Specialty · Shopify · Head of IT

Ward and Shopify for Specialty technology

Ward reads Shopify / Shopify Plus and delivers specialty cards scoped to technology. The business wants AI. You sign off on the architecture.

What a specialty Head of IT gets from Shopify / Shopify Plus

For Specialty Retail retailers, that means tracking 5,000+ SKUs across boutiques. High-consideration purchases, curated assortments, and customer lifetime value. Ward tracks the metrics that matter for margin-rich retail.

The business wants AI. You sign off on the architecture. Ward filters to what a Head of IT can act on and drops the rest.

The connection itself. OAuth-based connection. Ward reads via Shopify Admin GraphQL API. Real-time webhooks for order and inventory events.

app.getward.ai Live demo
Acme Specialty @Store Ops: Retail Analyst claude-sonnet default
A

Chat

Ask anything. Ward routes to the right agent and returns cited answers.

Why is conversion down at the flagship boutiques?
You · 9:42 AM
Schema Scout · routed to Store Ops Agent

I pulled traffic against conversion by hour for the four flagships. Traffic is fine. The gap is coverage and depth.

SignalFinding
traffic_conversionConversion 18.4% vs. 23.1% chain, all of the gap in 12–2p and 5–7p
labor.coverageOne associate on the floor through both peaks at 3 of 4 doors
inventory.depthTop 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.

8 parallel queries 3 sources cited confidence 0.91
Draft the clienteling outreach list.
You · 9:43 AM
Clienteling Agent · drafting outreach list
Querying traffic_conversion
Ask anything, Ward routes to the right agent. Cmd+K

Reporting

Pinned views built from saved data-lake queries. Every number re-derivable from its SQL.

7d13w52w
Revenue vs. plan
$27.5M
+4.4% WoW
Conversion rate
18.3%
−4.7pp
UPT, flagships
2.14
−0.18
At-risk CLV, top decile
$4.1M
−$310K
Revenue vs. plan 13 weeks actual, 6 weeks forecast, 80% interval
Actual Forecast 80% interval
% of plan 106 94 100 forecast → W−13 W−5 today +6wk
Holt-Winters + weather regressor MAPE 4.1% at 4wk Backtested 24 months Crosses plan in 3 weeks
Forecast error by horizon MAPE, 24-month backtest
1wk 2.1%
2wk 3.0%
4wk 4.1%
8wk 6.3%
13wk 8.9%
Accuracy bar for promo decisions: ≤5% at 4wk
Models in production Every forecast ships a model card
ModelHorizonMAPE
holt_winters4wk4.1%
arima_sarimax13wk8.9%
gbm_demand1wk2.1%
bayes_hiernew store11.4%

Sources

Connect external systems to the data lake.

NameTypeLast sync
shopify_orders_dailyimport2m ago
lightspeed_store_salesimport2m ago
netsuite_inventory_snapshotimport14m ago
retail_customer_ltvimport1h ago
retail_traffic_conversionimport1h ago
retail_clienteling_logimport1h ago
retail_ga4_website_dailyimport1h ago

Policies

Browse and manage Cedar access policies for your tenant.

TLS 1.3 AES-256 Read-only SOC 2 II
Policy IDEffectResources
ops-read-defaultpermitModel::*
crm-read-ltvpermitModel::"customer_ltv"
associate-pii-blockedforbidModel::"customer_pii"
merch-read-assortmentpermitModel::"sales_by_tier"
for Specialty on Shopify data, live product demo.

What Ward delivers

  • Federated query: data stays in your warehouse. No copies, no shadow lake
  • Read-only credentials. Cedar policies enforce least-privilege per agent
  • LLM-agnostic. Anthropic, OpenAI, Gemini, Ollama. Bring your own keys
  • Every query, every model, every source logged. SIEM-ready audit output
  • VPC peering, PrivateLink, SOC 2 II. Your security review is short

Metrics Ward monitors

CLV
Conversion rate
Units per transaction
Repeat purchase rate
Sell-through by tier

Specialty challenges Ward solves

  • Assortment curation
  • Customer lifetime value
  • Staff selling effectiveness
  • Clienteling optimization
  • Inventory depth vs breadth

Why this combination
is its own problem.

Shopify / Shopify Plus is the system of record for most specialty operators of your size, which means the readings Ward needs are already there. The gap is not data collection. It is that nobody has time to read orders & line items and product catalog every morning over every store.

What Ward has eyes on.

Coverage is store by store, category by category. Ward monitors CLV, conversion rate, units per transaction throughout 5,000+ SKUs and compares each store against its own baseline, not against the chain. That is the difference between knowing the estate is fine and knowing which seven boutiques are not.

Ward ingests Shopify rather than replacing it. Orders & line items, product catalog, inventory levels come across on a read-only connection, get enriched with contextual data, and come back as findings. Your Commerce is untouched.

What the first 90 days
actually look like.

  1. 01

    Week 1: connect

    Read-only credentials to Shopify / Shopify Plus. Ward ingests orders & line items, product catalog, inventory levels and starts building baselines. First cards land inside 48 hours, before baselines are stable, so you can see the shape of the output early.

  2. 02

    Weeks 2 to 3: baselines

    Ward needs roughly two weeks of history per store to separate a real deviation from normal variance. During this window the cards are directionally right and the thresholds are still moving.

  3. 03

    Weeks 4 to 12: operating rhythm

    Daily cards arrive daily 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

Orders & line items
Product catalog
Inventory levels
Customer profiles
Discount usage
Fulfillment data

Impact metrics with Shopify

Sell-Through Rate
Slow movers reallocated
Order velocity tracked; underperformers flagged before markdowns.
Return Rate
Return-prone patterns spotted
Behavioral signals identify high-return product and buyer combos.
Customer LTV
Re-engagement timed right
Purchase cadence and cohort data surface lapsing customers.
Inventory Turnover
Reorder points tightened
Demand signals optimize safety stock across the catalog.

Data lake enrichment

Ward enriches Shopify data with: Order & line items, Customer behavior, Marketing attribution, Returns & exchanges, Competitor pricing

The business wants AI. You sign off on the architecture.

Pain points
  • ×Business sponsor already chose the vendor. You inherit the security review
  • ×Every AI vendor wants write access and a copy of the production data
  • ×Model lock-in means rewriting the stack when GPT or Claude moves again
  • ×Audit trail is an afterthought. Compliance has nothing to pull on
  • ×Data lake project keeps getting bumped for the next thing the business wants
How Ward helps
  • Federated query: data stays in your warehouse. No copies, no shadow lake
  • Read-only credentials. Cedar policies enforce least-privilege per agent
  • LLM-agnostic. Anthropic, OpenAI, Gemini, Ollama. Bring your own keys
  • Every query, every model, every source logged. SIEM-ready audit output
  • VPC peering, PrivateLink, SOC 2 II. Your security review is short

74% of enterprise AI projects stall before production. Integration debt and security review are the top two reasons. Source: Gartner

Specialty KPI impact

CLV
Churn risk surfaced
At-risk customers identified before they leave.
Conversion Rate
Assortment + staffing
Cards that help convert high-intent browsers.
Revenue per SKU
Whitespace found
Underperformers identified, gaps in curated assortment.
Overstock
Less capital locked
Demand matching reduces slow-moving inventory.

Frequently asked questions

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.

The business wants AI. You sign off on the architecture. Ward solves this with automated insight cards: Federated query: data stays in your warehouse. No copies, no shadow lake. Read-only credentials. Cedar policies enforce least-privilege per agent. LLM-agnostic. Anthropic, OpenAI, Gemini, Ollama. Bring your own keys.

Ward delivers daily insight cards covering CLV, Conversion rate, Units per transaction, tailored for Technology decision-making. Each card includes what changed, why it matters, and what to do next.

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.

See what Specialty problems Ward catches.

Root causes, not just alerts. See it on your data.

Read-only to start · your LLM keys · SOC 2 Type II underway · or book a call directly

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.

Step 1 of 3
What are your goals?
Step 2 of 3
About your operation
Step 3 of 3
Your contact info