Using Hotel Reviews to Improve Family Travel for Children Who Need Extra Support

Those answers are rarely easy to find.

That is the problem behind my current Hotel Reviews project. I have been building a research and data workflow to identify negative hotel reviews that mention children with mental health, developmental, behavioral, or sensory-related challenges. The goal is not to call out individual hotels for isolated complaints. It is to surface patterns that may indicate where resorts could benefit from better support, clearer policies, improved staff training, or more thoughtful guest experiences.

This work is being developed in support of KindStay, an idea being shaped into a potential startup by my spouse, a PhD psychologist, and her colleagues. The team meets weekly to refine the concept, evaluate the opportunity, and move the work toward a more complete product and service offering. A marketing expert on the team is also developing the public website and brand presence.

KindStay is focused on helping hotels better navigate the real-world needs of families traveling with children who may require additional care, flexibility, or understanding. For hotels, this is both a guest experience challenge and a business opportunity: when families feel supported, they are more likely to trust the property, recommend it, and return.

My role has been as a data engineer and application developer: building the workflow that gathers, filters, organizes, and presents review data in a way the KindStay team can evaluate. The project has involved scraping and analyzing hotel review data from major travel and booking platforms, then filtering for language connected to children, kids clubs, autism, ADHD, anxiety, sensory needs, behavioral concerns, and related experiences. From there, the work requires more than simple keyword matching. A useful review signal has to be separated from noise, duplicates, unrelated complaints, and one-off situations. The real value comes from identifying whether multiple reviews point to a recurring operational issue or an opportunity for a hotel to improve.

That makes the work both technically complex and judgment-heavy. The system has to pull information from messy public review sources, normalize it, search across different language patterns, and support human review of sensitive topics. At the same time, the output has to be responsible: these are families describing difficult experiences, and hotels deserve context rather than broad assumptions based on a single review.

The current version of the project is mostly complete, with a few enhancements still underway. The next layer is focused on improving how results are grouped, prioritized, and translated into useful insights for hotels. The long-term aim is to help KindStay identify properties that may benefit from assistance improving their kids club experience and broader family support practices.

What makes this work meaningful to me is that it connects technical problem-solving with a very human challenge. It sits at the intersection of data, psychology, hospitality, and accessibility. A negative review is often treated as a reputation problem. In this context, it can also be a signal: a way to understand where families are struggling and where hotels have a chance to do better.

If KindStay can help hotels respond more effectively to the needs of children with difficulties, the impact goes beyond better reviews. It can mean less stress for parents, more inclusive vacations for children, and a stronger guest experience for resorts that want to serve families well.