. Only through this multi vendor ecommerce platform, you are going to be recognized by the vendors and the buyers. This multi vendor marketplace platform is going to earn you money so it cannot have any flaws.

One way of building a online multi vendor marketplace software is to build it from scratch. First, you need to hire a reputed multi vendor ecommerce platform development company that has ample knowledge about this field. Then you need to explain to them about your requirements and expectations.

They will develop and will show you the demo. During the demo session, you can let them know your modifications and they will also clarify your doubts. At last, your multi vendor marketplace platform will be ready to launch and you can start promoting your multi vendor marketplace software.

The major fact to be noted is, when you build a online multi vendor ecommerce platform from scratch you need to wait for a long time and you need to spend more on the development. If you are okay with it then you can proceed. Else you have another option to go with.

Another option is buying ready made online multi vendor marketplace software that will have all the essential features that are required to run the platform successfully. The software will be tested and proved so there will not be any flaws. You can instantly launch the software after purchasing.

You can get an instant solution to building a multi vendor online marketplace software. This method is quite very cost-effective and it is highly advisable for the startups that are new to this field. You can also customize the software to suit your business needs.

Must have Features in a multi vendor marketplace Platform

The features that are built in the online multi vendor ecommerce platform will determine the user experience and will gain customer satisfaction. Now let us check out the comprehensive features that are too in a multi vendor ecommerce platform.

  • Easy customization – the buying behaviors of the customers keep changing so the multi vendor ecommerce website should keep changing over a while. So customization is a default expectation in any multi vendor ecommerce platform.
  • Advanced search and navigation tool – the best user-interface will provide easy navigation and will let the buyers find the product in a simple way.
  • Payment gateways – the online multi vendor ecommerce website should have multiple payment gateways integrated with it. This will provide more convenience to the buyers
  • Secured website – the online multi vendor ecommerce platform should have an SSL configuration and should provide a secured transaction to the buyers and the vendors.
  • Multi-lingual and multi-currencies support – for reaching a global audience the online multi vendor ecommerce website should support multiple languages and currencies.
  • Review and ratings – the buyers expect this feature to be in the online multi vendor ecommerce platform they purchase the product.
  • Simple checkout – a complicated checkout process will make the buyers abandon the site. You need to have hassle-free checkout procedures in your online multi vendor ecommerce platform.

Revenue generation channels on a multi vendor marketplace Platform:

The main objective of building a online multi vendor ecommerce platform is to earn profit and generate more sales. This will be the ultimate motive for any entrepreneur. We need to know what are the revenue sources that a multi vendor marketplace software provides to the admin of the platform.

  • Commission fee – this is a mutual agreement made between the admin and the vendor where the vendor agrees to pay a certain percentage of commission on all products he sells through the online multi vendor marketplace platform. The commission percentage can vary from vendor to vendor.
  • Subscription fee – the admin can set a subscription fee and can make the vendors subscribe with the online multi vendor marketplace software and become a paid member of the platform. The membership needs to be renewed over some time.
  • Listing fee – the vendors will be charged when they want their products to be listed on the multi vendor marketplace platform.
  • Advertisement fee – you can allot some space in your online multi vendor marketplace platform for advertisement alone and can allow third-party to post their ads in the allotted space and you can charge them accordingly.\

How Products and Services are delivered in a multi vendor marketplace?

The multi vendor ecommerce platform will follow a hassle-free shipping and delivery process. This is where you can gain the maximum trust of your buyers and will also help you retain your customers effectively.

  • Once the order is placed by the buyer, the notification is sent to the concerned vendor from the multi vendor ecommerce platform.
  • The vendor will check the availability of the product and will arrange for shipping and delivery. In some cases, the admin of the online multi vendor ecommerce platform will take care of shipping and delivery.
  • The online multi vendor ecommerce platform will be integrated with shipping logistics and the logistic people will come and collect the product from the seller and will deliver it to the customers.
  • If a service is provided instead of a product then the service provider will get the notification and he will send his technical person to do the service to the customer place.

Conclusion

Understanding the importance and the functioning of a online multi vendor marketplace software will help you to build a flawless multi vendor ecommerce software. When you build a multi vendor marketplace platform with utmost perfection then you can easily win the market and can gain your audience’s attention with less effort.

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Feature Scaling. Why we go for Feature Scaling ?

What is Feature Scaling ?
Feature Scaling is done on the dataset to bring all the different types of data to a Single Format. Done on Independent Variable.
Some Algorithm, uses Euclideam Distance to calculate the target. If the data varies in Magnitude and Units, Distance between the Independent Variables will be more. SO,bring the data in such a way that Independent variables looks same and does not vary much in terms of magnitude.

#standardscalar #scaling-pandas #minmaxscalar #feature-scaling