Promos · Lightspeed · VP Supply Chain

VP Supply Chain: promos straight off Lightspeed

Know which promos actually work. Ward runs it off Lightspeed, scoped to what a VP Supply Chain owns.

How a VP Supply Chain runs promos off Lightspeed Retail

You find out about stockouts after customers do. Ward filters to what a VP Supply Chain can act on and drops the rest.

Promo Effectiveness is a finding type Ward runs continuously. Ward measures true promotional lift net of cannibalization, pull-forward, and pantry loading.

What Ward does with that: Ward isolates incremental volume from baseline, measures cross-SKU cannibalization, estimates pull-forward effects, and calculates true ROI.

Getting the data in. Ward connects via Lightspeed Retail API. OAuth-based authentication. Read-only access.

What it does

  • Net lift measurement (not gross)
  • Cannibalization quantification
  • Pull-forward detection
  • Promo ROI scorecards
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 Lightspeed data, live product demo.

What Ward has eyes on.

Ward pulls from Lightspeed rather than replacing it. Sales transactions, inventory counts, customer profiles come across on a read-only connection, get enriched with contextual data, and come back as insight cards. Your POS is untouched.

The promos model runs every morning, not on a reporting calendar. It catches the pattern, attributes the cause, and attaches what to do about it before the number reaches a review deck.

Why this combination
is its own problem.

Promo Effectiveness needs sales transactions and inventory counts at minimum. Lightspeed Retail 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: read-only connection

    Ward connects to Lightspeed Retail with read-only credentials and begins ingesting sales transactions and inventory counts. No config changes on your side. First insight cards arrive in two days.

  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 findings are directionally right and the thresholds are still moving.

  3. 03

    Weeks 4 to 12: operating rhythm

    Cards arrive every morning 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 Lightspeed Retail

Ward integrates with Lightspeed Retail POS for specialty and boutique retailers. In-store transaction data powers customer behavior and assortment insight cards.

Setup: Ward connects via Lightspeed Retail API. OAuth-based authentication. Read-only access.

Data Ward reads from Lightspeed

Sales transactions
Inventory counts
Customer profiles
Purchase orders
Employee performance

Impact metrics with Lightspeed

Customer LTV
Lapsing buyers flagged
Purchase cadence and segment data reveal re-engagement windows.
Conversion Rate
Staffing-timing link found
Transaction data reveals which staff and hour combos convert.
Revenue per SKU
Whitespace identified
Underperformers and assortment gaps surfaced from sales data.
Inventory Accuracy
Count-to-velocity matched
Inventory counts reconciled against POS sell-through live.

Data lake enrichment

Ward enriches Lightspeed data with: Sales transactions, Customer profiles, Weather & events, Competitor data, Demographic data

You find out about stockouts after customers do.

Pain points
  • ×Demand forecasts are off by 15-25% and nobody catches it until the shelf is empty
  • ×Supplier fill rate problems announce themselves at the receiving dock
  • ×Safety stock levels get set once a year and left alone
  • ×No early warning system for supply chain disruptions
  • ×Replenishment exceptions require manual triage every morning
How Ward helps
  • Stockout prediction cards arrive 24-72 hours before empty shelves
  • Supplier fill rate tracking with automatic escalation
  • Dynamic safety stock recommendations based on current demand signals
  • Weather, event, and macro-driven demand adjustments
  • Replenishment exceptions auto-prioritized by revenue impact

Stockouts cost retailers $1.14 trillion in missed sales globally each year. Source: IHL Group

Frequently asked questions

Ward connects via Lightspeed Retail API. OAuth-based authentication. Read-only access. Data points include: Sales transactions, Inventory counts, Customer profiles, Purchase orders, Employee performance.

You find out about stockouts after customers do. Ward solves this with automated insight cards: Stockout prediction cards arrive 24-72 hours before empty shelves. Supplier fill rate tracking with automatic escalation. Dynamic safety stock recommendations based on current demand signals.

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