Web scraping is now considered one of the most hyper-effective methods for collecting a large bulk of data that businesses need to understand better the market, customers, and even their brand growth.
And for web scraping to be seamless and efficient, there is the need for the process to be as automated as possible. This includes the use of highly-sophisticated tools such as proxies and Application Programming Interfaces (APIs).
Of course, web scraping can be done with other tools. Still, when combined with APIs, we see a seamless flow of data extraction and the easy elimination of the many hurdles commonly associated with data collection.
What Is Web Scraping?
Web scraping can be defined as the process of using machines to collect a hefty dose of data from multiple sources repeatedly.
The process is often repetitive to allow brands to collect up-to-date data that can be applied to solve current market issues.
However, the repetitiveness of the exercise makes it monotonous and quickly tedious, and this is where the machines come into play.
Software such as proxy servers and scraping bots take the stress off-web scraping by ensuring that the task is automatic and faster to complete.
What Are APIs?
An API is a communication protocol built attached to an application, an operating system, or a website that allows seamless communication between a user and the data source it is connected to.
For instance, giant software companies such as Facebook and Google have their APIs. These APIs allow users to connect and scrape specific data through the protocol.
Hence, API scraping is a popular type of web scraping but used only for collecting the same data type from the same source and for particular purposes.
Use Cases of Web Scraping
The following are some of the most common use cases of web scraping for businesses today:
- Price Monitoring
Several things contribute to the success of a digital brand, and setting the correct rates so happens to be top on the list.
When your prices are too high, you stand the risk of losing customers to your competition. Conversely, when the prices are set too low, you risk leaving money on the table and making way less than is advisable.
It is for this reason that brands take price monitoring as an essential step to staying in business.
Web scraping gives you the power to scrape price data continuously from significant eCommerce websites and your competitors so that you can set the best prices.
- Product Optimization
Brands that succeed and stay around for many years usually make products and services that are in demand.
Manufacturing to meet demand is one of the ways to create customer satisfaction which means better sales for your company.
Web scraping is generally used to study consumer sentiments and other market factors to produce what is currently in demand.
- Ad Verification
Running an ad is an integral part of marketing which is how companies get the word out about their products and services.
But when done wrongly, a brand can incur more losses than gains from ads. For instance, when an ad is left unmonitored, it is easy for criminals to hijack it and use it to impersonate your brand. Your competitors may also use your ads to learn more about your strategies and outperform you.
This is what makes ad verification a vital part of the business process. Ad verification is used to ensure that an ad is displayed correctly and running according to plan. And all these can only happen when you keep collecting an enormous amount of data through web scraping.
Use Cases of APIs
The primary application of APIs is in collecting similar and specific data from a particular source. For instance, when a brand needs detailed data from Facebook, it would be quicker and faster to use a Facebook API rather than begin a full-out web scraping process.
Scraping with APIs is straightforward and involves the interaction with JSON files and the return of files in the same format.
They do not include the use of other sophisticated tools such as residential proxies. But this could also make them limiting in some ways. Residential proxies are typically used to simulate organic traffic, while datacenter proxies are more useful for larger volumes.
Consider this; while web scraping allows you to scrape any data source from any part of the world, API scraping only limits you to collect the same data type from the same data source and for a specific purpose. This, perhaps, accounts for the most significant difference between both approaches.
How Web Scraping Differs From an API
As highlighted above, the most apparent difference between web scraping and API is that web scraping allows for customization. Users can collect any data from any website in the world. In contrast, API scraping will only enable you to collect precise data.
Secondly, API scraping is also governed by a strict set of rules, and the application dictates what data you are allowed to scrape and how frequently that can happen. This is unlike web scraping, where the only rule is to be ethical and only collect publicly available data.
On the flip side, scraping with API is more uncomplicated and straightforward, requiring only common knowledge of how to interact with JSON files and convert CSV files to SQL.
How to Combine Web Scraping and API to Complete Tasks
API scraping works more with specificity and little need for data. It can effectively fetch you small amounts of data from a specific application or website.
However, it cannot do more than this, and even that is restricted by rules and standards set by the platform.
This is why it is best to combine API with web scraping. This allows you to take more minor data when the need arises and switch to web scraping for more extensive data extraction when you need data on a large scale.
You can also easily use web scraping to evade restrictions and harvest data regardless of where you live.
This type of combination allows for data collection flexibility, which every business should have if it intends to keep collecting data uninterruptedly.
Conclusion
Web scraping and API scraping may be two different mechanisms of data extraction used by various organizations based on scraping goals, data needs, and level of expertise.
However, to enjoy the full benefits of data collection, it would make sense to combine both approaches.