Dynamic Pricing for Shopify
A Shopify-tuned deployment of the canonical Dynamic Pricing & Promotion Engine — wired to Shopify Discounts, Shopify Functions for custom pricing logic, and the storefront experimentation infrastructure.
- Engagement
- 6–12 week deployment · self-serve to custom packaging
- Built for
- DTC operators · Shopify-Plus brands · Multi-store DTC holdcos
Shopify stores price by intuition and run promotions on calendar habit — without elasticity modeling, the promotion calendar produces gross-sales lift that's mostly pull-forward from un-promoted weeks.
What this is
The canonical Dynamic Pricing & Promotion Engine, tuned for Shopify-native execution. See the canonical product page in the Operations Algorithms Suite for the modeling backbone, elasticity-and-cannibalization detail, and technical depth. The Shopify-tuned tuning consists of:
- Direct integration with Shopify Discounts API for price-list and promotion management.
- Shopify Functions integration for cart-evaluated pricing logic where the runtime budget permits.
- Shopify Markets support for per-market pricing recommendations.
- Storefront experimentation infrastructure integration for A/B testing of price points and promotion structures.
What you get
- The pricing model deployed against your Shopify data.
- Shopify Discounts API integration for execution.
- Shopify Functions logic for the cart-side decisions that warrant it.
- Operator UI consistent with Shopify Admin.
- Quarterly model refresh and experimentation infrastructure.
Engagement is shape, not list.
Length and price are functions of the data and the destination. The shape below is the typical engagement.
- Length
- 6–12 week deployment · self-serve to custom packaging
- Lead
- Bogdan
- Cadence
- Async, weekly
- Bar
- Production
Scoped during the discovery call against the actual data and the operation it integrates with.
Principal engineer. Architecture and most code ships through one keyboard.
Written updates between, calls when the decision needs the room.
Async correctness, capacity under burst, observability at every boundary.
Products this composes with.
Same suite, or vertical-specialized versions in another.
- Also in · Operations Algorithms Suite
Dynamic Pricing & Promotion Engine
An elasticity-and-promotion model — per-segment price elasticity (or discount-elasticity for negotiated B2B), promotion-cannibalization modeling, recommended timing and depth that maximizes net revenue.
- Same suite · Shopify Ops Intelligence Suite
Demand Forecasting for Shopify
A Shopify-tuned deployment of the canonical Demand Forecasting & Inventory Engine — wired to Shopify's Orders API, Inventory API, and per-channel data, integrated with the operator's replenishment workflow.
- Same suite · Shopify Ops Intelligence Suite
Shopify Operations Workflow Automation
An integrated operations-workflow layer — Shopify Flow for the standard triggers, custom orchestration where Flow's limits run out, and the cross-workflow coordination that the point-app stack misses.
What buyers ask about this one.
Can Shopify Functions actually run our pricing logic in real time?
Yes, within the constraints of the Functions runtime — fast, deterministic, cart-evaluated. For pricing logic that exceeds the runtime budget, the engine falls back to price-list updates via the API rather than runtime computation. The engagement scopes which logic runs where.
What about Shopify Markets and per-market pricing?
Shopify Markets integration is supported. The pricing model can produce per-market recommendations, fed to Markets pricing rules.
How is this different from the OAS canonical?
Same modeling backbone. What's different is the Shopify integration surface — Discounts API, Functions, Markets, the storefront-experimentation infrastructure. Cross-link to the canonical for the modeling detail.
What's the typical impact on DTC margin?
Per-engagement varies. Typical findings: 200–500 bps of margin uplift from elasticity-informed pricing and promo timing. Smaller stores often see larger relative impact because they're starting from less-sophisticated pricing.
Pricing?
Tiered per buyer profile. Discovery call covers the right tier.
If the deliverable matches the gap, the next step is one call.
We'll scope length and price against your data and the operation it integrates with. No retainer, no fishing.
Bogdan and team · async-first · OP—2026