Pricing · NetSuite · VP Merchandising

NetSuite plus Ward: pricing for a VP Merchandising

Your category managers are drowning in spreadsheets. Ward flags pricing movement in your NetSuite data and explains what caused it.

Price Optimization on NetSuite, for merchandising

Your category managers are drowning in spreadsheets. Ward pulls forward the inputs that change a merchandising decision.

What price optimization does: Ward monitors price elasticity shifts in real time and recommends adjustments that protect margin without sacrificing volume.

The mechanism. Ward continuously measures price elasticity by category, tracks competitive pricing signals, and models the margin-volume tradeoff.

Setup: Ward connects via SuiteTalk REST or SOAP APIs. Token-based authentication. Read-only access to your NetSuite instance.

What you get

  • Category-level price sensitivity
  • Competitive price monitoring
  • Margin-volume tradeoff modeling
  • Real-time elasticity measurement
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"
Pricing on NetSuite data, live product demo.

What Ward has eyes on.

The pricing model runs daily, not on a reporting calendar. It flags the pattern, explains the driver, and attaches a recommended move before the number reaches a review deck.

Ward reads straight from sales orders, inventory, purchase orders from Oracle NetSuite on a read-only connection. Nothing is written back, and your ERP configuration does not change. NetSuite stays the system of record.

Why this combination
is its own problem.

Oracle NetSuite was built for transactions, not for merchandising decisions. The data is right there and it is in the wrong shape. Ward reads sales orders and inventory and rewrites them as a decision.

What the first 90 days
actually look like.

  1. 01

    Week 1: connect

    Read-only credentials to Oracle NetSuite. Ward reads straight from sales orders, inventory, purchase orders 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: steady state

    Ward hands back cards daily, each with what caused it and the next step. Volume settles at a level a single person can read over coffee. The measure of success is not how many daily cards arrive, it is how many get acted on.

How Ward connects to Oracle NetSuite

Ward integrates with NetSuite SuiteCommerce, inventory management, and financials. Mid-market retailers get enterprise-grade insight cards.

Setup: Ward connects via SuiteTalk REST or SOAP APIs. Token-based authentication. Read-only access to your NetSuite instance.

Data Ward reads from NetSuite

Sales orders
Inventory
Purchase orders
Customer records
Financial summaries
Item fulfillment

Impact metrics with NetSuite

Inventory Accuracy
Discrepancies reconciled live
POS and fulfillment data cross-checked against NetSuite counts.
Order Fill Rate
Stockouts preempted
Demand forecasting layered onto NetSuite purchase orders.
Gross Margin
Margin erosion flagged
Pricing drift and vendor cost creep caught across financials.
Cash Conversion Cycle
Days of supply reduced
Demand-inventory alignment frees tied working capital.

Data lake enrichment

Ward enriches NetSuite data with: Sales orders, Weather & events, Customer segments, Vendor performance, Market pricing data

Your category managers are drowning in spreadsheets.

Pain points
  • ×Promo planning still runs off last year's playbook
  • ×Assortment reviews happen quarterly when they should happen daily
  • ×Price changes chase the market a week behind it
  • ×No visibility into true cannibalization across categories
  • ×Vendor negotiations lack real-time sell-through evidence
How Ward helps
  • Insight cards flag promo cannibalization the day it happens
  • Assortment gaps and whitespace opportunities surface automatically
  • Price elasticity shifts detected before margin erosion compounds
  • Category-level performance cards replace manual spreadsheet reviews
  • Vendor scorecards generated from actual fill rate and quality data

Retailers lose an estimated $300B+ annually to suboptimal assortment and promotional decisions. Source: McKinsey & Company

Frequently asked questions

Ward connects via SuiteTalk REST or SOAP APIs. Token-based authentication. Read-only access to your NetSuite instance. Data points include: Sales orders, Inventory, Purchase orders, Customer records, Financial summaries, Item fulfillment.

Your category managers are drowning in spreadsheets. Ward solves this with automated insight cards: Insight cards flag promo cannibalization the day it happens. Assortment gaps and whitespace opportunities surface automatically. Price elasticity shifts detected before margin erosion compounds.

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 pricing 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