How reliability of data will increase in the coming decade
In this world, every decision is backed by a conclusion made from solid data analysis. Data is like oil now and the absence of this can make you take disastrous decisions. Today travel industry, finance industry, food, stock market, and other such industries use data to make crucial decisions for their companies. Today we talk about Big Data and how we can train AI neurons to make them smart as we are. We are talking about AGI (Artificial General Intelligence) which is again dependent on a large dump of data. For example ChatGPT, it is trained on a large database to make it work like a smart chatbot.
The travel industry has become competitive and keeping yourself ahead of your competitors has become quite crucial. To gain a competitive edge in the market, hotel booking websites or OTAs track prices from their competitors to keep their prices lower. This helps them in generating more bookings and ultimately more revenue. But there are more than 200 OTAs around the globe and tracking them all at once is near to impossible. But solutions like hotel price API can help you track prices from these OTAs(like booking.com, Expedia, etc).
Once you have this data, hotel booking websites can adjust their own prices to get more bookings. They can show their visitors that they offer much lower prices than these BIG OTAs.
Similar techniques can also be used in the aviation sector. Once you have prices from multiple vendors you can lower your prices. But again there are multiple vendors and tracking all of them is not possible.APIs like Flight Price API can help you get every little detail from the number of stops to airline-offered prices. This helps in keeping your website up to date without managing all the hassle of tracking prices from multiple vendors.
The stock market is well-famous for data analytics. This is one industry that requires intense data analysis for making a decision of buying or selling the stock. Past year data is collected and one by one each trend is analyzed to predict the behavior in the near future. Mostly it is used by large investors or long-term investors to keep their investments safe.
Other than this search engines like Google, Bing, etc use AI which is again backed by a large database. Google uses user search patterns to show relevant ads on its apps. Similarly, the ads you see on your Instagram or Facebook feed are based on the searches you have made on these apps. Sometimes these companies sell and buy user data in order to show relevant ads to their audience.
Youtube uses your history to suggest you new videos which might be interesting to you. It even tracks your mouse scrolling pattern to suggest new videos. Like and dislikes are other factors that make youtube understand your mindset.
Youtube comments and Instagram comments are scraped by many data analysis companies to predict user sentiments for an election candidate. They analyze what a candidate should and should not talk about. But scraping any website is not easy and many times either your IP will be blocked or you will be shown a captcha. But you can overcome these issues by using a web scraping API that uses a new proxy/IP on every new request. This will help you collect a tremendous amount of data from any website.
Another industry is eCommerce. They also suffer from huge competition on multiple product lines. If you are selling clothes on your website then you will end up in a competition where just price tracking will not help. You will have to analyze the reviews and ratings of the product to analyze the trends of shopping. Just lowering your prices won’t help. You have to find a market gap where you can sell the product with better quality.
There are many applications of data and the points we discussed above were from a broader spectrum. With time data applications will increase and along with that your decision-making conscious will change too.
