We are at AMZ Innovate, New York from 13-14th November, 2023. We are also hosting a breakout session exclusively for Amazon Sellers. Meet us there for data chats & more!
Amazon-MWS-to-Snowflake-Made-Easy | Saras Analytics

Amazon MWS to Snowflake – Made Easy

14 minutes read


Table of Contents

Before we jump into what Amazon MWS is and how to replicate Amazon MWS to Snowflake and streamline reporting and analysis for Amazon sellers, let us look at why Amazon is such an important channel for sellers and what challenges sellers can overcome if they have access to their Amazon Seller data. If you want to jump right to the “Use a cloud data pipeline” section.

eCommerce is a competitive space and coronavirus or COVID-19 is going to make E-commerce even more competitive as retailers that hitherto have not taken to e-commerce are now going to embark on a new journey to start selling online. There are many avenues for sellers to sell their products online. An easy way to get started with ECommerce and validate an idea is by selling on an established marketplace. Marketplaces like Amazon simplify the selling process by providing the entire infrastructure needed for sellers.

Once sellers gain traction and sellers can prove that their products have demand, they can then expand their investments into selling their products more aggressively within Amazon as well on other channels as well. This model of selling in a marketplace works for many businesses where creating a brand is not necessary, but the attributes of the product are sufficient to generate revenue. For many sellers, marketplaces have become a necessity because an increasing number of people are buying from marketplaces is more than they buy from individual e-commerce websites. Amazon Seller Central is the seller portal to manage and sell on the global Amazon marketplace.

There are many popular marketplaces, but none are as comprehensive and as ubiquitous as Amazon.com. The growing popularity of Amazon.com is driven primarily by its prime membership program, arguably the most popular membership program in the history of membership programs has ensured that over 300 million people shop on Amazon.com and its subsidiaries annually.

Amazon.com is a self-contained ecosystem that provides sellers with all the tools that they need to market, sell, and fulfill their orders without using any other third-party tools. However, it is rare for any serious seller to rely only on Amazon.com or its subsidiaries as their sales channel. There are many reasons for not limiting oneself from selling on Amazon. None is more important than the fact that the risks of selling products in a single marketplace are so high that a change in rules of the marketplace or the company operating the marketplace deciding to sell a similar product might turn out to be a death knell for the seller’s business.

Market places also make it very different for brands to differentiate themselves by creating unique user experiences that make shopping a fun experience for customers. There are many combinations of channels that sellers use to promote and sell their products. They may choose to sell their products on their

  • On a branded website
    • There are many e-commerce platforms that the seller could choose from to run their own branded site. Some of these e-commerce platforms include Shopify, BigCommerce, Magento, WooCommerce, Kibo Commerce, Volusion, VTex, and many others.
  • On multiple market places including
    • Walmart
    • Flipkart
    • Myntra
    • Wayfair
    • Lazada
    • and many others.
  • On Amazon.com and its subsidiaries
    • Amazon.com in the US
    • Amazon.co.in in India
    • Amazon.ca in Canada
    • Amazon.co.mx in Mexico
    • and in many other countries.
  • In multiple retail outlets
    • Nordstrom, Target, Macy’s, and others.

Complexity increases with the addition of every sales channel. Not only is this complexity limited to operations, technology, people, but one of the biggest challenges is to identify effective ways to market products in each sales channel. For instance, if we consider marketing channels available to support online business, you will find a choice of:

  • Social Media ads
    • Some platforms include Facebook Ads, Instagram, LinkedIn, Twitter, and others
  • Digital ads and re-marketing
    • Criteo, Taboola, Outbrain, and others
  • PPC
    • Google ads, Bing ads, and others
  • Email
    • Mailchimp, Klaviyo, Hubspot, and others
  • Podcasts
  • Affiliate
    • Refersion, CJ Affiliates
  • Influencer marketing
  • Offline marketing and more

Choice, while being a great virtue, leads to complexity and this complexity when not managed properly, can, in turn, impact the efficiency of running an eCommerce business. Most eCommerce businesses grapple with this complexity; some well and many not so well.

In a competitive digital landscape that we live in, it has become imperative that eCommerce businesses of all sizes that aspire to grow and stay profitable have to look into their data deeply and leverage this for growth.

With the increase in competition, eCommerce Companies should strive to be more data-driven for various reasons. Some of these reasons include

  • Understanding the balance between demand and supply,
  • Finding opportunities to reduce wasteful spend,
  • Promote the right products
  • Optimizing digital assets to maximize revenue for the same marketing spend,
  • Improving ROIs on Ad campaigns and
  • Offering an engaging and seamless experience for customers in every channel that the customer engages with the brand.

Businesses these days need to be efficient in terms of their data analysis. They are struggling to make sense of the data generated from various applications and tools used to manage different processes efficiently.

Due to the reasons highlighted above, any eCommerce business typically operates at least 10-15 different software/platforms to deliver on their customer expectations. As a result, data silos are created, which makes it more difficult to consolidate data and use the data for reporting, operations, analysis, and taking informed forward-looking decisions.

For many sellers, Amazon.com happens to be the lifeblood of the business. In contrast, for many sellers, Amazon.com happens to be a channel to drive awareness about their products and to eventually leverage this awareness into traffic and revenue on their own branded site running on one of the platforms listed above. Regardless of which channel is seller decides to sell their products it is vital for them to track their business KPI’s daily, hourly if possible, to ensure that the business is profitably and operations are smooth.

Amazon Marketplace Overview

Amazon Marketplace is the fastest growing online marketplace with an active customer base of 310 million. This user base and the sellers who are interested in selling to this user base are both growing in double digits every year. Amazon is also on an international expansion spree. Amazon’s global marketplace provides sellers with an excellent opportunity to sell to a worldwide market with relative ease. However, fierce competition means that there is constant pressure on margins for sellers. Sellers need to do whatever is in their power to optimize outcomes from selling on Amazon.com and its subsidiaries.

The best performing sellers on Amazon are the ones who take advantage of the data that is available on Amazon.com and use the data and insights for growth. Amazon provides numerous reports to manage the day-to-day operations of selling on Amazon marketplace. However, these reports fall woefully short when it comes to performing an in-depth analysis of the performance of the channel.

Snowflake Data Warehouse Overview

Snowflake Data Warehouse is a widely used cloud data warehouse used by both start-ups and Fortune 500 companies. A cloud data warehouse acts as the consolidated data store for data generated in the business. Snowflake is a fully managed cloud service that enables analysts to forget data infrastructure management and focus their effort on analysis and business value generation. Snowflake is a Petabyte scale data warehouse that is affordable for businesses large and small.

For more information on Amazon MWS Data Connector, you can visit the linked article.


Why Do Businesses Need to Replicate Amazon MWS to Snowflake?

Sellers on Amazon typically rely on analysts who perform daily downloads of reports from Amazon.com. A channel manager or analyst is generally in charge of implementing this activity. They usually leverage reports available on the platform portals to report on the performance of the channel to their executive management. However, as channels grow, the problems grow along with them. What happens when

  • Products get sold in multiple Amazon marketplaces?
  • Products get promoted in each of these marketplaces?
  • There are other channels where sales are happening?
  • There is marketing spend on social media, podcasts, athletes, email marketing, others?
  • Sellers don’t use FBA, and you decide to ship products on your own?

Relying on manual reporting is a sure-shot way to ensure an under performing channel. We all have a limited amount of time every day to spend on managing, tracking, and improving business performance. The more time people spend on enhancing business performance, the more chance a business owner has to improve his company’s performance. If people have to log into multiple systems every day to

  1. run reports,
  2. wait for the reports to complete
  3. download those reports,
  4. copy the data over to a spreadsheet,
  5. run the Excel macros and then
  6. discover what is happening in their business.

And repeat this activity for every channel and every country, then, it is fair to say that there is just way too much time spent on unproductive endeavours. Manual reporting leaves less time for critical resources to think and strategize on improving business performance. Freeing up an analyst time from manual reporting can leave time for many kinds of analysis that may not have been possible or may have been possible but less frequently to address questions like the ones below:

  • How do you determine profitability?
  • How do you determine the LTV of your customers?
  • How do you determine a plan for future based on data from previous years?
  • How do you determine the impact of promotions?
  • How do you determine trends in customer support requests?
  • How do you identify which products to promote in your Amazon marketing efforts?
  • How do you determine which keywords to use in Amazon Ads?
  • How do you determine which products give you the best margin?
  • How do you determine profitability across products, countries, categories, and other dimensions?
  • How are shipping fees impacting profits?
  • How are commissions eating in to profitability?
  • How do you improve conversion rates?

Amazon recognizes this and has provided another way for businesses to get access to the data. It is called Amazon Marketplace WebServices (MWS). Amazon MWS offers a set of APIs that allow developers to extract data from Amazon.com and periodically and to submit reports on behalf of the seller by leveraging code.

What data is available using amazon marketplace web services?

Amazon MWS APIs are available for data extraction in a few broad categories. They are

  • Amazon Product APIs
  • Amazon Shipment APIs
  • Amazon Order APIs
  • Amazon Fulfillment APIs
  • Amazon Sales API

Replicating data from Amazon MWS to Snowflake

There are a couple of options to gain control of your Amazon MWS data for in-depth analysis and to build comprehensive channel reporting. For both these options Amazon MWS APIs are required. A thorough understanding of business requirements and the functioning of the Amazon Marketplace APIs is essential before developing the code needed to pull data from Amazon.

Build your Custom Data Pipeline

To build support for extracting data using Amazon APIs, the developer or analyst will have to follow the steps.

  1. Register with the Amazon Developer Portal
  2. Create API tokens also known as MWS Auth Token to pull data from Amazon MWS
  3. Read and understand API documentation thoroughly using the links above
  4. Handle Amazon Marketplace API rate limits to avoid getting blocked by Amazon or getting data slowly. Listed at the end of the article is a full list of all the rate limits of Amazon MWS APIs.
  5. Handle different data types used in the KPI’s for efficient data storage
  6. Schedule the API calls frequently to pull new data generated in the platform.
  7. Handle errors, changes and upgrades to the APIs, which happens quite frequently
  8. Handle notifications so that you are alerted when a script has failed.
  9. Handle incremental data extraction and avoid full data extraction with every replication task

Below are the links to crucial APIs and reports that you may need to pull Amazon Seller Central reports and other Amazon MWS APIs:

Although you may not need all the reports, there are definitely a few important reports that when automated can provide a great deal of opportunity for brands to optimize their Amazon channel. All these reports have their own quirks and operate under rate limits that Amazon enforces. Developers who intend to pull data from Amazon marketplace using Amazon marketplace APIs (Amazon MWS APIs) are required to understand the above mentioned reports, their data structures, and rate limits.

Once you have automated the extract of data using Amazon Marketplace APIs and you manage to save the data as a CSV or a JSON file, you can use the file to load Amazon MWS data into Snowflake. You can leverage Snowflake loading routines to accomplish the task of loading data.

You can leverage Snowflake loading routines to accomplish the task of loading data. However, understanding how to do it right is important and the links below can help.

  1. Snowflake loading features overview
  2. Understand the considerations to load data
  3. Using the COPY commands to load batch data

Use a Cloud Data Pipeline

Building support for APIs is not only tedious but it is also extremely time-consuming, difficult, and expensive. Engaging analysts or developers in writing support for these APIs takes away their time from more revenue generating endeavours. Leveraging a cloud data pipeline like Daton significantly simplifies and accelerates the time it takes to build automated reporting. Daton supports automated extraction and loading of Amazon MWS API data into cloud data warehouses like Google BigQuery, Snowflake, Amazon Redshift, and Oracle Autonomous DB.

Configuring data replication on Daton on only takes a minute and a few clicks. Analysts do not have to write any code or manage any infrastructure but can still get access to their Amazon MWS API data in a few hours. Any new data is generated is automatically replicated to the data warehouse without any manual intervention.

Daton supports replication from Amazon MWS API to a cloud data warehouse of your choice, including Snowflake Data Warehouse. Daton’s simple and easy to use interface allows analysts and developers to use UI elements to configure data replication from Amazon MWS to Snowflake. Daton takes care of

  1. Authentication
  2. Rate limits,
  3. Sampling,
  4. Historical data load,
  5. Incremental data load,
  6. Table creation,
  7. Table deletion,
  8. Table reloads,
  9. Refreshing access tokens,
  10. Notifications
  11. Infrastructure
  12. Access management, and

many more important functions that are required to enable analysts to focus on analysis rather than worry about the data that is delivered for analysis.

Daton – The Data Replication Superhero

Daton is a fully-managed, cloud data pipeline that seamlessly extracts relevant data from many data sources for consolidation into a data warehouse of your choice for more effective analysis. The best part analysts and developers can put Daton into action without the need to write any code.

Here are more reasons to explore Daton:

  • Support for 100+ data sources – In addition to amazon MWS, Daton can extract data from a varied range of sources such as Sales and Marketing applications, Databases, Analytics platforms, Payment platforms and much more. Daton will ensure that you have a way to bring any data, including Amazon MWS to Snowflake Data Warehouse and generate relevant insights.
  • Robust scheduling options allows users to schedule jobs based on their requirements using a simple configuration step.
  • Support for all major cloud data warehouses including Google BigQuery, Snowflake, Amazon Redshift, Oracle Autonomous Data Warehouse, PostgreSQL and more.
  • Low Effort & Zero Maintenance – Daton automatically takes care of all the data replication processes and infrastructure once you sign up for a Daton account and configure the data sources. There is no infrastructure to manage or no code to write.
  • Flexible loading options allows to you optimize data loading behavior to maximize storage utilization and also easy of querying.
  • Enterprise grade encryption gives your peace of mind
  • Data consistency guarantee and an incredibly friendly customer support team ensure you can leave the data engineering to Daton and focus instead on analysis and insights!
  • Enterprise grade data pipeline at an unbeatable price to help every business become data driven. Get started with a single integration today for just $10 and scale up as your demands increase.

Interested in learning more about data warehouses, their architecture, and how they are priced? Checkout our other articles.

We Saras, can help with our eCommerce-focused Data pipeline (Daton) and custom ML and AI solutions to ensure you always have the correct data at the right time. Request a demo and envision how reporting is supercharged with a 360° view.

  • What exactly is Amazon MWS?
    Signature-based authentication and delegated calling rights for vendors via the Amazon MWS authorization service make Amazon Marketplace Web Service (Amazon MWS) a secure environment. By seamlessly syncing information including orders, payments, and stock levels, MWS facilitates Amazon sales for merchants and suppliers. The integration of this data enables the automation of many tasks. Anyone with a business account on Amazon can use Amazon MWS at no cost. Amazon Product Advertising, Amazon Vendor Central, and Amazon Web store accounts are all valid options. To gain access to Amazon MWS, individual sellers can switch to a Professional seller account.
  • How can I acquire MWS tokens?
    You may verify that Seller Labs is a trusted third-party app developer by visiting the page where you manage your installed apps. Under the MWS Auth Token column, you’ll find a little blue link called View to the right of the Seller Labs developer row. As such, it serves as an API for both Amazon’s Vendor and Seller platforms. The MWS API, which was only used by sellers, has been replaced by the newer, more standardized SP-API suite.
  • What is Snowflake?
    Snowflake is a cloud-based data warehouse that provides a centralized location for storing and processing your data. Data loading, integration, and analysis can be performed with infinite scalability. The effectiveness and simplicity of its design are the key factors. Because to its columnar data organization and micro-partitioning storage architecture, Snowflake is able to process analytics queries at a considerably faster rate than a standard SQL (Structured Query Language) database. Snowflake can communicate with other BI, data integration, and analytics platforms without any additional configuration. In order to connect to external services, Azure provides integration capabilities including logic applications, API Management, Service Bus, and Event Grid. The user and AWS share the burden of data protection.
  • Could Snowflake replace Amazon Web Services?
    Snowflake’s ecosystem and integration are more comprehensive, as it includes support for ETL and BI tools, whereas WPS’s are more limited. In contrast to Snowflake, which requires zero management, using Amazon Web Services (AWS) necessitates time-consuming management because customers are responsible for their own cloud’s security. Using the interface provided by the Snowflake Connector for Python, programmers can write programs in Python that establish a connection to Snowflake and carry out any of the usual tasks. It’s an alternative to writing code in Java or C/C++ to access databases using Snowflake’s JDBC or ODBC drivers. Relational and semi-structured data are both stored in databases, as is the case with both Snowflake and Oracle storage. All information is kept in a single layer, requiring only a single round of changes. Compute is the part of the architecture that processes the queries.
  • Is Snowflake a server or database?
    Snowflake is a relational database that can be hosted in the cloud and used to create data warehouses. It is based on the cloud infrastructures of Amazon Web Services, Microsoft Azure, and Google Cloud Platform, and it combines the features of conventional databases with several novel ones. It’s one of a kind since it adapts to the requirements of modern businesses. Retraining to Snowflake is pretty straight forward if you have SQL experience, therefore no, Snowflake is not difficult compared to other programming languages.
  • Start your 14 day Daton Free Trial
    Explore Solution for Brands | Saras Analytics
    New call-to-action
    Contact us