Big Data has a future for every organization, and every organization will eventually be in the data business. Therefore, companies can grow rich using big data. They recognize the financial and business opportunities that big data presents.
To improve their business model, modern companies collect big data. Collecting data is only one step of using big data. Finding meaningful insights is the accurate measure of its success. With big data analytics, you can get your answer much more objectively. Moreover, with these insights, companies can make the best decisions for their business.
With these insights, companies can even create better products. Business decisions are more informed, customers’ behaviour is predicted, etc. Companies have a competitive advantage with today’s fast analytical systems as well. Companies like this will gain a competitive advantage in the financial world as well. We will provide examples of companies that make use of these methods.
1. Using Big Data To Develop Products
Producing a product usually involves developing the idea first. However, how can you figure out if your product idea is good? In the first two years after a product is introduced, stats show that 66% of ideas fail. Big Data in this scenario is of great help and will save a lot of money.
So, companies usually begin product development by analyzing the market demand and any potential for the product. Companies determine if customers are interested in purchasing the product. The potential competitors for the product. Before investing any money, they determine, for instance, whether the product will be profitable. Using big data analytics, they suit the product specifically to the customer. By doing this, they can take advantage of the customer and make money.
Customer insight and data analytics are two separate teams. Their big data analytics allows them to target customers individually, which puts them miles above their competitors. Understanding customer preferences helps them create the right products.
2. Using Big Data To Increase Sales
A company’s sales department is essential to its success. If a company does not generate sales, it will not be profitable. An organization can optimize its sales by using Big Data. Companies with intelligent sales departments ensure that they have detailed customer data. The data allows them to identify customer needs and turn them into leads.
With big data analytics, the company’s sales department can sell its products more effectively. Personalize customer service and give the customer more product choices. In this way, data analytics helps the company increase its revenue.
Amazon uses big data analytics to increase its sales. On Amazon, customers are often provided with product recommendations. These are usually based on the items they have recently purchased or their browsing history.
Moreover, Amazon analyzes the purchases million of its customers make together every day. Using this information, it recommends items that are frequently purchased together. Using big data, Amazon could make more sales by suggesting items you might enjoy buying.
3. Marketing And Advertising With Big Data
The marketing campaigns of many large companies have cost millions of dollars. Unfortunately, they have failed as a result of massive losses. What causes this to happen? What is it about some companies’ marketing failures despite enormous resources? These companies may face this outcome if they fail to use big data analytics to the fullest extent possible. It is the only solution in that situation.
Companies can monitor online activity and consumer base. Marketing campaigns should take account of current customer trends. Without these efforts, it won’t be able to achieve a target audience for it. It may offer the highest monetary returns and be the most profitable course of action for a company.
In marketing and advertising, Netflix is an excellent example of a company using big data. It is because it collects data on the search habits of consumers. Watches all the history of its 100 million subscribers before displaying targeted ads. Therefore, you can get recommendations based on your prior choice of movies for the next movie you should watch.
4. Selling Big Data To Various Businesses
So, to generate revenue out of Big Data, it is necessary to sell it. Data is becoming a valuable asset for companies these days to obtain customers and grow. Therefore, companies willing to buy data from consumers are ready to make it available to them. Thus, big companies can sell their data to other companies. They can earn much more money directly from their data. A majority of telecommunication companies sell their big data at some point, with around 50% doing so.
Acxiom, a company in the USA, sells consumer data to other companies who use it in marketing campaigns. You may have heard of Acxiom as the most prominent company on earth. Acxiom’s business model is based on the collection of people data. It sold that data to multiple banks and retailers during the 1980s. Directly or indirectly, 12% of the country’s marketing decisions are made using data gathered by this company. It reportedly holds information on almost all residents of the USA.
5. Using Big Data To Manage Risks
Every company must manage risks. Profits and increased profits can only be attained by managing risks. Analytics has played an essential role in managing risk. Companies can now effectively manage their risks. By taking into consideration all the information generated by a company, like:
- Levels of production
- Base of consumers
- The financial sector
- And so on.
Overall, the company has a massive amount of data that reduces any guesswork. This method clearly shows business decisions’ implications, therefore reducing risk. The business risk associated with Starbucks is reduced using big data analytics. They usually open their shops near other coffee houses and still succeed very well.
Their secret is to collect the location data for their shops. Customers’ preferences, demographics, traffic patterns, etc., should all be carefully analyzed by a company. There is no risk associated with the venture. Thus, they can select locations that provide the highest level of profit while reducing risk.