Lost Retail Sales workflow in Alloy.ai
Gain a holistic understanding of lost sales across your entire omni-channel supply chain and compare performance across retailers and time horizons to answer complex questions and make SSO recommendations to buyers.
Isolate exactly where lost sales stem from and explore recent low stock issues and upcoming out-of-stocks (OOS) at retail to take near-term corrective action to meet demand and prevent lost revenue.
Set up alerts that proactively show you when WoS for specific SKU / location combinations are predicted to be low based on open orders and in-channel inventory so you can start taking action before sales are at risk.
Deep dive into an industry best-practice guided workflow to discover areas where you’re missing out on retail sales and begin addressing root causes.
Questions you can answer with the Lost Sales workflow
- Which products at which retailers are losing sales due to out-of-stocks?
- Where is the POS $ impact the greatest? Where should I take corrective action?
- What was the in-stock % for a particular product last week?
Key insights on lost sales
A consumer electronics company improved On-Shelf Availability (OSA) by an average of 1.35% year-over-year, roughly $8.3M/yr at dealer cost.
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Frequently Asked Questions
Alloy.ai provides a guided workflow that enables brands to isolate the exact causes of lost sales, such as recent low stock issues and upcoming out-of-stocks (OOS) at retail locations. This detailed analysis allows for near-term corrective actions to meet demand and prevent revenue loss.
Brands can set up alerts within Alloy.ai that notify them when weeks of supply (WoS) for specific SKU/location combinations are predicted to be low, based on open orders and in-channel inventory. These proactive alerts enable brands to take action before sales are at risk, ensuring better inventory management and customer satisfaction.
Alloy.ai’s Lost Sales workflow assists brands in determining which products at which retailers are losing sales due to out-of-stocks, identifying where the POS dollar impact is greatest to prioritize corrective actions, and assessing the in-stock percentage for particular products over specific time periods. These insights support data-driven decision-making to enhance sales performance.