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Travel Appeal is gearing up for FoodHotelTech in Paris, so naturally we dove into the data to learn more about the French capital. By implementing our machine learning algorithm and semantic analysis methods, we investigated 8 of the top 10 Parisian boulangeries found in the Bonjour Paris blog post: And the Winner Is… The Best Baguette in Paris 2018.
After selecting our top 8 Parisian bakeries, we analyzed the total amount of feedback, average customer sentiment (satisfaction level), and reviewer demographics. We then compared satisfaction levels between locals and non-locals and uncovered the most appreciated aspects of each bakery.
We analyzed the following boulangeries to uncover the insights from customer feedback.
The takeaway we found to be the most interesting was the general satisfaction compared between locals and non-locals. Download the infographic below to discover the insights between the French and foreigner sentiment levels.
Deeply understanding customer satisfaction is crucial for any business manager. Knowing the sentiment levels between demographics is a competitive advantage any business can leverage. By personalizing the customer experience based on your client’s demographics and sentiment, your business can generate more positive reviews and feedback to climb the rankings against competitors.
Travel Appeal combines data science, artificial intelligence and human experience to reshape business strategies. Processing millions of data from different sources, we uncover customer behaviours - online and offline.
Interested in learning more about what your customers are saying? Get a free, customized report today! Improve your communication strategies, increase customer sentiment, welcome more clients and boost sales!