How Predictive Analytics is Used in The Movie Industry

There is a core element in the development (and even the mere existence) of Data Science: advances in technology, as they lead to an evolution in the execution of essential activities of this profession such as collection, visualization, cleaning and classification of data; the programming language or the creation of machine learning models. Characteristics that is anchored to the versatility of this science, since there is no area of life in society that cannot be studied through data analysis. 

 

Table of content

• Introduction

• Utilizing big data in the movie industry

• Predictive analytics: fundamental concept to boost the supply chain

• Applications of use of predictive analytics

• With predictive analytics, your business can benefit from the following:

• Conclusion

 

Introduction

One of those areas that can be read through the data is that of entertainment with programs like Merlin and other programs that do wide-ranging predictive analytics; however, obtaining relevant information requires a subset of data to find precise patterns. 

 

Utilizing big data in the movie industry

Through Data Science, correlations have been found in numerous categories related to the universe of the seventh art, including the types of characters, the complexity of the plot, the budget, the influence of the protagonists, marketing campaigns and social impact.

 

In this way, this discipline has made it possible to analyse and categorize the data that arises from the impact of a tape, whose corpus can be the response in social networks and critical reviews. However, it can be said that this buzz that surrounds a film is only a small part of what makes up the whole panorama to be analysed.

 

Likewise, it is important to mention that, when Data Science is applied in the analysis of the film industry, it is necessary to execute a specific data analysis plan at each stage of the work's life cycle: it must cover from development, post-production, to distribution.

 

Big data is a vital part of the strategy of all types of businesses in recent years. In addition to more traditional sectors, such as banking, insurance or commerce, some media outlets already have data experts on their staff. Not only do they help them create content based on the interpretation of data, but they also show them where they are failing and what they should do to keep readers.

 

Predictive analytics: fundamental concept to boost the supply chain

Predictive technology is beginning to be included as an objective within the strategic plans of companies to achieve the ability to make business decisions based on data. Therefore, predictive analytics becomes a fundamental concept for all types of organizations that need to boost their supply chain.

 

Predictive analytics processes and techniques

Predictive analytics techniques are those that have generated the most attention from companies as the results of their evolution are very promising, with a relatively low cost.

 

There are several techniques that allow the development of predictive models under machine learning methodologies.

 

The methodologies include:

• Supervised machine learning algorithms

It is understood by supervised machine learning by those algorithms that are executed in computers to learn automatically based on the data. Classification and regression algorithms are among the most widely used types of analytics algorithms. For example: Naive Bayes, Super Vector Machine, Decision Trees or Random Forest.

 

• Unsupervised machine learning data

Supervised learning uses known examples to obtain the leads while unsupervised learning does not have examples with a known label to make inferences. The unsupervised predictive analytics algorithm types are for clustering or anomaly detection problems.

Applications of use of predictive analytics

The predictive analytics offers several high - impact applications for businesses. Some of them are:

• Recommendation systems 

Amazon has among its business keys the recommendation system of its e-commerce platform. Product recommendations are given after analysing millions of data, establishing segments, determining behaviour patterns by type of market.

 

• Product creation

The Netflix company is a pioneer in the use of predictive analytics and applies it for several of its business objectives. With the analysed data of its subscribers, the company creates new products based on consumer trends.

 

• Consumption habits prediction

The Walmart supermarket chain uses the data from its different networks to improve the rotation of its stocks, fill the shelves of its stores with the products that are going to be consumed in real time.

 

• Predictive Maintenance

Shell, a power generation company, uses analytics to monitor the health and operation of its rigs for drilling operations. With predictive data, you can forecast machine breakdowns and anticipate the problem by replacing parts in a timely manner.

 

According to experts, demand and digital transformation must be customer-driven, where it is essential to take advantage of the opportunities offered by predictive analytics applied to the supply chain to achieve results in anticipation of demand.

 

With predictive analytics, your business can benefit from the following:

1. Increased productivity - you get access to data that can be easily used for analysis, which makes the sales team more efficient. Because forecasts are based on past data, you will not use simple assumptions when dealing with clients.

 

2. Reduced Costs - Because your processes will meet the requirements of your customers, you can save money without having to deal with inefficiencies.

 

3. Save resources - predictive analytics can always lead you to the desired result, thereby helping to save money and time.

 

4. Immediate Results - predictive analytics can help you quickly capitalize on future trends by focusing on new developments and different customer acquisition models based on current performance.

 

5. Better quality and functionality - companies use predictive analytics to improve decision making.

 

6. Improved risk management - predictive analytics allows you to react to problems before they become threatening, and allows you to reduce them to zero in real time.

 

7. Optimized Marketing - With predictive analytics, you can quickly understand your customers' behavior and optimize your ad campaigns to satisfy both old and new and potential customers. It also ensures that you always retain the most profitable customers.

 

Conclusion

Some of the many benefits of predictive analytics are listed above. Predictive analytics is having a positive impact in the movie industry and many producers are already keying into strategies that involve predictive analytics. HData System is one of the leading data analytics companies and we can assist with the analytics of data to the benefits of your business.

 

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