In today’s business landscape, data plays a crucial role. The world generates a staggering 2.5 quintillion bytes of data daily, and an average person produces approximately 1.7 MB of data every second concerning their online activities. The internet has expanded greatly, and businesses increasingly rely on digitalization. As a result, the importance of data analytics has rapidly increased. Currently, over 97% of companies worldwide are investing in AI and big data to some extent and seeing positive results from these investments.
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Research has shown that companies that utilize data analytics solutions increase their profits by an average of 8%, which can be substantial depending on the company’s size. These statistics set a precedent that organizations looking not just to sustain themselves in the future but grow as well are leveraging data analytics for efficient decision-making and gaining a competitive edge.
If your company is starting its data analytics journey, here are some basics to enhance data-driven decision-making and gain a competitive advantage.
Different Forms of Business Data
There are various types of data that are generated, and businesses can collect, sort, and analyze these in numerous ways to back their decisions:
Information about business operations, such as inventory level, supply chain efficiency, and employee productivity, is included in operational data. This information can pinpoint places where operations can be improved, costs lowered, and overall efficiency increased.
The business analytics process determines customer behavior and preferences. This allows companies to understand their target audience better, customize their offers, and optimize the customer experience. And in today’s competitive landscape, this knowledge can be a major asset.
Information on the success of marketing efforts is included in marketing data, including traffic to the site, opening rates for emails, and social media involvement. This information can target audiences and enhance marketing efforts more effectively.
Data on trends in retail revenue and consumer purchasing patterns are also included. This information can be used to anticipate future sales, identify growing regions, and optimize pricing strategies.
How Leading Companies Are Leveraging Data Analytics
There are numerous instances of businesses that have effectively used data to grow their businesses. Some case studies are shown below:
Uber is a global ride-hailing business that uses data to enhance customer satisfaction and optimize pricing tactics. To refine their pricing tactics and enhance the general customer experience, they gather information on driver behavior, passenger feedback, and traffic patterns. More than 110 million active users globally as of 2021 are a part of this ecosystem, which has led to their quick growth and success.
Uber can offer a more customized experience for stakeholders by effectively using data available to clients and drivers. The service provider tweaks its services depending on the markets and countries that it operates in. For instance, in South Asian countries, ride-sharing from Uber is not just limited to cars but also includes motorcycles. It is an effective channel that allows them to instill loyalty and increase revenues worldwide.
Who isn’t familiar with Netflix nowadays? The biggest streaming service in the world today started off as a simple movie rental company. Not only was the company able to evolve with the times, it was one of the first to jump on the data analytics bandwagon, ensuring that it could deliver a more personalized experience for customers across the board. The content that the service produces is driven by insights that are obtained from customer and sales data.
Netflix customizes the customer experience by using data. They gather information on users’ watching patterns, search requests, and ratings to make recommendations for new content that people are likely to appreciate. This has helped them develop quickly and be successful; as of 2021, they had more than 208 million subscribers globally. Their user base continues to grow massively thanks to their data-driven decision-making strategies.
Founded in 1971, Starbucks has grown into a household brand with over 32,000 stores spread over 80 countries. It is a global phenomenon in the beverages industry, and the reason that the company has been growing continuously for the past five decades is because of its reliance on innovation and personalized customer service. Nowadays, the brand is effectively utilizing data analytics to project user behavior and stay on top of relevant trends in the industry.
Starbucks optimizes store designs and customizes the consumer experience with data. They gather information on consumer preferences and purchasing patterns to improve their marketing efforts and menu selections. In order to increase productivity, they also optimize staffing levels and store layouts using data. As a brand, Starbucks has made customers the center of its attention and uses data to attract them in the most ideal ways possible.
Amazon, which began as a humble online bookstore, has now become one of the most highly esteemed brands globally. As a digital corporation, Amazon holds diverse assets, including eCommerce, cloud services, and various other industries. With millions of customers, Amazon possesses one of the largest data caches available and employs advanced analytical tools to tailor its offerings to users’ preferences.
Amazon, the giant e-commerce company, utilizes data to improve its pricing strategies and identify areas for potential expansion. They gather information on buyer behavior, past purchases, and product reviews to spot trends and improve their product selection. This has helped them dominate the e-commerce business; as of 2022, Amazon ships more than 1.6 million packages daily, translating to 66,000 orders an hour and a little more than 18 orders per second.
The use of data analytics in making strategic business decisions has become common today as more companies are adopting this approach. The effectiveness, accuracy, and comprehensiveness that come with data-driven strategy formulation are unmatched because organizations are not only able to quantify customer behaviors and purchase patterns today, but they are also able to predict what they are going to be like in the future.