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Insights Examples: Real-Life Examples of Business Insights Derived from Data Analysis
Examples of Data Insights

If your business collects data, you may be wondering what insights you can obtain from all the raw information.


This article aims to not only explain what data insights are but also provide examples of said insights. We’ll see how well-known brands have extracted insights from data and how those insights have helped their businesses.


What Are Data Insights?


Data insights are the knowledge and understanding a business can derive from analyzing data. The data collected for analysis could be anything from customer data to data that revolves around your company’s products or marketing efforts.


Until it's analyzed, raw data won’t provide meaningful insights. It’s simply cold, hard facts that relate to factors like customer behavior, target audience demographics, marketing channel activity, and so on. That changes when you use data analytics tools to sift through data, as you can gain actionable insights that pave the way for business success.

Why Are Data Insights Important?


Data insights are essential for the following reasons:


  • Make Informed Decisions: The insights you get from analyzing data can help you make informed decisions. Rather than relying on your gut instincts or using trial and error, you can analyze data and use the insights as a guide for your decision-making process. In turn, your data-driven decision-making will help you improve business performance.
  • Improve Customer Experience: Analyzing data can help you uncover valuable customer insights you can act on to cultivate customer satisfaction. A deeper understanding of your customer base will help you anticipate customer needs, improve customer retention, promote customer loyalty, and prolong customer lifetime value.
  • Fine-Tune Marketing and Sales Strategies: When you use customer insight tools, you can get consumer insights that tell you how your customers are responding to your marketing and sales strategies. These valuable insights will help you fine-tune your tactics so that your target market responds favorably to future campaigns.
  • Predict Future Trends: Data analytics can help you predict future trends and get ahead of potential problems. For example, you can get insights into what makes your customers churn and fix these issues for better retention.


If your business intends to maintain sustainable growth, it’ll need to do more than just collect data but also extract and act on the insights therein.


Real-World Examples of Using Data Analysis for Business Insights


The brands discussed below offer six real-world examples of how analyzing data can help a company get actionable business insights:


Nike


As one of the most recognizable sporting goods companies, Nike no doubt collects and analyzes a ton of data. In a blog post published on its website, the company reveals the role data analysis plays in shaping its shoe designs.


The insight Nike obtained from analyzing data was how 70% of its carbon footprint comes from the materials used to make its shoes. According to Nike’s footwear materials developer, Isabel Torres, this knowledge compelled the company to change its materials.


To that end, the company decided to incorporate more recycled components into its shoe designs. This task meant that Nike’s data analysts and shoe designers needed to be on the same page as to the percentage of recycled materials included in each shoe.


Currently, Nike has been able to achieve synergy between its data analysts, designers, and factory partners. Many of its shoes now have at least 20% recycled content (by weight) without compromising on quality. The company used insight from data analysis to improve its operational efficiency, lower its costs, and position itself as environmentally friendly.

Electronic Arts (EA), Romania


Electronic Arts, the video game developer, isn’t shy about attributing its successful video games to data collection and analysis.


In this blog post, its Romania division reveals that it analyzes data to get insights into how to improve gameplay, understand its players, and tailor experiences to their expectations.


The company’s Analytics Department has a Consumer Insights arm that helps EA make informed decisions about a game’s quality. Thanks to the Analytics Department’s data analysis efforts, EA gets insights about their customers’ needs. In particular, there’s a focus on how players expect their games to be and the frequency with which they’re updated.


To do the above, EA’s analysts sift through terabytes of data generated by its 650 million-strong player network. They track user behavior, in-game events, interactions, and more, and make the necessary adjustments to cultivate player satisfaction.

Netflix


Ever since making the transition from physical DVD deliveries to online streaming, Netflix and data analysis have been two peas in a pod. In a Medium article, Nirwal Govind, the company’s VP of Data Science & Engineering, explains how Netflix utilizes data to get insights that provide excellent customer experiences.


One of the main planks of Netflix’s use of data to get insights is a concept that the company calls streaming Quality of Experience (QoE). QoE refers to the way members interact with Netflix, and the company collects this data to not only understand but also predict its users’ behavior.


Mr. Govind uses the example of how tweaks to Netflix’s product will affect its’ members' watch hours. In that regard, Netflix uses two metrics:


  • rebuffer rate, which relates to play quality (how often the streaming gets interrupted as additional data is downloaded from Netflix’s servers);
  • and bitrate, which relates to picture quality.


By constantly analyzing data, Netflix can get continuous insights into these two metrics. More importantly, it helps the company give its members the best streaming experience possible.

Uber


In this 2021 blog post, Uber writes about how data analytics have been instrumental in providing users with a frictionless experience. According to the company, the insights it has obtained from its analysis are reflected in the app’s home screen, the messages users see, and more.


Uber collects and processes rider data, including the way its users use the Uber app. The blog post mentioned above reveals how the insights from its data analysis have affected the app’s evolution.


Notable mentions include:


  • Rides Shortcut: a feature that reduces the amount of taps it takes to book a ride; and
  • Dynamic Home Screen: a feature Uber believes increases engagement.


According to Uber, high-quality data (and the insights therein) has helped it not only improve the user experience but also retain users. The company attributes its understanding of what works best for its users when adding new features to data insights. Thanks to these insights, it maintains a balancing act to ensure said additions don’t degrade the user experience.

AstraZeneca


AstraZeneca is best known for being one of a handful of pharmaceutical companies that created an effective vaccine during the Covid-19 pandemic. In a blog post on its website, the company reveals how it uses analytics from data obtained from its clinical trials when developing new drugs.


Relying on data and models collected from past trials, the company is able to predict how patients will respond to treatment. It uses real-time data analytics to monitor and ensure that its novel candidate treatments are not just effective but safe.


The company’s REACT (real-time analytics for clinical trials) system also ensures rapid and robust decision-making during trials.


According to Dr Dónal Landers, Clinical Leader for the iDecide Programme and Director of the digital Experimental Cancer Medicine Team (digitalECMT), the insights help researchers understand the risk versus benefit balance of new drug candidates. These insights, Dr Landers, explains, have the potential to change the culture at AstraZeneca and speed up its processes.

Conclusion


Collecting and storing data is only half the equation when making business decisions. As the article's examples show, you also need to analyze that data for potentially transformative insights.


That said, during the data-collection stage, don’t neglect to use software to ensure data security. iDox.ai can help you discover and manage sensitive data so that you can safely extract insights when needed.


Try our seven-day full-access trial today to see how our software can protect your data.


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