Home Wine Business Editorial Expert Editorial Know Your Numbers: Econometric Modeling in Wine Pricing and Inventory Decision Making

Know Your Numbers: Econometric Modeling in Wine Pricing and Inventory Decision Making


Price elasticity calculations can help a winery predict how consumer demand will change for an SKU following a price adjustment.

By Nathan Hart

A data-driven decision making strategy can optimize your winery revenue and inventory depletion strategy. Data science and predictive analytics are becoming more and more instrumental in driving the decisions of the biggest companies in the world, and the wine industry is well-suited to ride that wave with the data it already has. Wineries are sitting on a gold mine of rich transactional history that can be used to understand their customers, their wine portfolio and the intersection of the two.

Why price elasticity of demand matters

In economics, price elasticity (or price sensitivity) is the percent change in demand given a percent change in price. Understanding the elasticity of demand for your products is critical to establishing your pricing strategy, and it positively impacts the profitability of your winery’s DTC businesses.

Price elasticity calculations can help a winery predict how consumer demand will change for an SKU following a price adjustment. In other words, when woven into demand forecasts, price elasticity calculations let you anticipate when you will sell out of any SKU — at any price point and any production level. Price elasticities can also be used to predict when unreleased SKUs are going to sell out, given a certain price point.

Knowing the price elasticity of your product(s) lets you tweak the price or the number of cases you send to market to achieve your depletion goals. Scenario planning with different price points and varying production levels lets you optimize what you should allocate to your direct-to-consumer market and what you should allocate to wholesale or your library program. 

The graph below illustrates how, by increasing the price of a wine by 12%, the forecasted depletion curve is extended, letting a winery adjust its remaining inventory to maximize sales.

This price adjustment lets the winery sell out stock on its expected timeline and generate an incremental $11,500 revenue for the current release.

Intelligent, data-driven decisions

Price elasticity can help in use cases beyond setting the price of a wine as well. Imagine a situation where you have a wine that’s selling out too slowly and bottling has already begun on the next vintage. You’re at risk of having excess inventory, and you’re worried that either you might depress sales of the upcoming release because you’ll have two vintages in the market or that you’ll end up with too much wine in your warehouse.

Your first instinct may be to discount the already-released vintage. Knowing how to influence consumer demand through price lets you optimize that discount, so you don’t leave money on the table or discount the actual value of the wine.

Imagine another situation, where you get an overwhelmingly positive response or a high rating on one of your wines, and it starts flying out the door. Your instinct may be to raise the price, but knowing the wine’s price elasticity lets you make an intelligent decision that keeps the wine in the tasting room (if you’d like) and/or that’s in line with your revenue goals for that wine.

One can take the use cases even further by calculating the cross-price elasticity of different SKU combinations in your portfolio to see how a price adjustment on one SKU impacts sales of another. For example, if you have a Chardonnay and a Sauvignon Blanc in the market, a higher price for one may cause accelerated demand for the other (if they’re perceived as near substitutes by your market). 

Understanding these data-driven relationships, in the context of how much has been produced and how the wines in your portfolio are currently selling, allows for more nuanced decision making.

DtC tools to grow your winery business 

With a little bit of data cleaning, econometric models can be built on top of years’ worth of your transactional history at the SKU level. You can even add other variables into these models for tighter estimates, controlling for macroeconomic indicators such as money velocity, the consumer price index, real household personal income and the like, or for market-specific factors including the number of club members you have, seasonality and the wines you are selling at any given time

As a winery owner, CFO or DTC manager, data-driven decision making and predictive analytics are no longer the future or a “nice-to-have,” but one of the most important tools in your toolkit. Price elasticity modeling can drive bottom line revenue and help you meet depletion goals for your portfolio. It also takes the guesswork out of your decision making. 

Being able to validate (or invalidate) where your price points should be or how much production you should take to market given a price point constraint will make your job a lot easier — and you can’t put a price tag on that.


 Nathan Hart

Nathan Hart is manager, consulting services at Mather Economics. Connect with him at [email protected] and learn more at www.mathereconomics.com.

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