7 EXAMPLES OF COMPANIES THAT USE BIG DATA TO THEIR FAVOR
Big data is one of those concepts you hear about all the time, but it’s hard to “land” with concrete examples. If you’ve never seen big data in action, it may be difficult for you to imagine the practical applications and benefits it can bring to your business.
To help and inspire you, we’ve compiled 7 examples of brands already using big data to achieve incredible results. Don’t miss them!
Table of Contents
7 examples of big data in brands
Netflix is estimated to save $ 1 billion a year thanks to its big data algorithms.
Its story began in 2006 when it launched the million-dollar “Netflix award” to whoever could create the best algorithm to determine subscribers’ opinion of a series or movie based on previous ratings. Today, 80% of the content that is played on Netflix comes from the recommendation system.
Netflix employs various traditional business intelligence tools (such as Teradata and MicroStrategy) and combines them with modern big data technologies such as Hadoop, Hive, etc. The result is an algorithm that predetermines the content that users are most likely to see.
In the end, the key to Netflix’s success is personalization, and big data is what makes it possible. Only then can they facilitate a unique experience for each user.
Apple uses big data applied to behavioural economics to draw conclusions about its user base and use them to its advantage. Here are the 6 principles of behavioural economics that have helped you build your brand:
- Tribalism: tribes are social groups with similar interests and beliefs, sharing the same identity. In this sense, users of Apple products are a tribe that shares the same aesthetic and lifestyle.
- Endowment effect: we tend to value the objects we already own more, and big data shows that we are willing to pay more for them. Apple implements this principle by allowing you to test products in its stores.
- Social proof: This principle is based on taking advantage of user testimonials and recommendations from family and friends.
- Heuristics: people use “mental shortcuts” to make quick judgments. Apple makes the most of this principle in its packaging since it is considered that if the packaging is well designed, the product will be as well.
- Halo effect: This cognitive bias judges the quality of a product based on impressions of previous products. Thus, Apple has built a long history of successful launches that cause its brand to be bought little less than blind.
- Price: Apple’s big data analysis reveals that their pricing strategy works, despite being unintuitive: their products are always priced high, and they never sell.
3) Barcelona Metro
Barcelona Metro has implemented the RESPIRA system, which uses artificial intelligence to improve ventilation and help control coronavirus infections in the Barcelona metro network.
This control system analyzes different variables, such as the thermal sensation, temperature, humidity, the quality of the indoor air in the stations and the electrical consumption of the ventilation. All these variables are centrally correlated to establish the optimal ventilation strategy thanks to a dynamic algorithm based on machine learning techniques.
The large retail giant is capable of analyzing a brutal amount of customer data. Its algorithms allow it to collect, analyze and use a massive amount of data from search and purchase history. Therefore, they can offer recommendations with a high probability of generating a purchase, optimize prices and the supply chain and detect fraud.
The secret of its success lies in its advanced big data analysis tools, such as advertising algorithms and the “Amazon Elastic MapReduce platform for machine learning“.
Since 2008, when it surpassed Gap, Zara has been the world’s largest clothing distributor. The secret to its success lies in its ability to spot new trends as soon as they emerge and ship garments to stores faster to meet the needs of its customers.
Zara’s supply chain relies on the use of data and analysis to make predictions and make sound decisions. The data comes from both daily inventory and store orders and customer feedback.
To analyze all this raw data and make the right decisions, Zara incorporates multiple artificial intelligence, automation and big data tools into its business strategy.
6) UOB Bank (Singapore)
UOB Bank of Singapore is a great example of big data for risk management. As a financial institution, there is great potential for loss if risks are not properly managed. So recently, in 2018, it piloted a risk management system based on big data. This allows them to reduce the calculation times of the variables at risk, from 18 hours to a few minutes. Thanks to this initiative, UOB Bank hopes to be able to carry out risk analysis in real-time, which will produce great savings in avoided losses.
The big data and analytics platform in the cloud used by PepsiCo, Pep Worx, helps the company advise stores on what products to buy, where to place them and what promotions to launch.
In preparation for the launch of Quaker Overnight Oats, PepsiCo was able to identify 24 million households to target its product. They then identified the shopping locations those households were most likely to use and created specific promotions for these audiences. By using this data to focus on a particular market, they achieved 80% product sales growth in the first 12 months after launch.