Cross Selling Recommendation
Cross-selling recommendation analytics is the process of using machine learning algorithms and data analytics to identify opportunities for cross-selling to customers.
This module will generate recommendations to salespersons and marketers daily for them to engage their customers for cross-selling. These recommendations can be integrated into your e-commerce platform. So the salespersons and marketers do not need to worry about what to recommend to his customers.
By leveraging this cross-sell module, businesses can identify opportunities for cross-selling to customers and create more personalized experiences.
Replacement Period Forecast
Replacement period forecast analytics is the process of using machine learning algorithms and data analytics to predict when a product or asset will need to be replaced. This involves analyzing historical data on the lifespan of the product or asset, as well as factors that may affect its lifespan, such as usage patterns, maintenance history, and environmental conditions.
By leveraging machine learning algorithms and data analytics, businesses can predict when a product or asset will need to be replaced, reducing downtime and maintenance costs. With this alert, your salesperson will be able to engage your customers to remind them on time to do the replace and will be able to increase the revenue and eliminate the lost sales due to poor follow up by salesperson.
Product Demand Gap Analysis
Product demand gap analysis is a process of identifying and analysing the gap between the actual demand for a product and the potential demand for that product for various segments of your customers. This analysis helps businesses to determine the reasons behind the gap and develop strategies to bridge that gap.
The system will setup your customers segment with product demand by analysing your historical sales data. The AI algorithm will discover the products demand pattern through the product's features, target audience, and unique selling points.
Once you have identified the gap, you need to analyse the reasons behind it. This includes understanding customer needs, product features, pricing, and marketing strategies.
Finally, businesses will based on the analysis of the reasons behind the gap, develop strategies to bridge the gap. This may include product improvements, pricing changes, marketing campaigns, and other initiatives.
By conducting a product demand gap analysis, businesses can gain valuable insights into the market and make informed decisions to improve their products and increase sales.
Clients Choose Us!
ISL brings more than 30 years of deep data mining experience to various market segments from Retail, F&B, Wholesales, Banking, Insurance, Telco, Manufacturing, Government and etc.
Artificial Intelligence Analytics is important to Every Industry as it allows you to Stand Out from competition, UNDERSTAND customers’ needs better, improve your service and TARGET customers with the right services or services at the right time.