Guac

What do they actually do

Guac provides demand-forecasting software for grocery retailers. The product ingests historical sales data and basic store/catalog details to generate short- and medium‑term demand estimates at the SKU and store (or region) level. Users see per‑SKU forecasts, confidence signals, and at‑risk items in a web dashboard and can export tables or suggested order quantities.

Day to day, inventory planners and category teams load data (often via CSV or a simple integration), review forecasts, make adjustments for promotions or local events, and then push or copy recommended orders into their existing systems. Early deployments are typically cloud‑hosted, with a focus on getting reliable sales feeds in, surfacing clear forecasts, and helping teams reduce stockouts and waste without changing core IT systems.

Who are their target customer(s)

• Inventory planner at a regional grocery chain: Spends hours reconciling spreadsheets and sales exports to build next‑week orders; still gets surprised by stockouts or excess perishables because short‑term demand patterns aren’t visible or reliable.
• Category manager / buyer: Can’t reliably predict how promotions or assortment changes will shift demand, leading to missed sales during promos or leftover, unsellable inventory afterward.
• Store operations lead or store manager: Deals with same‑day or next‑day stockouts and waste without clear, store‑level demand signals to guide timely reorders.
• Central procurement / purchasing lead: Must balance supplier lead times, case packs, and MOQs against uncertain demand, causing emergency rush orders or oversized purchases that raise costs.
• Head of supply chain / COO (small chain): Relies on manual, error‑prone processes and lacks easy ways to measure forecast accuracy or ROI, making it hard to reduce spoilage, labor, and carrying costs.

How would they acquire their first 10, 50, and 100 customers

• First 10: Founder‑led, hands‑on pilots with 8–12 regional grocers using CSV or simple API ingest; run short paid pilots with a clear KPI (e.g., fewer stockouts or lower waste) to convert the earliest paid accounts.
• First 50: Codify a repeatable pilot playbook and case studies; hire 1–2 vertical sales reps to run targeted outbound to similar chains and work regional grocery trade events to drive warm deals.
• First 100: Productize onboarding with connectors and a self‑serve tier for small chains; add reseller/connector partnerships with POS vendors/wholesalers and use ROI content and marketplaces for steady inbound while CS expands within accounts.

What is the rough total addressable market

Top-down context:

TAM is the annual spend by grocery retailers on demand‑forecasting and replenishment software. Practically, it’s the number of target grocery stores or chains multiplied by the annual price per store or per chain.

Bottom-up calculation:

Example per‑store model: assume ~40,000 target U.S. grocery locations; at a mid‑market price of ~$3,600 per store per year and 10% adoption, that implies ~$14.4M in reachable ARR. Early stages might be smaller (e.g., 2% adoption at $600/store ≈ $0.48M), and long‑term expansion across geographies and higher‑touch deployments could push into hundreds of millions.

Assumptions:

• ~40,000 addressable U.S. grocery locations (to be verified).
• Pricing bands between ~$600 and ~$12,000 per store per year depending on service level.
• Adoption scenarios ranging from ~2% (early) to ~20% (mature, multi‑country).

Who are some of their notable competitors

• Shelf Engine: Forecasting and automated purchase orders for perishable grocery items; competes on perishable accuracy and auto‑ordering workflows.
• RELEX Solutions: Enterprise retail planning for grocery (forecasting, replenishment, supply rules); heavier system aimed at larger chains.
• Blue Yonder: Large enterprise provider of retail forecasting and replenishment used by national grocers; overlaps on store/SKU forecasting and integrated planning.
• Lokad: Probabilistic demand forecasting and inventory optimization with a technical/API‑centric approach; less focused on packaged ordering workflows.
• o9 Solutions: Enterprise AI planning platform for retailers and CPGs (demand, S&OP, supply); broader planning scope for complex, multi‑tier supply chains.