Introducing DIVE – Machine Learning Service by Pivotree
Leverage Machine Learning to ignite your Master Data Management efficiencies.
Meet DIVE – a Machine Learning platform that integrates with your existing MDM application to automate the manual data management processes that slow you down. We built DIVE to help companies optimize their Master Data Management processes and put their efficiency into high gear.
DIVE’s algorithm is built on a basis of continuous data analysis that uses existing information to further automate manual data processes.
Most Common Use Cases of Automation
Automated Mapping of Unstructured Data
DIVE automatically structures data from your vendor saving them time and making you their favorite customer.
Automated Product Classification
DIVE automatically classifies your raw data and sends back classification suggestions with 80-90% accuracy.
Automated Data Normalization
DIVE uses historical data and current trends to automatically generate business rules and standardize data.
Automated Product Recommendation
DIVE analyzes your Master Data Management and eCommerce data to generate recommendations and product references.
How It Works
Through the customer portal, users can upload/delete catalogs, create models with cross-validation on selected attribute combinations, and update/re-train models to improve their results. DIVE will build specific models and provide metrics on the applicability of each model to the dataset. Plus, all portal functionality can be utilized via REST APIs for technical users.
How It Benefits Your Business
SaaS Based Application
Multi-Tenant Architecture
API Accessibility
Configurable Machine
Learning Algorithm
Custom Reports Capability
Multiple Data Domains Compatibility
How It Benefits Your Business
Endless Aisle Opportunity
With the ability to now handle hundreds of thousands of SKUs, your business can offer more products and better variety, as well as handle more vendors.
Improved Vendor Experience
Manual information mapping can be a daunting task. Automated mapping streamlines the process and makes vendors love working with you.
Faster Time to Market
Auto-classifying 80-90% of your product data helps get products to market faster.
Maximized Revenue Generation
Product recommendation directly impacts overall revenue with visitors more likely to return and buy based on a product suggestion.
Better Data Quality
Machine Learning automates many data management processes, which in return eliminates human error for improved data quality.
Improved Employee Satisfaction
By automating manual data processes, product managers can focus on high-value tasks that keep them engaged and motivated.
Did you know that on average it takes a company 30-45 seconds to classify one product SKU?
Potential time savings:
10,000 SKUs x 30 seconds = 83 hours
By automating a product classification process your company could be saving hundreds of hours on each product catalog update.
