Predictive Analytics is the skill of finding patterns in large data sets. The data can be from the past or present, and using tools of predictive analytics, future trends can be forecasted. Data is an asset and through predictive analytics, this data changes into an insight. By determining the propensity of the customers towards a particular product, idea, policy or service, an establishment can strive to make it better by formulating the needed alterations based on current demand and the likelihood of the level of its success in future. Major industries like Healthcare, E-commerce, Banking and Finance and Travel are embracing this technique to increase its profits and establish a better relationship with its customers.
Predictive Analytics in E-commerce is used by online retailers to read the mind of the customers. With the increase in competition, it has become necessary to know the contemporary techniques of attracting customers and provide them with the best experience. For example, Flipkart is working on a project to see how analytics can be used to sense the anxiety level of the user and address it accordingly. “If we can determine the anxiety level, we can automatically route them to our select set of people who have expertise in dealing with these situations,” said Amod Malviya, Flipkart’s chief technology officer.
a. Proliferation of Sales
Algorithmic technology and AI in e-commerce is proliferating the sales by helping to optimize the prices, anticipate the demand and understand the customer behavior. Predictive analysis supports real-time prices which get altered according to- History of purchase, price the competitor is offering, price in past, preferences, etc.
b. Customised Experience
Retail giants analyze a huge amount of data to give a customized experience to the customers. Amazon does target marketing by recommending the products which the customers are likely to buy. By using technologies like pixels it can infer what you will buy before you buy. It uses the potential of suggestion, for example, if you buy a certain product, it brings in forth the suggestions of the products bought by people who bought the same product as you are purchasing. This method helped them to increase their revenue up to 30% annually.
c. Understand the Competitiveness
Through predictive analytics in ecommerce, the retailers are able to comprehend the competitiveness of a product. Trends like – which product is selling and giving huge profit, which product needs to be discontinued, at what place its demand is most, at what time of the month or season it is usually bought, what kind of people are purchasing it, etc can be determined using this tool. Thus, sellers can anticipate demand in advance of need, reducing the chances of losing prospects to competitors due to a shortage of supply.
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Predictive analytics is changing healthcare industry for the better and is bridging the gap between patient and the doctor. It helps the doctor in deciphering what will exactly work for the patient. The global healthcare analytics market is expected to reach USD 24.55 Billion by 2021 from USD 7.39 Billion in 2016, at a CAGR of 27.1% during the forecast period. Predictive analytics can bring on the urgent reforms which the healthcare industry needs the most today.
a. Saves the Budget
According to the National Academy of Medicine, the United States healthcare system spends $750 billion on unnecessary services. Predictive analysis can reduce the wastage of money by analyzing the areas that need money to be spent on and the likelihood of the particular patient being subjected to a particular kind of disease. Predictive analytics in healthcare can save up to 15% of its budget.
b. Increases the Accuracy of Diagnosis
Physicians can use the predictive algorithms as an assistance towards making a more accurate diagnosis. It can help in giving targeted treatments as the doctors would know what works for a particular patient.
c. Prevention is Better than Cure
It is highly applicable in the field of Genomics. By analyzing the susceptibility of a patient towards a particular disease and by recommending a lifestyle change beforehand, the vulnerability towards a particular disease can be reduced. Instead of waiting to get sick, one can just avoid it by predicting the likelihood of it. For example, CancerIQ uses predictive analytics to predict, preempt and prevent adverse outcomes of cancer.
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3. Banking and Finance
Given the colossal amount of data banking and financial sector has, Predictive Analytics in Banking and Finance sector can offer a great array of opportunities for financial institutions to make better investments, policies, mitigate the risk involved and achieve greater returns.
a. Reduces Risk and Frauds
Cyber security is one of the major concerns. Through Predictive Analytics, the vulnerabilities in the network can be detected. Banking and Finance sector has resolved to Predictive Analytics to minimize the network breaches and protect their valuable information. For example, PayPal is using Predictive Analytics from a long time to protect their clients from fraudulent users. It analyses the historical payment data, and then through build machine learning algorithms, it assesses each transaction for potential cases of frauds.
b. Better Decisions
The Financial sector is able to make more informed decisions through Predictive Analytics. For eg, JPMorgan Chase uses Big Data Analytics to comprehend how the behavior of consumers affects the US economy. According to Diana Farrel, CEO of the JPMorgan Chase Institute, there is a wide range of questions that this technology can provide an insight into. She says, “With this kind of analysis, the institute will be able to answer the questions to help policymakers make more informed decisions.”
c. 360-Degree Customer View
Predictive Analytics can help in understanding the likelihood of the customer’s response towards a new marketing offer, service or policy. It helps in understanding the risk profile of the customer and provides an insight into the debt collection and recovery models for profitability. Thus, it gives a prediction regarding the behavior of the customer and his lifetime value.
How is Banking and Finance changing with modern technologies:
4. Travel and Hospitality
a. Using Social Media to understand the customer
Through the social media analysis, the interests of the people and where would they like to go and the amount of money they might spend can be estimated. It helps in predicting the kind of hotels or airlines a particular set of people would prefer. This increases the likelihood of a person opting for the recommended suggestion, consequently increasing the revenue. For eg, if the millennials in India usually get excited about trips to Andaman or Ladakh (which can be inferred from their social posts), the travel agencies can customize their packages accordingly and offer it in a period when they are most likely to have holidays.
b. Price Adjustment
Better data has resulted in better predictions, giving a flexible pricing. The concept of open pricing has also cropped up. The judgment to whether increase the price, lower it or hold it becomes clearer by forecasting the demand. This helps in balancing price with the customer’s budget and brings customer-centric marketing into practice.
c. Data Aggregation for a Speedy Decision-Making
It helps in catering to the future demand of the customers and in targeting a particular set of customers in a particular period, that is, the right buyers at the right time. The hotel staff can be informed beforehand to be prepared during the days when they might be expecting a huge amount of visitors.
How is travel industry leveraging modern technologies for improving its business efficiency:
This is how the major industries like Healthcare, BFSI, E-commerce, Travel and Hospitality are using Predictive Analytics to boost up their sales and services. We at NewGenApps provide a great expertise on Predictive Analytics. If you want to know how Predictive analytics can help your business, we are here to help you.