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Stop Paying for Sales You Would Have Gotten Anyway.

We help retail, e-commerce, and multi-channel brands isolate true incremental revenue through holdout-backed segmentation, CDP activation, and predictive customer lifetime value (LTV) modeling.

Who We Work With

Built specifically for Retail CMOs, VPs of Marketing, Directors of CRM, and Analytics Leaders who need to clean up fragmented customer data across enterprise warehouses (Snowflake, BigQuery, Databricks) and activation platforms (Braze, Adobe Analytics, legacy ESPs).
  • Retail & E-Commerce Brands with 100k+ customer profiles struggling to measure real campaign lift.
  • Marketing Teams migrating off legacy marketing systems to modern CDPs without losing historical targeting logic.
  • Commercial Leaders who need to tie CRM, RFM segmentation, and retention campaigns directly to incremental gross margin.

Customer Data Pitfalls That Waste Commercial Budget

  1. Migrating ESPs/CDPs Before Fixing Segmentation Schemas
    Buying advanced marketing automation tools without pre-defined RFM logic and behavioral triggers just means sending generic email blasts faster.

     
  2. Measuring Campaign Revenue Instead of Incremental Lift
    Attributing 100% of purchase revenue to promotional campaigns without holdout control groups leads to discounting margins for customers who were already going to buy.

     
  3. Data Warehouses Disconnected from Activation
    Storing millions of row-level transaction records in cloud warehouses without automated feedback loops into campaign
    execution engines.
     
  4. Proprietary Vendor Lock-In & Technical Debt
    Building complex segmentation logic directly inside third-party SaaS black boxes rather than your central warehouse. When you switch execution tools, years of custom business rules are lost—forcing expensive rebuilds. We engineer segmentation natively inside your warehouse so your business logic remains portable and permanent.

     

Our Methodology

  1. Behavioral & RFM Segmentation (Decode Patterns, Not Averages)
    We replace static list blasts with dynamic behavioral clustering. By applying statistical modeling and RFM frameworks to raw transaction records, we uncover high-margin, high-LTV customer cohorts and churn-risk indicators.

    The Result: clear, automated segment definitions that feed directly into your marketing tools.

     
  2. Control-Group Incrementality & Lift Testing
    We replace static list blasts with dynamic behavioral clustering. By applying statistical modeling and RFM frameworks to raw transaction records, we uncover high-margin, high-LTV customer cohorts and churn-risk indicators.


    The Result: Eliminate wasted promotional spend and reallocate budget to high-yield customer segments.

     
  3. CDP Activation & Operational Integration
    Insights in a slide deck don't drive revenue. We bridge the gap between your cloud data infrastructure and campaign execution by engineering automated SQL pipelines and dynamic syncs into engagement engines like Braze, Iterable, and Klaviyo, or composable CDPs.

    The Result: Real-time data activation across marketing channels without manual CSV exports.

Real-World Impact
Case Study: Enterprise Retailer CDP Migration & Incrementality Audit

  • ​The Challenge: A multi-channel retailer was running promotional blasts to their entire file, attributing 100% of campaign revenue to promotional emails without controlling for organic buyer baselines.
     
  • The Intervention: Implemented holdout control group testing, cleaned historical RFM schemas in Snowflake, and engineered dynamic segmentation pipelines into their campaign execution engine (Braze).
     
  • The Measurable Result: Identified that ~76% of campaign-attributed revenue was unincremental (purchases that would have occurred anyway). Reallocated marketing spend away from unneeded discounts, reducing annual promotional spend by over $1.5M while maintaining customer acquisition velocity and protecting gross margins.

Our Core Principles

  • No Vanity Dashboards:
    We refuse projects focused on building "pretty charts" that don't drive explicit commercial or retention decisions.

     

  • No Blasts Without Controls:
    If you can't measure incrementality against a non-exposed control group, you can't prove marketing value.

     

  • Data Warehouse First:
    We build sustainable segmentation directly inside your data warehouse or CDP—never locked inside proprietary vendor black boxes.

I highly value Mark's guidance and trust his recommendations due to his customer-centric approach, domain expertise, and strategic thinking.

Vivek B. - DVP, Analytics Insights & Optimization

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