(Code) Deep Learning for NLP: Predicting multi-dimensional hotel ratings

Working on making a repository of notebooks demonstrating applications of AI/ML to business problems with real datasets. This is the first installment of this series. In this notebook, I cover Neural network architecture Embedding layers LSTM Layers Attention layers Training details and model diagnostics The application is in predicting multi-dimensional hotel quality ratings (service, rooms, … Continue reading (Code) Deep Learning for NLP: Predicting multi-dimensional hotel ratings

5 principles for responding to customer reviews

First HBR now online! Much thanks to coauthors KT Manis and Alex Chaudhry for putting this concise summary of our previous JMR together. https://hbr.org/2020/05/5-principles-for-responding-to-customer-reviews The takeaways from the takeaways: Principle 1. Address a positive online review by providing a generic, short response. Principle 2. Delay responses for positive reviews. Principle 3. Respond to all negative … Continue reading 5 principles for responding to customer reviews

Sniping that WholeFoods delivery slot and other web scraping projects

Wholefoods Getting groceries delivered has been a bit of a challenge recently. I had been getting deliveries from Reading Market (through Mercado which subcontracts DoorDash(?)). Their lead times are now over 2 weeks. It appears WholeFoods is taking a different approach by releasing delivery slots at random times throughout the day. However, every time I … Continue reading Sniping that WholeFoods delivery slot and other web scraping projects

Designing an Effective Service Chatbot by Anticipating Customer Needs

If you’re anything like me, you avoid calling customer service at all costs. The anticipated pain, whether rational or not, of waiting on hold and having to deal with another human interaction is sometimes just too much of a barrier to making a phone call. I often end up using automated chat functions even though … Continue reading Designing an Effective Service Chatbot by Anticipating Customer Needs

Identifying hotel renovations using machine learning

EVENT ANNOUNCEMENT There will be a data science meetup on Weds. 3/6 at 6:30 pm. It will be located at CoWork Oasis. Dr. Gustavo Arriaga will be giving a talk/demo about identifying hotel renovations using machine learning. Topics covered include: NLP techniques (phrase modeling, topic modeling, etc.) Classification methods (Random forests, neural networks, etc.) Refreshments … Continue reading Identifying hotel renovations using machine learning