Real Time Analytics can be measured by effectively tracking metrics and setting up KPIs. There are a variety of metrics to measure for real-time web analysis, many of which you may be tracking on a daily, weekly, or monthly basis already.

Not all data sets are valuable in real time, and it’s important to focus on tracking the ones that matter most to your business, as recording this type of information can use significant storage. To make the most of your storage, learn what key performance indicators everyone should track, expanding on this list as you come across metrics that matter to you.

1. Active Users

It’s important to know how many active users you have and what they are doing on your website or mobile app. By knowing how many active users there are, you can use peak times to run featured ads and social media posts.

2. Sessions, Pageviews, and Bounce Rate

Where your users are on your site or in your app and how long they stay is one of the best ways to understand user behavior. Session length and bounce rate are crucial indicators for successes and areas for improvement. This insight into the features and content that your users value most will help you develop and improve your service.

The bounce rate is an important metric linked closely to sessions and pageviews, helping you know which aspects of your service are underperforming. In real time, this behavioral information can help you catch an error on a page and fix it to manage your retention rate.

3. User Location

Knowing where your users are located can help you understand patterns related to your most successful content. If you can identify locations that are actively sharing your content or using your service more prominently, you can use this to increase the circle of influence and the impact of your advertising campaigns.

If you run an eCommerce site and one of your ads is doing particularly well in a specific territory, you can try to target more ads to that region, or send call to action emails to capitalize on the attention.

4. Traffic Source

With immediate data, you can react to both positive and negative changes instantly. You should always know which marketing funnel your customers are coming from. If there is a sudden spike in traffic, it will let you know a certain marketing channel or campaign is successful, allowing you to highlight or enact a call-to-action.

Alternatively, a sudden drop will alert you of a problem with one of your marketing campaigns. Instead of wasting time finding the source of the problem, you’ll be able to immediately start working on a solution. This can help you turn the problem around and get your funnel working again!

5. Errors, Crashes, and Bugs

Tracking the errors your website or mobile app in real time can help you fix a problem immediately. Crashed sessions, failed links, unresponsive gestures, and other problems with the responsiveness of your website or mobile app can not only cost you sales while the problem persists, but they harm your reputation and brand.

Fixing errors that occur regularly in a timely fashion can help you gain a competitive edge, and build a great reputation along the way. Having instant data is the best way to make the most of these opportunities.

6. Advertising Costs

A clear understanding of how much you are spending on your advertising campaigns may not always be something you need to know off-hand, but there are times when it can be valuable. If you are monitoring expenditures on Facebook ads, you’ll know how much you are able to increase the spending if a post, page, or product goes viral.

By having this information immediately available, you can capitalize on opportunities for advertising that your competitors are missing. Emphasizing the right advertising campaign at the perfect time will increase the amount of exposure or ROI you receive per dollar spent.

7. Free-to-paid Conversion: B2C/Consumer Tech

Business-to-consumer (B2C) companies sell products or services directly to consumers. From brick-and-mortar stores to online ecommerce retailers, these companies often use free memberships or trials to entice subscriptions. Business cycles in this segment tend to move fast; every interaction prospects have with the company is important.

Potential subscribers who take advantage of free trials don’t always convert. To crack the code, you can use real-time analytics to find out where users are dropping off and why. It could be that many users do want to subscribe after their free trial is over, but the activation process is complicated. Using real-time analytics, you find that users drop off when they have to switch devices to activate their membership. The faster your team can host activation on one device, the better your free-to-paid conversion rate may be.

Other tactics like lowering costs, extending the deadline, and finding user engagement moments can all be tracked and experimented with real-time analytics.

8. Conversion Rate: Ecommerce

Ecommerce companies depend on visitors making purchases on their websites and then coming back for more. The conversion rate KPI measures the percentage of visitors who end up buying something.

Real-time analytics can help ecommerce companies pinpoint exactly where the friction is in the buying experience. For instance, if users are abandoning their carts when trying to add or remove an item, use real-time analytics to fix the problem and see if it worked. It could be a matter of a few clicks. Instead of having to click specific boxes on each item to remove them, perhaps you can add a “delete all” button for more convenience. Once you add the option, you can monitor the change in real-time to see if it was effective.

Changing the buying experience to have fewer clicks, altering the design or copy of the page, changing inventory, and sending notifications are all real-time data opportunities in ecommerce.

9. Subscriber Retention: Media and Entertainment

Media and entertainment companies can use real-time analytics to find new ways to drive retention. For this segment, converting prospects into subscribers isn’t necessarily as important as finding out why subscribers stick around. Retention—the rate at which subscribers remain customers—is a huge indicator for long-term success.

One way to increase retention is tracking revenue-driving subscribers with real-time analytics. These subscribers are long-haulers, often called power users. They use every little bell and whistle your product offers and spend the most time consuming content. Real-time analytics can be used to watch what this group of users is doing.

If you can come away with a specific pattern of behavior, you may be able to incentivize those same actions for the rest of your user base. For instance, you might find that users who create a “Watch List” are more likely to remain subscribed. Using real-time analytics, you can test ways to get users to create a Watch List: notifications, bigger buttons, added descriptions. Experiments like this can tell you if your strategies are working or not.

10. Cost per Lead: B2B/SaaS

The cost per lead KPI represents how much a business has to spend to generate a prospective subscriber. Getting this cost as low as possible while still maintaining a healthy stream of leads is important for SaaS companies details a hypothetical formula, “You spend $1,000 on a pay-per-click campaign and convert 10 visitors into leads. Your cost per lead is $100. If you convert 100 visitors, your cost per lead is $10.”

According to the above formula, creating more converted leads is the way to keep costs low. This is where real-time analytics comes in. By following the behaviors, preferences, and actions of converted leads in real-time, businesses can alter the lead generation experience at a faster pace.

Take a basic landing page prospects visit to fill out a form and go deeper into the funnel. You can use real-time analytics to change things like copy length, headlines, and design to drive more form fills. The best part? Once you find a winning landing page using real-time analytics, you can take that same formula and test it in another marketing campaign.

Keep tuned to my next post releases.

Reference

Datepine (Feb 2022). KPI examples and templates. https://www.datapine.com/kpi-examples-and-templates/google-analytics

 

 

 

Real Time Data Analytics to Increase Customer Retention

No company can exist without customers! Attracting customers and even more importantly, retaining those customers is necessary for a company. Real Time Data can certainly help with that! It allows a company to observe customer trends and then market their products specifically keeping their customers in mind. More data that a company has about its customer base, the more accurately they can observe customer trends and patterns which will ensure that the company can deliver exactly what its customers want. This is the best way to increase customer retention. After all, happy customers mean loyal customers!

An example of a company that uses Real Time Data to Increase Customer Retention is Amazon. Amazon collects all the data about its customers such as their names, addresses, search history, payments, etc. so that it can provide a truly personalized experience. This means that Amazon knows who you are as soon as you log in! It also provides you product recommendations based on your history so you are more likely to buy things. And if you buy lots of things on Amazon, you are less likely to leave Amazon!

 

 

Real Time Data Analytics to Create Efficient Marketing Campaigns

How can a company reach new customers? Marketing campaigns! However, if a great marketing campaign can get customers for a company, a poor marketing campaign can make a company lose even its existing customers. Real Time Data is necessary to analyze the customer base and understand what people want so that the marketing campaign is successful in converting more people. This can be done by monitoring the current online trends, understanding customer behavior in the market and then cashing on that to create a successful marketing campaign.

An example of a company that uses Real Time Data to create Marketing Campaigns is Netflix. Have you noticed that as soon as you open Netflix, they have movies and series marketed specifically for you? They do this by collecting data on your watching habits and search history and then providing targeted adverts. So, if you have been watching mystery movies recently, that’s what you will be recommended in the future as well!

 

 

Real Time Data Analytics for Supply Chain Handling 

The supply chain begins with the creation of raw materials and ends at the finished products in the hands of the customers. And for large companies, it is very difficult to handle this supply chain. After all, it can contain thousands of people and products that are moving from the point of manufacture to the point of consumption! So, companies can use Real Time Data to analyze their raw materials, products in their warehouse inventories and their retailer details to understand their production and shipment needs. This will make Supply Chain Handling much easier which will lead to fewer errors and consequently fewer losses for the company.

An example of a company that uses Real Time Data for Supply Chain Handling is PepsiCo. While the most popular thing sold by PepsiCo is Pepsi of course, did you know they sell many other things like Mountain Dew, Lays, 7Up, Doritos, etc. all over the world! And it is very difficult to manage the Supply Chain Handling of so many things without using Real Time Data. So, PepsiCo uses data to calculate the amount and type of products that retailers want without any wastage occurring.

 

Keep tuned to my next post release, I would cover the topic related to Real Time Data Analytics : Metrics we can track using Real Time Data. Come back and review this information on 2.14.2022.

 

Reference

John Kopanakis (Feb 2022). 5 Real-World Examples of How Brands are Using Big Data Analytics. https://betterprogramming.pub/7-real-time-data-streaming-tools-68907be5ac4b 

 

 

Everyone excepts their data the second its updated. Large corporations and Fortune 500 companies use real time data for predicting the consumer trends that drive the revenue growth. Real time analytics are becoming more popular and feasible for companies of all sizes, as the cloud provides various tools that can be quickly implemented.

AWS Kinesis

It’s a managed streaming service on Amazon Web Services (AWS). It provides flexibility to users to spend less time managing the infrastructure components and services instead focus more on development and implementation layers. Kinesis can ingest videos, IoT telemetry data, application logs, and other streaming data. Companies like Netflix used AWS Kinesis to process multiple terabytes of log data every day.

Kafka

The Apache Kafka framework is a distributed publish-subscribe messaging system that receives data streams from disparate source systems. It is widely used for tracking service calls and IoT sensor data. LinkedIn uses for tracking operational metrics and activity data.

Apache Storm

Storm is popular distributed real time computation system that works for big data with a simple processing model to carry out powerful abstractions. Data refreshes in few milliseconds on micro batch processing, which makes it a reliable data processor. Reliability is a factor that helps Storm stand out as a real time computation data processing system. It is based on the phenomenon of “fail fast, auto restart”. This allows it to restart the process without distributing the entire operation in case a node fails. This technology is user friendly and robust, which has made it popular among small and medium enterprises along with large sizes organizations.

Keep tuned to my next post release, I would cover the topic related to Real Time Data Analytics : Companies who use Real Time Data. Come back and review this information on 2.7.2022.

 

Reference

Seattle Data Guy (Feb 2021). 7 Real Time Data Streaming Tools. https://betterprogramming.pub/7-real-time-data-streaming-tools-68907be5ac4b 

Make decisions at the speed of your business

Better decisions do need to be faster decisions as the pace of business increases. Businesses working locally or globally need the best information continuously, more often delivered in a dashboard with immediate insights. The primary and most important benefit of real time data in the enterprise is simply being able to support decisions whenever and wherever possible.

Increase business agility and optimization

Business agility that has proven successfully in several industry sectors are the creation of small, well-informed, tightly focused teams called squads. By giving squads a mandate to act quickly so close to business operations, we enable faster and smarter responses to a changing business environment. However, this approach can only be effective if a squad has the needed data, which must continuously be kept up to date to match the team’s urgency. That’s a great use case for real-time data.

Quickly detect and address operational issues

Companies use real-time analytics to monitor the balance of incoming orders and product or parts availability so they can move quickly to increase supplies that are running short, and to detect the need for short-term contract labor if production, packaging or shipping is falling behind target.

Identity and act on short-term market changes

Industries such as stock trading is sensitive to rapid market fluctuations. Real time data is essential to business survival in these scenarios. Real time data is invaluable to all these scenarios. It’s possible to move more slowly if inventories and margins allow to take a deep breath and ride through some disruptions. However, few businesses have such luxury these days. Instead, we have had to become much smarter about using data to enable faster and more efficient monitoring of our markets.

Personalize the customer experience for online marketing

Online retails are a prime example of real time data usage and its effectiveness. Today, we are more likely to be recognized by a bot that has access to real time data from online behavior. And while the bot may not greet users, it certainly will ensure that the homepage, special offers, recommendations and, in some cases, even the color scheme reflect what it has learned about user behavior over numerous sessions. Numerous organizations use real time technology to personalize their websites and online advertising for individual customers, without people even realizing that it is working behind the scenes to serve up what they think of as the normal customer experience.

Improve customer service with up-to-date information

Customer service providers have heavily invested in real time data integration for their services and operations (Donald Farmer, 2021). For example, call center agents look up someone’s customer records, they should be able to see information on the local outage, faulty equipment, unusually high bill, canceled flight or other issue that prompted the call, right then as they’re talking with the customer. This kind of insight driven by real-time applications is standard practice now.

 

 

Keep tuned to my next post release, I would cover the topics related to Real Time Data Analytics : Tools used for Real Time Data Analytics. Come back and review this information on 1.31.2022.

 

Reference

Donald, Farmer (2021). 6 top business benefits of real time data analytics. TechTarget Network. https://searchbusinessanalytics.techtarget.com/feature/6-top-business-benefits-of-real-time-data-analytics

 

Real time data analytics enables users to analyze and draw data insights in real time. My name is Santoshkumar Pandi an experienced Data & Analytics professional with over 11+ years of experience. As a Data & Analytics leader my expertise in data engineering, business intelligence, data science and working with cross functional business functions and stakeholders would help me share great real insights on how to use Real Time Data Analytics and drive the key decisions through data insights.

Real time analytics is getting visibility to data as the transaction occurs and enters into the data storage. It lets users to see, analyze and understand data and make key decisions in real time. One of the closest use case of real time data analytics is with stock exchange data, users would like to see the market trends in real time to make key decisions of buying or selling stocks. Real-time analytics allows individuals and businesses to react without delay. They can seize opportunities or prevent problems before they happen.

By comparison, batch-style analytics might take hours or days to yield results. Usually, batch analytical applications or tools would yield only “after the fact” insights. Real-time analytics would help to get ahead of the curve.

 

How do Real Time Analytics Work?

Real time data analytics tools or solutions can push or pull data. The response time for real time analytics tools can vary from nearly instantaneous to a few seconds or minutes (Sisense, 2022). Trading platforms would need to respond to new information within seconds. Retail products can get by with a minute between updates.

The components of real-time data analytics include:

• Aggregator — Compiles real time streaming data analytics from many different data sources.
• Broker — Makes data in real time available for use.
• Analytics Engine — Correlates values and blends data streams together while analyzing the data.
• Stream Processor — Executes real time app analytics and logic by receiving and sending data streams.

 

Who Uses Real Time Analytics?

• Real time stock platforms, e-commerce retailers, financial banks to decide immediately on the moving trends of data and take key decisions.
• Targeting individual customers in retail outlets with promotions and incentives, while the customers are in the store and next to the merchandise.
• Customer relationship management (CRM), maximizing satisfaction and business results during each interaction with the customer.

 

Keep tuned to my next post release, I would cover the most important topics related to Real Time Data Analytics : Benefits of Real Time Data Analytics. Come back and review this information on 1.24.2022.

 

References

Sisense. (2022, Jan 22). Real-time-analytics. Sisense. https://www.sisense.com/glossary/real-time-analytics/