AI-powered margin intelligence that tells your reps exactly what to price on every deal — and shows them why. Built for Value-Added Resellers who are done guessing.
Your reps are pricing deals on gut instinct, hallway conversations, and tribal knowledge. Every deal is a guess — and the guesses are costing you millions.
MarginArc lives directly on the Salesforce Opportunity record — right where your reps already work. No new tabs. No context switching.
Every deal gets scored 0-100 on a red-to-green spectrum. Reps instantly see if their pricing is optimal, and exactly what features are helping or hurting their score.
See your win/loss record against every competitor at every account. Know exactly who you beat, who beats you, and what strategies work.
Contextual intelligence cards for every deal: OEM benchmarks, competitive pressure alerts, services attach opportunities, and network-sourced market trends.
Model different deal structures in seconds. See how registration type, competition level, and value-add change your margin and win probability side by side.
MarginArc delivers value on Day 1 from your existing Salesforce data. But the real magic? It compounds. Every closed deal, every competitive outcome, every market shift makes the recommendations sharper.
Three steps to transform how your team prices deals.
Install the managed package. MarginArc reads your Opportunity data — wins, losses, margins, competitors, OEMs — to understand your pricing history.
Our engine blends rule-based scoring with k-nearest-neighbor analysis of your historical deals. 15+ features. Real-time. No black boxes — every recommendation is explained.
Recommendations appear directly on the Opportunity record. Reps see the score, the margin, the win probability, and the reasoning. One click to apply.
Four proprietary ML layers that compound over time. The longer you use MarginArc, the smarter it gets — and every recommendation is fully explainable.
Feature engineering + Bayesian priors
The moment you connect MarginArc, it reads every Opportunity in your Salesforce and extracts 15+ signals from each deal. Each deal becomes a unique point in a high-dimensional feature space. Simultaneously, we compute Bayesian prior distributions for expected margin by segment — and these priors tighten with every deal you close.
Similarity search + probability surfaces
Once you have enough deal history, MatchIQ starts finding patterns humans can't see. For every new deal, it searches your entire history using distance-weighted nearest-neighbor analysis in 15-dimensional feature space. Simultaneously, WinSurface™ builds a multi-variate logistic model that maps margin × deal features to win probability — not a simple curve, but a surface across all 15 dimensions.
Ensemble stacking + federated network intelligence
Now the real magic: three independent models — rules engine, similarity matcher, and probability surface — each produce a margin. PricePoint blends them via stacked generalization with cross-validated weights that shift as your data grows. Early on, rules dominate. Over time, the ML models take the lead. Add the MarginArc Network's anonymized, firewalled data from non-competing VARs, and you've got a data advantage no single mid-tier VAR could build alone.
Online learning + regime detection
After a year of closed deals, MarginArc enters its most powerful mode: continuous self-improvement. Every deal that closes — win or loss — updates the model in real time via stochastic gradient descent. No batch retraining. No downtime. And if market conditions shift, DriftGuard™ detects it automatically using CUSUM statistical process control and accelerates the learning rate 10× for a 30-day adaptation window.
Every recommendation is shaped by a rich feature vector spanning deal structure, customer behavior, competitive dynamics, and network intelligence — expanding as your data matures.
No single mid-tier VAR has enough data to compete with the giants. But together? Together, you see everything.
Non-competing VARs contribute anonymized deal outcomes to a shared intelligence layer. No one sees your raw data — everyone benefits from the aggregate.
See how CDW, SHI, Presidio, and other competitors price across the network. Know their win rates, margin patterns, and weak spots.
When a network member appears as your competitor, their data is automatically excluded. Zero information leakage. Full trust.
Network data increases recommendation confidence by up to 23% vs. your data alone. More data = better recommendations = more profit.
The world’s largest VARs know they need this. The problem is proven. The ROI model is proven. They just can’t build it — cultural inertia and existing processes block execution.
We ship in weeks, not quarters. No consultants. No committee approvals. Just a Salesforce package and an API key.
Enterprise VARs have pre-negotiated OEM pricing and could build this in-house. Mid-tier VARs have standard discounts, more pricing flexibility, and no data science team. That’s where we win.
Every feature maps to a real pain point we’ve heard from sales leaders at mid-market resellers.
Stop spending 3+ hours per deal in margin review meetings. MarginArc gives the answer before the meeting starts.
New hires don’t have 10 years of pricing instinct. MarginArc gives them institutional knowledge from day one.
Expanding into cybersecurity? Cloud? Use management knobs to accept lower margins strategically while the algorithm learns.
Different reps pricing the same deal at different margins? MarginArc normalizes pricing based on deal attributes, not who’s selling.
Know exactly how to price against CDW, SHI, or Presidio at each account. Historical matchup data turns guesswork into strategy.
Stop choosing between “safe low margin” and “risky high margin.” MarginArc shows the risk-adjusted expected value.
Join the VARs who are turning margin setting from an art form into a science. Book a 15-minute demo and see MarginArc on a live Salesforce org.