Implementing predictive analytics provides an edge to different businesses. With advancements in computing technologies and high market competition, businesses seek diverse ways to get ahead, and predictive analytics offers a trove of information to predict future outcomes. It enables data analysts and business experts to skim past real-time data and predict a customer’s future behavior. Data analysts can acquire better insight beyond comprehending a customer’s past behavior and instead use the gathered data to look forward to the future possibilities that bring success to a business.
Machine Learning, the subset of Artificial Intelligence (AI) and computing technology, can accelerate the work pace by automating all the manual operations in a business, identifying customer behavior, and improving customer satisfaction by recommending additional products. This predictive analytics guide will focus on two crucial aspects important for every business owner – promotion and price optimization – and why businesses should implement them.
Why Is Predictive Analytics Important For A Business?
With the increasing use of Artificial Intelligence and Machine Learning and the drive toward their adoption due to the benefits, the predictive analytics market size will reach USD 28.1 billion by 2026, states research.
Predictive analytics work by collecting, assembling, organizing, and using the ever-increasing volumes of data to draw a conclusion that leads to profitable results. The sales and marketing experts and the business team can use predictive analytics to evaluate the new pricing strategies and promotional activities to generate sales and revenue per the market trends. Some of the other benefits of predictive analytics for pricing and promotion optimization include the following:
- Provides actionable insights to devise ways that help to hedge against the competition
- Saves time and business resources by eliminating the need for manual research and testing
- Reduces the cost of ineffective marketing campaigns
- Helps businesses attract, engage, and retain customers
- Analyzes the historical data of a company to identify factors that lead to product failures
4 Ways to Implement Predictive Analytics in Business
Implementing predictive analytics for promotion and price optimization will allow businesses to predict the future better and create a satisfactory user experience for their customers. Thomas Goulding, a renowned professor for the Master of Professional Studies in Analytics program, says during his conversation with Northeastern College of Professional Studies, “Data analytics today is allowing us for the first time to take the massive amount of data we’ve been assembling for years and use it for predictive purposes rather than in just descriptive ways.”
Here are the two ways to implement predictive analytics in one’s business.
Price optimization involves analysis of customer purchase patterns and deciding the price that maximizes the company’s revenue. Predictive analytics considers a few aspects, such as competitor’s pricing, market condition, customer demand, and more, to serve customers with the best possible price. Inferenz follows a unified analytics-based approach to implement predictive analytics that leads to improved sales, higher margins, and lower costs.
Inferenz recently worked with a Germany-based pharmaceutical company to implement predictive analytics; you can check the detailed case study here and see how our predictive analytics and machine learning experts created a model that understood vital parameters for positive and negative patients.
By implementing predictive analytics for promotion optimization, business owners can use historical data to determine the impact of their past promotions and prepare the best future promos that save costs and maximize revenue. One can connect the promotions to inventory management to collect data and proactively ensure that the business meets promotional demand and reach its targeted price goal.
Supply Chain Management
Predictive analytics models can help businesses with supply and demand forecasting, optimize their logistics and transportation, optimize prices, and improve customer service. The historical data is carefully analyzed to predict which products are high in demand and the price customers are willing to pay.
If you want to learn how to implement the technology in SCM, read our comprehensive predictive analytics for supply chain management tutorial.
Predictive analytics in marketing efforts is used for customer and audience segmentation based on how they will react to the advertising campaign. Many leading brands like L’Oréal are integrating the technology to predict beauty trends ahead of time and develop products that match customer expectations. Data analytics is also used in lead prioritization, churn prediction, and ad personalization.
Looking for ways to learn how predictive analytics can improve your marketing strategies and improve ROI? Check out predictive analytics for a robust marketing strategy tutorial here.
Grow Sales With Inferenz’s Predictive Analytics Experts
No matter the industry, business owners can lean into data by implementing predictive analytics to gain in-depth insights into how customers interact with their business. Based on predictive models, business experts can make data-driven decisions to maximize profits and mitigate potential risks.
If you want to implement predictive analytics for promotion and price optimization, contact the experts at Inferenz. who can not only help you evaluate the predictive model but can also devise the implementation method that best fits your business needs.