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Looking to gain a competitive advantage with specialized insights into consumer sentiment, user behavior, and competitor strategies? Alternative data gives you that edge with valuable information from novel sources that include social media websites, mobile application data, search engines, and much more.
Alternative data is literally an “alternative” to traditional data such as economic reports, investment news, press releases, corporate annual reports, consumer reports, and trade journals. The key difference is the publisher. While traditional data tends to get published by established agencies and firms, alternative data typically comes from digital, user-generated sources.
The current nature of alternative data is precisely what makes it so relevant, leading to an explosion of its use in recent years. According to Grandview Research, the market size for alternative data in 2020 was valued at $1.72 billion and is expected to grow at a compound annual growth rate of 58.5% from 2021 to 2028. This growth rate, coupled with an increase in use cases, may even lead to alternative data becoming less of an “alternative” and more of a mainstream source of information as its use overtakes traditional data across the investment and e-commerce spaces.
“Retail and e-commerce sectors were among those most affected, both positively and negatively, by the COVID-19 pandemic. Businesses had to undergo massive changes or be swept away by the changing landscape. As a result, we can see that a large portion of companies are now attempting to optimize their performance through newly available data sources on the web.“
– Tomas Montvilas, Chief Commercial Officer, Oxylabs.io
Oxylabs’ latest survey of 250+ senior data decision-makers from leading retail and e-commerce businesses across the UK revealed that roughly 52 percent obtained data via integrations with 3rd party databases, 48 percent purchased data sets from data vendors, and 47 percent used data scraping and manual data collection.
Data scraping (also known as data extraction or web scraping) uses scripts to crawl the web, extract publicly available data, and parse (or “clean up”) the data to prepare it for use by analysts. While web scraping methods may vary widely across businesses, two typical scenarios include:
In-house web scraping requires a team of developers, system administrators, data analysts, and data specialists to create and configure the scripts that crawl and extract data from the web. Typically favored by large companies, in-house operations require a substantial capital outlay to conduct and maintain the process and offer benefits such as increased flexibility and customization.
Demand for solutions on a smaller scale has led to the development of ready-to-use, customizable web scraping tools that smaller companies can use to conduct web scraping on a budget. Besides being cost-effective, these applications reduce the management and development burden. They can also lead to better efficiency by allowing businesses to divert focus from the complex extraction process to deriving insights for use in business strategies.
Manual data collection is exactly as it sounds: the manual collection of data via copying/pasting or downloading from digital sources. The manual data gathering uses standard spreadsheet programs to clean the data before analysis along with the extraction process. When contrasted to web scraping – which can extract hundreds of pages in seconds – the manual collection is time-consuming, inefficient, and subject to human error.
Use cases for alternative data span marketing to pricing strategies and are growing continuously as the amount of user-generated data on the internet increases.
Some current ways you can use alternative data include:
Scraping public social media sites to learn about popular products in different categories
Extracting user-generated content from public social media sites for use in pricing strategies
Scraping review sites to gauge sentiment for use in product development
Extracting data on competitors, including popular products and keywords used in product descriptions
Scraping consumer data from e-commerce sites for use in upsells and cross-sells
Extracting data from e-store to gain insights into user behaviour for use in site optimization and marketing, including actions taken, products clicked, status updates, comments, and reviews
Scraping for keywords used in comments and reviews to refine marketing on the website, email, and social media
Monitoring price differences for use in dynamic pricing strategies
“E-commerce and retail sector’s exponential growth and rising global importance led us to look deeper into the transformation it went through. These business fields were always heavily driven by data, precise calculations, and predictive analytics. Therefore, we focused partly on data management as the digitalization of business opened new areas of opportunity. We hope our survey will reveal the same insights to decision-makers in every sector and lead to data collection and management adoption amongst them.“
– Julius Černiauskas, Chief Executive Officer, Oxylabs.io
The e-commerce industry is investing more time and resources than ever before into creating strategies for scraping alternative data. Oxylabs’ survey of over 250 e-commerce company executives is now available as a whitepaper, offering valuable insights into how alternative data is being obtained, how it is being used, and who is using it.
How widespread is the use of alternative data for e-commerce in the UK?
What businesses are using alternative data? What sizes and which sectors?
How is my competition collecting alternative data?
Has COVID-19 impacted data collection practices and budgets?
What challenges are my competitors facing when collecting data?
What alternative data and web scraping strategies are my competitors planning to use in the upcoming year?
To get the answers to these questions – and much more – download our whitepaper: The Growing Importance of External Data in the E-Commerce Industry.
About the author
Vice President, Global Partnerships
For over 15 years, Gediminas Rickevicius has been a force of growth for leading information technology, advertising, and logistics companies around the globe. He has been changing the traditional approach to business development by integrating big data into strategic decision-making. Currently, as a Vice President, Global Partnerships at Oxylabs, Gediminas continues his mission to empower businesses with state-of-art solutions for web data extraction.
All information on Oxylabs Blog is provided on an "as is" basis and for informational purposes only. We make no representation and disclaim all liability with respect to your use of any information contained on Oxylabs Blog or any third-party websites that may be linked therein. Before engaging in scraping activities of any kind you should consult your legal advisors and carefully read the particular website's terms of service or receive a scraping license.
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