Connect your pricing stack
Connect code, catalog, transactions, costs, inventory, metrics, constraints, and experiment history behind pricing.
Pricing & promotions
The applied science factory for improving pricing and promotions
Pavo learns how your pricing and promotions work across transactions, margins, and past tests. It finds opportunities, builds the evaluation, and runs experiments to improve incremental margin.
Current pricing stack
rules · offers · margin model
Transactions + costs
prices · volumes · margin
Inventory + response
stock · elasticity · churn
Candidate policies
price · offer · audience · timing
Guardrail envelope
margin · fairness · stock · churn
Controlled test
a held-out set of stores
Incremental margin moves
Increase experimentation velocity
Explore elasticity, targeting, and markdown policies in parallel. Move stronger ideas to controlled tests faster.
Increase win rates
Evaluate candidates across cohorts, uncertainty, and margin floors. Reserve live traffic for the strongest evidence.
Force multiplier for your team
Automate elasticity analysis, incrementality evaluation, and experiment preparation.
How it works
From a margin goal to a controlled test. Connect your stack, verify what Pavo understands about your system, then start giving it projects.
Build system understanding
Pavo reconstructs how your production system works. Your team verifies the system book.
Run applied science projects with Pavo
Give Pavo a metric goal and guardrails. It frames the problem, runs analyses, compares policies, and opens PRs.
Capabilities
Applied science capabilities for the whole team.To test pricing and promotion policies faster, without losing sight of margin or customers.
Applied science judgement
Picking the right problem, the right approach, the right lever
- Finds where the margin is leaking - which segment, which SKU, and whether it's price, promo, or eligibility
- Knows whether to fix the elasticity model, the targeting, the discount depth, or the guardrail
- Grounds it in your own past price tests and demand behaviour, not just what's in the repo
Scientific rigour
Explores widely, and ships only what's proven
- Compares multiple elasticity and targeting policies against one shared evaluation, instead of betting on one price test
- Estimates policy value from historical tests and transactions, then reserves live traffic for the strongest candidates
- Tests incrementality against cannibalisation and seasonality, and checks candidates against approved margin floors
Knowledge compounds
Every iteration makes the next one cheaper
- The work itself produces new knowledge - how your segments respond to price, which promos are truly incremental, where discounting stops working
- Written back to your system book, reviewed by your team, reused next time - it stays with you
- Your team owns the learnings, so v2 to v3 to v4 gets faster, not just further
Use-cases
Our one-size-fits-all price rules leak margin when demand shifts by SKU and market
Pavo compares hierarchical, choice, and causal demand models, calibrates price response with experiments, then measures contribution margin, conversion, and volume within approved price bounds.
Price responseContribution marginConversionVolume
We discount customers who would have bought anyway, so campaign lift is not incremental
Pavo compares uplift and causal models for eligibility and discount depth, optimises offers under budget rules, then validates incremental margin in a controlled holdout.
Incremental marginOffer costBudgetRetention
Our markdowns clear too late or too deeply, leaving inventory or giving away margin
Pavo compares rule-based, counterfactual, and multi-period markdown policies, then measures sell-through, realised margin, and leftover inventory across the full selling horizon.
Sell-throughRealised marginLeftover inventoryPrice changes
Security and trust
The security posture your compliance team wants
ISO 27001
Certified
SOC 2 Type II
Compliant
Encryption
Encrypted in transit and at rest, with managed production keys.
Access control
Least-privilege access, enforced with MFA and reviewed quarterly.
Data control
Tenant-segmented, with retention and customer-controlled deletion.
Monitoring and response
Continuously monitored, centrally logged, and ready to respond.
Tested and patched
Independently pen-tested, scanned, and kept current against threats.
Resilient by design
Multi-AZ with backups and a tested continuity and recovery plan.
Full reports, policies, and the complete control list are available on request through the Trust Center.
Build a pricing system that improves, with every experiment.
Start with one pricing decision and one metric. Pavo helps your team understand the system, evaluate better policies, and ship the first team-approved experiment.