Why Is Real-Time Analytics of Paramount Importance for Enterprises?

According to a study in 2022, 80% of firms reported increased revenue from real-time data analytics. Real-time analytics is simply the process of analyzing real-time data and using the results to make decisions.

It’s the new frontier for user research and customer behavior research; real-time analytics give us real-time insight into an enterprise’s products or services as well as how customers interact with them.

It allows companies to identify market opportunities and enables faster adjustments to their products or services with respect to customers’ needs and to minimize customer churn.

Benefits of Real-Time Analytics for Enterprises

Real-time analytics bring actionable insights to the fore for better decision-making. Here’s a rundown of the benefits accrued to enterprises across sectors:

Micro-Targeting Precision

Using real-time analytics, brands can segment their audience in certain classes, revealing what their customers like to engage with, how they respond when making purchases, and more. In this way, personalization can be done to a level completely unknown before. Organizations can easily personalize their messaging, offers and even the precision of the actual product that’s sold and hence have a much higher rate of conversion.

Fraud Detection Agility

According to IBM’s latest report, the average data breach cost in 2023 is a staggering $4.45 million. With such an active threat landscape, it is easy to see why organizations in core industries (like financial services) are concerned. However, real-time analytics can help save time. For instance, thanks to real-time analytics solutions, financial institutions like banks and insurance companies can identify fraud cases in real-time that they would not be able to identify if not for the analytics. Also, they are easily able to prevent fraud cases from happening in the first place.

Operational Anomaly Detection

Real-time analytics can help organizations by discovering abnormal patterns of activity in machines and processes to help detect anomalies early and avoid concerns and problems which will help industrial plants become more efficient and run smoother.

Personalized Patient Treatment

Healthcare providers can use real-time data to identify what treatments a patient will have a positive response to, or what treatments may be more appropriate for a particular condition or injury. This will improve healthcare delivery, minimize incidents of misdiagnosis, exaggerations of problems, and delays in treatment.

Reactive Pricing Strategy

By leveraging real-time operational insights, retailers can make real-time pricing updates according to fluctuations in demand, competitor pricing changes, and other issues to keep them competitive in the marketplace. This maximizes revenue and profits.

Challenges in Implementing Real-Time Analytics

By now, we’ve seen how real-time analytics can accrue several advantages for diverse sectors. However, there are some challenges as well that transpire from the inherent complexity of the analytics function.

Consider this; real-time data streams can be massive and rapid, requiring significant computing power and storage. Many real-time applications require a threshold for event rate beyond which the data cannot be processed in real time. That said, here are some major challenges in real-time analytics:

• Complexity: Real-time data analysis is complex in nature. It involves transforming, monitoring, and processing data streams in real-time.
• Latency: Data latency is measured in seconds or milliseconds. Real-time analytics solutions must process the data quickly to deliver actionable insights without delay.
• Volume: Many real-time applications deal with massive volumes of data. They require robust analytics tools and techniques to deal with extensive volume.
• Lack of Skilled Resources: Real-time analytics requires highly skilled personnel to handle massive amounts of data. These professionals must be domain experts and adept in data management and processing.

Navigating Challenges with Emergys’s Managed Services Prowess

Navigating the discussed challenges with managed services requires a strategic and comprehensive approach that aligns business objectives with advanced technological solutions. What does this entail? For a start, enterprises must look for managed services providers that offer 24*7 monitoring, enhancement and support, platform upgrades, and more.

Once partnered with expert service providers, organizations can leverage specialized skills to tackle complexities seamlessly and professionally. These managed service partners offer tailored solutions, addressing resource limitations and staying attuned to rapid tech evolution.

For example, at Emergys, we enable enterprises to leverage real-time analytics to:

• Boost pattern and trend recognition
• Unearth relatively deeper business insights
• Develop a better grasp of customer needs
• Narrow down the scope of business performance improvement
• Effectively respond to changing market
• Predict trends and shifts in demand

How do we accommodate this? Emergys’ real-time data analytics solutions offer organizations a potent combination of advanced analytic models, scalable and secure cloud infrastructure, and a rich palette of features. In this way, we link customers with actionable insights that boost the quality of their initiatives. For example, we provide them with:

• 24*7 support for big data technologies and cloud platforms
• Data storage and processing
• Upgrades, maintenance, configuration, migration, etc.
• Creation of visual analytics functions and reporting

All these managed services are designed to ensure a timely flow of actionable insights, facilitating continuous improvement in operations, democratizing access to data analytics functions, and reducing the total cost of ownership (TCO).