Guest Intelligence: Restaurant-Trained Analytics
Guest Sentiment Analytics Built Exclusively for Restaurants
Why You Should Care About Guest Feedback
Simple: tangible traffic and sales impact.
Customer feedback – and specifically how you show up online – has a clear correlation on your bottom line. But ensuring you prioritize action for predictable revenue-targeted outcomes can seem like an impossible task.
Like the aggregated numbers in the chart above, the Black Box Intelligence model tells you:
Get Led Where You Need to Go
How Restaurant-Trained Analytics Lead to Guest Sentiment Improvement
We help you move faster by telling you where you need to go, how to get there and why quicker than anyone else.
Where you need to go:
We provide a clear breakdown of why your ratings are what they are. Pinpoint exactly what’s holding you back.
How to get there:
We go to a level of detail others cannot. Know exactly what you need to do to drive impactful change.
Why:
30 years sales and traffic benchmarks project exact improvement to expect from changes you make.
Find Out More
Learn how we can convert the feedback you receive into traffic and sales.
How it’s Faster and Why This Matters
Restaurant Specificity Means Our Model Adapts to Industry Trends and Your Initiatives Quicker.
Restaurant-Trained Analytics
What Does “Restaurant Trained” Mean? And Why Does it Matter?
No One Does it Like Us
Context Over Keywords: How Our Model Guarantees Accuracy
Quality over quantity: our model is trained on millions of guest feedback submissions exclusively about restaurants over a period of 15+ years. But the key is how it’s been built and developed over time.
- Focused: The entire process of building our model has been consistently underpinned by the goal of solving the same problem: making restaurants more successful.
- Unique: We are the only vendor that has the dataset we do – 25 million restaurant-specific reviews and 3 million annotated data points – which means no one can monitor the market as we do.
- Specificity: Model has been taught exactly what to look for by examining nothing but restaurant feedback. Goes way deeper than keywords.
- Proprietary: Model combines the best of Large Language Models (LLM) (i.e. ChatGPT) with proprietary BBI restaurant data, which – again – means what goes in is specific, focused and clean.
Our restaurant-trained model has been perfected with:
Technically Speaking…
How We’ve Built Our Restaurant Customer Sentiment Model
Restaurant-Trained Analytics In Practice
Example in Action: Temperature
“Temperature” is a completely context-specific concept in the restaurant world. Here’s how our analytics engine ensures every piece of customer feedback triggers accurate analysis.
Drill Down for Context
Read Every Review. Or Don’t.
The model is designed to surface all the key things you need to know to improve how you run your business.
But it also allows you to deep dive into every issue right down to exactly how guests talk about it in the feedback they provide.
So you don’t need to read every piece of feedback you receive to steer your restaurant along the right path, but you can if you want.
Questions to Ask
Checklist
Checklist
When assessing analytics models, ask:
- Does an underlying engine power your model or is it proprietary?
- What was the goal and intent when building it?
- Was it developed for a specific type of feedback (e.g. restaurant feedback)?
- How accurate is the model? How is accuracy measured?
- How does the model predict impact?
- What industry knowledge does the team who build the model have?
- What level of detail is available out of the box?
Artificial Intelligence
Is it AI?
“AI” is thrown around a lot nowadays. Technically, our restaurant-trained analytics model is Natural Language Processing (NLP), which is a specific strand of AI.
