Competitor price monitoring – Why Use It

The market is dynamically changing more than ever. Competition is growing more stiffer and stiffer with each passing day but so are the business opportunities. Previously companies used to depend solely on manual tools and techniques to track price surges and they used to guess the market trends with minimal information. This meant inaccurate decisions and probably a counter move that depreciates the business even further.

In order to stay up, companies should know what is happening in the market and what the competitors are doing. Product prices are the main thing that may attract customers or vice versa. Many a time reducing price is the only option if you need to gain more customers but there is always a problem, and in this case, it is the competition from other business that can probably spoil your new move. They may reduce the price even further and by the time you become aware of it, you might have lost all the business opportunity linked with the product.

Competitor Price Marketing

You might have understood the role of competitors in affecting your business. To make your business profitable, you need to be aware of the competitor’s move and also about the customer price offers. Previously, this method was slow and used to be quite complex but today, with growing digitalization, this has become faster and more accurate. Today, software is available to keep track of competitor pricing and also about the latest product trends in the market.

Why use it?

Today’s market has become multi-dimensional and more diverse than ever before. Growing economy has lead to more products and more customers. This means more business but with this growth, there is also an increase in the businesses and therefore more competition.

To stay ahead of the competition and to get more customers, you need to make sure that you attract more people and one way of doing it is by offering the cheapest prices. This is where a Competitor price Monitoring can help you.

With this software, you can keep track of the competitor prices for the products you have tagged. This won’t only help you to adjust your prices in a better way but will also help you to understand your competitor’s reaction to the price changes implemented by you. This is how big MNCs like Amazon function. They keep track of the prices offered in the market and immediately match their prices to attract more customers.

As per a study, 74% of business don’t track their competitor for prices and this costs them thousands if not lakhs. Just with a competitor, you can enhance the business and can gain a huge technical advantage over your customer. This is exclusive for online retailers and therefore should be used extensively.

You can avoid a lot of mistakes while assigning new prices. Most businesses use Excel to record data and then this is used for predicting new costs. This is a slow process and there are huge chances of mistakes. Using Competitor Price Monitoring software can not only help you make better decisions but also will enable you to save time and resources, thereby increasing your ROI.

How Does Web Scraping Services Work

Web scraping is a technique used to extract data from websites. Web scraping is also called as Web harvesting or Web data extraction. Web scraping can be done

manually or by using a software. Web scraping is used for contact scraping, to gather real estate listings, to monitor online price changes, for weather data monitoring, website change detection, product review scraping, tracking online reputation, Web data integration, Web mash up and research.

Working

Web scraping a Web page involves fetching it and extracting it. Fetching the page is done by downloading it. Web crawling is done to fetch pages for Web scraping. After fetching the Web page, the content of the page is parsed, searched and the data is reformatted and copied. The pages are Web crawled regularly, so that, new pages are fetched for later processing. Web scraping services can Web crawl, extract, monitor and refine the fetched data. They then convert the data into a ready to use form. Web scraping services use high end technologies and makes outsourcing, a better option for most of the companies. A Web scraper is an Application Programming Interface (API) to extract data from a website. Application Programming Interface are a set of subroutine definitions, communication protocols and rules for building a software.

Since Web pages are built of text based mark-up language like HTML, and contain useful data in text form, the Web scraping service creates a mechanism to get the HTML code. The DOM structures of the website are then monitored to identify the nodes containing target data. After the identification of the nodes containing target data, a node processor is created to output the data in a normalized format. The node processor can be changed in accordance to the client’s requirements and data processing preferences. The system receives an URL at the input and outputs  normalized data. Based on the URL, the server decides which reader should process it, prioritizing the highest quality reader with proper customization. In the absence of a priority reader, the URL is forwarded to a default reader, which is either the most stable reader or a third party device. There is also a feedback support, implemented by the Web scraping server to promptly receive complaints if there is any low quality content. This is performed to ensure the high quality of the content. Newer forms of Web scraping involves listening to data feeds from Web servers.

Techniques

Web scraping involves automatically collecting or extracting data from the world wide Web. Some of the techniques involved in Web scraping are

• Manual copy and paste
• Text pattern matching
• HTTP programming
• HTML parsing
• DOM parsing

Conclusion

Web scraping services are used to extract information from websites.

Recent Trends In Web Data Mining

Web mining is the application of data mining techniques to extract the knowledge available in Web data. It includes Web documents, hyperlinks between documents, usage logs of web sites, etc. Nowadays its trend to extract data from different sources and organizes them for better usage

Firstly it was a ’process-centric view’, which defined Web mining as a sequence of tasks. Second was a ’data-centric view’, which defined Web mining in terms of the types of Web data in the mining process. The attention paid to Web mining is  in research of software industry, and Web-based organizations. It is the chance to capture them in a systematic manner, and identify directions for future research..

Web data mining consists of 3 following tasks

• Resource finding: It involves the task of retrieving intended web documents. It is the process by which the data either from online or offline text resources are available on web.
• Information selection and pre-processing: It involves the automatic selection and preprocessing of specific information from retrieved web resources. This process transforms the original retrieved data into information. The transformation could be renewal of stop words, stemming or it may be aimed for obtaining the desired representation such as finding phrases in training corpus.
• Generalization: It automatically discovers general patterns at individual web sites as well as across multiple sites. Data Mining techniques and machine learning are used in generalization 4. Analysis: It involves the validation and interpretation of the mined patterns. It plays an important role in pattern mining. A human plays an important role in information on knowledge discovery process on web.

 

Many businesses have been adopting the process of data mining to catch up with others. Business taking important information through data mining is widely used for decision making purposes. Here are some recent trends in Data Mining are:

• Multimedia Data Mining: It is one of the latest processes to catch up because of growing ability to capture useful data from different sources. Different sources include audio, text, hypertext, video, images etc. and data is transformed into a numerical representation in different format.
• Ubiquitous Data Mining: This involves mining of data from mobile devices to get information of individuals. These having several challenges like complexity, cost privacy, etc. these methods has a lot more opportunities to be enormous in these type of industries.
• Disturbed Data Mining: Though data mining has gained popularity as it involves mining huge amount of information stored in different company location. To extract this data highly sophisticated algorithms are used to provide proper insights and reports based on them.
• Satial And Geographic Data Mining: The new type of data mining includes extracting information from environment, astronomical, and geographical data as image is taken from space. These data mining can reveal various aspects such as distance and topology which is used in geographical information system and navigation too.
• Time Series and Sequence Data Mining: These type od data mining studies about cyclical and seasonal trends. It is helpful in analyzing random events occur outside normal events. It is mainly used by retail companies to access customer buying and their behaviors.