AI FOR ECOMMERCE AND ONLINE BUSINESSES
Improve customer retention
Recommend more relevant products and increase your profits
Automate process and save man-days
HOW IT WORKS?
Analysis
The first phase of each project is focused on describing and understanding the problem.
- Ontology - what is the root cause of the problem and which type of data yields the best information
- Insights - what patterns and features can be extracted from available data
- Metric - how to calculate ROI and measure the progress; if you can't measure it, you can't improve it
Data preparation
In the second phase of each project we focus on the data infrastructure.
- Infrastructure assessment - what technologies are available and which format of the data is needed
- ETL pipelines - turn raw data into features that are usable in predictive modeling and machine learning algorithms
- Normalization and preprocessing - good features and simple model is much better combination than poor features and complex model
AI Prototyping
In the final phase of each project we focus on machine learning and experimenting. This is where the real fun begins!
- Modeling - exploring several mathematical models to find out which one is the best at addressing the business case
- Optimization of hyperparameters - the performance of each machine learning model is determined by its hyperparameters. We will tune them using our genetic algorithm framework
- Evaluation and deployment - at the end of the day you will get tailored AI module ready for use; you will be able to save time and money and bring additional value to your customers
