Nowadays, whiskey lovers form communities on different forums such as Reddit (e.g. there are 172k members on /r/whiskey, 140k members on /r/Scotch), reviewing and discussing whiskey. These become a valuable data source for whiskey sellers to understand the customers' views on their products.
We, Whiskey Lens, attempt to use Natural Language Processing to understand the sentiment of these reviews, and scores each product by each taste category such as Sweetness, Spiciness, Fruitiness, Smokiness, as well as an overall score. Providing these data to whiskey sellers would allow them to understand if they are making the whiskey they want to make.
Take Erik and his distillery as an example. He wanted to make a single malt whiskey that is sweet but not smokey. After launching the product, he went on Reddit to see if anyone is talking about his whisky. Reading a few threads, he saw a wide range of comments, describing his whisky with words such as "dark chocolate", "caramel", "dried fruit". Erik wishes to further understand what his customers think. Therefore, he decided to log into the Whiskey Lens dashboard. The dashboard showed him a score of 3/5 for sweetness and 2/5 for smokiness, which gave him better insight into either modifying the current product or when making future products.
This business will be B2B subscription-based business model. The most basic subscription tier gives access to whiskey details of a limited number of their own products. Moving up the tiers, the client will have access to details of a wider range of their own products or even products of their competitors.
AI used in the whiskey industry includes using AI to create a new recipe, using ML to analyze people's flavor preferences and matches them with their perfect whisky. Researchers at Virginia Polytechnic Institute have attempted to use NLP to standardize whiskey notes. There has been no previous attempt to use AI and NLP to quantify the reviews, i.e. scoring each taste category based on comments or articles.