Data analytics for business:
Case studies & success stories

What is data analytics?

Data analytics is the science of analyzing, organizing, and storing data to make successful decisions and gain important insights. No lucrative company can exist without it, as it helps comprehend customers better and create compelling marketing strategies that strengthen overall productivity. This results in increased income and lower costs.
An impressive number of data analytics advantages make this tool applicable to any business sphere.

There are four basic types of data analytics, here they are and their benefits:

1. Descriptive analytics: this type of data analytics outlines the events during a specific timeframe. It answers whether the number of views has gone up or which month the sales were stronger.
2. Diagnostic analytics: By covering more varied data inputs and a bit of hypothesizing, diagnostic analysis concentrates on why something happened. For example, whether some external factors affected the sales or did the latest marketing campaign bring the expected results.
3. Predictive analytics: This type allows forecasting what is likely to happen. Predictive analytics solutions can help to determine whether an investment in new products is justified while investors choose where to put their funds.
4. Prescriptive analytics: Unlike predictive analytics, prescriptive analytics not only predicts the future but also submits a definite set of actions that may change the success of a future project for the better. It allows teams to get information about potential events and choose the most effective strategy for them.

In recent years, exploratory data analysis has been gaining huge popularity. EDA is a subfield of data analytics that concentrates on comprehending the underlying patterns and relationships within a data set. It is a crucial part of any Big data development process as it summarises essential data characteristics mostly with the use of visual methods. The main advantage of EDA is that it helps to make hypotheses and find the direction of later analysis. As a result, it helps establish patterns, anomalies, and trends before handling more complicated analyses.

All in all, data analytics is a broad field that includes numerous techniques whose main goal is to transform raw data into priceless insights that lead to several impressive benefits for your business. Read on to see it in action.

Data analytics and business: Key insights

Companies that deal with their data analytics usually reap a competitive advantage due to their ability to hasten alterations that spur innovation. Here are five major benefits of Big data analytics in business:

Advance decision-making capabilities

First of all, data analytics allows business leaders to expedite and advance the accuracy of business decision-making.
It prevents them from wasting money on faulty operations, unwise marketing campaigns, inefficient strategies, and dubious concepts for future services and products.

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Leveraging a data-centric problem-solving model allows companies to establish their organizations as more proactive in recognizing opportunities. This approach allows them to rely on the accuracy of data rather than just intuition or industry experience. It should be mentioned that decision-makers must comprehend that data can present definite patterns or propose results but doesn’t give a hundred percent guarantee. A defect in the analysis or data collection process can also result in inaccuracies or provide misleading information.

Gain greater insights into target markets

Access to customers’ digital footprints gives businesses priceless knowledge about their demands, inclinations, browsing, and purchasing actions. Organizations that analyze data gathered from targeted markets can more quickly pinpoint patterns and trends and tailor services and products to their needs.

Improve operational inefficiencies and minimize risk

To boost operational efficiency, companies gather huge numbers of customer feedback and data. As a result, it allows them to deduce meaningful patterns to advance their services and products. Data analytics for business can also benefit by determining possibilities to lower expenses, smooth operations and maximize profits.

Create targeted strategies and marketing campaigns

Businesses can leverage data to shape their approaches and implement targeted marketing campaigns, ensuring that promotions reach and catch proper audiences.

By wisely utilizing business and data analytics, marketers can evaluate customer tendencies, monitor online shopping, and evaluate point-of-sale transactional data to improve customized advertising to target new or changing consumer segments, thereby strengthening the overall efficiency of their marketing efforts. As a consequence, businesses get advanced customer-oriented marketing strategies that meet and outpace expectations, foster development, and boost brand loyalty.

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Identify new product and service opportunities

One of the best ways data analytics brings innovation to businesses is by allowing them to analyze their ongoing target audience, foresee and pinpoint product or service deficiencies, and create new solutions to address these requirements.

Companies can utilize data to track customer feedback and product performance in real time and resolve what their opponents are doing to retain a competitive position. Data analytics insights also allow leaders to upgrade existing services or products to display developing customer desires, refine marketing targets, and advance customer services.

Business data analytics solutions: Success stories

After getting acquainted with how data analytics is used in business and what impressive results it can bring, an interest in knowing real-life cases comes to mind. Here are 5 Big data use cases of leading brands that you can look up to while developing your own successful example.

Amazon

The list of successful Big data examples won’t be full without the leading E-commerce brand whose rapid growth and prosperity are mostly based on its database. To make a choice, Amazon’s team processes, collects, analyses, and stores customer information.

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Furthermore, the company monitors the items that were bought and browsed, the delivery addresses, and the product reviews. As a result, the brand has been among the top 10 Fortune 500 companies in the world for 5 years. Here are three ways how Amazon uses data to stay the best:

1. Big data allows Amazon to set prices based on product availability, item preferences, shopping patterns, activity on the site, and other aspects. Following Big data analytics models, product prices are updated every 10 minutes, and due to this, the brand always offers competing prices to its customers.
2. Amazon monitors all user activities, including purchases, adding items to their Wishlists, and even viewing products. In this case, the company uses Big data to boost the shopping experience and encourage purchases. The information gathered allows them to suggest a similar product to the one that was returned to the shop.
3. Amazon’s patented anticipatory delivery system exploits vast amounts of data to predict the items a customer is going to buy, along with their delivery date and location. Once the customer places an order, the products are dispatched from the main warehouse to ensure swift delivery.

Netflix

With over 301.63 million subscribers Netflix has become one of the most powerful streaming platforms, but it couldn’t be achievable without data analytics for business. The company’s detailed gathering of huge amounts of data plays a vital role in its prosperity.

Netflix can boast of advanced user experience by collecting customer satisfaction and responses to a TV show or a film. The service can find the time and date a user watched a film whether it was resumed or paused, or finished. It can even store screenshots of repeatedly watched scenes, search history, the given ratings, and themes that were searched for. This knowledge bolsters Netflix to take any decision, including personal suggestions for any user and the improvement of their original content.

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Data analysis also influences on Netflix’s developing custom marketing. The team comprehends what users would like to watch and tailors its marketing campaign according to their needs. This approach also helps in creating original content while selecting a definite image based on the content choices of subscribers collected by Big data.

Google

In the past years, Google has made a big contribution to data evaluation by developing several open-source tools and techniques such as TensorFlow, Google BigQuery, Dataflow, Apache Beam, Datalab, etc. Thanks to these developments, the Google team can analyze millions of sites and bring users the needed information within seconds. Here’s how it works in simple words:

1. Based on trends, search history, locations, and more, Google analyses and comprehends user requirements.
2. The information is processed by an algorithm that performs intricate computations. It seeks to align the entered questionnaires with all the available data.
3. Google’s algorithms establish what exactly a user searches for (facts, news, people, statistics) and extract the required data from a relevant feed.
4. The search engine finally presents ranked or sorted search results based on authority and relevance, tailored to meet the user’s needs.

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Spotify

Spotify is one of the largest providers of music streaming services, with 252 million subscribers. This impressive result couldn’t be possible without data analytics for business growth. Spotify team collects and analyses enormous amounts of data connected with devices used for playing, music playtime, and regional and demographic data. First of all, it is done to advance and customize the user experience.

By using machine learning and artificial intelligence, they generate unique content for every user that matches their preferences at the exact moment. This approach results in users’ desire to keep listening and discovering new music from the suggested recommendations and, this way, constantly use the app. Besides improving user experience, Big data also allows Spotify to better market its products.

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Simply put, Spotify uses information about its listeners to develop ads targeting its ideal audience. The launched “Spotify for artists” application also helps artists better sell their music. Artists can learn information about the most streamed tracks and the cities with the most active fan base, which can considerably help them plan tours and concert sets.

Apple

As the main technological trendsetter, Apple always goes ahead with any project and heavily relies on Big data analytics and business intelligence.

Analyzing data helps the brand to know how consumers use their products in real life and tailor future developments in line with users’ demands.

Here are some ways in which data analytics for business strategy allow Apple to enhance its services and sales:

1. Product development: Apple analyses usage patterns, market trends and customer feedback to gain insights into what improvements and features should be carried out. As a result, their products are always upgraded to address the changing needs and expectations of users.
2. Customer support: Apple leverages Big data to enhance its customer support services. By examining data from customer interactions, Apple can pinpoint recurring problems and deliver more effective and efficient resolutions.
3. Personalized user experience: By picking and analyzing data from numerous sources, including online purchases, customer interactions, biometric data, and app usage, Apple brings sharply aimed commercials, proposals, and content to users.
4. Heath and fitness: the right use of data makes the Apple Watch a powerful tool that can track physical activity, monitor heart rate, and detect irregular heart rhythms so precisely that it can help users treat medical disorders and even enhance defense against sickness.
5. Marketing and sales: To advance sales performance and develop targeted marketing campaigns, Apple actively uses data about customer purchasing behavior and preferences.

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Data analytics for small business: What to learn

It’s no secret that Big data analytics and business intelligence are the best at showing themselves when used by big companies that have amounts of data that are so huge that no human being could fully analyse and structure them. In this case, data analytics and artificial intelligence come to help and benefit even from earlier untapped unstructured data like free text fields, contracts and emails.

But will data analytics for small businesses be as effective as for the big ones? The answer is positive. Nowadays, any company that wants to enlarge the outcome of its work has to analyze its data wisely, that is why its size doesn’t matter. Here are some data analytics services for small businesses that can help to scale up:

Conclusion

Any leader wants his company to be successful. The key tool to achieving this goal will definitely be investing in data analytics for business. Big data technology has changed the rules of the game for all industries and companies should take it seriously to stay affluent.

No matter how big your business is, the application of this technology will be both effective for a small start-up company and an already prosperous business. Leading brands like Amazon and Apple know how to use data, and this is what makes them so successful. Learn how to make up your data, and you can be one of them.