Head of Procurement: specialty pricing, read from Shopify / Shopify Plus
Price on elasticity you can measure. Ward runs it on Shopify data over your specialty fleet, scoped to procurement.
Price Optimization for Specialty on Shopify, scoped to procurement
Price Optimization is a finding type Ward runs continuously. Ward monitors price elasticity shifts in real time and recommends adjustments that protect margin without sacrificing volume.
In a Specialty Retail store base the job is 5,000+ SKUs over boutiques. High-consideration purchases, curated assortments, and customer lifetime value. Ward tracks the metrics that matter for margin-rich retail.
Merchandising wants Ward. You sign the contract. Ward returns findings scoped to procurement decision-making.
How Ward delivers Pricing insight cards: Ward continuously measures price elasticity by category, tracks competitive pricing signals, and models the margin-volume tradeoff.
Getting the data in. OAuth-based connection. Ward reads via Shopify Admin GraphQL API. Real-time webhooks for order and inventory events.
What it does
- Real-time elasticity measurement
- Category-level price sensitivity
- Competitive price monitoring
- Margin-volume tradeoff modeling
Chat
Ask anything. Ward routes to the right agent and returns cited answers.
I pulled traffic against conversion by hour for the four flagships. Traffic is fine. The gap is coverage and depth.
| Signal | Finding |
|---|---|
traffic_conversion | Conversion 18.4% vs. 23.1% chain, all of the gap in 12–2p and 5–7p |
labor.coverage | One associate on the floor through both peaks at 3 of 4 doors |
inventory.depth | Top 20 styles at 1.4 units per size, walk-away rate +9% |
Recommend: add floor coverage to both peak windows, deepen the top 20 styles to three per size at the flagships, and route the walk-away list to clienteling.
traffic_conversion…
Reporting
Pinned views built from saved data-lake queries. Every number re-derivable from its SQL.
| Model | Horizon | MAPE |
|---|---|---|
holt_winters | 4wk | 4.1% |
arima_sarimax | 13wk | 8.9% |
gbm_demand | 1wk | 2.1% |
bayes_hier | new store | 11.4% |
Sources
Connect external systems to the data lake.
| Name | Type | Last sync |
|---|---|---|
shopify_orders_daily | import | 2m ago |
lightspeed_store_sales | import | 2m ago |
netsuite_inventory_snapshot | import | 14m ago |
retail_customer_ltv | import | 1h ago |
retail_traffic_conversion | import | 1h ago |
retail_clienteling_log | import | 1h ago |
retail_ga4_website_daily | import | 1h ago |
Policies
Browse and manage Cedar access policies for your tenant.
| Policy ID | Effect | Resources |
|---|---|---|
ops-read-default | permit | Model::* |
crm-read-ltv | permit | Model::"customer_ltv" |
associate-pii-blocked | forbid | Model::"customer_pii" |
merch-read-assortment | permit | Model::"sales_by_tier" |
Why Pricing matters for Specialty retail
Specialty pricing lives or dies on value perception. The opportunity lies in separating products with "curation premium" tolerance, where customers won't compare, from items cross-shopped against Amazon where a gap triggers showrooming. Ward segments pricing power by product and customer segment to maximize margin without triggering comparison behavior.
What Ward has eyes on.
Coverage is store by store, category by category. Ward keeps a running read on CLV, conversion rate, units per transaction over 5,000+ SKUs and compares each store against its own baseline, not against the chain. That is the difference between knowing the footprint is fine and knowing which seven boutiques are not.
The connection to Shopify / Shopify Plus is read-only and runs on your schedule. Ward ingests orders & line items, product catalog, and the rest of the feed, then joins it with external context your Commerce does not carry: weather, local events, competitor pricing.
Price on elasticity you can measure. Ward runs the model continuously rather than on a reporting cycle, which is why a finding lands the morning the pattern starts instead of at the end of the period.
At the metric level. Ward tracks showrooming risk by SKU, curation premium tolerance, customer segment sensitivity, and associate-driven upsell effectiveness, staffed departments tolerate higher prices because of the service component.
Why this combination
is its own problem.
A Head of Procurement does not need the pricing model explained. They need to know which stores moved, why, and what to do by end of day. Ward writes the finding at that altitude.
- 01 Exclusive collaborations and artisan products often have 30-60% pricing headroom that gets left on the table because chain pricing logic uses cross-category averages.
- 02 Specialty retailers price their entire assortment defensively against Amazon when only 15-30% of SKUs are actually being showroomed; the rest carries unrealized margin.
Benchmarks. Specialty showrooming-vulnerable SKU share: 15-30%. Exclusive and curated products typically carry 100-300 bps of unrealized margin. Associate-driven categories tolerate 5-15% higher pricing than self-service equivalents because of the service value.
What the first 90 days
actually look like.
-
01
Week 1: read-only connection
Ward reads from Shopify / Shopify Plus with read-only credentials and begins ingesting orders & line items and product catalog. No config changes on your side. First insight cards arrive in two days.
-
02
Weeks 2 to 3: calibration
Baselines stabilize per store and per category. Ward stops flagging normal variance and starts flagging exceptions. This is the window where the false positive rate drops sharply.
-
03
Weeks 4 to 12: operating rhythm
Cards arrive on a daily cycle and get triaged like any other queue. Most teams find the volume settles into something one person clears in ten minutes. What matters is the action rate, not the alert count.
How Ward connects to Shopify / Shopify Plus
Ward connects to Shopify and Shopify Plus via the Admin API. Orders, products, inventory, and customer data power Ward insight cards for omnichannel retailers.
Setup: OAuth-based connection. Ward reads via Shopify Admin GraphQL API. Real-time webhooks for order and inventory events.
Data Ward reads from Shopify
Impact metrics with Shopify
Data lake enrichment
Ward enriches Shopify data with: Order & line items, Customer behavior, Marketing attribution, Returns & exchanges, Competitor pricing
Merchandising wants Ward. You sign the contract.
- ×Business sponsor saw the demo. You have a week to vet a vendor you didn't pick
- ×AI vendors price by seats and tokens. Total cost is unknowable until invoice three
- ×Multi-year commits with auto-renew. No exit if the pilot stalls
- ×Renewals come back 30% higher, with no room to push back and no benchmark to cite
- ×Security and DPA reviews start after the team has already committed
- ✓MSA, DPA, SOC 2 Type II underway, and architecture review available before signature
- ✓Month-to-month contracts. No multi-year lock-in. No auto-renew traps
- ✓Transparent pricing set by scope and store count
- ✓14-day insight guarantee. If Ward doesn't deliver, month two is on us
- ✓AI strategy, orchestration and reporting-layer work in enterprise grocery at nine-figure revenue. Reference calls available before signature
Enterprise SaaS spend grew 18% YoY. 53% of subscriptions are underused or duplicative. Source: Gartner
Specialty KPI impact
Frequently asked questions
Ward monitors price elasticity shifts in real time and recommends adjustments that protect margin without sacrificing volume. For Specialty retail specifically, Ward monitors 5,000+ SKUs across your boutiques and delivers automated insight cards with root cause analysis and recommended actions.
Ward tracks CLV, Conversion rate, Units per transaction, Repeat purchase rate, Sell-through by tier at the store-category level. Ward continuously measures price elasticity by category, tracks competitive pricing signals, and models the margin-volume tradeoff.
OAuth-based connection. Ward reads via Shopify Admin GraphQL API. Real-time webhooks for order and inventory events. Data points include: Orders & line items, Product catalog, Inventory levels, Customer profiles, Discount usage, Fulfillment data.
Yes. Ward reads Shopify data and combines it with contextual signals (weather, events, demographics) to generate Specialty-specific insight cards. No custom development required.
Merchandising wants Ward. You sign the contract. Ward solves this with automated insight cards: MSA, DPA, SOC 2 Type II underway, and architecture review available before signature. Month-to-month contracts. No multi-year lock-in. No auto-renew traps. Transparent pricing set by scope and store count.
Ward delivers daily insight cards covering CLV, Conversion rate, Units per transaction, tailored for Procurement decision-making. Each card includes what changed, why it matters, and what to do next.
Ward tracks showrooming risk by SKU, curation premium tolerance, customer segment sensitivity, and associate-driven upsell effectiveness, staffed departments tolerate higher prices because of the service component.
Ward identifies a minority of the assortment, branded items available on Amazon, being actively showroomed. The majority, including exclusive collaborations and artisan products, has near-zero price sensitivity because customers can't comparison shop. Ward recommends matching online pricing on showroomed SKUs while implementing increases on non-comparable items, delivering a net margin improvement with better competitive perception on the items that actually get compared.
First insight cards arrive within 48 hours of data connection. Ward needs approximately 2 weeks to establish stable baselines for your specific operation.
No. Ward sits on top of your existing stack. It is the proactive intelligence layer that watches your data continuously and delivers insight cards, so your team acts on findings instead of hunting for them.
Related solutions
See what Specialty pricing problems Ward catches.
Root causes, not just alerts. See it on your data.
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