Competitive And Pricing Intelligence

Pricing intelligence using data scraping

Price intelligence is also known as competitive price monitoring. It is the awareness about the market price and how it impacts the business. Modern techniques like data mining and data scraping are used to analyze the information. Price intelligence is useful as it gives information on increased consumer price sensitivity, increased competition among the competitors, and increased price transparency. Price scrapers or price bots provide pricing intelligence solutions. Price scraping is a technique used to lift off the pricing data from the e-commerce websites. Competitors use this data scraping technique to steal the dynamic data regarding the pricing. Many tools and technologies like cURL, HTTrack, Scrappy, Selenium, Wget, PhantonJS, and so on. The scrapers can also use third-party scrapers to target the data. They target multiple websites, pull the pricing, and catalog information and sell it to the competitors. Price intelligence has various advantages like optimization of pricing strategy, improvement of the in-store experience, boost pay-per-click, repricing etc. Scraping is done to analyze the website value of target and competitors and competitive edge.

The competitor can completely analyze the data provided by the data scraping technique and override the pricing strategy by undercutting the prices. An entrepreneur can achieve success by using the data scraping tool. The company can also many customers by reducing the price of their products or services, compared to the competitors.

But price scraping has its disadvantage. There is a huge drain of information from the websites. The companies that use data scraping techniques illegally must also deal with scrapers and competitors in the court.

Competitive intelligence using data scraping

Competitive intelligence is the process of defining, forming, analyzing, and distributing data and information about the products, customers, demand, competitors, and competition. This data would help the executives and managers in taking a strategic decision for the company. It is a legal business practice so, you need to worry about court and privacy case.

With the increase in technology and advancements, many companies have been established. Many budding start-ups are also coming into the play. If a company wants to stay on the top of the leader board, then it must use the technology. Data scraping is the latest technique used to extract data on and about different companies.  Web scraping is done to gain information on the competitors. Having data about your competitors would serve as a huge advantage.

Data scraping would give you all the information about the market and competitors.

Assessing the Data like a Data Scientist


What is data mining?

Today everyone is behind data; whoever has big data rules the world. Companies pay a hefty amount to data mining firms and data scientists to gain hold of data.

Like the name suggest this means digging of data, the process of extracting usable data from a large set of any raw data, it means analyzing a large chunk of data with the help of one or more software. The application of data mining can be executed in multiple fields, such as research and science.

Businesses can learn more about their customers and develop effective strategies to leverage resources in a more optimized manner. Data mining uses sophisticated algorithms to evaluate the probability of future events.

What data can do?

Since last decade there have been advances in the speed that enables us to move beyond the traditional and time-consuming practices to automate data

analysis. Complicated data have the potential to unravel relevant insights. The major consumers of these data are banks, manufacturers, retailers, and telecommunications providers.

The techniques to mine the data have become more sophisticated, because of data we’ve been looking ahead by mapping out patterns into the future. Data mining does not work by itself; it discovers hidden information in gathered data.

Data mining won’t give out all the Information; it discovers predictive relationships which are not necessarily causes of behavior. For example; data mining will determine that males with income of 30000-60000 who have certain subscriptions will buy a given product. This information will help companies to develop a targeted marketing strategy; however, data only will give the leads that a consumer might be interested in the product but it doesn’t say that they will buy the product because they belong to this population.

Which tools can be used to mine data?

There are several tools to mine data, some of them are open sourced and some are paid. Here are a few tools which can help in mining the necessary data.

  • Rapid Miner is one of the best and open source tools to predictive analysis, this tool can be used for a various range of applications including for business applications, research, machine learning, and commercial application.
  • Weka also known as Waikato Environment, this software is based on the freemium model. This can be used for data analysis and predictive modeling, this software contains algorithms which supports machine learning.
  • Sisense is licensed software. This is extremely useful and suited when it comes to internal reporting within the organization. This software helps in generating highly visual reports; these are specially designed for non-technical users.

Data mining solves few problems and will lead companies to their customers by analyzing data which are already in the database, but this also takes the right skills and tools to execute and get desired results.

The scope for finding the necessary findings will be ever greater, companies as long as they can figure out how to mine and execute it effectively. Businesses will be able to learn about their consumers, the tools will help to make business decisions with the gathered data.