A GUIDE TO DATA-DRIVEN DECISION-MAKING

Data-Driven Decision-Making: Main to Know. Part 2

Explore benefits and successful cases to profit from data-driven decision-making. See tips to break your business.

Sasha Andrieiev
3 min readSep 16, 2022

Successful Cases of Data-Driven Decision Making

Finally, to prove the efficiency of the data-based approach, it’s also worth mentioning the most famous examples of data-driven decision making based on the experience of companies with global recognition.

Google

Google is the name that is literally synonymous with data-informed decision making. The major goal of the company is to ensure all the decisions are based on data or analytics to ensure the best efficiency and value. That is why, they have repeatedly stressed in their company’s culture that they focus on discussion, not pithy answers at meetings.

For instance, to help the HR departments work with large amounts of various data, Google launched the People Analytics Department. The main goal of this department is to analyze the manager’s performance across different teams, which helps define the teams with better productivity and profitability.

With this data, Google’s HR department established eight behaviors for good managers and the top three challenges managers might face in their roles. What is more, Google has discovered what makes a good manager and created the “Great Managers Award” to encourage employees to nominate managers they felt made a difference and get more motivation for further work.

Amazon

Amazon has been widely known for its first-class personalized recommendation system, based on data-driven customer behavior analysis. In other words, the eCommerce platform leverages various customer information to deliver the offers with high accuracy, including past purchasing experience, reviewed and ranked products, abandoned items, and many more. Also, the company deeply analyzes the key engagement metrics such as click-through rates, open rates, and opt-out rates to further decide what recommendations to push to which customers.

Once integrated, product recommendations have become one of the leading drivers that increase sales performance and improve customer satisfaction scores. As of 2021, the customer satisfaction score of the online retailer was 78 out of 100 ASCI points (Statista).

Netflix

Another example of brilliant customer targeting with data-driven processes is shown by Netflix. The company started as an average old-fashioned DVD-sharing business. However, after leveraging data-driven decision making they have managed to better understand the current and predict future customer’s needs, and as a result grow to the world’s largest Internet streaming service today.

Needless to say, Netflix bases all of its decisions on data. Even such minor ones as:

  • The color palette for the covers
  • Personalized drip marketing strategies
  • Upcoming content

With advanced data and analytics, Netflix can provide personalized suggestions and relevant marketing content, optimize production planning, predict the popularity of original content once it’s life, and empower technical performance as well.

Conclusion

The rapid development of data analytics solutions has significantly changed the performance of many businesses across different industries. More and more companies today started leveraging big data to enhance their decision making. And, according to the notable improvements we can see today, this approach helps companies to grow faster than ever.

What is more, data-based decisions have become more accessible and universal today. So, employees from both technical and non-technical fields can effortlessly gain valuable insights into the business daily.

Nevertheless, it’s not just enough to pull up the data to succeed. Companies need to set up clear goals, data targeting, and analysis strategies to make a profit from it. Contact Jelvix for a personal consultation on a data-driven decision making strategy to discover how to make the most of it for your business today.

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Sasha Andrieiev
Sasha Andrieiev

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