The speed of sound. The speed of light. The speed of electricity. 

These are all pillars of measuring time—and it’s because of innovators, scientists, and philosophers across the generations that we have measurements and understanding of time. 

But, the world has changed, and so has how we value time and speed. 

In the digital world, real-time has become an essential component of analytics, which companies can significantly benefit from. But, there are some questions about real-time analytics, and we’re not referring to the philosophical ones.

What exactly is real-time analytics, and how does it work?

Read on to find out—and how your brand can leverage real-time analytics for deeper product analysis, customer experience, and more. 

What is real-time analytics?

Many analytics platforms define real-time differently, from seconds to days to weeks. But what is real-time, and how does it work?

Generally speaking, real-time analytics utilizes logic and mathematics when processing data to provide fast insights, and inform agile business decisions. 

Not everyone measures real-time in the same way: 

• For some users, real-time means analytics are deduced within minutes. 
• For others, real-time refers to the analytics systems on standby, ready to compute whenever a user decides to request a query. 
• In addition, some consider real-time analytics to be continuous or streaming and constantly digesting and reading data. This is executed within seconds. 

At Scuba, real-time analytics is what we consider the purest form of real-time. To us, real-time analytics means the ability to continuously digest and analyze data streams, provide insights, and hone in on data points at their closest arrival—which can be within seconds.

Getting live, streaming data is key for businesses—and real-time analytics tools have the capacity to digest large amounts of data in a quick, efficient manner. In turn, this enables brands to quickly act on insights and data to improve their product, customer service, retention, and more. 

Real-time analytics in theory is both exciting and promising. But how do real-time analytics literally work? Let’s take dive behind the inner workings of real-time data to find out. 

How does real-time analytics work?

While real-time analytics tools may vary slightly, the majority of them operate using four core components. Under the hood of real-time analytics, there typically are:

Depending on the speed at which companies need data analyzed, real-time analytics tools can also include additional components but aren’t essential. However, fast insights, such as in seconds, tools may also incorporate the following:

• Processing in memory: This enables latency reduction by integrating a processer in a memory chip.
• In-database analytics: Analytics logic is built into the database and occurs when data is processed.
• In-memory analytics: Data is queried in random access memory, not physical disks.
• Massively parallel programming: Multiple processors, which have their own operating system and memory, are assigned to specific parts of a program.

Real-time analytics vs. batch processing analytics

Real-time streaming analytics and batch processing analytics are two methods leveraged by companies to deduce insights about their customer experiences, product, and more. However, the two are very different:

• Batch processing analytics: A set of data is collected over a period of time and then manually implemented into an analytics system. This process’s namesake comes from the action itself: collect a batch of information and submit it to be analyzed and digested. Batch processing is also high latency, meaning answers to queries submitted are at least a few minutes old. In short, much of the data processed is static—and batch processing analysis is effective when handling data that doesn’t change. For example, batch processing is often used for monthly or biweekly payroll and billing. 

• Real-time streaming analytics: Under this model, data is digested by analytics tools as data bits come continuously. This provides users with quick analytics and visualizations that can then be acted on. Streaming analytics is low latency, meaning a platform can operate a high volume of data with minimal delay. 

Depending on your brand’s analytics needs and goals, investing in real-time analytics or batch-style analytics may be best—and some companies even use both. 

Curious about who and what companies use real-time analytics? Read on to find out.

Benefits of real-time analytics

Leveraging real-time analytics into your arsenal of tools has a plethora of benefits. By capturing live, continuous insights paired with customer journey visualizations, real-time analytics can elevate a brand’s customer experience, product analysis, retention, and more. In addition, real-time analytics provides several other benefits:

• Combining multiple data sources that are traditionally siloed: A major challenge when it comes to analytics is capturing all data across many internal and external siloes. Most real-time analytics tools aggregate all your data, providing an all-encompassing picture of customer journeys and product analysis. 
  
  

• Tracking and monitoring customer data: Real-time analytics gives you a live snapshot of how your customers are behaving and what their customer journey looks like. Getting the most updated data analytics enables companies to act quickly to optimize customer experience or address any issues, like churn or drop-off.
  
  

• Drive better decision-making and make processes more agile: When brands have a robust understanding of what their customer journeys and product analysis look like, they can work smarter and faster. Leveraging the most up-to-date analytics enables companies to pivot to agile decisions and optimization. 
  
  

• Data visualization: Most real-time analytics platforms also offer data visualization, which can go beyond numbers on a dashboard. Some platforms, like Scuba, generate a comprehensive view of varying customer journeys, so brands can literally see how and where their customers are behaving. 
  
  
• Real-time testing: A/B testing traditionally takes time to be executed and produce results. However, real-time analytics disrupts that norm. Instead, real-time analytics gives companies fresh insights they can leverage to forecast customer behavior and journeys. This caliber of immediate information can be used to better optimize A/B testing.
  
  
• Cost efficiencies: Brands can cut costs across the board when using real-time data analytics. With automated analytics and functions, this reduces the manual effort needed by analysts, data scientists, and engineers—which can reduce a brand’s overall time to recovery, resolution, and acknowledgment. Additionally, the insights generated from real-time data can pinpoint areas of a customer journey or product analysis previously unnoticed. All of which can improve your product, customer experience, and profit. 
  
  

• Faster response time: Sometimes analytics aren’t generated fast enough for a company’s needs. Real-time analytics is streaming—meaning data is continuously digested and analyzed. This gives brands the upper hand when noticing a stark drop in retention or increase in churn and the capacity to respond quickly to customer needs. For example, if a payment confirmation link isn’t working and a customer can’t purchase your product, real-time analytics can detect and flag the issue. And in turn, enables brands to be agile in handling any issues. 
  
  

• Delights customers now: Real-time analytics can directly improve a customer’s experience in a quick, positive manner. Brands can leverage insights in real-time to be notified of points of friction or unexpected issues—and tend to them immediately. Acting quickly to change a customer’s experience immediately not only makes a customer happy but allows brands to improve their product and services.
  
  

• Highlights brand sophistication and responsiveness: Operating in real-time gives companies an elevated approach to their business goals and customer satisfaction. Whether it’s pulling fast, up-to-date reports for stakeholders, or fixing a customer issue minutes within an issue is detected, brands can enhance their operations, analytics, and overall brand reputation.

Who can use real-time analytics?

Real-time analytics can be leveraged by anyone—but can be challenging for those without advanced tech experience, like data analysts or engineers. However, self-service real-time analytics platforms, like Scuba, are built to empower teams across businesses with their intuitive, no-code design.

Regardless of what team you’re in (and tech experience), real-time analytics is a versatile tool that can be used by anyone: 

Marketing

It’s essential for marketing teams to understand customer journeys, points of success, and areas of friction. Marketers can leverage real-time analytics to gain insight into how well content, ads, and segmentation is working. Moreover, real-time analytics can improve and enrich customer data platforms brands (CDPs) use for better insights. 

Some examples in which marketers can use real-time analytics:

• Quickly seeing which marketing channels offer the lowest customer acquisition costs.
• Understanding which marketing campaigns are most effective in generating new leads.
• Quickly segmenting audiences to know which personas are most likely to convert or churn.

Real-time data also gives marketers a more clear understanding of what customers want and resonate with. In today’s world, customer experience and personalization drive a brand’s success. So, marketers can tap into that with real-time analytics. By investing in real-time customer journey analytics, companies can increase their new customers and revenue by 44 percent. 

Product Management

Real-time analytics gives product teams quick, accurate, and expansive insights into how customers interact with product features, messaging, packaging, and more. For example, product teams can get a granular, real-time view of how a customer or prospect is navigating through a demo. Based on following that customer’s journey, teams can make agile changes in product or enhance a product feature that is wildly successful. 

Analysts & Data Scientists

Analysts and data scientists can benefit from real-time analytics in a number of ways. Real-time analytics enables analysts to capture the most recent snapshot of a customer journey, spot trends, run queries, and conduct experiments with the most accurate data. Instead of relying on analytics tools that may not have the capacity to update data daily, analysts can provide their team and business leaders with data that is relevant, fresh, and constantly evolving. Some real-time analytics platforms, like Scuba, also provide analysts and data scientists with a system that automatically updates and continues to digest data as it comes in. Additionally, modeling data and building a common analytics model that everyone in the business can use is often another challenge that Scuba’s real-time analytics platform can resolve easily. 

Engineers

Data security and management are critical for business success, and real-time analytics can be leveraged by software engineers. Companies need to ensure they remain compliant with regulations, like GDPR, to protect against data loss and breaches. With real-time analytics, engineers can build and manage their data structures with data reliability and speed. Engineers can also utilize real-time analytics in the following ways:

• Monitor internal and external activity as it happens—and work in tandem with analysts to format data in a way that is easily used.
• Build scalable, unified data infrastructure that is supported by fast, accurate, up-to-date data.
• Review event logs across a network in real-time to monitor any suspicious activity.
• With real-time analytics platforms like Scuba, engineers can analyze new behavioral patterns, without ETL, pre-aggregated data, or the need for company-wide technical expertise.

Service

Customer service teams leverage real-time analytics to provide better customer experiences, and gain deeper insights into a customer’s journey. Reviewing, monitoring, and analyzing data in real-time gives customer experience teams the ability to do the following:

• Increase customer lifetime value.
• Provide an elevated customer experience in comparison to competitors who do not leverage real-time analytics.
• Identifying friction points in a customer’s journey, to then address and reduce those problems.
• Reduce churn and improve retention rates.
• Make agile business decisions and pivot quickly to address sudden changes in customer behavior and journeys. 

Leadership

Real-time analytics are key to success and profit for any brand—and can be leveraged by company leaders. Driving revenue and accomplishing business goals are top of mind for executives who are facing an ever-growing bar of success. A Forrester study found that 90 percent of enterprise leaders understand the importance of real-time analytics, and 84 percent believe executing real-time corrections is essential. 

Executives can rely on real-time analytics to provide fast, accurate, and comprehensive analysis reports, and make informed decisions on those findings. Real-time analytics platforms, like Scuba, digest and unify data in a single platform and provides leaders with real-time visibility across different data siloes. Business leaders can use real-time analytics to accomplish the following:

• Make agile, strategic business decisions. 
• Reduce costs and increase profits in an efficient manner.
• Improve and create products based on customer journey experiences. 
• Provide accurate, unified reports to stakeholders and board members. 

Real-time analytics is on the rise. Scuba can help you dive in.

Real-time analytics is revolutionizing the way businesses approach customer experience and product analysis. With insights that are fresh and quick to see, real-time analytics gives businesses and team members across the organization the power to make informed decisions. 

However, not every analytics platform is equal. Some platforms provide near-real-time data analytics, getting businesses close--but not close enough. This is where Scuba can bring you up to speed. 

Scuba is a real-time customer intelligence analytics solution that provides you with the answers you need in seconds. Scuba digests data from multiple sources and can store both structured and unstructured data, so your analyst teams don’t have to spend time prepping and cleaning data. Instead, users across a company can dynamically visualize customer journey maps in real-time, and analyze new patterns as they emerge.

Want to make better informed, agile business decisions and improve your customer experience at the same time? Explore Scuba today.

Watch this video where CloudBees merges customer data from multiple data sources, and then starts to perform deep analysis with Scuba in under an hour.