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25 benefits and best practices to get started with real-time analytics


The Team at CallMiner

December 13, 2022

Business performance improvement graph image
Business performance improvement graph image

Companies today manage ever-increasing volumes of data. With a variety of analytics tools available, companies of any size can now benefit from analyzing their data and uncovering insights to make more informed business decisions about everything from marketing messaging to new product development.

However, today’s technology landscape includes real-time analytics, which enables companies to gain immediate insights into customer service conversations, customer sentiment, and more. These real-time insights mean companies can take action and make improvements faster and more efficiently than ever.

Read this blog for expert tips and best practices for getting started with real-time analytics tools, such as:

  • Understanding your company’s analysis requirements
  • Knowing the target end users
  • Having a real-time analytics enthusiast on your team to champion the initiative
  • Using conversation intelligence software to map out a growth strategy
  • Aligning real-time analytics with your business processes
  • Applying real-time analytics to relevant use cases
  • …and more
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What is real-time analytics?

Real-time analytics refers to the processes and tools used to collect, manage and analyze data as it’s created. The primary difference between traditional analytics and real-time analytics is that traditional analytics typically relies on historical data, while real-time analytics provides the continuous intelligence agile companies need to maintain a competitive advantage.

To get the maximum value from real-time analytics, choosing the right real-time analytics tools for your business’s needs is crucial. For example, conversation intelligence tools like CallMiner analyze every customer interaction throughout the customer journey, empowering companies to deliver a seamless omnichannel customer experience.

Below, we take a look at some of the key benefits of real-time analytics tools and best practices for getting started with real-time analytics tools.

Benefits of real-time analytics tools

1. Drive service improvements with real-time analytics. “Real-time streaming audio recording can feed a conversation intelligence engine as the call unfolds and provide invaluable insight that can be used immediately to drive service improvements, save a defecting customer, or mitigate dispute or compliance risk, for instance. AI-powered analytics can automatically score your calls and identify the most impactful insight for immediate business improvement. Further, with real-time recording and speech analytics, you can trigger immediate attention and next-best action based on the most impactful customer indicators with automatic data-driven intelligence.” - Understanding post-call vs. real-time audio capture, CallMiner; Twitter: @CallMiner

2. Real-time analytics enables you to predict outcomes to reduce risk. “Businesses that utilize real-time analytics greatly reduce risk throughout their company since the system uses data to predict outcomes and suggest alternatives rather than relying on the collection of speculations based on past events or recent scans -- as is the case with historical data analytics. Real-time analytics provides insights into what is going on in the moment.” - Kate Brush, Real-time analytics, TechTarget; Twitter: @TTBusinessTech

3. They go deeper than standard web analytics. “Customer analytics tools go deeper into customer behavior than other general web analytics tools. These tools pull in customer data from various mediums like web, mobile, email, and your product. You can create segments based on behavioral patterns, then predict and offer the products and services those distinct groups of customers might buy.” - 9 types of web analytics tools — and how to know which ones you really need, What’s New in Publishing; Twitter: @wnip

4. Make faster, informed business decisions with real-time analytics tools. “Real-time data analytics allows faster, more informed decisions, an improvement from conventional decision-making, usually done with stale data or in the absence of it…With real-time insight into your market, your target audience and your competitor’s activities, you can form up-to-date strategies that reflect the changing trends of the market. For example, if a competitor lowers their prices, real-time analytics lets business analysts see the change immediately and make specific recommendations to management that realign priorities.” - Michael Dixon, Few tips to implement a real-time data analytics strategy, Selerity; Twitter: @SelerityAU

5. Getting a clear picture of the customer journey helps you win repeat business. “Capturing their interactions post-discovery, such as communication with a call center or visit to a retail outlet, helps brands see which of their assets are helping them along their path. What’s more, brands need to know what those who convert do post-purchase–this information helps companies win repeat business and encourage customer advocacy.” - Corey Patterson, How to choose the best marketing analytics tool for the web, MarTech; Twitter: @martechismktg

6. Continuous intelligence provides situational awareness. “Continuous intelligence (monitoring) systems run all day, listening to events as they occur, until they detect a threat or opportunity that requires a response by a person or system. The system proactively ‘pushes’ an alert or other notification to a person via email, screen pop or other mechanism; or it triggers an automated response.” - Christy Pettey (based on a talk by W. Roy Schulte, Distinguished VP Analyst at Gartner, at the Gartner Business Intelligence & Analytics Summit), 6 Best Practices for Real-Time Analytics, Gartner; Twitter: @Gartner_inc

7. Real-time analytics helps you connect with customers across touchpoints. “Today's consumers expect personalized shopping experiences that allow them to move seamlessly from one channel to another. This is especially true in our post-pandemic world, where hybrid services like curbside pickup and buy online, pick up in-store (BOPIS) have become the norm. For retailers, this makes real-time, cross-channel data imperative for effective customer service.

“To engage with consumers effectively at their preferred touchpoints, brands must be able to track their changing contexts 24/7. This requires cross-channel data that's immediately processed and served, rather than stored in a database for analysis later.” - Jay Kulkarni, 5 Benefits of Establishing a Real Time Data and Insights Strategy, ANA; Twitter: @ANAmarketers

8. Real-time analytics helps you react to sudden market fluctuations. “For businesses that are dependent on sudden market fluctuations, real-time data analytics is not just a boon but also a way of ensuring survival. With most companies gone online, these rapid changes are felt in many industries. So, enterprises need actionable data to help them make the right decisions at the right time.” - Hind Naser, 5 Major Advantages of Real-Time Data Analytics, VEXXHOST; Twitter: @vexxhost

9. You can create personalized customer experiences with real-time analytics. “Online retail is a prime example of how real-time data enables new and more effective customer experiences. In the old days of the brick-and-mortar store, attentive staff would recognize, greet and guide the regular and best customers. Today, you're more likely to be recognized by a bot that has access to real-time data from your online behavior. And while the bot may not greet you, it certainly will ensure that the homepage, special offers, recommendations and, in some cases, even the color scheme reflect what it has learned about you over numerous sessions.” - Donald Farmer, 6 top business benefits of real-time data analytics, TechTarget; Twitter: @TTBusinessTech

10. Your team can launch new and exciting data projects. “The obvious benefit of having more data sources and more time to process them is that you can launch new and ambitious analytics projects. A modern stack allows organizations to process data from their marketing channels instead of relying on third parties, allowing data teams to gain more insights and have more freedom.

“This is especially useful if the goal of analytics is to map out customer journeys. Access to all marketing data means successful and less productive channels can be easily identified. For example, your data team can compare whether the organic SEO spend is providing better results than paid acquisition.” - Nahla Davies, How a Modern Cloud Analytics Stack Can Optimize the Value of Your Data, Dataversity; Twitter: @Dataversity

11. Real-time analytics supports organizational transparency. “Open communication and transparency among team members ensures everyone is in alignment. When departments can access real-time reporting, this improves the effectiveness of their daily workflow, largely because real-time reporting makes it easy for everyone to share information. At the same time, this system reduces delays in workflow.

“Transparency can also reduce the risk of fraud. Reporting delays create windows of opportunity for dishonest team members to alter information. You can avoid these problems by implementing a real-time reporting system, including audit controls for security. And if errors happen or fraud occurs, real-time reporting can detect these issues faster.” - The benefits of real-time reporting, Jotform; Twitter: @Jotform

Best practices: Getting started with real-time analytics tools

12. Use conversation analytics to map out a growth strategy. “Using the exact keywords and phrases customers have chosen to describe their own experiences with your brand to map out a growth strategy or a marketing approach is relatively easy to do with the help of conversation intelligence. Your marketing team should be grounding their efforts to raise brand awareness in the actual experiences of your audience through the use of conversation intelligence.” - Benefits & best practices for adopting conversation intelligence, CallMiner; Twitter: @CallMiner

13. Understand your company’s analytics needs. “Before implementing real-time analytics into your business, you need to have a clear idea of your company’s needs. What is your goal with real-time reporting? Is it essential for the whole company or just an individual team? How will your team utilize the insights? These are some of the questions you need to ask yourself before getting started with real-time analytics.” - Guide to Real-Time Analytics, Memgraph; Twitter: @memgraphdb

14. Identify the end-users. “To capture the most value from Big Data, you need to implement a strategy that involves everyone in the company, from the C-suite to your customer-facing teams. Consider how analytics applies to different roles within your organization. Which users need simplified solutions to support decision-making? Do you need sales or marketing-specific tools? Do you have data science capabilities?” - How to Select the Right Data Analytics Tools & Platforms, 3Pillar Global; Twitter: @3PillarGlobal

15. Ensure your real-time analytics tools can handle your data volume. “To analyze data at the speed of business, companies need real-time analytics solutions that can ingest large volumes of data in motion as it is constantly generated by devices, sensors, applications and machines. In addition to processing data in real-time (also known as ‘streaming’), the solution must be able to capture and store data when it is not in motion for analytics on ‘batch’ data.” - Ronald van Loon, Modernize and Future-Proof Your Data Analytics Environment, CIOCoverage; Twitter: @CioCoverage

16. Choose real-time analytics tools that can be implemented easily without disrupting your business activities. “As with anything new, you need to consider the process of implementing it into your existing system. You want to avoid any disruption if possible, but you also need to consider that this change is a major paradigm shift for your business. That means you have to look at what adjustments, if any, are needed to your company culture to deal with this new, faster method of real time analysis.” - Real-Time Analytics, RingCentral; Twitter: @RingCentral

17. Look for real-time analytics tools that can work with multiple data sources. “Modern analytics tools can combine multiple sources of complex data, and analyze structured, semi-structured, and unstructured data. It’s important to select tools that don’t require assistance from your IT department. Having the ability to gather and combine data from different systems onto a single dashboard allows you to have a complete view of your business performance.” - 11 Factors To Consider While Choosing An Analytics Tool, IT Convergence; Twitter: @IT_Convergence

18. Choose real-time analytics tools capable of qualitative analysis such as sentiment analysis. “One highly useful qualitative technique is sentiment analysis, a technique which belongs to the broader category of text analysis—the (usually automated) process of sorting and understanding textual data. With sentiment analysis, the goal is to interpret and classify the emotions conveyed within textual data. From a business perspective, this allows you to ascertain how your customers feel about various aspects of your brand, product, or service.” - Emily Stevens, The 7 Most Useful Data Analysis Methods and Techniques, CareerFoundry; Twitter: @careerfoundry

19. Align your organizational culture with the new way of working and analysis. “Real-time data analytics is a whole new model of working. In a traditional analytics system where organizations usually get their insights once in a week, real-time data analytics gives you insights every second. So, it is an entirely different approach to working and analysis. Similarly, the organization's work culture should be in line with this faster analysis method so that it can affect the business appropriately.” - What is Real-time data analytics? Top 5 Challenges and solutions, Tech Blogger

20. Have an advocate on your team to encourage user adoption. “Make sure you have an ‘evangelist’ or ‘advocate’ internally, someone who is passionate about the solution and adoption within the company. If you don’t have a person or team who is passionate about the solution you will find your BI software is just as productive as a gym membership 4 weeks after the New Years resolution that prompted it.” - Thomas Spicer, How To Select Data Analytics and Business Intelligence Tools, Openbridge; Twitter: @openbridgeinc

21. Ask the right questions to get the most out of your data. “To get the most out of your data analysis, you need to ask the right questions. It’s nice to keep track of information such as sales, customer retention and gross revenue. However, these are vanity metrics. In other words, outside of goal setting, they do little more than boost your ego.

“In addition to tracking these metrics, you must ask insightful questions. For example, which vendors offer the most value, and which product lines need the most improvement? Then, review the granular details that reveal the consequences of your current operational practices.” - Ryan Ayers, The Small Business Owner’s Guide to Data Analytics,; Twitter: @businessdotcom

22. Integrate real-time analytics with business processes. “It is important to empower the ground-staff to become ‘smarter’ through close coupling of real-time analytics and business processes. The analytics piece will only point a worker towards a data anomaly or interesting fact. The worker needs to be able to couple it with the relevant business process to take the right decision. For e.g. if a customer service person finds an incoming call from a customer who has mostly had issues related to mobile bills (the real-time CRM systems will flag it off immediately) it would be most appropriate to route it directly to the relevant account manager.” - Tanya Oberoi, 5 Best Practices for Real-Time Analytics, Great Learning; Twitter: @Great_Learning

23. Apply real-time analytics to relevant use cases. “In some situations, delivering real-time analytics is not only a waste of money but also counterproductive.

“‘For example, putting your financial revenue report in a real-time analytics environment may not be appropriate, especially if orders are frequently canceled, moved, or manipulated,’ says Theresa Kushner, senior director of data intelligence and automation for IT and business services provider NTT Data Services. ‘How would the sales manager react when one minute she’s hit her target and the next, in real time, she’s dropped to 88%?’”

“By understanding which analytics can truly benefit from real-time support, IT can ensure real-time analytics initiatives generate significant value for the enterprise.” - John Edwards, including quotes from Theresa Kushner, director of data intelligence and automation for NTT Data Services, Real-time analytics: 7 tips for success, CIO; Twitter: @CIOonline

24. Adopt real-time analytics driven by AI for faster analysis. “Put simply; AI allows businesses to analyze data and draw out insights far more quickly than would ever be possible manually, using software algorithms that get better and better at their job as they are fed more data. This is the basic principle of machine learning (ML), which is the form of AI used in business today. AI and ML technologies include NLP, which enables computers to understand and communicate with us in human languages, computer vision which enables computers to understand and process visual information using cameras, just as we do with our eyes; and generative AI, which can create text, images, sounds and video from scratch.” - Bernard Marr, The Top 5 Data Science And Analytics Trends In 2023, Bernard Marr & Co.; Twitter: @BernardMarr

25. Encourage your team to take ownership of data quality. “Getting useful insights from real-time data also depends on the caliber of the data. A lack of data quality will spread across the whole analytics workflow in the same way that bad data collection may affect the performance of the entire pipeline. Nothing is worse than business conclusions drawn from false data.

By sharing responsibilities and democratizing data access, you can provide a high level of concern for the correctness, comprehensiveness, and integrity of data. Effective solutions will make sure that everyone in every function can recognize the value of accurate data and encourage them to take ownership of preserving data quality. Also, to guarantee that only trustworthy data sources are used, a similar quality policy must be applied to real-time data using automated procedures, as this reduces unnecessary analytics efforts.” - Nina Zumel, Top Challenges of Using Real-Time Data,; Twitter: @RTInsights

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