GroupBy

GroupBy tracking and usage

Websites using GroupBy by countrymarket share · top 8 countries
21%
🇺🇸US
3.8%
🇲🇽MX
3.8%
🇨🇦CA
3.8%
🇬🇧GB
3.8%
🇦🇺AU
1.9%
🇯🇵JP
1.9%
🇭🇳HN
1.9%
🇬🇹GT
Websites using GroupBy by industrymarket share · top 5 industries
Shopping
47%
Fashion & Beauty
21%
Wholesale & Distribution
16%
Manufacturing & Industrial
11%
Pharmaceuticals
5.3%
0%13%25%38%50%
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We track 53 websites using GroupBy, along with their country, traffic, industry and platforms. There are 11 websites using GroupBy in United States.

Filter by country
🇺🇸 United States11 sites
🇲🇽 Mexico2 sites
🇨🇦 Canada2 sites
🇬🇧 United Kingdom2 sites
🇦🇺 Australia2 sites
🇯🇵 Japan1 sites
🇭🇳 Honduras1 sites
🇬🇹 Guatemala1 sites
🇨🇷 Costa Rica1 sites
🇸🇻 El Salvador1 sites
🇵🇦 Panama1 sites

About GroupBy

GroupBy is an IT company headquartered in Toronto. It has been active since 2013. It is active in the field of eCommerce and serves as a product discovery platform. It is known for its reliance on Google Cloud Retail Artificial Intelligence and it comes with many capabilities. The platform is suitable for both B2B and B2C. GroupBy is known for giving a clear picture of customer shopping behaviour through its 360-degree view. It also helps improve the quality of the product catalogue. It provides high-quality searches and recommendations through its reliance on Artificial Intelligence and Machine Learning. It helps users with the process of extraction, transformation and loading of data.

Category
Search Engines
Official websitegroupbyinc.com↗

Websites using GroupBy

showing 25 of 53
WebsiteCountryTrafficIndustry
cvs.com🇺🇸USTop 5KPharmaceuticals
jared.com🇺🇸USTop 50KFashion & Beauty
officedepot.com.mx🇲🇽MXTop 50KWholesale & Distribution
kay.com-Top 50KFashion & Beauty
shopmyexchange.com🇺🇸USTop 50KShopping
bjs.com🇺🇸USTop 50KShopping
motion.com🇺🇸USTop 100KManufacturing & Industrial
wbmason.com🇺🇸USTop 100KWholesale & Distribution
neweracap.jp🇯🇵JPTop 100KFashion & Beauty
applied.com🇺🇸USTop 100KWholesale & Distribution
mybinding.com🇺🇸USTop 500KShopping
kayoutlet.com🇺🇸USTop 500KShopping
ernestjones.co.uk🇬🇧GBTop 500KShopping
peoplesjewellers.com-Top 500KFashion & Beauty
banter.com🇺🇸USTop 500KShopping
hsamuel.co.uk🇬🇧GBTop 500KShopping
zalesoutlet.com🇺🇸USTop 500KShopping
radioshack.com.mx🇲🇽MXTop 500KShopping
motioncanada.com🇨🇦CA-Manufacturing & Industrial
zales.com-Top 50K-
binding101.com-Top 500K-
cabelas.ca🇨🇦CATop 500K-
officedepot.com.pa🇵🇦PATop 1M-
officedepot.com.sv🇸🇻SVTop 1M-
officedepot.co.cr🇨🇷CRTop 1M-
Showing 25 of 53 websitesView detailed list →

Frequently asked

What are some common uses of GroupBy technology?›
GroupBy technology is widely used for various purposes, including data analysis, report generation, trend identification, and statistical calculations. Some common operations performed using GroupBy are sum, average, minimum, maximum, and counting of grouped data.
What is GroupBy technology?›
GroupBy is a technology that is primarily used in databases and data manipulation tools, such as SQL, Pandas, or Excel, to organize and aggregate data into meaningful groups based on certain criteria or shared characteristics. This helps in performing efficient analysis, filtering, and summarization of large datasets.
How does GroupBy work with multiple columns?›
When using GroupBy with multiple columns, data is organized into groups based on the unique combinations of values in the specified columns. This allows users to categorize and aggregate data based on the defined multi-dimensional hierarchy, enabling more complex analysis to be performed.
Can I use GroupBy with non-numeric data?›
Yes, GroupBy technology can be applied to non-numeric data as well. Depending on the data manipulation tool being used, you can perform various operations on grouped non-numeric data, such as concatenation, counting, or applying custom functions, to gain insights or transform the data.
What are some common challenges with GroupBy technology?›
While GroupBy is a powerful tool, users may face challenges like managing very large datasets, handling missing or inconsistent data, selecting appropriate aggregation functions, and understanding the implications of the chosen operations on the data. Proper data preprocessing, knowledge of available functions, and careful interpretation of results can help overcome these challenges.

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