Crude Oil Trading and Markets - Search Queries/Keywords Dataset
A dataset of over 1000 scraped search keywords, related searches and search suggestions related to crude oil markets and global oil pricing.
Update Frequency
Monthly
Key Fields
Crude Oil Related Keyword(s)
Avg. Search Volume (per month)
Keyword Difficulty (%)
CPC (USD)
Competitive Density (0-1)
Results (in Million)
Record Identifier
Date/Time Scraped (UTC)
Background
In the nineteenth and early twentieth century the global crude oil prices were relatively consistent. In the 1970s, there was a significant increase in the price of oil globally, partially in response to the 1973 and 1979 oil crises. In 1980, globally averaged prices spiked to over US$107.
Historically, there have been a number of factors affecting the global price of oil. These have included the Organization of Arab Petroleum Exporting Countries, led by Saudi Arabia, resulting in the 1973 oil crisis.
The Iran–Iraq War (1980–1988), the 1990 Invasion of Kuwait by Iraq, the 1991 Gulf War were chronologically adjacent events that accelerated price changes.
Fast forward to 2013, the oil supply glut that led to the largest oil price declines in modern history in 2014 to 2016. This 70% decline in global oil prices was one of the three biggest declines since World War II.
By 2015 the United States was the 3rd largest producer of oil moving from importer to exporter. The 2020 Russia–Saudi Arabia oil price war resulted in a 65% decline in global oil prices at the beginning of the COVID-19 pandemic.
Structural drivers affecting historical global oil prices include are "oil supply shocks, oil-market-specific demand shocks, storage demand shocks", "shocks to global economic growth", and "speculative demand for oil stocks above the ground". Source: Wikipedia, Our World In Data and the U.S. Energy Information Association
Overview
We created this dataset to better understand crude oil markets and pricing. At a minimum, this dataset provided us with critical context around crude oil conversations taking place today.
There are many tools to accomplish this goal. For example, real-time search trends and keywords are easily available through API's provided by Google, Bing and third-party vendors.
As one example, you could use the Bing Suggest API for "crude oil prices" or just "crude oil". Using this API, we can have real-time formatted search suggestions returned. You can keep running similar queries and capturing results overtime to build your own dataset.
You could also use other keyword generation tools that can automatically run queries and build results into a nice list. These tools typically input keywords into Google's Suggest API, and then add letters in alphabetical (or some other) order. And if you let these tools run long enough they can help you find a lot of keywords. This is another simple approach that helps aggregate more query data.
It is important to note that these tools provide insight into what is being searched for/suggested "right now" - but we need accurate data collected over a time-frame.
To accomplish this, we built a custom wrapper around these tools that runs for a specified time duration across multiple locations tuned for crude oil related queries. The dataset that you see here on AWS is a result of this approach. Output rows can include trailing dots (..) for some or even all of the rows. You can also download a sample to see exactly how the rows appear (scroll down to the sample download section below).
Overall, there are over 900 unique terms in the dataset. Here is a quick visual of a few top terms that appear in queries in the dataset. For example,"WTI" (i.e., West Texas Intermediate) occurs in over 50 queries and "oil" in over 1100 out of a total of over 1500 queries in the dataset.
The keywords were collected (over 3 months) using a custom web search scraping framework. Results from various search engines and locales were utilized. Duplicate keywords and those that were not relevant to crude oil were filtered. Note that this dataset is a subset of a broader crude oil-related data collection effort, so if you need additional crude oil keyword datasets, feel free to reach out.
Save time finding actionable crude oil trading and pricing related content. For example, consider running the queries in the dataset and reviewing the results. Or you could use the queries to better understand crude oil markets.
Fine tune crude oil trading strategy.
Have a professional 360 degree view of crude oil related queries.
Are you a first-time AWS user?
It's easy to get setup on AWS and takes no more than a few minutes.
Step 1 - Go to aws.amazon.com and click "Sign in to the Console"
Step 2 - On the Sign In page click "Create a New AWS Account"
Step 3- Fill in your email and payment details.
Here are some tips for Step 3:
Tip 1 - You will have the option to select between a "Personal" or "Professional" AWS account. The difference between these options is the information that AWS will ask you for. Both account types have the same features and functions. For example, if you are buying on behalf of a company and using a corporate credit card, consider picking Professional. Otherwise, consider picking Personal as your account type.
Tip 2 - You will also have the option of picking a support plan. Even if you go with Basic or free option initially, you can always upgrade your AWS support plan anytime.
After you complete Steps 1-3, a confirmation page appears that indicates that your account is being activated. Check your email and spam folder for an email message that confirms your account was activated. Activation usually takes a few minutes but can sometimes take up to 24 hours.
During activation, you can sign in to your new AWS account, but you might see a Complete Sign Up button. You can ignore the button. After you receive the activation message, you have full access to all AWS services.
Step 4 - At this point you should have an activated AWS account. You can now go ahead and subscribe to any AWS Data Exchange dataset. You can accomplish this by following the instructions at:
There is no other place where customers can find data files, data tables, and data APIs from a vast portfolio of third-party datasets. AWS continuously innovates to make the world's third-party data easy to find in one data catalog, simple to subscribe to with consistent pricing options, and seamless to use with AWS data and analytics and machine learning services.
Additional Questions?
If you have questions about this crude oil keywords dataset or other related datasets on AWS, contact us at awsdataexchange@refdb.org
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
This listing uses a single pricing dimension called Product Access (Units). You buy access to the dataset under one contract. The dataset contains crude oil trading and market search queries and keywords, curated for refining or fine-tuning large language models. There are no tiers, instance sizes, or usage add-ons to choose between. Pricing scales only by the number of access units you commit to under the contract term. All buyers receive the same product access through this one option.
Top-of-mind questions for buyers
What does one unit of Product Access grant me?
One unit grants access to the crude oil trading and markets dataset under your contract. The dataset holds search queries and keywords for the domain. Access units control how many entitlements you commit to, not separate data volumes or feature sets. Each buyer receives the same dataset through this dimension.
How is this dataset intended to be used once I have access?
The dataset is curated for refining or fine-tuning large language models in the crude oil trading and markets domain. You use the search queries and keywords to improve a model's accuracy and domain understanding. It is prepared as domain-specific training material rather than a live feed or software tool.
Does my cost change based on usage or data volume after I subscribe?
No. This listing uses one contract-based dimension with no usage metering or tiers. Your cost is set by the number of access units you commit to under the contract. Querying or processing the dataset does not add usage charges through this dimension.
www.refdb.org
Helpful?
Vendor refund policy
Refunds are not offered for this product.
How can we make this page better?
Tell us how we can improve this page, or report an issue with this product.
Give us feedbackReport a problem with this product or seller
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA).
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
This release contains information on West Texas Intermediate(WTI) crude oil prices. WTI is usually delivered in Cushing, Oklahoma. Cushing, Oklahoma is an important location for oil due to world oil prices being determined there as a result of WTIs being the most traded oil futures contract globally.
The Refining Margins & Crude Arbitrage dataset provides crude refining margin information for relevant crude grades in seven key refining centers around the world. The dataset also includes arbitrage calculation capability (~1,500 constructions available) between the available refining margins, enabling users to compare the profitability of refining different crude grades through a representative refinery by location and configuration.
S&P Global Energy World Refinery Database provides an in-depth, historical and forward-looking view of the entire downstream value chain, from crude inputs to detailed product outputs.