Retail & Online Commerce
Forecast demand at the SKU-store-week level, personalize every touchpoint through your CDP, and connect Shopify, Salesforce Commerce Cloud, or your OMS into one coherent operating picture that merchandising, supply chain, and marketing all trust.
What holds retail leaders back
Inventory forecasting still breaks when promotions, seasonality, and channel mix shift faster than spreadsheets can absorb. NRF data shows US retailers lose an estimated $82 billion annually to inventory distortion — stockouts and overstock combined. The signals live across merchandising plans, POS feeds, ecommerce platforms, and marketplace dashboards that never reconcile in time for a single forecast the whole network can execute against.
Personalization at scale sounds straightforward until catalog depth, loyalty tiers, regional assortment, and marketplace dynamics enter the picture. Running on Amazon, Walmart Marketplace, and DTC simultaneously means three different pricing strategies, three different margin structures, and recommendation logic that has to respect all of them without eroding GMROI or cannibalizing your own channels.
Supply chain visibility rarely fails at a single node. It fails in the gaps between PO systems, WMS platforms, 3PL portals, and carrier EDI feeds where exceptions hide until they hit OTIF metrics and the customer. Retailers managing hundreds of vendors and multiple DCs need exception-based alerting, not another dashboard to monitor.
Customer experience fragmentation follows naturally: marketing in Klaviyo or Braze, service in Zendesk or Gladly, fulfillment in your OMS — each owns a slice of the journey yet none sees the full story. That fragmentation shows up as repeat contacts, inconsistent answers, and churn that looks random until you unify behavioral, transactional, and operational signals in one customer view.
Where Birdeye Labs plugs in
Demand Forecasting
SKU-store-week prediction models that ingest POS sell-through, promotional calendars, weather, and marketplace velocity so planners can rebalance allocation before the next replenishment cycle. Output feeds directly into your ERP or planning system to improve weeks-of-supply accuracy and reduce markdown exposure.
Personalization
Recommendation models integrated with your CDP — Segment, Bloomreach, or mParticle — that optimize for GMROI, not just click-through. Content ranking tuned to catalog constraints, margin targets, and loyalty tier rules with A/B testing baked into the deployment pipeline so you measure lift, not guesses.
Supply Chain
Inbound exception detection across PO, ASN, and carrier EDI feeds so merchants know about delays before they hit OTIF. Outbound allocation optimization across DCs and ship-from-store nodes that balances delivery speed, shipping cost, and inventory position in real time.
Customer Intelligence
Sentiment analysis across reviews, NPS surveys, and service transcripts in Zendesk or Gladly. Churn prediction combines browse behavior, order cadence, return patterns, and support history so retention teams intervene with the right offer through the right channel at the right margin.
Plan a retail AI roadmap
We start with the workflows that move GMROI, fill rate, or customer lifetime value in your network, then design models and integrations your merchandising, supply chain, and marketing teams will actually run in production. If you are modernizing forecasting, personalization, or omnichannel operations, we should talk.
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