The 2006 quote from Clive Humby, “Data is the new oil,” signifies its importance in the knowledge economy. But just as refining crude oil, we get valuable products; data refinement and analytics churn actionable information. Most likely, your competitors already have a fact-driven strategy in place, as everyone – investors, marketers, brands, manufacturers, retailers, and supply chain players – are looking for crucial information to gain competitive advantage.

The conventional sources of information include industry journals, newspapers, and government reports. More recently, businesses are rapidly exploring and utilizing alternative data. A properly designed web scraping strategy can overcome many of these challenges.

Sources of Alternative Web Data

Unlike the traditional sources, alternative data comes from, you guessed it, alternative sources. These include, among others:

  • Social media feeds, posts and comments
  • Communications metadata from emails
  • Web scrape from blogs and articles
  • Crowdsourcing on online message boards
  • Credit cards and POS systems usage data
  • Social media sentiments (hashtags, likes, dislikes, love, anger, etc.)
  • Web search traffic
  • Geolocation details
  • Weather and climate facts

Alternative data is unstructured and does not conform to any conventional notions of databases. By choosing proxies for web scraping, your scraper remains anonymous. The sentences may be malformed; there may be incorrect spellings, too much use of acronyms & abbreviations. Many articles may not even have a verified author to analyze her other online activities.

For this, you can use residential IPs. One of the most important reasons to use residential IPs is to eliminate your chances of getting detected and blocked. It provides a largely untapped, almost impossible to manipulate source, to read and understand the current public sentiments.

Process of Web Scraping

Analysts need to put in a lot of effort to collect and refine alternative data as it is mostly unstructured and needs categorization by multiple parameters.

Data analytics is applied to this aggregate information to analyze competition, market trends, pricing decisions, and new product offerings.

However, web scraping is not an easy task and has its share of challenges too.

  1. Restricted bot access
  2. Complicated and ever-changing web page structures
  3. IP blocking and use of honeypot traps
  4. Slower load times, dynamic content, and CAPTCHA
  5. Data may be behind a login or paywall

Use Proxies for Web Scraping

  • A Proxy acts as an intermediary between you and the internet, hiding your true identity (IP) behind itself. A scraper may need to scan a website hundreds of times each day, raising alerts at the target web servers. It can result in an IP ban or blocking.
  • Proxies generate new IP using rotation strategy, provide geography-specific IP addresses to overcome geo-restrictions.

Use residential IPs

  • Residential proxies can be static, where each scraper is assigned a dedicated IP address. It is needed to fill online forms, online transactions, or access geo-restricted content. The IP address belongs to an ISP, and the target web server may not flag it.
  • IP addresses can be dynamic or continually changing, mainly in web scraping, data mining, or cop sneakers, where each iteration requires a new IP address.

Web Scraping and Analytics for Alternative Data

We collect massive amounts of online data in web scraping using a search-engine-like crawler. It scans social media, news websites, blogs, articles, and online retail stores.

The web scraping bots use one link to parse the entire network of interconnected sites to download the maximum amount of relevant or related material.

The crawler collects targeted information like product details, pricing variations, shipping info, refund policies, product searches, web traffic, service terms, and customer reviews.

The Seven Main Reasons for using Web Scraping and Data Analytics:

1. Apply dynamic pricing strategy

In dynamic pricing, a store adjusts the prices continuously, sometimes within minutes, in response to real-time demand and supply data. For example, Amazon updates its rates every 10 minutes.

Airlines’ pricing buckets, surge pricing in taxi-hailing apps, and hotel booking portals are dynamic pricing examples.

2. Market research

To better understand the competitive landscape, you need as much data on your products and services and all known and any potential competitors. The analysis reveals target audiences and their needs, market trends and projections, and customer feedback about current services.

Let’s say you are in the online education business. Before finalizing new geography to launch your program, you want to analyze potential alternates, their potential market, and competitors’ presence.

We can filter web searches and social media conversations for such a service from different alternates using web scraping. We can then help you identify the best candidate to launch your services.

3. Improve your decision making with real-world data

Millions of people share their views on social media posts and comments, generate web search traffic, and use their cards. It is nearly impossible to fudge the facts on such a grand scale.

With real-world info available in real-time, you can ascertain consumer feedback and perception and improve the decision-making process related to the concerned matter’s decision-making process.

4. Monitor your industry and competitors

Understanding the current scenario in the industry is very crucial. Contemporary research on the industry’s state can help you draw up a SWOT analysis and threat-perception matrix to deal with any potential challenges.

For example, let’s say you are operating a food delivery app. Details for parameters like the number of downloads for your and competitors’ apps, number of active users, the weekly number of orders placed, number of tweets tagging you or them, etc. all provide deep insights.

5. Better Risk Assessment

Every business has its fair share of risks. As an industry player, you need to know about the apparent dangers and imminent threats. These may come from climate change, government policy change, social unrest, or any other reasons.

Web scraping can help you flag such potential threats raised by concerned citizens in newspaper articles, social media campaigns, and public records. Forewarned is forearmed.

6. Fulfill the Unmet Consumer Demands

Even if you don’t have a readily available product or service, you may still find visible data analysis patterns pointing towards an unmet demand.

Conclusion: there may be a niche group of people concerned about it and talk among a small circle of enthusiasts. Tapping such markets can be very lucrative and may result in profits from the word go.

7. Geolocation Data

You can identify a general pattern for a typical shopper with scraping and analysis of different users’ geolocation details. It can help you identify a key location on their movement path, to place a physical storefront or advertisement for an online store.


As we all know that web scraping makes sure that you follow the procedure hassle-free, there is one more element that can advantage you to conduct this method in a safe manner. The use of proxy servers can confirm the correct security of web scraping activities.

Efrat Vulfsons is a data-driven writer and freelance publicist, parallel to her soprano opera singing career. Efrat holds a B.F.A from the Jerusalem Music Academy in Opera Performance.

Web scraping stock photo by Profit_Image/Shutterstock