Pricing · NCR · VP Merchandising

VP Merchandising: pricing straight off NCR

Price on elasticity you can measure. Ward runs it off NCR, scoped to what a VP Merchandising owns.

How a VP Merchandising runs pricing off NCR Voyix

Your category managers are drowning in spreadsheets. Ward filters to what a VP Merchandising can act on and drops the rest.

Price Optimization. Ward monitors price elasticity shifts in real time and recommends adjustments that protect margin without sacrificing volume.

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

How the connection works. Ward reads NCR transaction data via API or data export. Real-time or batch, depending on your NCR configuration.

What it does

  • 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 NCR data, live product demo.

What Ward has eyes on.

Ward ingests POS transactions, item-level sales, tender data from NCR Voyix on a read-only connection. Nothing is written back, and your POS configuration does not change. NCR stays the system of record.

The pricing model runs on a daily cycle, not on a reporting calendar. It picks up the pattern, accounts for what caused it, and attaches the next step before the number reaches a review deck.

Why this combination
is its own problem.

Price Optimization produces a lot of output that is technically correct and operationally useless to merchandising. Ward filters on whether the finding changes a decision a VP Merchandising can actually make.

What the first 90 days
actually look like.

  1. 01

    Week 1: read-only connection

    Ward reads from NCR Voyix with read-only credentials and begins ingesting POS transactions and item-level sales. No config changes on your side. First cards arrive inside the first 48 hours.

  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 daily cards are directionally right and the thresholds are still moving.

  3. 03

    Weeks 4 to 12: steady state

    Ward delivers cards every morning, 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 daily cards arrive, it is how many get acted on.

How Ward connects to NCR Voyix

Ward integrates with NCR Voyix POS and Aloha for convenience and restaurant retail. Transaction-level data powers daypart analysis and impulse optimization.

Setup: Ward reads NCR transaction data via API or data export. Real-time or batch, depending on your NCR configuration.

Data Ward reads from NCR

POS transactions
Item-level sales
Tender data
Daypart summaries
Loyalty data

Impact metrics with NCR

Attach Rate
Adjacencies mapped per daypart
Impulse cross-sell patterns identified by time of day.
Daypart Revenue
Underperforming hours exposed
Traffic and weather data pinpoint revenue-light dayparts.
Shrinkage
Slow-bleed loss detected
POS anomaly patterns caught that periodic audits miss.
Basket Size
Bundle opportunities surfaced
Item-level sales mined for actionable upsell patterns.

Data lake enrichment

Ward enriches NCR data with: POS transactions, Weather & events, Loyalty data, Competitor proximity, Demographic 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 reads NCR transaction data via API or data export. Real-time or batch, depending on your NCR configuration. Data points include: POS transactions, Item-level sales, Tender data, Daypart summaries, Loyalty data.

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