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4 Ways Businesses Can Use Web Data Extraction

I bet you’ve heard a lot about the term web data extraction or web scraping these days. Today I want to share with you how you can leverage web data extraction to cope with some painful problems that you encounter in your business.

No one can deny that data is the most valuable asset for today’s business in any field. Start-ups often find themselves hard to compete with business giants even though they have ingenious ideas. The reason is simple, these tech giants hold much more data than all other companies combined. The need for data extraction is obvious. If you don’t collect data, you put your business at stake.

To most businesses, it’s not about the quantity, but the quality and efficiency that really matter the most. Let’s make some real-world examples:

Table of Contents

· Price Optimization
· Lead generation
· Sentiment Analysis
· Investment Decisions

Price Optimization
If you own an e-commerce business, you know how difficult it is to set up the right price to attract customers. If you set the price too high, you scare away the prospect. However, without raising prices, it will be difficult to get more profit. Here is how web data extraction can help:

Extract customers’ information, and find out disgruntled customers. Then bring up their satisfaction by fine-tuning your market strategies. If they think you set the price too high, you put in a bundle to decrease the marginal cost. The point is that people love to pay more for a product with more value. And we can improve our product or service that our competitors are missing.

Next, make a dynamic pricing strategy. The price is not a firm set. This is commonly seen when you buy airline tickets. The price gets extremely high during the holiday season. whereas the flight ticket will be very cheap if the destination is not popular. This is due to market demand. You can use web data extraction to track prices on promotion events, like Black Friday. This enables you to keep up with the changes and adjust your pricing strategy in a timely manner.

dynamic-pricing

Lead generation
Needless to say, it is so important for a business to get successful — more leads! Of course, you can buy contact lists, but they are not quality leads. Even worse, people might unsubscribe your email or mark you as spam. In order to collect quality prospects from websites, we need to optimize the search process. Now a web data extraction tool is the perfect fit for this. It automatically searches and extracts millions of leads in a short time.

First, identify the relevant attributes like ages, education, job title, career, company, geolocation, etc.
Once you set the attributes. Find a target group, forum, social media where these people may likely assemble.
Use Octoparse to collect their information and export to excel spreadsheet. And now we can work to convert more leads.

Sentiment Analysis
We all know how hard it is as a newcomer to make a breakthrough in the world of e-Commerce. In fact, a perfect e-Commerce marketing strategy is born on itself. It takes time and progress to make it work. Before we hit the ultimate goal and achieve the optimal marketing plan, we need to study both our competitors and customers.

· First, we can start by monitoring our competitors with data extraction. You can monitor mentions, reviews, posts, campaigns, etc.
· Then we use these data to feed the deep-learning model to analyze the text. Then gives you the attitudes of the public, whether being positive, neutral or negative. You even can analyze at a granular level.
· After that, you are able to forecast future trends and customer sentiment. From there on, it is much easier to tailor your marketing campaign to suit the taste of your audience.

Investment Decisions
Data extraction has a long history in the investment world. For example, hedge funds extract alternative data to avoid the risk of flops. It helps them avoid unexpected risks and potential investment opportunities.

For example, Thasos, a mobile data provider, found a significant increase in overnight shifts from Tesla Factory by collecting geographical coordinates from worker’s smartphone devices. And they deduced the rise of Tesla’s stock price since the surge of overnight shifts could indicate the boost in Tesla production.

Alternative data can be tricky to collect as they are less readily and less structured. To this sense, web data extraction is the most approachable solution to pull any data from a wide range of web sources and syndicate to your database in preparation for investment decision making.

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