Article | May 31, 2021
According to Google trends, predictive data analytics has gained a significant amount of popularity over the last few years. Many businesses have implemented predictive analytics applications to increase their business reach, gain new customers, forecast sales, and more.
Predictive Analytics is a type of data analytics technology that makes predictions with the help of data sets, statistical modeling, and machine learning. Predictive analytics uses historical data. This historical data is fed into a mathematical model that recognizes patterns and trends that are then applied to current data to forecast trends, practices, and behaviors from milliseconds to days and even years.
Based on the parameters supplied to them, organizations find patterns within that data to detect risks, opportunities, forecast conditions, and events that would occur at a particular time. At its heart, the use of predictive analytics answers a simple question, “What would happen based on my current data and what can be done to change the outcome.”
In the current times, businesses have multiple products offerings at their disposal to choose from vendors of big data predictive analytics in different industries. They can help these businesses leverage historical data discovering complex data correlation, recognizing patterns, and forecasting.
Organizations are turning to predictive analytics to increase their bottom line and gain advantages against their competition. Some of those reasons are listed below:
• With the growing amount and types of data, there is more interest in utilizing it to produce valuable insights
• Better computers
• An abundance of easy to use software
• Need of competitive differentiation due to tougher
As more and more easy-to-use software have been introduced, businesses no longer need statisticians and mathematicians for predictive analytics and forecasting.
Benefits of Predictive Analytics
Competitive edge over other businesses
The most common reason why multiple companies picked up predictive analytics was to gain an advantage over their competitors. Customer trends and buying patterns keep changing from time to time. The ones who can identify it first will go ahead in the game. Embracing predictive analytics is how you will stay ahead of your competition. Predictive analytics will aid in qualified lead generation and give you an insight into the present and potential customers.
Businesses opt for predictive analytics to predict customer behavior, preferences, and responses. Using this information, they attract their target audience and entice them into becoming loyal customers. Predictive analytics gives valuable information about your customers such as which of them are likely to lapse, how to retain them, whether you should market directly at them, etc. The more you know about them, the stronger your marketing will become. Your business will become the leader in predicting your customer’s exact needs.
Retaining existing customers is almost five times more difficult than acquiring new ones. The most successful company is the one that invests money in retaining those customers as much as acquiring new ones.
Predictive analytics helps in directing marketing strategies towards your existing customers and get them to return frequently. The analytics tool will make sure your marketing strategy caters to the diverse requirements of your customers.
Earlier marketing strategies revolved around the ‘one size fits all’ approach, but gone are those days. If you want to retain and acquire new customers, you have to create personalized marketing campaigns to attract customers.
Predictive analytics and data management help you to get new information about customer expectations, previous purchases, buying behaviors, and patterns. Using this data, you can create these personalized marketing strategies that will help keep up the engagement and acquire new customers.
Application of Predictive Analytics
Customer targeting divides the customer base into different demographic groups according to age, gender, interests, buying, and spending habits. It helps companies to create tailored marketing communications specifically to the customers who are likely to buy their products. Traditional techniques do not even come close to identifying potential customers as well as predictive analytics does.
The major constituents that create these customer groups are:
• Socio-demographic factors: age, gender, education, and marital status
• Engagement factors: recent interaction, frequency, spending habits, etc.
• Past campaign response: contact response, type, day, month, etc.
The customer-specific targeting for the company is highly advantageous. They can:
• Better communicate with the customers
• Save money on marketing
• Increase profits
Customer churn prevention
Customer churn prevention creates major hurdles in a company’s growth. Although it has been proven that retaining customers is cheaper than gaining new ones, it can become a problem. Detecting a client’s dissatisfaction is not an easy task as they can abruptly stop using your services without any warning.
Here, churn prevention comes into the picture. Churn prevention aims to predict who will end their relationship with the company, when, and why. The existing data sets can help develop predictive models so companies can be proactive to prevent the fallout.
Factors that can influence the churn are as follows:
• Customer variables
• Service use
• Competitor variables
Using these variables, companies can then take necessary steps to avoid the churn by offering customers personalized services or products.
Risk assessment and management processes in many companies are antiquated. Even though customer information is abundantly available for evaluation, it is still antiquated.
With advanced analytics, this data can be quickly and accurately analyzed while maintaining customer privacy and boundaries. Risk assessment thus allows companies to analyze problems with any business. Predictive analytics can approximate with certainty which operations are profitable and which are not.
Risk assessment analyzes the following data types:
• Socio-demographic factors
• Product details
• Customer behavior
• Risk metrics
Evaluating the previous history, seasonality, and market-affecting events make revenue predicting vital for a company’s planning and result in a company’s demand for a product or a service. This can be applied to short-term, medium-term, and long-term forecasting.
Predictive models help in anticipating a customer’s reaction to the factors that affect sales.
Following factors can be used in sales forecasting:
• Calendar data
• Weather data
• Company data
• Social data
• Demand data
Sales forecasting allows revenue prediction and optimal resource allocation.
Healthcare organizations have begun to use predictive analytics as this technology is helping them save money. They are using predictive analytics in several different ways. With the help of this technology, based on past trends they can now allocate facility resources, optimize staff schedules, identify patients at risk, adding intelligence to pharmaceutical and supply acquisition management.
Using predictive analytics in the health domain has also helped in preventing cases and risks of developing health complications like diabetes, asthma, and other life-threatening problems. The application of predictive analytics in health care can lead to making better clinical decisions for patients.
Predictive analytics is being used across different industries and is good way to advance your company’s growth and forecast future events to act accordingly. It has gained support from many different organizations at a global scale and will continue to grow rapidly.
Frequently Asked Questions
What is predictive analytics?
Predictive analytics uses historical data to predict future events. The historical data is used to build mathematical model that captures essential trends. That predictive model is based on current data that predicts what will happen next or suggest steps to take for optimal outcomes.
How to do predictive analytics?
• Define business objectives
• Collect relevant data available from resources
• Improve on collected data by data cleaning methods
• Choose a model or build your own to test data
• Evaluate and validate the predictive model to ensure
How does predictive analytics work for business?
Predictive analytics helps businesses attract, retain, and grow their profitable customers. It also helps them in improving their operations.
What tools are used for predictive analytics?
Some tools used for predictive analytics are:
• SAS Advanced Analytics
• Oracle DataScience
• IBM SPSS Statistics
• SAP Predictive Analytics
• Q Research
"name": "What is predictive analytics?",
"text": "Predictive analytics uses historical data to predict future events. The historical data is used to build a mathematical model that captures essential trends. That predictive model is based on current data that predicts what will happen next or suggest steps to take for optimal outcomes."
"name": "How to do predictive analytics?",
"text": "Define business objectives
Collect relevant data available from resources
Improve on collected data by data cleaning methods
Choose a model or build your own to test data
Evaluate and validate the predictive model to ensure "
"name": "How does predictive analytics work for business?",
"text": "Predictive analytics helps businesses attract, retain, and grow their profitable customers. It also helps them in improving their operations."
"name": "What tools are used for predictive analytics?",
"text": "Some tools used for predictive analytics are:
SAS Advanced Analytics
IBM SPSS Statistics
SAP Predictive Analytics
Article | March 23, 2021
Learn, re Learn and Unlearn
The times we are living in, we have to upgrade ourselves constantly in order to stay afloat with the industry be it Logistics, Traditional business, Agriculture, etc.. Technology is constantly changing our lives the way we used to live, living and will live. Anyone who thinks technology is not their cup of tea then I would say he /she will have no place in the world to live. It’s a blessing or curse on human race, only time will tell but effects are already surfacing in the market in the form of Job cut, poverty, some roles are no longer needed or replaced with.
Poor is getting poorer and rich is getting richer. Covid19 has not only brought the curse on human race but it has been a blessing in disguise for Tech giants and E-commerce. Technology not only changing the business but every human’s outlook towards life, family structure, the globalization of talents etc. It is nerve wrenching to imagine just what the world will look like in coming 20 years from now. Can all of us adapt to learn, re learn and unlearn quote? Or we have to depend upon countries/Governments to announce Minimum Wage to sustain our basic needs? Uncertainties are looming as the world is coming closer due to technology but emotionally going far. It’s sad to see children, colleagues communicating via emails and messages in the same home and office. Human is losing its touch and feel.
Repercussion to resists of learning, unlearning and relearning can bring down choices to none in the long run. Delay in adapting to change can be increasingly expensive as one can lose their place in a world earlier than one think. From 1992, where fewer people used to have facility of internet around , People used to stay in jobs for life but same people are now not wanted in the jobs when they go for interview as they lack in experience just because they have been doing what they were doing in one job without exposing themselves to the world’s new requirement of learn , re learn and unlearn. Chances of this group, getting a job will be negative. World has thrown different types of challenges to people, community, jobs, businesses , those people used to be applauded for remaining On one job for life ,same group of people are looked differently by corporate firms as redundant due to technology. So should people keep changing jobs after few years to just get on to learn, re learn and unlearn or continue waiting for their existing companies to face challenges and go off from the market? Only time and technology will determine what is store for human race next.
According to some of the studies, its shown the longer the delay in adopting technology for any given nation, the lower the per capita income of that nation. It shows extreme reliance on Technology but can all of us adopt to the technology at the same rate as its been introduced to us? Can our children or upcoming next generations adopt technology at same scale? Or future is Either Technology or nothing, in Short Job or Jobless there is no in between option?
Stephen Goldsmith, director of the Innovations in Government Program and Data-Smart City Solutions at the John F. Kennedy School of Government at Harvard University, said that in some areas, technological advancements have exceeded expectations made in 2000.
The Internet also has exploded beyond expectations. From 2000 to 2010, the number of Internet users increased 500 percent, from 361 million worldwide to almost 2 billion. Now, close to 4 billion people throughout the world use the Internet. People go online for everything from buying groceries and clothes to finding a date. They can register their cars online, earn a college degree, shop for houses and apply for a mortgage but again same question is arising , Can each one of us at the same scale use or advance their skill to use technology or we are leaving our senior generations behind and making them cripple in today’s society? Or How about Mid age people who are in their 50s and soon going to take over senior society , Can they get the job and advance their skill to meet technology demands or learn, unlearn and re learn or Not only pandemic but even Technology is going to make human redundant before their actual retirement and their knowledge, skill obsolete. There should be a way forward to achieve balance, absolute reliance on Technology is not only cyber threat to governments but in long term, Unemployment, Creating Jobs or paying minimum wage to unemployed mass will be a huge worry. At the end of the day, humans need basic and then luxury. Technology can bring ease of doing business, connecting businesses and out flows, connecting Wholesalers to end users but in between many jobs, heads will be slashed down and impact will be dire. Therefore Humans have to get themselves prepared to learn, unlearn and re learn to meet today’s technology requirement or prepare themselves for early retirement.
Article | March 21, 2020
Splunk extracts insights from big data. It is growing rapidly, it has a large total addressable market, and it has tremendous momentum from its exposure to industry megatrends (i.e. the cloud, big data, the "internet of things," and security). Further, its strategy of continuous innovation is being validated as the company wins very large deals. Investors should not be distracted by a temporary slowdown in revenue growth, as the company has wisely transitioned to a subscription model. This article reviews the business, its strategy, valuation the sell-off is overdone and risks. We conclude with our thoughts on investing.
Article | April 2, 2020
Data analytics has many purposes in the banking industry, ranging from improving cybersecurity to reducing customer churn. Every interaction from ATM withdrawals to loan applications — provides FIs with valuable data about customers’ financial lifestyles. Banks can even harness external regulatory, trading and social media engagement data, all of which can be processed and analyzed to benefit their operations.Financial data is useful in helping banks develop wide-reaching marketing campaigns, but social data is critical to developing offers for specific customers. Santa Rosa, California-based Redwood Credit Union, for example, found that social data was particularly important when offering auto loans. It initially extended preapproval for such loans every two years based solely on members’ credit scores and vehicle purchase histories, but it soon discovered that there was a much more reliable indicator and updated its preapproval frequency accordingly.