Sales Director
Big Data is a term often heard in the digital technology world. It refers to large datasets that are analysed to understand patterns and trends around customer and user behaviour. Big Data is used across various industries to assist businesses in making decisions about improving customer experience. Believe it or not, these datasets can also be used to enhance your telephony operation.
In this article, we delve into how using Big Data analysis can significantly boost your VoIP operations, giving you insight into how to improve and amend your processes.
To learn more about VoIP technology, how it works, and how it can help your business, our article ‘What is VoIP?’ has everything you need.
Boasting a global market worth $274 billion, the real power of Big Data lies in its transformative potential for any system it measures. For VoIP users, this can offer significant benefits, pulling on the wealth of data it provides, including call patterns and customer behaviours.
By analysing this data, you can optimise system performance, call quality, security, and user experiences - all of which can lead to a more efficient and effective VoIP system for your business.
Big Data analysis isn't just about fixing current issues; it can also predict future needs and roadblocks for your business communication. Let’s break down the specific areas where Big Data can significantly impact your VoIP system.
Quality of Service (QoS) technology is crucial for businesses using VoIP, ensuring satisfactory performance across your VoIP system. Big Data analysis allows you to monitor and assess call quality metrics such as latency and call dropouts over certain periods; you can then use this data to improve your service.
You can also use the Mean Opinion Score (MOS), which uses either human feedback or automated tools to evaluate call quality and give you insights into potential issues.
Predictive Analytics (PA) takes this a step further by preempting QoS issues. This process uses detection algorithms to identify unusual patterns in call quality data. By doing this, it can then trigger automatic adjustments to your network settings, allowing network performance to stay at a high level.
Like any internet-based platform, VoIP systems are vulnerable to threats like fraud, viruses and other malicious attacks. Big Data analysis, which analyses data from VoIP systems, can help you identify and prevent these risks before they cause damage.
Using the data collected from real-time monitoring, you can detect unusual call traffic patterns and filter out suspicious behaviour, while also reviewing historical calls and customer data to identify recurring issues.
Data like this can be used alongside threat detection algorithms too. These include statistical and machine learning-based anomaly detection, both of which are programmed to classify and respond to potential VoIP security threats.
Our article, ‘What Does the Evolution of Online Security Mean for VoIP?’, provides more detail on VoIP security.
If you want to boost your VoIP system’s performance, Big Data analysis can help. By analysing network traffic, you can understand if additional system capacity is needed. If so, consulting with your VoIP provider on resource allocation and load balancing can prevent network congestion by identifying the peak usage times of your service.
You can also use historical data by sending it to your VoIP provider, who can then perform predictive maintenance. This process includes analysing past data to anticipate hardware failures, schedule maintenance, reduce downtime, and ensure continuous high standards of service. In some VoIP models, providers have started offering AI integrations to perform this function.
For businesses looking to stand out, you can use Big Data analysis to tailor your customer journey and experience to your audience's needs. By examining customer usage patterns, you can personalise services and identify key selling opportunities across your customer base.
Analysing call logs is another smart way to pinpoint issues. This can help you identify common problems or questions asked by customers. You can then highlight these in team meetings or training sessions to improve customer experience.
Taking on extensive data analysis may seem daunting, but with the right approach, it can be both manageable and compelling. Here’s a step-by-step guide to help you move forward with confidence.
Before diving into big data analysis, it’s important to have a clear understanding of your current VoIP setup. By assessing your existing hardware, software, and network infrastructure, you can identify the data sources you have available to work with.
This includes call logs, performance metrics, and customer interaction records. You’ll then be able to understand what essential data is available and what might be missing. Ask questions like ‘Which area of our current communications could benefit most from data analysis?’. These kinds of specific questions will help with the next step.
Next, think about what you’d like to achieve. Zoning in on your goals will help you stay on track and measure your success as you progress. Think about what you want to improve. It might be better call quality, more streamlined processes or a more accessible customer experience.
By setting clear objectives like ‘reduce call drop rates by 10%’ or ‘boost customer experience scores by 15%’, you’ll be clear on the end goal of your data analysis.
The tools you choose will play a critical role in your big data integration. Look for analytics platforms that are compatible with your VoIP system and can handle the volume and variety of data you plan to analyse.
Many VoIP providers offer built-in analytics tools. For example, T2K’s 3CX system allows you to log call analytics, helping monitor call traffic and customer behaviour. Alternatively, there are third-party platforms that can integrate with your VoIP system.
These include Salesforce’s Tableau, which allows you to analyse, collaborate, and share your big data insights. Elsewhere, tools like Apache Hadoop let users store and process big datasets on clusters of computers using simple programming models.
Once you’ve gathered your preferred tools, you’re ready to start collecting and organising your data. First, you’ll need to check that all relevant data points are captured consistently. You may want to include data like call logs, network performance metrics, customer engagement records or support tickets from your IT/help desk.
Look into where each of these sub-sections of data is collected to ensure they’re being recorded accurately; you may be able to automate some of these collection processes too, to save time.
Before you dive in and try to analyse everything at once, it’s best to take one step at a time. Starting small and specific gives you the confidence to gradually expand your analysis, incorporating more data and complex cases as you learn.
This approach lets you better manage the process and learn from each step, ensuring a successful integration. For example, you might begin by analysing call quality data for one of your teams, or over a specific time period.
Once you’ve collected and organised your data, it’s time to analyse it. By using the analytics tools (or similar platforms) we mentioned earlier, you’ll be able to identify patterns and trends in your data.
Using trend analysis can help you spot patterns over time, whereas predictive analysis can support you in forecasting future trends based on historical data. Remember to keep your specific goals in mind when analysing your data, too. This will allow you to identify areas to revisit in detail later.
After you’ve analysed your data, you can use the results to make decisions and necessary changes. This might include network optimisation, reviewing your workforce numbers, providing training or investing in new systems. For example, if your data shows call quality drops during certain times, you may want to increase your bandwidth or alter VoIP network settings for those periods.
It’s important to remember that big data analysis is an ongoing process. Monitoring your VoIP system and the impact of your changes can help you to identify and prevent future issues. Once you have an initial framework for your analysis, you can use it repeatedly to ensure your system operates at its best.
Some ideas for monitoring your system include reviewing VoIP performance metrics to track your changes, and using customer feedback to gauge how your audience feels about your service.
For newcomers to Big Data analysis, we hope you’ve enjoyed and gained insight into using your VoIP data to boost business performance. By following a structured approach—assessing your current system, identifying your goals, choosing the right tools, and analysing data— you’ll have the information you need to drive future business success.
Using this process, you can optimise essential areas of your telephony operation, such as call quality, network performance, security, and user experience. You’ll also be able to use what you’ve learnt to predict future issues and address security threats, ensuring high-quality communication for your business.
If you’d like to understand more about how Big Data analysis can benefit your VoIP system, contact T2K today.
Having worked for T2k for nearly 25 years, it's fair to say that Lee is an expert when it comes to all things telephony and business communications. Overseeing the commercial side of the business, he has helped the company evolve and grow through the decades. In recent years, and with the advent of VoIP and hosted telephony, Lee has made sure that T2k is at the forefront of technological developments. With a firm interest in helping businesses navigate the world of telecoms, Lee is responsible for the majority of the content on this website.
