Demand Sensing
Near-term signal detection that updates the forecast before decisions are made
Demand OS ingests daily POS, marketplace, and order signals and adjusts the one-to-four-week forecast automatically — before replenishment decisions are made, not after the week closes.
Book a Demo24 hrs
Time to detect and flag an organic demand spike in order data
Daily
Signal refresh cadence vs the industry-standard weekly planning cycle
1–4 wks
Near-term horizon sharpened with real-time signals before the weekly review
What does demand sensing AI software do?
Demand OS ingests daily POS, marketplace, and order signals and adjusts the one-to-four-week forecast automatically. Replenishment decisions reflect what is actually selling right now — not what sold last week.
The Problem
Why weekly planning cycles miss what already happened
Weekly forecasts stale before Monday
Ecommerce demand can shift 30% in a single day during a promotion or viral event. A planning process that runs on weekly cycles cannot respond fast enough to prevent stockouts or excess before the window closes.
Channel signals scattered across platforms
Demand data from a Shopify storefront, Amazon Seller Central, wholesale EDI, and retail POS lives in separate systems updating at different intervals. Without a unified daily feed, the near-term forecast always lags the actual sales picture.
Promotional lifts detected in the rearview
The point of a promotion is to move inventory. If the sell-through spike is not visible in the planning system until the weekly refresh, replenishment cannot respond fast enough to sustain momentum or prevent overstock on the tail.
Replenishment orders based on last week's reality
Purchase orders generated from a baseline that is seven days old carry the demand picture of last Monday. In fast-moving categories, that gap between signal and decision is where margin is lost.
The Capability
How Demand Sensing sharpens the near-term baseline
SENSING CAPABILITY
Daily ingestion from all demand channels
Demand Sensing connects to POS systems, marketplace feeds (Shopify, Amazon Seller Central, Walmart), retail EDI, and order management systems. Data is pulled daily on a configurable schedule. The near-term forecast updates without a planner doing anything.
Learn more →SENSING CAPABILITY
Statistical anomaly detection and planner alerting
The system compares daily order flow against the baseline and flags statistical deviations within 24 hours. Spikes above a configurable threshold surface as an exception with the revised near-term forecast and a days-of-cover calculation.
Learn more →SENSING CAPABILITY
Near-term signal feeds inventory optimization
The sharpened one-to-four-week forecast from Demand Sensing flows directly into Inventory Optimization's replenishment recommendations. When demand is accelerating, the system surfaces a re-order alert before inventory runs out.
Learn more →In Practice
A DTC apparel brand avoids a stockout during a viral social moment
The Situation
A direct-to-consumer apparel brand sold across its own Shopify storefront and Amazon. Demand for one SKU spiked 4x within 18 hours following an organic social media mention. The brand was running on a weekly planning cycle and had 3 days of cover remaining when the spike began. The planning team had no visibility into the intra-week demand acceleration.
What Demand OS Did
Demand Sensing detected the statistical anomaly in Shopify order data within 24 hours of the spike beginning. An exception alert was surfaced with the revised near-term forecast and a days-of-cover calculation showing a stockout within 48 hours. The system identified available inventory at a 3PL facility that could be reallocated to online fulfilment. The AI Copilot answered the team's question — "what SKUs are at risk right now?" — in under two minutes.
The Outcome
The brand avoided a stockout by reallocating 3PL inventory and expediting a partial replenishment order. Lost sales from the event were under 3% of potential volume. The same exception template was used to pre-position inventory for a planned influencer partnership two months later — converting a reactive response into a planned playbook.
Key Metrics
What teams gain from daily signal visibility
Demand sensing AI software earns its keep the day a spike hits. Demand OS reports all three numbers continuously, from the pilot's first cycle.
24 hrsTime to detect and surface an organic demand spike from order data30%Ecommerce demand can shift in a single day during a sale or viral event4–5 wksFastest go-live time for ecommerce pilots with daily signal integration
Related
Explore more Demand OS capabilities
Demand OS for Ecommerce
Real-time signals, returns-adjusted forecasting, and flash-sale inventory positioning.
Learn moreDemand OS for Retail
Seasonal forecasting, promotional lift modeling, and store-level replenishment.
Learn moreDemand OS vs o9 Solutions
Planner-first design vs an enterprise IT platform, with published positioning up front.
Learn moreSee how demand sensing capabilities differ across vendors in our guide to the 5 best AI-powered demand forecasting tools.
Frequently Asked Questions
Demand Sensing questions answered
What data sources does Demand Sensing connect to?+
Demand Sensing has native connectors for Shopify, Amazon Seller Central, Walmart Marketplace, TikTok Shop, and major retail EDI formats. It also ingests daily order and shipment data from ERP systems including SAP, Oracle, and NetSuite. For platforms not on the standard connector list, a flat-file ingestion path is available with no custom development required.
How does the system decide what counts as a significant demand shift?+
Anomaly detection uses a configurable statistical threshold — by default, a deviation more than two standard deviations from the rolling baseline triggers an alert. Thresholds can be set at the category, brand, or SKU level. High-velocity SKUs and seasonal items can have separate sensitivity settings to reduce false positives during expected peak periods.
Does Demand Sensing replace the AI Forecasting Engine or work alongside it?+
Demand Sensing works alongside the AI Forecasting Engine. The forecasting engine produces the statistical baseline for each SKU. Demand Sensing takes that baseline and sharpens the one-to-four-week near-term horizon using live signals. The two capabilities are connected — near-term accuracy improvements from Demand Sensing feed back into the model evaluation loop for the next training cycle.
How quickly can Demand Sensing be configured for a new channel?+
For supported connectors, channel configuration takes one to three days including authentication, historical backfill, and validation against the existing baseline. For custom or legacy channels using the flat-file path, configuration takes three to five days depending on data quality. Most ecommerce pilots are live with Demand Sensing running within the first two weeks.
Can Demand Sensing handle promotional events differently from organic demand?+
Yes. Promotional event windows can be configured with expected uplift multipliers so the anomaly detection system distinguishes between a planned promotional spike and an unexpected organic demand shift. During a planned promotional window, the alert threshold adjusts to avoid flagging expected volume as an anomaly. Unplanned spikes outside the promotional window still surface as exceptions.
Get Started
Ready to sense demand in real time?
Talk to a demand planning specialist and see Demand Sensing live on your own channel data. You leave with accuracy benchmarks, a scoped pilot plan, and published pricing — all in one conversation.