Ronald van Loon

How You Can Improve Customer Experience With Fast Data Analytics

Fast Data Analytics

In today’s constantly connected world, customers expect more than ever before from the companies they do business with. With the emergence of big data, businesses have been able to better meet and exceed customer expectations thanks to analytics and data science. However, the role of data in your business’ success doesn’t end with big data – now you can take your data mining and analytics to the next level to improve customer service and your business’ overall customer experience faster than you ever thought possible.

Fast data is basically the next step for analysis and application of large datasets (big data). With fast data, big data analytics can be applied to smaller data sets in real time to solve a number of problems for businesses across multiple industries. The goal of fast data analytics services is to mine raw data in real time and provide actionable information that businesses can use to improve their customer experience.

Fast data analytics allows you to turn raw data into actionable insights instantly

Analyze Streaming Data with Ease

The Internet of Things (IoT) is growing at an incredible rate. People are using their phones and tablets to connect to their home thermostats, security systems, fitness trackers, and numerous other things to make their lives easier and more streamlined. Thanks to all of these connected devices, there is more raw data available to organizations about their customers, products, and their overall performance than ever before; and that data is constantly streaming.

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With big data, you could expect to take advantage of at least some of that machine data, but there was still an expected lag in analysis and visualization to give you useable information from the raw data. Basically, fast data analytics allows you to turn raw data into actionable insights instantly.

With fast data analytics services, businesses in the finance, energy, retail, government, technology, and managed services sectors may create a more streamlined process for marketing strategies, customer service implementation, and much more. If your business has an application or sells a product that connects to mobile devices through an application, you can see almost immediate improvements in how your customers see you and interact with your business, all thanks to fast data analytics.

Consider a few real-world examples of how fast data analytics have helped companies across business sectors improve their performance.

A Financial Firm Monitors Flow of Business Transactions in Real-Time

The world of finance has always been fast-paced, and today a financial firm can have many millions of transactions each day. There’s no way to spare the time or effort to constantly search for breaks and/or delays in these transactions at every hour of the business day. However, with fast data analytics, they found that they could consistently monitor the flow of business throughout the day, including monitoring of specific flow segments, as well as complete transactions.

With the right fast data analytics service, the firm was able to come to a proactive solution in which they could monitor the production environment using their monitoring software’s automated algorithms to keep a constant eye on transaction times. The software’s algorithms determined whether transaction flows were within acceptable parameters or if something abnormal had occurred, giving the firm the ability to respond immediately to any problems or abnormalities to improve their customer experience and satisfaction.

A Large Insurance Firm Ensures Faster Claim Processing

In another case, a large health insurance provider with over three million clients was in the process of a massive expansion. As the firm expanded, though, they noticed a disturbing trend. Over the span of a single month, the average processing time for claim payments had increased by a dramatic 10%, but only for a single type of transaction. While they had the tools necessary to analyze the operating system problems, the servers’ hardware, application servers, and other areas where the problem could be originating, they were dealing with monitoring tools that were half-a-decade old.

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(Image Source: Shutterstock)

Thanks to these outdated monitoring tools, the insurance provider had a very expensive problem on their hands, as finding the solution was taking up over 90% of their tier-three personnel’s time and energy. Not only that, but customers were actually finding the majority of their application problems before the provider’s IT support could detect them.

To immediately diagnose the problem and get ahead of it, the insurance firm deployed a fast data monitoring service that immediately diagnosed what was causing the delays in claims processing transactions. The solution was found promptly – one claim type was sitting in a queue long enough that it would time out – and that the addition of new branch locations was causing over-saturation of their architecture design. By reconfiguring their middleware, they were able to accommodate the load increase and solve the problem without taking up valuable employee time and resources.

Just a few of the benefits of deploying this service were:

  • A 40% decrease in the mean-time-to-repair for the software problem.
  • A 60% decrease in the time spent by third-tier personnel to solve the problem.
  • A 35% decrease in the number of open tickets at help desk.
  • More than 30% improvement in the average processing time for claims.

A Securities Firm Ensures Dodd-Frank Compliance

Enacted in 2010, the Dodd-Frank Wall Street Reform and Consumer Protection Act is a US federal law that was enacted to regulate the financial industry and prevent serious financial crises from occurring in the future. Securities firms and other financial institutions must ensure that they are Dodd-Frank compliant in order to stay in business and avoid the risk of serious litigation. One such securities firm implemented fast data monitoring and analysis for Dodd-Frank compliance for all of their SWAP trades.

To be Dodd-Frank compliant, firms must report all SWAP trades “as soon as technologically possible”. Within a few minutes of the execution of a trade, a real-time message and a confirmation message must be reported, as well as primary economic terms (PET). If a message is rejected for any reason, it must be resubmitted and received within minutes of execution.

Without monitoring of their reporting systems, the securities firm found that they were in danger of being found non-compliant should anything go wrong within their internal processes. Fast data analytics solution gave them the real-time monitoring they needed to stay compliant.

How Can Fast Data Analytics Help Your Business?

As you can see from these examples, fast data analytics makes it possible for businesses to quickly turn raw machine data into actionable insights by tracking transactions, identifying issues with hardware and software, and reducing customer complaints. With the ability to identify and solve these issues faster and more efficiently, fast data analytics services can significantly improve any business’ customer experience.

These processes can all be monitored in real-time, giving you access useful analytics and insights for time-sensitive activities. Fast data analytics can help you stay compliant with government and/or industry regulations, avoid preventable losses and it improve your personnel’s efficiency by pinpointing errors and problems without taking up a lot of employees’ time and energy.

By Ronald van Loon

Ronald van Loon

Ronald has been recognized as one of the top 10 Global Big Data, IoT, Data Science, Predictive Analytics, Business Intelligence Influencer by Onalytica, Data Science Central, Klout, Dataconomy, is author for leading Big Data sites like The Economist, Datafloq and Data Science Central.

Ronald has recently joined the CloudTweaks syndication influencer program. You will now be able to read many of Ronald's syndicated articles here.

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