Seasonal Adjudication

Powering a more predictable seasonal demand

Improve seasonal forecasting accuracy with machine learning and self-tuning algorithms that reduce stock outs and overstock, driving higher profits.

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Our Seasonal Adjudication Solution

Using deep machine learning, BeverageX analyzes every item in your product catalog to account for differing seasonal patterns across a host of parameters including location, category, subcategory, etc. Each SKU is assigned a custom seasonal profile based on a relative goodness of fit. All the while, self-tuning algorithms continually look for comparable data patterns and adjust to a better fit.

Combined with predictive ordering, seasonal products are replenished with precision, lowering risk and driving profitability.

Our Benefits

More Accurate Forecasts
Our machine learning algorithms continuously monitor seasonality to optimize re-order points and quantities, driving profitability.

Management by Exception
Our platform monitors all seasonal items against their forecasted demand. Any item behaving outside this predicted pattern is flagged, and an email is immediately sent to store employees to act on its behalf, driving efficiencies.

Maximized Profitability
Our solution suggests and adjudicates each seasonal item based on its added profits as compared to all items in a retailer’s catalog. This machine learning approach maximizes profits daily.

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