Specialty · Shopify · Head of E-Com

Ward and Shopify for Specialty e-commerce

A specialty Head of E-Com running Shopify gets CLV, conversion rate, units per transaction keeps a running read on each day, with what caused it attached.

What a specialty Head of E-Com gets from Shopify / Shopify Plus

Your online and offline data live in different worlds. Ward returns cards scoped to e-commerce decision-making.

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

Getting the data in. 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

  • Unified insight cards across online and in-store channels
  • Cross-channel promo effectiveness with true attribution
  • Customer journey tracking across digital and physical touchpoints
  • BOPIS fulfillment performance monitoring with exception cards
  • Full-funnel marketing attribution to in-store conversion

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 was built for transactions, not for e-commerce decisions. The data is right there and it is in the wrong shape. Ward pulls from orders & line items and product catalog and rewrites them as a decision.

What Ward has eyes on.

Ward reads straight from 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 insight cards. Your Commerce is untouched.

Every one of your boutiques gets its own baseline. Ward keeps a running read on CLV, conversion rate, units per transaction against it and surfaces only the deviations that hold up. The two that show up most in specialty retail are assortment curation and customer lifetime value, and both are baseline problems before they are P&L problems.

What the first 90 days
actually look like.

  1. 01

    Week 1: connect

    Read-only credentials to Shopify / Shopify Plus. Ward reads straight from 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: 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.

  3. 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

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

Your online and offline data live in different worlds.

Pain points
  • ×Nobody can see one inventory position across every channel
  • ×Online promo performance is measured separately from in-store
  • ×Customer behavior data is siloed by channel
  • ×BOPIS/BORIS operational complexity is growing unchecked
  • ×Digital marketing attribution stops at the click
How Ward helps
  • Unified insight cards across online and in-store channels
  • Cross-channel promo effectiveness with true attribution
  • Customer journey tracking across digital and physical touchpoints
  • BOPIS fulfillment performance monitoring with exception cards
  • Full-funnel marketing attribution to in-store conversion

Retailers with unified omnichannel data see 30% higher lifetime value per customer. Source: Harvard Business Review

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.

Your online and offline data live in different worlds. Ward solves this with automated insight cards: Unified insight cards across online and in-store channels. Cross-channel promo effectiveness with true attribution. Customer journey tracking across digital and physical touchpoints.

Ward delivers daily insight cards covering CLV, Conversion rate, Units per transaction, tailored for E-Commerce 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