To discuss about Predictive Analytics, we have Adam Bataran, Managing Director of GTM Global Salesforce Platforms at Bluewolf with us.
Follow the answers Mr. Bataran pitches to understand the entire concept better.
The question: What does predictive analytics mean and what value it imparts to the businesses today?
The answer: Predictive Analytics functions by implementing data, machine learning techniques and statistical algorithms to predict the future business outcomes and trends, based on past data and figures. It involves a number of distinct but advanced analytics disciplines and technologies – from deep data mining techniques and statistical analysis to predictive modeling and machine learning answers the most sought after question, “what will happen next?” or “how the customers will react to this?”.
Predictive analytics is all about creating valuable business insights and more than accurate foresights about a company from massive chunks of data, to help management decide the next-best approach and result in improving customer experiences.
More and more companies are leveraging the boons of predictive analytics – increasing volumes of data availability, coupled with cheaper and faster computing ability, and the development of such simple and user-friendly AI software have enticed a lot many companies to achieve long-etched business goals and enjoy a competitive advantage.
According to Bluewolf’s most recent State of Salesforce report, 75% of companies who have increased investment in analytics enjoy revenue gains as a perceptible business outcome. Ergo, organizations assuredly look up to predictive analysis as it anticipates future business outcomes right.
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The question: How can machine learning and AI fuse with predictive analytics?
The answer: Machine learning and AI are the next milestones of analytics. The cognitive computing systems goes on trying to learn about your business and later intelligently predicts customer’s behavioral patterns, industry trends and lot more.
Another crucial finding of the Bluewolf State of Salesforce report is the increase in investments, which makes analytics actionable and approachable to staff and customers serves as the best way to transform applications from just being smart to intelligent.
To understand cognitive applications better, check out the following 4 points:
- They comprehend unstructured data, such as language and imagery
- They infer, reason and extract concepts
- After each interaction, they hone their never-ending expertise
- Interaction with humans is done in a more natural way through them
AI and machine learning uncovers business patterns of relationships between different factors, relationships, causes, interactions and non-linear systems to analyze how the desirable outcomes are reached.
The question: What would you suggest to businesses deploying predictive analytics?
The answer: Here are five key thoughts to keep in mind while deploying predictive analytics:
- Constant sharpening of skills is essential to get the best valuable insights and forecasts, based on the data you have.
- To derive the best, you need to understand the actual business problem.
- Once you are done with identifying the business problem, discover the right software and expertise to develop predictive models.
- Let’s break a myth – no business does have access to perfect data.
- Irrespective of the raw data, predictive analytics is always high on competitive advantage.
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