Website Data Collection the Right Way

Online tracking

Online tracking is the best way to collect data from your customers. When a user enters your website, they usually leave a lot of data points, especially if they're interested in your products or services, and register for a newsletter. The data collected from your customers can vary from demographic information to email and phone numbers.

However, it can also help you track the performance of your web pages. You can monitor website traffic, analyze bounce rates, see the best-performing sites, discover if you attract more users from laptops or mobile devices, and more.

Data collection tools vs collecting data on your own

As briefly mentioned before, web scraping tools are much faster and more efficient than collecting data on your own. However, there are some cases where it's more beneficial to collect data on your own.

One of those cases is if you only need a relatively small amount of data and you don't need to update it constantly. Let's say you only want to see how many tech companies there are in your city right now and it doesn't matter to you if that number changes next year. In this case, it's not worth paying a fortune for an entire dataset or a scraping tool.

However, if you need refreshed data every month for useful insights, then it's much more cost-effective to buy datasets from providers or employ data collection tools.

How do businesses use collected data?

It depends on the business, but collected data, or scraped data, can be used in a wide variety of ways.

For example, if you're an investor, you can use firmographic data to generate a list of companies for a competitive advantage. You could extract a list of startups from the entire dataset based on your preferences. Let's say you're interested in startups that were founded in 2021, are located in San Francisco, and have less than 50 employees. You can simply filter the database based on those parameters.

If you're in the HR platform business, you can use employee data to improve talent sourcing and talent intelligence. The more profiles you have, the better the chance that you will be able to provide the best-fit candidate to your client. Also, you can use employee data along with job posting data to conduct market research and uncover certain trends in the job market.

In short, there are as many use cases as your imagination and business direction allow. If you want to discuss your particular use case, contact our sales team by clicking the button in the upper-right corner of the window.

Web data collection best practices

There are several things to keep in mind when preparing to collect data: have a clear goal, establish data pipelines and storage places, decide on a collection method, and evaluate the data.

Have a clear goal

Before collecting third-party data, you must have clear definitions of what you're looking for. This way, you can train the algorithm to only collect relevant data that will help your business objectives. First and foremost, you need to identify whether you need qualitative or quantitative data. After that, you can delve a little deeper and make more advanced modifications.

Establish data pipelines and storage places

A data pipeline is imperative because it will enable the movement of new data from the source to the destination. At the same time, you need to think about the data warehouse, data lakes, or other storage options where the scraped data will be stored.

Decide on a collection method

The collection methods range from public crowdsourcing to web scraping. You need to identify your data needs and decide on the collection method that will bring you the most value.

If you need internal data, you will probably benefit the most from collecting and analyzing customer data that's abundant in your internal business databases from all of the users’ website activity.

If you need external data, you will most likely find useful data in public web sources, such as social media platforms and business websites.

Evaluate the data

After collecting the data, you will need to evaluate its quality and legitimacy to ensure a successful artificial intelligence or machine learning model. Here are the most important things you need to check:

• Evaluate its tangibility. One option to do that is to analyze a small subset of the data and see the frequency of errors.
• Evaluate data transfer processes. Check if there are any technical issues and what impact they have on the transfer process. Also, see if there are any duplicates and server errors.
• Evaluate data completeness. Check if any of the data was not collected and whether it's important to your goals. Also, see if the algorithm didn't develop a bias towards one side. If you're scraping qualitative data, there should be both good and bad reviews, for example.

Conclusion

Web data collection is a process that allows businesses to leverage data to improve business decisions. However, it’s important to always keep the data fresh and accurate. It’s one thing to collect some data once, and another to always keep it updated.

In short, you should establish your business goals, align them with your data needs, get the data either yourself or from a provider, and leverage it to reach those goals. We've also prepared a guide that explains how to prepare for working with web data if you need some expert guidance.