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|Real-Time Analytics – What Is It?|
|What Does In Real-Time Mean?|
|What Is Real-Time Big Data Analytics?|
|What Are The Benefits Of Using Real-Time Analytics?|
|Real-Time In Google Analytics|
|How Does Google Analytics Count Active Users On-Site?|
|Other Tools That Provide Real-Time Data|
A business can survive today only if they have swift decision-making capabilities, and at the same time, they need to have a 360-degree view of the situation to make the correct decision. This can only be done if they have all the information they need. Information – apt, and accurate - is what makes or breaks a business.
Real time analytics refers to the entire gamut of technological processes that helps a business process through live data and make sense out of it. Decisions need to be taken quickly, for which technological support is provided by the analytics system.
However, another important aspect is that there is no single uniform strategy that suits all the scenarios. Every scenario faced by an organization is dynamic and unique, hence the decision-making team requires data that represents the ground scenario as accurate and as recent, as possible. Combining these two aspects – live data and analytical capability, is what forms the basic concept of real-time analytics.
Real-time analytics is a branch of the business intelligence and analytics field that deals with real-time data and provides meaningful and conclusive insights that empower an organization to make instantly effective and informed decisions. In some cases, real-time analytics could be made available when requested, in which case there could be a lag in the actual events transpiring and the information received by the user.
However, the better use of real-time analytics is when it is used in continuous form, i.e., when the data is tracked live so that every update is available to be reviewed instantaneously.
Organizations use real time analytics not only for tracking external data related to customers and competitors, but also internal data that could improve their functional excellence, manufacturing processes, and engineering project execution, among many others. Many organizations also employ the use of artificial intelligence to make decisions based on pre-set parameters which are fed by the real-time analytics output.
With real-time analytics, businesses are presented with data representation, generally, in the mode of centralized dashboards that contain multiple information – historical data vis-à-vis live data, continuous inflow of updates, predictive analytical reports.
To understand the concept of real-time, let us take an example from our daily life. We all use navigation systems while we drive. We get live updates on the traffic ahead, while on the go, and based on this, we choose which route to take or which to avoid. This is what we can term in real-time.
In business scenarios, real-time is of paramount significance for success. All organizations depend on real-time information for making decisions.
In the manufacturing sector, real-time data is heavily relied upon for manufacturing products that meet the customer requirements and comply with the relevant standards. Let us take the example of a wire manufacturing factory.
A wire is manufactured based on the technical specification provided by the customer and it also must comply with multiple standards incorporated by the regulatory bodies in the country.
When the wire is manufactured, all the desired parameters are pre-set into the production line and then the entire wire manufacturing process is monitored, and the data displayed on a centralized dashboard.
The Quality Assurance team continuously monitors this data and if they find at any point, the manufactured wire is non-compliant with the standards, that wire length gets rejected.
In terms of procurement functions currently, many organizations choose to conduct auctions over traditional face to face negotiations, to finalize a big value order. Suppose you are a participant in one of these auctions, you will get to view the real-time bids of other participants. You then have a real-time view of the target prices that you need to quote to bag the order.
Real-time, in the business context, this refers to the immediate quantitative representation of events unfolding that could have any impact on the business decisions.
Multi-billion-dollar conglomerates have a huge amount of data at their disposal that they need to process. Their data sets are so gigantic in volume and dynamic in nature, that using conventional methods to analyze these data becomes an impractical approach.
Big data refers to these complex sets of data, for which specific high-tech computing needs to be employed to make any meaningful sense of the mammoth data at hand. Big data is characterized by the following features:
We have discussed real-time analytics in our previous sections, so what does it mean when it comes to real-time big data analytics and how is it different?
The real-time big data analytics refers to analytical systems that support deriving meaningful interpretation out of the terabytes of data available or big data. The real-time big data is useful only if the system can provide a meaningful output of it, in a defined time frame, for the consumption of its user.
It is important to note here that the timeframe within which the user needs a meaningful interpretation of the big data is defined as per the user requirements. Big data is being fed into the analytical processing systems in either of two ways – either the data is pushed into the system continuously or the system itself creates a data pull that continuously checks if any new data has arrived.
The way your business inputs the data also determines the time taken by the system to respond. The time taken by the system, from the moment new data is recognized to output is fed to the user, is known as the latency period. Technologies are rapidly evolving each day to ensure that this latency period is brought down as close as possible, if not exactly, to zero.
Not all the data that is getting collected is relevant for decision making. Data in its raw form serves no purpose. The purpose of real-time analytics is to enable the user with useful data that can give them a clear picture of the various factors that need to be considered for making a correct decision.
With the help of real-time analytics, an organization can reap multiple benefits that would help grow their business by making informed choices.
A sudden fall in website visitors or increasing order fulfillment duration is some of the indicators that the business processes are not functioning properly. Having real-time visibility of the irregularities will support in identification of the issues and elimination of the process gaps.
Organizations always roll out campaigns targeted at attracting customers. Various parameters are defined based on which the success of the campaigns is defined. Having real-time insight into the reactions of these targeted customer segments allows the decision-makers to tweak these parameters and experiment to obtain the desired results.
Many online businesses conduct trials regularly by making minor changes and observing the reactions of the users to these changes. Meaningful action can only be taken by these businesses only if they have the real-time data of the user feedback.
When real-time analytics is used in conjunction with predictive analytical systems, organizations get very useful inputs on the trends that are expected to be the next big thing. It also helps in determining if the strategy being employed currently suits the market trend or it is outdated. Comparing historical data with current data helps in the performance analysis of various functions.
Employing real-time business analytical tools across the organization cuts through many ineffectiveness in the system. It results in streamlining processes as well as the reduced need for IT support. All of this contributes to significant savings in terms of time and finances.
Real-time analytics provides the organization with the unique opportunity of gaining an advantage over its competitors. Incorporating the big data component adds to this and helps the organization to have a first-mover advantage over its rivals.
Google Analytics real-time reporting feature provides its subscribers with valuable insights into the performances of their various strategies and changes implemented on their website.
These reports have a wide cross-functional utility, starting from the marketing department and covering other departments like Customer Support, IT Support, and Sales. Real-time reports generated by Google Analytics vary when compared to the customized reports generated by it.
The focus of Google Analytics’ real-time report is primarily to represent the live data, based on some pre-set parameters by Google. The data presented is instantaneous, the report delivered within a couple of seconds of a visitor landing on the website. Following are the categories of real-time reports generated by Google Analytics:
The Overview section displays the ongoing activities on the website. It displays an overall summary and includes the number of users present, the most preferred source, and social traffic origins. It provides an evaluation of the pages viewed in half-hour duration and the most popular pages viewed.
This section displays the location of the active users on the website. The location data initially displayed is the nation from where the users belong, but detailed location data like city or region is also made available if you click on nation-wide figures.
This section displays from which medium the visitor was directed to your website, and the source from which the visitor arrived at your webpage. For example, if a user was browsing YouTube and from there got redirected to your webpage, then the medium will be social, and the source will be YouTube. The data is ranked based on the popularity of medium and source at that moment. Also, data about these parameters, for the previous half-hour is available in this section.
This section displays which pages of your website are currently most visited, along with the quantum of active visitors.
This section displays the report of the campaigns or events you have created on your website. You can also view your active events for the last thirty minutes.
This section displays goals getting achieved currently. These are target activities set by you that form significant contributing parameters determining your business’ success. The report also displays the achievement of the set goals, in the last thirty minutes.
There are two active user reports available in Google Analytics – one under the real-time report section and the other under the audience report section. Both count active users differently.
A unique active user is identified by Google Analytics using cookies. Every time a visitor visits your website, a unique identifier is tagged by the system. The next time this user visits, they are tagged as returning users.
It is important to note that even if someone visits the same page from different browsers or devices, they will be tagged as unique users each time. For active user data report generated from the real-time segment, Google Analytics counts each unique visitor landing on the website, as an active user.
It gives a representation of the quantum of current unique traffic on your website. For active user data report generated from the audience report segment, Google Analytics displays total unique visitors over a defined period. It gives a representation of the quantum of traffic on your website over 1 day, 7-day period, 14-day period and 28-day period.
There are other tools also available in the market that provide real-time data. We will cover these in the following sections.
Targeting primarily customers from the media industry and retail segment, IO Technologies provides real-time analytical software solutions. Their software is used by these businesses to acquire data that easy-to-understand and formatted in a lucid manner.
It employs a column storing technology and non-schema-based database, to build an agile solution for their customers that provides accurate responses to customer queries. Their proprietary technology helps in maintaining a robust user ID map through which the unique identity of a user is preserved despite multiple digital interactivities.
GoSquared is an analytical software program that aids in growing its customers’ business, by converting visitors into customers and thereafter obtain repeat business from these customers. It helps the performance reports of any marketing campaign you have initiated in online media.
It helps in the identification of opportunities to contact any unknown visitors on your webpage and then convert them into a verified lead. It supports engagement, conversion, and onboarding of these verified leads to prospective buyers.
It offers a range of solutions, which can be used separately or together by businesses to arrive at an informed and real-time decision suitable for meeting their business objectives.
Touted as a simpler alternative to Google Analytics, Gauges is an analytical software solution program that aims to simplify the real data analysis by providing simple and clear data interpretations and website statistics.
This is a suitable alternative to Google Analytics for those who do not require advance features and are content with a basic, albeit accurate, picture of the website visitor data, to form a suitable business strategy.
Clicky lays claim to be the earliest web analytical solution across the globe to provide live, real-time goal tracker services for your website. As compared to Google Analytics, which can at times take up to a day to start tracking the performance of a goal, Clicky starts providing performance parameters immediately upon setting up a goal.
As you can see, real-time analytics is important and tools like IO Technologies are leaving no stone unturned in making big data easily accessible.
by exchange, 2021