Oxylabs’ 2020 Trend Report: Residential Proxies

The fourth part (out of six) of our annual trend report The Rising Demand for Data: Oxylabs’ 2020 Trend Report is out! In this part, you will learn all about how Oxylabs’ clients used our residential proxies in 2019. Read the previous part which details specific Case Studies here!

For a shorter summary, we’ve written the key takeaways for you as well. However, we urge you to read the full report for a more comprehensive understanding. This can be easily done by entering your email in the form below and downloading the file. 

• In 2019, there was a 165.3% growth in the total number of requests. 

• Meanwhile, total residential proxy traffic volume grew by an impressive 177.5% in 2019.

• The 2019 spikes in traffic volume were directly related to the e-commerce industry’s economic stimulation, starting with the initial preparations for Black Friday to the Christmas period.

Global companies indicate an increasing demand for residential proxies

Research conducted by Oxylabs Data Analysis Department has found that in 2019, there was an astonishing 165.3% growth recorded in total requests volume via residential proxies, compared to 2018 historical data.

On the subject of residential proxy traffic in 2019, there was a substantial 177.5% surge noted in total traffic volume, compared to 2018 residential proxies’ recorded metrics.

Taking a closer look at the residential proxy requests and the traffic graph below, we can see that the most prominent period was noted from mid-November until the end of 2019, which correlates with datacenter proxies’ recorded metrics.

The increase in traffic volume is directly related to the e-commerce industry’s economic stimulation, from the initial preparations for Black Friday to the Christmas period. Our clients were mainly gathering data for product and pricing intelligence, in order to stay competitive and increase the volume of sales. 

Residential proxies remain an excellent solution for almost any web scraping job due to the low probability of them being identified as automated traffic by even the most protected data sources, as statistics reveal.