Analyzing real time information in order to make decisions is a part of the human brain. Every day humans make thousands of decisions to take actions. Similarly, modern business intelligence is designed to help businesses make decisions based on collection and processing of data.
Real-time data analytics is a modern concept which involves processing of available information in order to make better business decisions. Here, mathematics and logic is used to make proactive decisions in real time. In order to meet the demands of an ever changing business world, real time data analytics has proven essential for growth.
The increasing popularity of real time data analytics:
Modernizing data infrastructure has become increasingly important for businesses to keep up with their current and real time time business needs. In order to understand customer needs, changing market demands, developing technology and IT sector, and competitors’ advantage, it is important to employ real time data analytics in BI.
As per studies conducted by Gartner, all new major businesses are using corporate business intelligence to improve their decision making skills. Since 2020, the entire workplace and workload of the corporate sector is being run on cloud data warehouses. Use of data warehouse tools has increased in recent years where data collection, processing and analysis has taken over where centralized cloud data stores are conducting real time data analysis with ease.
The way business is done keeps changing. Business intelligence and consulting firms which offer services of real time data analysis to help companies revolutionize their performance immensely. They conduct rapid data processing, identifying important factors and themes, and then finally presenting data visualization. In more detail, the process of real time data analysis includes: data mining, importance of data visualization in business, and then finally evaluation.
The 8 best and noteworthy examples of analytics:
Before exploring the examples and use cases of real time data analytics, it is important to look at how it works. Within seconds data is pulled in at intervals and output in the form of information and insight is sent out. In order to create reports, businesses hire the services of expert consulting firms like Ascend Analytics to create helpful insight reports with data visualization in no time.
Understanding the impact of real time data analytics is vital. Companies are run by best decisions made in the light of worthy knowledge. Following are some of the leading use cases of real time data analytics.
Designing marketing campaigns
Launching a marketing campaign when introducing a new product or running promotional campaigns can be challenging for businesses. Usually brands rely on A/B testing and market research to test the viability of the campaign. However, this is not done in real time. Since the use of real time data analytics has automated the process in real time. Now, brands receive metrics for conversions and post impressions to tweak the campaign as per customer’s taste.
Facilitating financial trading
Buying and selling decisions are supposed to be rapid. For data analytics in financial services, real time analytics have proved advantageous. Traders now utilize news gathered from different sources like social media and traditional news channels to make smart business decisions. On the other hand, the credit scoring process also requires the use of real time analysis for approving and denying loans. Minimizing risks is easy with real time data analytics and informed decisions produced best results.
Other than that recording stock market manipulation factors like insider trading is also done with these tools.
Healthcare related devices like smartwatch showing real time health metrics like heartbeat, number of steps taken, blood pressure etc helps physicians treat patients. For healthcare providers and insurance companies, aggregated real time data offers real insight into value based decisions. Especially when it comes to patient’s history, it is important that the doctors have access to vital insight in order to provide better healthcare and this data can be provided by the healthcare analytics consulting because they are expert at sorting the data.
Improving the furniture industry
It might seem surprising but the furniture industry is also flourishing with the help of real time data analytics. An example of this is the furniture brand Man Wah whose marketing team has increased sales up to 14% with the help of real time data analytics and digital media. Thanks to the use of SAP ERP, the brand has experienced inpeovement in their business processes. It uses improved business intelligence solutions to make smarter business decisions.
Putting the customer first in the service industry
In order to boost customer satisfaction, customer service is dependent on real time analytics around the customers. Delivering impeccable customer service is made possible with real time data analytics in the following ways:
Helping brands identify what market trends are and how they are going to impact their business. Building a stronger buyer profile is also possible with customer behaviour and understanding their intentions. Customers are now looking for new experience that go beyond the product itself. People like what they can relate to, which is why companies are using insights to offer a customized experience.
Other than that, colouring your product against upcoming trends, focusing on customer demographics and identifying areas for improvement are some of the ways data analytics are used to research the market. Setting differen goals for your brand becomes easier thanks to access to big data and analytics. As an intellectual asset, Big data is only going to influence the ways different sectors do business.
Optimizing the streaming services
For streaming services, real time data analytics has proved helpful. Customer experience on their applications in new guided by personalised suggestions and content recommendations. These recommendations are personalised thanks to machine learning and A/B learning.
It also helps in predicting the popularity of the upcoming streaming content via posters and trailers, and caters to their caution before releasing the actual show.
Hulu and Netflix are using better database management tools as well, for accurate and timely inventory of their digital content. These streaming platforms look towards data analytics to then categorize and market specific content to their segregated customer base depending on the seg demographics.
Use cases in the hospitality industry
There age several key benefits of using real time hospitality analytics. Restaurants and hotels can easily manage their CRM and bookings for an enhanced customer experience. Managing a smooth workflow and staffing for every shift is also possible.
Along with streamlined process of everyday workflow, managing inventory and logistics for daily delivery is also managed. Another important factor is effective marketing. Your catering, hotel, AirBnB, or restaurant business can flourish if you use big data and its insights for tailored marketing. Ushering the consumer to complete a purchase ensured expansion of customer base. Hospitality industry uses real time data analytics and its approaches by first understand the current workflow, consulting with a firm to develop a solution to extract data, and then analyze to develop insights.
Revolutionizing the manufacturing process
The production capacity of manufacturing industry depends on data analytics. As an example of real time data analytics, manufacturer are using data to improve their inventory management troubleshooting, quality control, and maintenance. Here’s how it works:
As an example, let’s consider that a manufacturing company suffers from the issue of overstocking due to lack of proper management and manual data entry process. Thanks to real time data analytics, now order management can be synced with inventory stock in the warehouses to fulfill orders in a timely manner.
Manufacturers, according to Forbes , are only achieving the 40% of their potential. This is because they are busy handling data and information manually. The previous examples of real time analytics show inventory, production workflow, employee management and logistics processes can be simplified and streamlined with big data.
Real time analytics enables better database management. So whatever information is entered into the system can be automatically categorised. Especially companies who want to scale their businesses are looking towards business intelligence and machine learning powered by better cyber security.
This data driven world is ever changing with new tools and approaches launched in the market. Data analysis report examples shared above for different industries show the important of big data is ever changing. Businesses are in the competition to adapt quickly to the changing market trends. This is why real time analytics has developed a strong hold over how business decisions are made.