
True Fit
The Fashion Genome platform for hyper-personalized sizing and conversion optimization.

The Revenue Operations platform for identifying high-intent leads through predictive signal-based intelligence.

MadKudu is a premier predictive operations platform engineered for modern B2B Go-To-Market (GTM) teams, specifically those navigating the complexities of Product-Led Growth (PLG) and hybrid sales motions. By 2026, the platform has evolved from a traditional lead scoring engine into a comprehensive 'Revenue Copilot' architecture. It ingests massive datasets from CRM systems (Salesforce, HubSpot), product analytics (Amplitude, Mixpanel), and data warehouses (Snowflake, BigQuery) to generate real-time behavioral insights. Its technical core utilizes proprietary machine learning models that segment users based on 'Fit' (firmographics), 'Intent' (external signals), and 'Behavior' (product usage). This allows RevOps teams to identify Product Qualified Leads (PQLs) and expansion opportunities with high precision. The 2026 iteration features advanced LLM-powered enrichment and automated signal discovery, which removes the manual heavy lifting of defining scoring weights. MadKudu sits as the orchestration layer between a company's data lake and its execution tools, ensuring that sales teams focus only on accounts with the highest propensity to convert or expand, effectively reducing CAC and increasing NRR.
MadKudu is a premier predictive operations platform engineered for modern B2B Go-To-Market (GTM) teams, specifically those navigating the complexities of Product-Led Growth (PLG) and hybrid sales motions.
Explore all tools that specialize in predict customer churn. This domain focus ensures MadKudu delivers optimized results for this specific requirement.
Explore all tools that specialize in churn prediction. This domain focus ensures MadKudu delivers optimized results for this specific requirement.
Uses unsupervised learning to surface hidden correlations between product actions and conversion that humans might miss.
Directly queries Snowflake or BigQuery without requiring data to be piped through a third-party ETL.
A generative AI interface that allows RevOps managers to query their data using natural language to build segments.
Allows running multiple scoring models (e.g., one for Self-Serve, one for Enterprise) on the same lead simultaneously.
Writes scores and signals directly back into operational tools like Intercom, Outreach, and Marketo.
Analyzes your best customers to find similar high-fit accounts within your database or external intent feeds.
Provides sub-second enrichment and scoring for web forms to enable dynamic routing.
Connect your Primary CRM (Salesforce or HubSpot) via OAuth2.
Authenticate your Product Analytics source (Segment, Amplitude, or Mixpanel).
Establish a read-only connection to your Cloud Data Warehouse (Snowflake/BigQuery) if applicable.
Define your 'North Star' conversion event (e.g., Trial to Paid, MQL to SQL).
Run the MadKudu 'Historical Analysis' to identify correlations in your past data.
Configure the 'Fit' model using firmographic and technographic data points.
Configure the 'Behavioral' model to track specific in-app milestones.
Map the MadKudu output scores to custom fields within your CRM.
Set up 'Signal' alerts for Slack to notify Sales reps of high-intent activity.
Perform a final data validation check and toggle the sync to 'Live' mode.
All Set
Ready to go
Verified feedback from other users.
"Users praise the platform for its ability to unify product and sales data, though some note the setup complexity for non-technical users."
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