The development of technology nowadays has skyrocketed. In fact, technology is responsible for particular industries that did not exist before. There are now various big data companies that provide solutions in the conversion of raw data into applicable trends to help businesses make wise decisions and resolve every issue.

Using data is absolutely essential for businesses on an everyday basis, whether it’s using customer data to market a new product range or simply just to understand how potential customers interact with your company. Moreover, the use of big data companies is becoming increasingly more important for those looking to exploit the next frontier of competition, innovation and productivity. However, while the use of big data is crucial to fuelling future growth and marketing strategies, one of the main struggles is actually obtaining all of the data that you’re wanting to analyse.

Luckily, there are a number of web scraping tools and technologies that can do all of this for you, before assembling the data in an easier to digest format. Despite this, though, actually using this data for your business will vary depending on what industry you operate within. As such, here’s a few examples of big data applications in different industries.

Retail / Consumer

Using customer and sales data within the retail sector is hugely advantageous to those who have incorporated a data-driven approach into their marketing strategies. This is because it can help to drive future campaigns and offers a greater understanding of your customer’s buying habits. By using data, you’ll be able to segment your audience to promote the right products to the right people, as well as:

– Merchandising and basket analysis

– Campaign management and customer loyalty programs

– Supply chain management

– Event and behaviour based targeting


Within the world of finance, big data is mainly used in risk analysis and compliance / regulatory reporting, but there are also plenty of other different applications too. One of the primary examples of when this can be best utilised is in credit scoring for those who are looking to obtain finance to purchase goods or borrow money from an accredited lender. Fraud detection is another common use of big data in this industry, but it can also be extremely useful in fraud prevention too, as well as:

– Risk analysis and management

– Credit Risk, scoring and analysis

– High speed arbitrage trading

– Trade surveillance

– Abnormal trading pattern analysis

Web / Ecommerce

The use of big data in the web / ecommerce industry is essential for any digital strategy that aims to build a bigger picture of your audience, how they interact with your business online, and their entire customer journey from introduction to conversion. All of this is imperative to your online business, as it can help you to understand how you can drive more sales through your website and where most of your custom is coming from. With this information, you can best decide which marketing channels work best for you. In addition to this, big data can also be used for:

– Large-scale clickstream analytics

– Ad targeting, analysis, forecasting and optimisation

– Social graph analysis and audience segmentation

– Cross-channel & Event analytics

– Abuse and click-fraud prevention


For the telecommunications industry, one of the main uses of big data is to gain an insight into their customer’s usage via call detail record analysis, as this becomes vital information when seeking assurances in revenues and for optimising prices. In doing so, telecommunications companies can utilise this information to understand more about how, when, where and why their customer’s use telecommunications services. Further to this, telecommunications companies can also use big data for:

-Revenue assurance and price optimisation

– Customer churn prevention

– Call detail record (CDR) analysis

– Network performance and optimisation

– Mobile user location analysis


In summation, big data is commonly used across a number of different industries and for varying reasons, whether it be to assess the financial risk of a customer’s credit application or to simply drive more sales as part of a larger growth strategy. While its use is highly advisable, physically acquiring masses of data will take a long time, so the use of a web scraping tool or service is the most effective method of doing so.