Santosh
Sahoo
Global Head — Data Foundations Consumption, MuleSoft + Informatica (Salesforce)
“Driving consumption growth and commercial impact at the intersection of AI, SaaS, and GTM.”
In Brief
Who I Am
I lead Data Foundations Consumption at MuleSoft + Informatica — a $900M+ portfolio where I'm responsible for driving commercial adoption and measurable value for enterprise customers across global enterprise accounts. My work sits at the intersection of AI strategy, GTM execution, and operating models.
Over 20+ years spanning TCS, Infosys, Tech Mahindra, Cognizant, and MuleSoft, I've developed a core belief: the gap between what technology can do and what organizations actually consume from it is the defining challenge of the AI era. I build frameworks to close that gap.
Outside of work, I'm a proud dad to Shan and Sachi.
Proprietary Frameworks
How I Think About Enterprise Value
Three frameworks developed across 20+ years of enterprise technology leadership. Each one built to solve a specific gap between capability and consumption.
AI Platform Relevance
CARGO
Composability · Actionability · Reusability · Governance · Orchestration
A five-dimension framework for evaluating enterprise AI platform relevance across hybrid, legacy, and AI-native contexts. CARGO answers the question every enterprise architect is quietly asking: can this platform actually operate at our scale — not just in a greenfield demo?
Customer Interaction Velocity
TTC
Time to Credibility
In the age of knowledge abundance, every customer interaction must lead with value — or it will be the last one. TTC measures how quickly you earn the right to a second conversation, and gives you the preparation framework to dramatically shrink that time.
Expansion Signal Model
ICB
Ideal Customer Behavior
ICP tells you who will land. ICB tells you who will expand. ICB identifies the specific behavioral patterns of customers who grow — and turns those patterns into leading indicators for commercial strategy. 'Who they are' predicts landing. 'How they behave' predicts expansion.
My Work
What I've Built at MuleSoft / Salesforce
Building a Consumption Growth Engine
Led the build-out of MuleSoft's Consumption Value function — a global team responsible for driving platform adoption and measurable growth across a $900M+ business. Combining org design, playbook creation, and a shift from traditional NRR to consumption growth rate as the north star metric.
Harnessing Product Telemetry for Revenue
Built a framework for turning product usage data into a commercial motion. The Consumption Cohort Matrix segments customers by utilization and contract term to prioritize where high-touch effort creates the most leverage:
Scaling High-Touch Without Scaling Headcount
Redesigned the engagement model to be intentional rather than relationship-dependent. Segmented the account base into four ARR tiers and replaced the always-on named CSM model with a data-triggered High-Value Engagement cycle — engagements triggered by adoption signals, account team requests, or ACV thresholds, not by customer loudness.
“80% of ARR is generated by 25-30% of customers. High-touch has to be intentional, not reflexive.”
Land-to-Expand: A Cross-Functional Motion
Post-sales growth at scale isn't owned by one function — it's a coordinated motion across the entire go-to-market team. Each role has a defined lane:
When every team has a defined role in the expansion motion, consumption compounds. When they don't, it doesn't.
The Frameworks Behind the Work
Product Data for CCOs
Four dimensions of turning product telemetry into a commercial motion — presented to Chief Customer Officers across the global portfolio.
Adoption
Customer Journey Funnel
Goal — Define a common language for Product, Sales and CS on onboarding and adoption
Retention
Consumption Cohort Matrix
Goal — Create an early detection system for attrition and expansion
| Consumption Cohorts | Remaining Contract Term % | ||||
|---|---|---|---|---|---|
| 0–25% | 26–50% | 51–75% | 76–100% | ||
| Utilization % | 0% | No Usage | No Usage | No Usage | No Usage |
| 1–25% | On Track | Off Track | Off Track | Off Track | |
| 26–50% | On Track | On Track | Off Track | Off Track | |
| 51–75% | On Track | On Track | On Track | Off Track | |
| > 75% | Upsell | Upsell | Upsell | Upsell | |
Track product usage vis-à-vis contract length
Expansion
Value Quantification
Goal — Use product data to automate Value Delivered for all customers
Example — Developer Productivity
Advocacy
Customer Marketing & Reference
Goal — Identify customers for stories, marketing and reference
Examples
- —Early adopters of new features / modules
- —NorthStar Customers — Usage Breadth and Depth
- —Customer Story / Reference Targets — NorthStar + High ROI
Productizing Customer Success
Treating Customer Success as a product — with a clear promise, a cohesive ecosystem, tiered plans, and a P&L — to create scalable, monetizable CS at enterprise scale.
Framework
A Product Approach to Customer Success
Goal — A clear Promise + Continuous Value + Ecosystem + $$
Framework
Tiered Success Plans
Goal — Elevated experience across ecosystem for each tier
Plays
CS Plays Journey
Goal — Defined plays for every stage of the customer lifecycle
Measurement
Value Measurement Spectrum
Goal — Capture and refresh value realization from Day 1 through advocacy
How I Think About GTM
Revenue Architecture for the Post-Sales Era
Three convictions that shape how I build
The best GTM signal is already in your product
Most companies treat product telemetry as an engineering metric. The highest-performing post-sales orgs use it as a commercial signal — detecting churn risk before renewal conversations begin, mapping white-space domains to find expansion before the customer asks, and generating value proof automatically so teams spend time on strategy, not spreadsheets.
Frameworks: Consumption Cohort Matrix · Value Quantification
CS doesn’t scale. Designed engagements do.
The named high-touch model breaks under margin pressure. The answer isn’t to go fully digital — it’s to be intentional. A segmented account base, data-triggered engagement logic, and a Next Best Engagement cycle means the right customers get deep attention at the right moment — not just the ones who email the most.
Framework: High-Value Engagement Cycle (Prepare → NBE)
Consumption growth requires a mirrored org, not just better CSMs
In a consumption business, expansion lives at the intersection of CS and Sales — not inside either function alone. When the CS org mirrors the Sales structure, shares incentives on consumption and expansion, and operates a Two-in-a-Box model at the account level, revenue compounds. Siloed orgs, even with great individual contributors, consistently underperform.
Framework: Sales-CS Mirror Model · Shared Consumption Incentives
Writing
Latest from the Blog
Essays on enterprise AI, integration strategy, customer success, and the occasional reflection on leadership.
AI Will Be Diffused Through Software — Not Vibe-Coded Apps
The next phase of enterprise AI isn't standalone AI apps. It's AI embedded into the software enterprises already run. Context is the delivery mechanism.
Doing vs. Learning: Why You Need to Build Something Real with AI
Watching demos, reading papers, and taking courses is not the same as building something real with AI. The learning gap in enterprise AI is a doing gap.
2026 Prediction: Context Is All You Need
Every AI capability gap I see in enterprise today comes down to one missing ingredient: trusted, real-time context. The organizations that solve context will win the AI decade.
Let's Talk
Working on an enterprise AI challenge?
Whether it's a speaking engagement, advisory conversation, or just comparing notes — I'd like to hear what you're working on.