I've seen several feedback items here about recommendations being not exactly on the mark, and I agree with that. EXAMPLE: I'll add another example here where I was on Amazon and I was looking for "Starbucks Italian Roast Dark Roast Whole Bean Coffee, 12 Ounce (Pack of 6)" and the recommendation was for "Fivesso Relax Me Coffee Soaps: 3-Pack" POSSIBLE CAUSE: What this shows me is that there is a certain "product name on page" to "best matched inventory items on Ethically" search going on. Sure enough, both contain the word "coffee" but they're not the same thing. SOLUTION(s): * If the best match scorer doesn't find a good quality match, don't return anything. Business tradeoffs apply - is the cost of showing a bad match worse than showing "something"? * Change the best-match scorer. Current matcher seems to be based on string token similarity, which is a great starting point, but there are several alternatives around. Depends on dev bandwidth to swap these components out. Some excellent implementations I love are: * https://github.com/seatgeek/fuzzywuzzy * https://spacy.io/api/matcher etc
