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Success Stories

In the following sections, we will learn more about the following success stories:

📄️ 1mg Prod2vec

Gurgaon (India) based 1mg is an online pharmacy and healthcare platform that offers medicines, lab tests, and doctor consultations. Launched in 2013 as Healthkartplus, 1mg initially focussed on the alternative medicine space with AYUSH products. Over the years, it rebranded itself as 1mg which is an online pharmacy and healthcare platform that offers medicines, lab tests, and doctor consultations. Today, 1mg provides a wide range of healthcare services. 1mg also provides information on medicines. It facilitates lab tests at home. At present, the platform has about 2,000 tests and 120 verified labs listed and users can consult a doctor across 20 specialties. The company earns from its services like diagnostics, sale of medicines, preventive healthcare, and online consultations, as well as through native ads on its platform.

📄️ Etsy Personalization

Two-sided marketplaces such as eBay, Etsy and Taobao have two distinct groups of customers: buyers who use the platform to seek the most relevant and interesting item to purchase and sellers who view the same platform as a tool to reach out to their audience and grow their business. Additionally, platforms have their own objectives ranging from growing both buyer and seller user bases to revenue maximization. It is not difficult to see that it would be challenging to obtain a globally favorable outcome for all parties. Taking the search experience as an example, any interventions are likely to impact either buyers or sellers unfairly to course correct for a greater perceived need.

📄️ Santander Banking Products

The goal of the bank is to predict which new products customers will purchase. The data starts on 2015–01–28, and has monthly records of the products each customer has, such as a credit card, savings account, etc. In addition, the dataset also records user personal data such as average income, age, gender, and so on. The monthly statistics are provided until 2015–05–28. Finally, the model predicts which additional products a customer will start using from the following month, 2016–06–28. Thus, the dataset spans 17 months from 2015–01–28 to 2016–05–28, and the output set contains only the timestamp corresponding to 2016–06–28. Models are therefore trained on sequences of 16 months to predict products acquired on their respective last month.

📄️ Scribd Real-time

Transformer based model architecture can be applied to recommendation applications as well but recommendation problems are a bit more complex than NLP domain so it needs to be adapted according to the business needs. Therefore, instead of predicting next word based on the past sequence of words, at Scribd, we are interested in predicting what user would like to read next based on rich user interaction history with multiple types of documents and multiple types of interactions, where position in sequence & relative time are both important factors.

📄️ The Long Tail

Here is an excerpt from the book The Long Tail by Chris Anderson: "In 1988, a British mountain climber named Joe Simpson wrote a book called Touching the Void, a harrowing account of near-death in the Peruvian Andes. It got good reviews but, only a modest success, it was soon forgotten. Then, a decade later, a strange thing happened. Jon Krakauer wrote Into Thin Air, another book about a mountain-cämbing tragedy, which became a publishing sensation. Suddenly Touching the Void started to sell again".