Demand Forecasting on Lightspeed Retail data
Demand Forecasting needs sales transactions and inventory counts. Lightspeed has both. Ward does the rest.
Demand Forecasting on Lightspeed Retail data
What demand forecasting does: Ward combines historical patterns, weather data, local events, and economic signals to forecast demand at the store-SKU-day level.
Under the hood. Ward builds store-level demand models incorporating seasonality, weather forecasts, promotional calendars, local events, and macroeconomic indicators.
Getting the data in. Ward connects via Lightspeed Retail API. OAuth-based authentication. Read-only access.
Capabilities
- Event and holiday modeling
- Automatic reorder point recalculation
- Store-SKU-day level precision
- Weather-driven adjustment
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…
Reporting
Pinned views built from saved data-lake queries. Every number re-derivable from its SQL.
| Model | Horizon | MAPE |
|---|---|---|
holt_winters | 4wk | 4.1% |
arima_sarimax | 13wk | 8.9% |
gbm_demand | 1wk | 2.1% |
bayes_hier | new store | 11.4% |
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 |
Policies
Browse and manage Cedar access policies for your tenant.
| Policy ID | Effect | Resources |
|---|---|---|
merch-read-default | permit | Model::* |
finance-read-shrinkage | permit | Model::"inventory_shrinkage" |
vendor-blocked | forbid | Model::"labor_*" |
region-west-only | permit | Tenant::"acme" |
Why this combination
is its own problem.
Most demand projects stall at data access. This one does not, because Lightspeed already exposes sales transactions, inventory counts, customer profiles through an API Ward reads directly.
What Ward has eyes on.
Ward pulls from sales transactions, inventory counts, customer profiles from Lightspeed Retail on a read-only connection. Nothing is written back, and your POS configuration does not change. Lightspeed stays the system of record.
The demand model runs daily, not on a reporting calendar. It detects the pattern, explains the cause, and attaches a recommended action before the number reaches a review deck.
What the first 90 days
actually look like.
-
01
Week 1: connect
Read-only credentials to Lightspeed Retail. Ward reads sales transactions, inventory counts, customer profiles and starts building baselines. First daily cards land inside 48 hours, before baselines are stable, so you can see the shape of the output early.
-
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.
-
03
Weeks 4 to 12: operating rhythm
Daily 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
Impact metrics with Lightspeed
Data lake enrichment
Ward enriches Lightspeed data with: Sales transactions, Customer profiles, Weather & events, Competitor data, Demographic data
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.
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.
Related solutions
See what demand problems Ward catches.
Root causes, not just alerts. See it on your data.
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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.