When we talk about Big Data, we usually think of examples of Big Data applications from large companies such as Amazon , Spotify, or Netflix. These companies use Big Data in a very specific way.
These large companies have used big data
Analysis to data in companies better understand the behavior of their users, in order to find patterns and infer those conclusions to the rest of the users,
The success of these large companies is that through the analysis of large amounts of data they have managed to provide a better service to their customers . For fantuan database example, Spotify has been able to group songs by themes that users may like. In this way, they have managed to get users to spend more time listening to music , showing them songs that they may also like based on their tastes. This translates into less abandonment, more subscriptions and more income from advertising.
What this streaming audio company has
Achieved is that music lovers who like to constantly discover new groups have an unlimited source of suggestions . These data in companies suggestions are what are sqls in inbound marketing? filter your leads very successful because they are based on recommendations from millions of users who spend a large number of hours on the platform. Thus, it is easy for us to like many of the recommendations offered by the platform.
To do this, Spotify uses a recommendation system, with three types of algorithms : collaborative filtering, raw audio model, and natural language processing.
How can these BigData algorithms help small and medium-sized businesses?
Just like large companies, small and medium-sized businesses can create recommendation systems that increase the average shopping basket.
An e-commerce site can take advantage of these cell phone number algorithms data in companies to find patterns of behavior among its users. Sometimes, we are not able to see through a simple analysis which customers who buy product “X” also buy product “Y”. Recommendation systems, sometimes very simple, will provide us with associations and patterns of behavior that can help us improve customer service, achieve more loyal customers and customers who buy more often.
Other uses of Big Data in the company
One of the most important sources of traffic that e-commerce has today is traffic that comes from search engines .
Search engines work with keywords. The user enters a query and the search engine attempts to provide the most relevant results based on a large number of variables.
Since the dawn of computing, one of the greatest challenges that experts have faced is getting machines to understand human language . There have been many algorithms and approaches for this purpose, but in recent years Natural Language Processing (NLP) is one of the systems that has come closest to achieving this goal.
Big Data and SEO positioning
Google works with algorithms like BERT each of their sentences. Google’s BERT is data in companies one of the most advanced systems , capable of interpreting the meaning of sentences based on their context through two-way analysis.
We as marketers can take
Advantage of this pre-trained system to retrain based on our needs.
In recent times, the importance of “transactionality” has become evident. Google classifies queries into three types: informational, navigational, and transactional. Thus, if we are an e-commerce, our product sheets must be adapted for transactional searches .
With BERT training, we can carry out this classification
Classifying the percentage of our transactional keywords, the best Google results, and our competition. With this, we can see what percentage is optimal and thus, modify our texts to take advantage of this information .