The power of data is resonant in the modern business world. Now valued at $37 billion, the analytics industry is thriving like little else in the world’s economy. As a subset of data services, predictive analytics is one element of data collection and application that brings its own set of benefits to all kinds of industries.
By first defining what predictive analytics is, we can explore the variety of uses and applications it has in the workplace. While the field of data science can be difficult to understand, we can break predictive analytics down by its immediate value in business to comprehend its uses.
Here we will explore the definition of predictive analytics, its many benefits, and its applications across industries.
What is Predictive Analytics?
Predictive analytics is a subset of data science that—as you may have guessed—is focused on the future. While business intelligence and other explorative data studies focus on the past and present, predictive analytics combines the two to model what the future may look like. This can take the form of predicting vehicle breakdowns maintenance, industry trends, or even workplace accidents.
No system can truly predict the future (not yet, at least), so predictive analytics aren’t a guarantee. However, they can bring immense value to all types of industries.
Take a look at how predictive analytics is already being used in fleet management, for example. By integrating sensors and smart devices into transport vehicles, companies are gathering the kind of data metrics they need to make an informed prediction about when maintenance needs to occur or a breakdown is imminent. This allows them to take trucks off the road, get them fixed, and save millions of dollars and potentially human lives.
Businesses that make use of predictive analytics will undoubtedly have the leg up on the competition. Companies that integrate smart data are already setting themselves apart from those that do not, setting off a trend that will see predictive analytics emerge into every aspect of our lives.
The Benefits Involved
The benefits of predictive analytics for business are evident in the example of how Target cornered the new baby market to boost revenues. In this instance, Target statistician Andrew Pole was able to analyze a variety of customer data metrics, such as shopping behaviors tied to impersonalized ID and credit card numbers, and pair those patterns to a likelihood of pregnancy. The company then sent out mailers with advertisements for baby products to customers that had engaged in the determined shopping behaviors. This resulted in uncanny success, allowing Target to even find out when a teen girl was pregnant before her father did.
Using techniques like this, Target’s revenues nearly doubled within a 10-year timespan. This demonstrates the value of data in business, where every data point can be converted into currency. Data is so valuable in fact, that one study determined that a Fortune 1000 company could increase its revenues by $2 billion by improving its data application strategies by a meager 10%.
Among value growth potential, predictive analytics offers benefits such as:
- Improved customer response
- Enhanced decision-making capabilities
- Optimized marketing campaigns
- Detection of cyber criminal and fraudulent behaviors
There is ultimately little that predictive analytics cannot help a business achieve. Paired with artificial intelligence analysis and modeling, predictive analytics is capable of examining a large data set to produce informed recommendations that it would take a human thousands of hours to generate.
There is no limiting the scope of predictive analytics. The combination of big data, AI, and machine learning have blown the doors open on what is now possible in business. From transportation to cybersecurity, predictive analytics offers techniques that better manage systems and protect user data for reduced costs and improved revenues.
Here’s what you should know.
Transportation and Logistics
The ability to predict and manage transportation routes, supply chains, vehicle weight, and efficiency is transforming the transportation and logistics industry. Typically, analysts have had to carefully calculate and manage the weight ratio of trucks along with the routes that goods need to take to get to their intended destination. Now, with predictive analytics, technicians can run high-powered programs to automatically generate ideal outcomes that take all of this into account.
In the world of COVID-19, such devices are being used to manage routing efficiency. This has been invaluable in redirecting supply chains where there have been delays and issues caused by the virus. In the same fashion, the predictive analytics that make autonomous vehicles possible have powered delivery vans in China and are progressing in automated vehicle tech in the United States as well.
Financial technology, or fintech, has received a substantial boost from the benefits offered by predictive analytics. These technologies are improving systems like crowdfunding, mobile payments, and even insurance technology.
In the insurance industry, little is better than predictive analytics for being able to anticipate risk and generate a corresponding quote. Predictive modeling connects the dots to determine liability and more quickly get an accurate picture of risk values than a human assessor might. This helps measure cost and risk accordingly to better save companies and individuals money.
The chatbot industry is predicted to reach a value of $1.25 billion while saving businesses an estimated $8 billion because of the value that predictive analytics and AI technologies bring to this aspect of automated customer service.
Chatbots enhance customer experience by generating data patterns through customer interactions to better provide service and improve targeted products and recommendations. As businesses look to provide accessible customer service at any given time, the availability of a chatbot to predictively troubleshoot problems or manage an account are adding substantial value to the industry.
Predictive Analytics may be the most valuable in terms of marketing, where data can be used to better model customer behaviors. Companies can then create a marketing campaign that is responsive to those behaviors, generating personalized and accurate predictions and recommendations.
Predictive Analytics has been linked to finding high-value customers with a success rate twice as high as competitors who do not use predictive modeling. This puts marketing professionals at a significant advantage, allowing them to seize valuable slices of an e-commerce economy ripe for the harvest.
Finally, predictive analytics gives any company that manages a digital platform added levels of cybersecurity never before seen. An AI system can accumulate vast amounts of data regarding fraudulent or cyber-criminal activity, then assemble them in a usable model which it can compare to new access point data. If something seems off, the system can then intelligently shut down the unauthorized attempt, making for safer security systems.
In a world in which remote work is now so common due to the pandemic, the need for predictive analytics in cybersecurity is greater than ever before. With users now logging into private networks from home, cybercriminals are looking to capitalize on the abundance of unprotected IP activity. Predictive software can be a formidable barrier against cybercrime and valuable data loss.
As a subset of big data analytics, predictive analytics offers insights into the future that bring value to every decision making process. The benefits of using this tech offer reduce costs and higher revenues while creating abundant business solutions that span industries. As the world attempts to recover from the coronavirus pandemic, the use of predictive analytics can help manage faltering supply chains as well as more highly trafficked e-commerce sites to provide ideal consumer experiences alongside safe business practices.