Achieving success with big data analytics

Large volumes of data can be analyzed and business decisions based on that data can help companies perform more effectively.

This suggests that Big Data Analytics is the most profitable route right now!

Is it any wonder, then, that an increasing number of businesses are adopting a data-driven business model?

Here are some real-world instances of companies that have found success with big data analytics and how they are using big data analytics to their advantage. 

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A. Advertisers May Use Big Data Analytics to Solve Their Problems and Get Marketing Insights

Big data analytics may aid in the transformation of all corporate processes. This involves making certain that marketing initiatives are effective.

Let’s face it, the truth is many businesses have squandered millions of dollars on ineffective marketing. What is causing this? It’s quite likely that they missed the research stage.

After years of cautious optimism, the marketing and advertising technology industry may finally fully embrace big data.

A more detailed analysis is possible in the marketing and advertising industry. This entails tracking online activity, monitoring point-of-sale transactions, and detecting dynamic changes in client behavior on the go.

Collecting and analyzing consumer data is required to gain insights into their behavior. This is accomplished using a method similar to that employed by marketers and advertising. As a consequence, you’ll be able to run more concentrated and targeted ads.

Businesses may save money and increase efficiency by using a more focused and customized strategy. This is because they employ the correct items to target high-potential prospects.

Advertisers benefit from big data analytics since it allows them to better understand their clients’ purchase habits.

We can’t overlook the massive problem of ad fraud. Organizations may define their target clientele with the use of predictive analytics. As a consequence, organizations may have a more relevant and effective reach while avoiding the massive costs caused by ad fraud.

  • Netflix

Let’s start with Netflix, which has made several attempts to leverage big data to improve key aspects of its services.

The most visible manifestation of this, at least to the general public, is in their data-driven recommendation platform.

This has improved the company’s relationship with consumers while also saving money and influencing the sorts of information that hits the servers.

If you’re looking for successful instances of big data-driven marketing, look no further than Netflix.

  • Airbnb

Airbnb is one of the most successful big data success stories, as the firm has built so much of its business around gaining important insights from data. The data science they employed greatly improved their marketing efficiency.

Airbnb used big data to figure out where the greatest and worst performances were geographically, and then using the information to draw intelligent conclusions and make beneficial improvements.

To learn more about how Ascend can help you grow your company and succeed in the big data age, contact us today!

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B. Companies May Use Big Data Analytics for Product Development and as a Innovation Driver

Another significant benefit of big data is its capacity to assist businesses with product innovation and redevelopment.

Big data has essentially become a means of generating new income streams by allowing product innovation and development.

Before building new product, lines or revamping old ones, companies start by rectifying as much data as is technically possible.

Every design process must start with determining what exactly meets the clients’ needs. A business can investigate client demands through a variety of means.

The company may then use big data analytics to determine the best way to profit on that requirement.

You’ll need a lot of data to increase the quality and simplify your production process. This implies that these businesses will need to devise ways to keep track of their products, competition, and client feedback.

After the data has been gathered, an analysis is carried out to ensure that logical thinking is used before a plan of action is established.

Fortunately, when it comes to obtaining and utilizing big data, product makers of all sizes have a distinct edge. As a result, these businesses may quickly increase their product range by developing novel items.

  • Uber Eats

Uber has been the taxi industry’s leader for a few years, so it came as no surprise when they announced they will be expanding its services to include anything from transporting passengers to delivering food.

They joined the crowded food delivery sector and, owing to the data they gathered as a cab behemoth, they are here to stay.

They wanted to be known as a delivery service that always delivered food when it was still warm, so they sought to model the physical environment in such a manner that they could anticipate the time of food delivery as accurately as possible.

To make this project work, they also gathered information on how long it takes to prepare a particular dish, so they could pinpoint the exact moment when the delivery person should come to pick it up.

This step allows drivers to pick up more meals on the go (because they don’t have to wait for the food to be prepared), and Uber is incentivizing them to carry more than one meal each trip by offering a bonus for each meal they collect.

This isn’t the first time it’s been done, but they’re doing it better than anyone else since they’re utilizing data. They’ve gone so far with this that they’ve hired meteorologists to assist them forecast the weather and how it will affect the delivery.

Uber Eats is a perfect illustration of how Big Data and data analysis can help firms extend their offerings and gain a significant competitive edge.

Airbnb used big data to figure out where the greatest and worst performances were geographically, and then using the information to draw intelligent conclusions and make beneficial improvements.

  • Apple

Apple is well-known for its mastery of cutting-edge technologies.

They’ve been known to employ big data technologies, and now they’re also doing big data analytics, with big data influencing a lot of their decisions.

The information they gathered is utilized by the organization to determine the best route to take when it comes to new goods and services they plan to provide.

Apple can use big data to figure out how people use applications in their daily lives and adjust future designs to match user preferences.

Apple has used big data to aid in the development of new products as well as the design of apps and technologies for future releases.

To learn more about how Ascend can help you grow your company and succeed in the big data age, contact us today!

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C. Brands May Utilize Big Data Analytics to Increase Customer Retention and Acquisition

Any firm relies on its most valuable asset: its customers. There is no firm that can call itself successful without first building a strong consumer base. 

Even with a client base, though, a company cannot afford to ignore the fierce competition it confronts. 

If a company takes too long to figure out what its customers want, it’s all too simple to start selling low-quality goods. In the end, you’ll lose customers, which will have a negative impact on your business’s overall performance.

Businesses may utilize big data to observe numerous customer-related patterns and trends. It is critical to observe client behavior in order to elicit loyalty. 

Theoretically, the more data a company collects, the more patterns and trends it will be able to detect. In today’s corporate world and technological era, a company may quickly obtain all of the client data it requires. This implies that the modern-day client is relatively simple to comprehend. 

To summarize, having a big data analytics plan to optimize the data at your disposal is all that is required. A firm will be able to obtain important behavioral insights that it needs to act on to maintain its client base if it has a proper customer data analytics framework in place.

Understanding consumer insights will enable your company to provide exactly what your customers desire. This is the first and most important step in achieving great client retention.

  • Starbucks

Starbucks is a multinational company with a well-known logo and a reputation for misprinting customers’ names on cups.

Personalization is the key to success in today’s world, and Starbucks is doing just that — they’re leveraging Big Data to improve the customer experience!

They acquire data by offering their clients Starbucks rewards programs and mobile applications that allow them to understand more about their customers’ purchasing behavior.

Starbucks will then use this information to promote goods to its loyal consumers, develop stronger marketing campaigns and new menus, and choose where their next store will be located. 

This system is so well-organized that it will recommend items to clients based on the season, weather, and location.

Customers who haven’t visited the business in a while receive tailored emails with offers in order to re-engage them or send them discounts.

  • Burberry

Burberry, a well-known British fashion house, is likewise leveraging big data and artificial intelligence to improve performance, sales, and customer experience.

Naturally, their clients utilize a mobile app to access loyalty and rewards programs. Burberry urges customers who utilize these services to give their data, which they then use to make appropriate suggestions for both online and in-store items.

What’s most intriguing is how this transfers to Burberry’s traditional brick-and-mortar locations. 

Sales representatives and sales assistants have access to company-owned tablets that offer purchasing recommendations and more information about specific consumers. Employees have access to a customer’s purchasing history, preferences, and even social media posts.

They may utilize this information to deliver a more tailored experience, thus increasing revenue.

All items at Burberry stores have unique RFID tags, taking this notion of knowledge and digital information in a new direction.

When customers enter a store, a mobile app experience will speak directly with them about various products. They may discover where items come from and even get styling advice.

It’s a fantastic combination of digital and physical connection that increases their customer service and reaction time.

  • DBS Bank

As one of Singapore’s major banks, DBS bank is no stranger to competition, and in a climate where fintech competitors are on the rise, the brand must innovate to stay ahead of the pack. 

DBS has aggressively invested in AI and data analytics to give hyper-personalized insights and suggestions to its clients, allowing them to make smarter financial decisions.

This entails giving intelligent banking features such as investment suggestions on financial goods and instruments, stock recommendations based on investor profiles, and odd transaction alerts, to mention a few.

DBS hopes to improve the way clients bank by analyzing their data sources and transforming their brand from just a bank to more of a trusted financial counsellor.

Data will be used by employees across the bank to address business difficulties, uncover opportunities, and develop more intuitive customer experiences and products.

Today, putting the customer’s experience first is critical. 

You’ll be able to find insights into your customers’ pain issues and how they engage with your platform by analyzing crucial customer data, allowing you to better serve them.

To learn more about how Ascend can help you grow your company and succeed in the big data age, contact us today!

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Ascend Analytics and Big Data Analysis 

Big data is a potent instrument that may provide a major competitive edge to a company. Organizations may use it to save time and money, target audiences, influence decisions, and improve customer experiences.

Ascend offers a comprehensive suite of data analytics and predictive analytics consulting services. It enables real-time data streaming from a variety of sources and facilitates in the extraction of crucial insights from high-quality data.

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