The passion for wine tourism has once again made wineries the center of attention. However, in a digital market where online reviews and social media comments influence as much as an in-person tasting, knowing in real time what is being said about your winery holds great strategic value.

What is Sentiment Analytics?
It is the use of natural language processing (NLP) techniques and artificial intelligence to classify as positive, negative, or neutral the opinions that visitors share on Google Reviews, TripAdvisor, Instagram, X, or wine-specialized forums. With deep learning algorithms —for example, BERT trained in Spanish— we can also break down specific emotions (joy, surprise, disappointment) and identify recurring themes (service, environment, wine quality).
Challenges Faced by a Rural Winery
Challenge | Impact |
Volume and dispersion of opinions | Difficult to manually monitor multiple platforms. |
Colloquial language and regionalisms | Local nuances may confuse generic models. |
Limited IT staff | Rural SMEs often lack data science teams. |
Loss of dissatisfied visitors | A negative comment without a response can deter future wine tourists. |
Benefits of Implementing Sentiment Analytics
- Early detection of issues: act before negative feedback escalates.
- Adjustment of the winery experience: adapt guided tours, pairings, or signage according to what your guests value most.
- Campaign segmentation: target specific promotions to profiles that show greater emotional affinity.
- Loyalty and cross-selling: turn a satisfying visit into a subscription to your wine club. Results from similar programs in the tourism sector have already shown improvements in competitiveness and visibility.
Practical Use Cases
Sentiment analytics not only provides an overview of your winery’s reputation but also enables concrete, tailored actions. Through practical use cases, emotional data can be transformed into operational decisions that enhance visitor experience, improve staff management, and strengthen brand positioning.
- Reputation alert: a dashboard notifies if the average sentiment drops below 80%.
- Emotional heat map: cross emotions with days of the week to optimize staff shifts.
- Label analysis: find out if your new organic wine generates more “local pride” than “innovative flavor”.
Recommended Tools and Solutions
Type | Examples | Notes |
Spanish SaaS | MeaningCloud, MonkeyLearn | Specific models for Spanish, integrable via API. |
Open Source | spaCy + spaCySpanSent, HuggingFace (BETO) | Zero cost; requires an expert for training. |
Social Listening | Hootsuite Insights, Talkwalker | Includes sentiment analysis and benchmarking with neighboring wineries. |
CRM-Wine | Vinipad, WineDirect | Combines bookings, sales, and customer sentiment in a single profile. |
How Can DIGIS3 Help You?
- Maturity assessment: we help you evaluate if you're ready for an AI pilot.
- Experimentation labs: test your models.
- Specific training.
- Guidance for accessing funding: guidance to find regional, national, and European funding.
Take the first step: request your free assessment via info@digis3.eu and discover how to turn opinions into business decisions.