Prescriptive analytics is one of the best types of Data Analytics. This is also known as the future of data analytics, as there are four essential types of data analytics:
- Descriptive: This mainly deals with current data that what is happening.
- Diagnostic: This deals with the reason of data why a certain thing happens
- Predictive: This deals with forecasting data like what is going to happen.
- Prescriptive: This explains what to do now, and what strategies should be implemented.
These four types are widely used in different businesses to manage data and take decisions accordingly. In today’s era, businesses purely depend upon data, facts and figures are crucial to increase performance and bring development and growth.
What is Prescriptive analytics?
The primary objective of prescriptive analytics is to provide recommendations by analyzing the available data, past experiences, and current performance. Due to this great facility, it has been considered the most valuable data-driven decision-making tool.
In prescriptive data analytics, enormous data are resolved in an efficient and effective manner because of machine-learning algorithms and it also reduces the chance of mistakes in comparison to human work. It also uses the “if” and “else” statements and accordingly on the basis of processed data it just provides the required information which is like now what to do in this situation. It will provide you with a different course of action.
6 Examples of Prescriptive Analytics in Action
Venture Capital: Investment Decisions
The best example of venture capital is an experiment that was conducted by Harvard Business Review. In this experiment, they simply test the qualities of an algorithm’s decision. They run the data that which startup is best to invest and it was in comparison to angel investors’ decisions. The results were astonishing the algorithm performed much more effectively without being biased.
The experience also explained that when employees are also experienced has possessed a tool like prescriptive analytics which knows the best way of utilizing the algorithms the efficiency in business will be increased.
Sales: Lead Scoring
Prescriptive analytics also plays a vital role in terms of sales. They provide the lead scoring facility which is also known as lead ranking. Basically, this is a methodology that is adapted by the sales department of a firm or an organization. The purpose of lead scoring is to target the customers as per the selected characteristics.
Actions you can assign value to include:
- Page views
- Email interactions
- Site searches
- Content engagement, such as attending webinars, downloading e-books, or watching videos
These are certain attributes on that basis in your lead score you can add the highest point which is adding value to serious customers. For instance, an individual who deliberately visits and checks details or product pages should gain a high score because they intend to purchase. Similarly, a person who only visits to check the careers, one who only seeks job opportunities on your website can be added with negative scores. This will bring effectiveness in your lead ranking.
Content Curation: Algorithmic Recommendations
The best algorithm is that it is always suggested to you as previously we talked about that it behaves according to some past experiences. Likewise, if you have seen a review video of a book on YouTube so the algorithm will process it accordingly and suggest more related videos and content might be you find interesting.
Apart from it, TikTok’s “for you” page is the perfect example of prescriptive analytics. It is also similar to lead ranking. For instance, if you have seen the complete video so the algorithm will count it as a strong sign, and accordingly you will get the rest material.
Banking: Fraud Detection
The algorithm system is way too fast and it is also widely used in the banking sector for different purposes. Let’s take an example of how it works for the banking sector. If you are a customer of any particular bank so the algorithm will record your transactions and it will note your monthly report. If in certain cases your transaction increased by double so the immediate action will be performed by an algorithm.
Product Management: Development and Improvement
Prescriptive analytics also works in terms of product development and improvements. The simple way is to identify the trends, collect behavioral data, conduct market research, survey the customers and their current interactions with customers then analyze the data, you can perform it manually or algorithmically, and you will have the recommendation and accordingly, you can develop your product.
Marketing: Email Automation
Another example is email automation in this process the algorithm also works as smartly as it contains different categories and accordingly sends them the relevant content. Through this process, the companies became able to send personalized messages this strategy increases the chances of changing a lead into a potential customer.
