Imagine you could poll your entire market in real time

That’s the essence of what we do at Stock-Warning. Instead of relying only on delayed sales feedback or partial data from distributors, we create digital representations of real consumers in every micro-region—whether that’s a municipality, a zip code, or even smaller clusters.

These digital consumer models continuously capture and simulate real-time demand fluctuations for each SKU. By aggregating millions of individual signals, we can build an always-on, hyper-local picture of what consumers want, when, and where.

When combined with SKU-level delivery data (supply), this demand intelligence lets us anticipate where and when shelves are most at risk. The result: a living early-warning system that sees demand shifts before they show up in sales numbers.

It’s like having a constant market survey, but powered by AI—faster, more granular, and infinitely scalable.

FAQs

  • How Do We Ensure Accuracy?

    Continuous Model Training
    Our models are constantly retrained with proprietary survey data collected in every market where we operate. This ensures that digital consumer demand signals always reflect real-world behavior.

    Implementation Validation
    During onboarding, we assess and calibrate the demand module’s accuracy against your actual sales and delivery data, so the system is tailored to your reality from day one.

    Proven Results with Clients
    Multiple client case studies demonstrate measurable improvements in early stock-out detection and resolution, validating the reliability and impact of our approach.

  • How Do We Get Real-Time Data?

    Continuous Social Listening
    We capture signals from social media platforms where consumers express preferences, trends, and purchasing behavior in real time.

    External Real-Time Sources
    Beyond social media, we integrate multiple live data feeds — from local events to seasonality factors — to enrich our demand models.

    Daily Demand Signals
    These signals are aggregated and updated every day, ensuring that our models reflect the most current consumer behavior and market shifts.

  • How Difficult Is It to Implement?

    Fast and practical. Proof of Concepts are usually up and running in just 3 months.
    The main factors that determine speed are:

    Data Readiness – how quickly store- and SKU-level delivery data can be shared.

    Priority Alignment – ensuring commercial, logistics, and IT teams are aligned on objectives.

    With the right preparation, implementation is smooth and quick—delivering measurable results in weeks, not years.

  • How Much Does It Cost?

    Low Setup Costs
    Implementation costs depend on the scale of the study, but are orders of magnitude lower than installing hardware or equipment inside retailers.

    Recurring Subscription
    Once the model is live, clients simply pay a recurring fee to:

    Update demand information in real time.

    Run the Stock-Warning algorithm continuously.

    This model keeps costs predictable, transparent, and far below traditional solutions, while scaling effortlessly across regions.