Personalized Pricing through AI

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The prices of wine bottles are extremely variable. If the pleasure of tasting a wine does not always depend on its price, some criteria determine the cost: the appellation, the domain, the ageing potential, the production method, the critics… In addition to the factors that influence the price of a bottle of wine, there are many particularities, notably exogenous factors.

The first article explains the major economic and societal challenges of artificial intelligence (AI) in the wine industry. We will then focus on the likely impact of AI on value transformation, more commonly known as disruption. David will then examine the contributions of AI on professional pricing in wine distribution. Finally, we will reflect on the impacts of wine price personalization for consumers at the dawn of AI-managed dynamic pricing.

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A radical change in the relationship between retailers and customers

Dynamic pricing uses a consumer’s data to predict what they are willing to pay. The days of one price for all are increasingly a thing of the past. The price tag is still in place in stores, but as the retail industry moves away from fixed prices, online companies are leading the way.
In 2016, Amazon unveiled its grocery ideal with Amazon Go. Customers sign in at the door and download an app to shop. Sensors and cameras detect every item shoppers put in their cart and the app automatically charges them when they leave the store. Note that Amazon Go customers were identified by the app before they even started shopping, which could allow such algorithms to personalize prices in the future.

Until now, these variations were dictated by fundamental market logic: an algorithm detects a peak in demand and raises the price. But new developments in artificial intelligence (AI) are radically changing the relationship between retailers and customers. In addition to supply and demand, the maximum price the consumer is willing to pay is also becoming an important factor.
Similarly, online retailers are beginning to use the data they’ve collected to determine how well people respond to special offers. They can then adjust their pricing strategies accordingly.

The subject is complex since it includes biases in the recommendations: if a platform only considers the average value of a product, it ignores the risk of dissatisfaction. If it is guided only by the objective of immediate satisfaction, it will remain cautious and will not expose users to discoveries.
Currently, the technology giants are racing to develop the perfect virtual assistant. The goal is to persuade consumers that they can save time and energy by delegating mundane tasks like ordering groceries to these artificial agents. The more consumers become dependent on virtual assistants, the more responsibility the algorithms behind these AI elements will have to negotiate with the dynamic pricing algorithms of retailers and other businesses.

The end of impulse buying. When artificial agents will be able to negotiate with each other

There could be positives: unlike humans, who fall prey to impulse buying, virtual assistants could provide rational discipline in their purchases. On the other hand, the more complex the interaction between artificial agents becomes, the more opaque the results may be.
An interesting side effect of dynamic pricing is that it reminds us of the moral dimension inherent in prices and pricing strategies. Fixed prices are a surprisingly recent invention, linked to the rise of the department store. They were adopted because they had obvious accounting advantages. Until the advent of online sales, this egalitarian component of shopping was never really challenged. Dynamic pricing undermines this moral tradition. A delivery service, for example, may decide to charge you more for a delivery in an upscale neighborhood or in a sensitive suburb.
While it is true that AI can be used to personalize prices to serve customers, let’s keep in mind that price personalization can be a harmful practice if it is based on exploitation, distortion, or exclusion.

This concludes David’s chronicles on the impact of artificial intelligence on the wine economy.