Promos · Shopify

Run promos straight off Shopify

Promo Effectiveness needs orders & line items and product catalog. Shopify has both. Ward does the rest.

Running promo effectiveness off Shopify / Shopify Plus

What promo effectiveness does: Ward measures true promotional lift net of cannibalization, pull-forward, and pantry loading.

The mechanism. Ward isolates incremental volume from baseline, measures cross-SKU cannibalization, estimates pull-forward effects, and calculates true ROI.

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

The short list

  • Promo ROI scorecards
  • Net lift measurement (not gross)
  • Cannibalization quantification
  • Pull-forward detection
app.getward.ai Live demo
Acme Retail @Merchandising: VP Analyst claude-sonnet default
A

Chat

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

Why did Store 37 miss target last week?
You · 9:42 AM
Schema Scout · routed to Merchandising Agent

I pulled Store 37’s last 28 days against the chain baseline. Two root causes, both compounding.

SignalFinding
labor_efficiencyRev/labor-hour −22% vs. cluster, staffing mismatch at 11a–1p peak
inventory.freshFresh fill 83%, backroom replenishment lag at 2–4p
promo.liftBOGO 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.

8 parallel queries 3 sources cited confidence 0.92
Show me how to fix the staffing mismatch.
You · 9:43 AM
Labor Agent · drafting schedule diff
Querying labor_scheduling
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. forecast
$48.2M
+4.2% WoW
Gross margin %
24.1%
−3.2pp
Fill rate, fresh
83.4%
−4.1pp
Shrink, West region
2.41%
+0.8pp
Revenue vs. forecast 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
sap_pos_transactionsimport2m ago
sap_inventory_shrinkageimport2m ago
sap_labor_schedulingimport14m ago
retail_inventory_weeklyimport1h ago
retail_google_ads_dailyimport1h ago
retail_meta_ads_dailyimport1h 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
merch-read-defaultpermitModel::*
finance-read-shrinkagepermitModel::"inventory_shrinkage"
vendor-blockedforbidModel::"labor_*"
region-west-onlypermitTenant::"acme"
Promos on Shopify data, live product demo.

What Ward has eyes on.

The connection to Shopify / Shopify Plus is read-only and runs on your schedule. Ward pulls from orders & line items, product catalog, and the rest of the feed, then cross-references it with external context your Commerce does not carry: weather, local events, competitor pricing.

The promos model runs each day, not on a reporting calendar. It catches the pattern, accounts for root cause, and attaches the next step before the number reaches a review deck.

Why this combination
is its own problem.

Promo Effectiveness needs orders & line items and product catalog at minimum. Shopify / Shopify Plus carries both, at the grain the model needs. That is the whole integration story: no middleware, no staging warehouse, no custom extract.

What the first 90 days
actually look like.

  1. 01

    Week 1: connect

    Read-only credentials to Shopify / Shopify Plus. Ward pulls from orders & line items, product catalog, inventory levels and starts building baselines. First insight 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 insight cards are directionally right and the thresholds are still moving.

  3. 03

    Weeks 4 to 12: steady state

    Ward delivers insight cards each day, each with what caused it and what to do about it. Volume settles at a level a single person can read over coffee. The measure of success is not how many cards arrive, it is how many get acted on.

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

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.

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 promos 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