Stop guessing. Ward monitors pricing for Specialty.
Your Specialty data holds the answers. Ward finds them.
Why pricing matters
in specialty retail.
Specialty pricing is about value perception, not competitive matching. 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.
Industry 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.
Amazon showrooming defense, home goods retailer
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.
What Ward actually tracks
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.
Data signals
POS at SKU-store-day, online competitor scrapes (Amazon, brand DTC), search trend volume per SKU, exclusivity flags, and category staffing metadata.
Three pitfalls Ward catches
in specialty pricing.
- 01 Specialty retailers price their entire assortment defensively against Amazon when only 15-30% of SKUs are actually being showroomed; the rest carries unrealized margin.
- 02 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.
- 03 Associate-driven upsell categories (consultative beauty, jewelry, custom furniture) tolerate higher prices than self-service categories, but pricing rules don't differentiate.
How Ward runs pricing
for specialty retailers.
-
01
Score every SKU on showrooming risk
Ward tags SKUs by Amazon comparability, exclusive-vs-distributed status, and search volume, separating defended from differentiated.
-
02
Match competitively on the showroomed minority
Cards recommend price matching on the 15-30% being actively cross-shopped while flagging the 70-85% with pricing headroom.
-
03
Test upward moves on differentiated items
Ward designs price tests on exclusive and curated products in matched stores, tracking margin and basket effects over 6-8 weeks.
What a Ward card looks like.
Dairy category showing -1.4 elasticity this week vs -0.8 baseline. Consumers responding to price changes 75% more than normal.
Chat
Ask anything. Ward routes to the right agent and returns cited answers.
I pulled Store 37’s last 28 days against the chain baseline. Two root causes, both compounding.
| Signal | Finding |
|---|---|
labor_efficiency | Rev/labor-hour −22% vs. cluster, staffing mismatch at 11a–1p peak |
inventory.fresh | Fresh fill 83%, backroom replenishment lag at 2–4p |
promo.lift | BOGO crackers cannibalized Brand Y by 28%, net category +6% |
Recommend: re-baseline Store 37 schedule against true peak, raise replen window to 1p, and review the BOGO before next cycle.
labor_scheduling…
Dashboards
Pinned views built from saved data-lake queries.
Models
Browse, search, and manage data–lake model definitions for your tenant.
| Name | Namespace | Version |
|---|---|---|
retail_pos_transactions | retail | 1.0 |
retail_inventory_snapshot | retail | 1.2 |
retail_labor_scheduling | retail | 1.0 |
retail_promo_calendar | retail | 1.1 |
retail_supplier_performance | retail | 1.0 |
sap_inventory_shrinkage | sap | 1.0 |
ga4_daily_events | marketing | 1.0 |
meta_ads_ad_level | marketing | 1.0 |
Sources
Connect external systems to the data lake.
| Name | Type | Last sync |
|---|---|---|
sap_pos_transactions | import | 2m ago |
sap_inventory_shrinkage | import | 2m ago |
sap_labor_scheduling | import | 14m ago |
retail_inventory_weekly | import | 1h ago |
retail_google_ads_daily | import | 1h ago |
retail_meta_ads_daily | import | 1h ago |
retail_ga4_website_daily | import | 1h ago |
Architecture
Two ways to connect. Federate against your live systems, or ingest into Ward’s data lake. Toggle below.
sap.possnow.inventoryPipelines
Move data from sources into models on a schedule.
| Name | Source | Model | Status | Schedule |
|---|---|---|---|---|
sync_sap_pos_transactions | sap_pos_transactions | pos_transactions | enabled | hourly |
sync_sap_labor_scheduling | sap_labor_scheduling | labor_scheduling | enabled | daily |
sync_sap_inventory_shrinkage | sap_inventory_shrinkage | inventory_shrinkage | enabled | daily |
sync_retail_inventory_weekly | retail_inventory_weekly | inventory_weekly | enabled | weekly |
sync_retail_google_ads_daily | retail_google_ads_daily | google_ads_daily | enabled | daily |
sync_retail_ga4_website_daily | retail_ga4_website_daily | ga4_website_daily | enabled | daily |
Streams
Real-time ingestion pipelines.
pos.txnstore_037, basket $42.18inv.movedc_west → store_104labor.clockstore_022 shift_startpos.txnstore_211, basket $19.04
Policies
Browse and manage Cedar access policies for your tenant.
| Policy ID | Effect | Resources |
|---|---|---|
merch-read-default | permit | Model::* |
finance-read-shrinkage | permit | Model::"shrinkage" |
vendor-blocked | forbid | Model::"labor_*" |
region-west-only | permit | Tenant::"acme" |
Entities
Principals and resources referenced by Cedar policies.
| Entity UID | Type | Tenant |
|---|---|---|
Tenant::"acme" | Tenant | acme |
Model::"sap.pos_transactions" | Model | acme |
Model::"sap.inventory_shrinkage" | Model | acme |
Model::"sap.labor_scheduling" | Model | acme |
Model::"retail.toast_pos_daily" | Model | acme |
Model::"retail.ga4_website_daily" | Model | acme |
Providers
Manage LLM API keys and the model profiles that use them.
| Name | Provider | Used by | Created |
|---|---|---|---|
anthropic-default | Anthropic | 3 profiles | Apr 22 |
openai-default | OpenAI | 2 profiles | Apr 22 |
gemini-default | Gemini | 1 profile | Apr 22 |
ollama-onprem | Ollama | 2 profiles | Apr 22 |
LLM-agnostic. Bring your own key, route per task. No lock-in.
Settings
Manage your dashboard preferences and account.
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Specialty pricing:
the shift.
- ×Assortment curation
- ×Customer lifetime value
- ×Staff selling effectiveness
- ✓Real-time elasticity measurement
- ✓Category-level price sensitivity
- ✓Competitive price monitoring
Questions about specialty pricing.
Specialty pricing is about value perception, not competitive matching. 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.
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.
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.
First pricing insight cards arrive within 48 hours. Robust specialty baselines form within two weeks. Ward needs 3\u20136 months to reach statistical confidence at the individual store level. High-ticket, low-frequency retailers should expect longer baselines than replenishment-oriented specialty.
Specialty pricing
by data source.
More Specialty insight cards.
Specialty retailers: see what pricing problems Ward catches.
Root causes, not just alerts. See it on your data.
Find out what your data has been hiding.
Tell us about your operation. We’ll show you the problems Ward catches, and the ones your current tools miss.