Analysis of Biscuit Type Dog Treats

Data was scraped from a popular retailer of pet products using the Selenium and BeautifulSoup libraries in Python. First, individual urls were built by scraping each page of search results.  Then, using Selenium and a few try/except statements, I obtained the relevant information for each product. Selenium, a new library for me,  allowed me to easily navigate the Java based elements with differing layouts. 

There are 445 ingredients listed in the data provided, the number of unique ingredients is lower due to spelling differences. The majority are standard for processed foods but a few standout. Refined sugars, salt, and palm oil in excess can all cause digestive issues in dogs. Five treats list garlic, seven have green tea extract, and one contains yeast. These are widely considered toxic to dogs and should be avoided. 

It seems most commercial treats consist of fillers (wheat flours, animal meals, oils), enriched with different supplements, and a variety of preservatives (salt, tocopherols, BHA, sodium metabisulfite). I think we can do better for our canine friends.

To understand the costs associated with a homemade recipe, I used ChatGPT to generate a dog treat recipe for analysis. Ingredients were selected from the list of ingredients present in the data with a few criteria: they should be minimally processed, available in retail quantities, and otherwise suitable for my dogs diet. 

The findings revealed that commercially available treats tend to contain high levels of additives, fillers, and, at times, potentially toxic ingredients. Through exploring the relationships that exist within the data, I found that price does not seem to correlate to rating,  contrary to research suggesting unidimensional review systems favor perceived value over perceived quality. Additionally, I found that limited ingredient recipes are priced ~10% higher than unlimited ingredient recipes. Further looking at ratings shows that limited ingredient recipes tend to review more favorably but less often. All of this to suggest that consumers who value limited ingredient recipes are okay with paying a small premium and are generally more satisfied with their purchases. 

I used ChatGPT to generate a recipe to examine the cost of producing dog treats. This is not without issue, but after tweaking the query and resubmitting it, I had a reasonable starting point. When examining the cost of producing dog treats, I found that scaling, and scaling without excess waste, does increase profitability in my hypothetical business. There is opportunity to reduce costs through bulk or online purchasing and/or printing labels at home. Labor and utilities were not considered as part of this analysis, at this scale I don't believe this effects the outcome significantly. The quick facts of this analysis say you could prepare and package a homemade recipe for $1.07 per ounce, and with a 30% profit margin in mind, your price to the consumer rises to $1.53 per ounce. With the consumers willingness to pay more for less ingredients, I think this is a reasonable price for a wholesome and homemade product. 

While this analysis attempts a comprehensive understanding of biscuit type dog treats, I believe it could be expanded on with additional information. More granular rating and review information would allow you to better understand why products are getting their reviews. One could categorize ingredients and attempt to compare 'natural' options versus their counterparts, brands and manufacturers could be compared against one another. There's always more questions to be answered. 

In conclusion, this analysis has given me valuable insights into the dog treat industry. It's allowed me the opportunity to understand what is in available products, how they're are viewed, and how a homemade product may be able to compete with what is currently available. It's encouraging to see that this could be a viable side hustle or a future opportunity for entrepreneurship. Next step? Recipe testing.