G2M Platform

No-Code Machine Learning Platform for Business Analysts

Freemium

Description

G2M Platform, previously known as Analyzr, offers a no-code interface designed for business analysts to construct machine learning models efficiently. The platform facilitates the aggregation of first- and third-party data sources, allowing users to select relevant variables and choose suitable algorithms to build predictive models tailored to specific business needs. It emphasizes transparency, enabling users to understand the models rather than getting bogged down in complex technology setups.

The platform focuses on delivering actionable insights by handling the underlying engineering complexities. Users can train models, review outcomes, and refine them iteratively. Outputs from the models, such as clustering, propensity scoring, regression analysis, and A/B testing results, can be integrated back into native systems. This allows businesses to make data-driven decisions, identify growth opportunities, predict customer behavior, generate reliable forecasts, and assess marketing effectiveness.

Key Features

No-Code Interface: Build machine learning models quickly without writing code.
Tailored Predictive Modeling: Create models specifically suited to unique business requirements.
Transparent Models: Understandable and accessible models for end-users.
Data Aggregation: Combine data from first- and third-party sources.
Algorithm Selection: Choose the best-fitting algorithm for the dataset.
Actionable Insights: Generate outputs that feed back into native systems for decision-making.
Scalable Infrastructure: Cloud-based scalability using managed Kubernetes.
Secure Data Handling: User data can be encoded and controlled locally.
API Access: REST API available for integration (Premium/Enterprise).
Production-Ready Models: Deploy models ready for operational use (Premium/Enterprise).

Use Cases

Clustering: Uncover potential growth pockets or identify at-risk groups by bundling prospects and customers.
Propensity Scoring: Target more accurately and improve conversion rates by predicting propensity to buy or churn.
Regression: Generate more reliable forecasts using broader data sets to inform proactive decisions.
A/B Testing: Assess marketing campaign effectiveness accurately by adjusting for relevant factors.