Competitive Intelligence Through Data Scraping

10 min readJun 14, 2024

Every company in the online market faces inevitable competition of some kind from companies that sell similar products and services. While on one side, it provides consumers with multiple options for products, services, price brackets, and quality, it poses a challenge for businesses. Brands have to work harder to attract customers when there are so many competitors pitching their products/services with lucrative offers and variations.

To differentiate, brands must have a ‘competitive moat’ or the ‘x-factor’ that fends them against competition and makes them stand apart in crowded e-marketplaces. Competitive Intelligence is the way to ensure you have them both. But how do you gather competitive intelligence data and how do you use it? One of the most popular methods for gaining competitive intelligence is data scraping or web scraping.

This article focuses on how you can gather competitive intelligence with data scraping. The article also details its importance, and use cases. Finally, the article also suggests the best practices for extracting data for competitive intelligence.

Let us first understand what competitor intelligence is when it comes to online businesses.

What is Competitive Intelligence?

Competitive Intelligence (CI) is the information or data that you possess about your online competitors that can be analyzed to make decisions that help you get ahead of your competitors.

In an extended way, competitor intelligence is all about the data analysis of the target audience, price points, product information, sales dynamics, CRM activities, promotions & marketing funnels, social media presence, selling regions, and brand positioning of your key competitors. The data analysis of these aspects provides insights into how your competitors sell, what inventory they keep, how they price their items, what content they write in product descriptions etc. These insights are referred to as competitor intelligence.

So, Gathering CI will Involve Two Steps:

You gather the required data for competitive intelligence
You analyze the data to obtain competitive insights

Key Sources of Competitive Intelligence Data

Competitor intelligence data needs to be extracted from reliable sources. The most authoritative and genuine sources of pulling out competitor intelligence data are as follows:

Competitor Websites
Search Engines Results
E-commerce Platforms
Online marketplaces
Social Media Profiles and Pages
Review and rating Websites
Google Reviews
Online databases
Live News Websites
Recent Press Releases
Product Pages on Google Shopping
Market research websites
Consumer Forums and Discussion boards
Industry publications
Competitor marketing materials
Competitor digital ads

Which Data Should You Gather For Competitive Intelligence?

While all your market competitors together may be generating thousands of gigabytes of data every year, month, or even in a week or day, you need not gather all their data. You need only the key insights that can help you gain a competitive edge.

The Data You Should Focus On For Extraction Includes:

Target Audience that your competitors are pitching their products/services
Markets where your competitors sell
Price points at which products and services are charged
Product descriptions written by competitors including product meta description
Discount offers, promotional deals, and coupons offered by competitors
Reviews and feedback of competitors on Google reviews, review platforms, and social media
Social media mentions and sentiment data
Product comparison sites, newsletters, research sites
Cart data on ecommerce sites where your competitors sell

Why is Competitive Intelligence Important?

Neglecting what competitors are doing can get you out of the business. See the example below to understand why competitor intelligence is crucial.

Suppose your competitor sells 5 types of home office tables on Amazon. One of the tables sold by your competitor has four unique features that the tables marketed by you don’t have. First, it has features that prevent the laptop from falling from the table. Second, it has a smart system for adjusting heights, which makes it compatible with sitting on both a bed and a chair. Third, it has a cantilever design that helps it get close to your body while sitting on the bed as the wheels will go inside the space below the bed. Lastly, it has an ergonomic footrest as an added benefit. These features are very crucial differentiators for people who work from home. These four features alone are enough to kill your business if you are selling tables without these features.

The difference is evident. Table A with those four unique features sells more than its competitor Table B which is visible in the almost 10X reviews that it has garnered. If you collect data from your competitors and analyze it with the proper tools, you will know what are your competitors’ product differentiators.

Competitive intelligence is critical to knowing your competitors better. But can you manually check the whole Amazon Website to find such data? With thousands of SKUs, it will be impossible to do it manually. This is where you need data scraping. With web scrapers, you can continuously get such data for smart analysis.

What is Data Scraping for Competitive Intelligence?

While there are many ways to obtain competitor intelligence data like market reports, competitor websites, surveys, newsletters, premium databases, etc., most of these are arduous activities and also do not provide real-time data (except for competitor websites or e-marketplaces where your competitors sell).

In fast-paced marketplaces, where consumer preferences change weekly, product demands fluctuate daily, and sentiments change in minutes with every social media trend, you cannot afford to have outdated data.

This is where real-time competitive intelligence is required with data extraction methods that can provide the most recent data about your competitors and ongoing trends. Data Scraping or Web Scraping is the way you can get competitor data in real time.

This is usually done by using web data scrapers.

Data scrapers are tools or software programs that crawl through the web to find relevant, real-time, and accurate competitor data. These scrapers pull competitor data from the web and present it in easily readable formats like CSV files, JSON, or Excel sheets. This data can be used for competitive intelligence.

How to Use Scraped Data for Competitive Intelligence?

Once you get the data in readable formats, the next step is to apply data analytics tools to extract the trends, patterns, and hidden insights in the competitor data. You can use data visualization tools to get a better and more engaging presentation of the data.

Here Are Five Use Cases Of Competitive Intelligence That Leverage Data Scraping:

1. Benchmarking Against Competitors

The data received from scraping can be used for comparing your products/services with that of your competitors. Compare prices, features, descriptions, promotions, etc., and try to find the areas where your strategy falls short of your peers. Find the areas for improvement. Check review data and see what customers are pinpointing. Check for the sentiments of customers. Focus on the most appreciated and least appreciated areas. See where your competitors get bad reviews. This is your chance to excel.

2. Trend Analysis

The scraped data when analyzed using powerful BI tools (in your case CI tools, Competitor Intelligence tools) can give valuable insights like shifting industry trends or stocking of a particular product by your competitor. The CI tools can tell you what your competitors are planning or what products will be in demand in the near future by analyzing the market trendlines.

3. Inventory Analysis

You will exactly know what products are listed by your competitors. This info about stocks helps you plan, list, and organize your own inventory on online channels where you are selling (own website, ecommerce marketplaces, etc.) From stocking the right products to keeping the optimal quantity, you are not left behind by your competitors in any aspect of your business.

4. Content Analysis and Optimization

On ecommerce marketplaces like Amazon or Google search engines, products with better content in terms of product descriptions, meta descriptions, meta tags, and keywords rank on the top and are therefore shown above all other listed products. This means that if your competitors are winning the SEO game, they will beat you on the SERPs. Therefore, by proper data scraping tools, you have to extract the SEO-related data of your competitors and bring your own product descriptions and keywords to par with your competitors who are ranking high.

5. Pricing Strategy Optimization

Constantly monitor your competitors’ pricing strategies with data scraping. Now check if your competitors have dynamic pricing or not. See how they price their products, and what are their payment terms. You can analyze what payment options, discounts, promotions, deals, coupons, and loyalty points they offer to their customers. If you want to stay ahead competitor pricing intelligence is something that you cannot ignore. Based on competitor pricing strategy create your own optimal pricing strategy that matches and excels your competitors.

Data Scraping for Competitive Intelligence: Key Considerations and Best Practices:

#1 Identifying the Data Sets for Scraping

The web is a universe in itself. You cannot web scrape all the data of your competitors. Even if you shortlist all the websites where your competitors are, these websites may contain thousands of web pages. For efficient and focused data scraping you will need to jot down the key insights that you need. For example, price points, product descriptions, brand names, availability info, related categories, reviews, features, etc. If your purpose is digital shelf analytics, plan data sets accordingly.

#2 Choosing the Right Data Scraping Techniques & Tools

You will have to determine the best scraping technique and tools based on the complexity of competitor websites, their frameworks, programming languages, security layers, anti-bot measures, etc. For instance, determine whether the websites you need to scrape provide an API. APIs are official ways of sharing data between two consenting parties and are often preferable due to legal considerations. Websites built with modern frameworks like JavaScript, Meteor, and Angular may require more sophisticated scraping tools that can handle dynamic content. You will need to decide whether you need scraping APIs, pre-built data scrapers, or custom data scrapers for your purpose. Consulting with a data scraping service provider can assist you if these topics are complicated for you.

#3 Avoid Overloading Servers For Respectful Data Scraping

To ensure a respectful data scraping process without overloading servers, implement rate-limiting. Rate limiting means limiting the number of requests that your scrapers will send to competitor servers in a particular time frame. This is necessary to avoid overloading the competitor’s website servers or other ecommerce platforms where you are scraping data. Pushing limits will overload servers and you won’t be able to extract the required data.. Websites may communicate rate limits via HTTP headers, such as Retry-After, X-RateLimit-Limit, X-RateLimit-Remaining, and X-RateLimit-Reset. Also, it is prudent to check the website’s robots.txt file for scarping directives. (Indications that which parts of the site can or cannot be crawled).

#4 Use IP Proxies and Rotation Techniques to Avoid IP Blocking

Regularly changing the IP address from which requests are sent can significantly reduce the chance of being detected and blocked by websites. Makes it harder for websites to trace and restrict your scraping activity by IP rotation techniques. Use Proxy servers that act as intermediaries between your scraping tool and the websites you’re targeting. By routing your requests through proxies, you can use multiple IP addresses to distribute your scraping activity. Introduce deliberate pauses between requests to mimic human browsing behavior

#5 Implement Error-handling Measures

There are errors such as connection errors, timeouts, and HTTP status errors that can delay or hinder the scraping process. Such errors may occur due to issues in your scraping scripts. However, you can implement error-handling measures like setting up circuit breakers to temporarily pause your scraping if a high number of errors occur.

#6 Always Legal and Ethical Data Scraping

You can face huge legal trouble for scraping data that is protected by law under patents, copyrights, intellectual property rights, or any proprietary content. You need to deploy smart scrapers that are capable of knowing such rights attached to the content or web pages. Be cautious when scraping content that may be copyrighted or proprietary. Unauthorized use of such content can lead to legal disputes and infringements on intellectual property rights. Therefore, ensure you understand these intricacies and maintain high ethical standards while scraping to obtain competitive intelligence data.

# 7 Go for Regular (preferably real-time) Scraping

Markets change every day, preferences change every day and your competitors may come up with new strategies, upgrade their products, dynamically change their price lists, and also add or remove products from their websites. These changes are indications of changing market trends and shifting consumer preferences. Keeping your competitive intelligence game up is not possible without regular and continuous data scraping. You have to set up a system for data scraping and data analysis for competitive insights.

Conclusion

In the online business, staying ahead of the competition is non-negotiable. Competitive Intelligence (CI) eliminates guesswork and provides you with insights for making decisions that get you ahead of your competitors. However, the key to effective CI lies in the quality and timeliness of the data you gather for CI analysis. Traditional methods of data collection, while valuable, often fall short of providing real-time insights. This is where automated web data scraping is the most prudent way of gathering competitor data.

If you are looking for reliable data scraping solutions for competitive intelligence gathering from competitors’ websites, e-marketplaces, and social media platforms, X-Byte should be your first choice. Xbyte offers high-quality data-scraping solutions (APIs, prebuilt scrapers, custom scrapers, enterprise scraping plans, real-time scraping, and many more) for flawless competitive intelligence.

This Blog Originally published here.