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:

The specific traffic and sales value of guest sentiment improvement
What specific factors are causing guest sentiment to be at its existing level
How exactly you can improve guest sentiment
Financial impact you can expect when you do improve guest sentiment

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.

Turn on a dime: What’s hurting your business? How is that promotion performing? Surface answers quicker.
Future proof: Our model – like the market – is constantly evolving. It keeps you ahead of trends and provides context, faster.
Focus on what matters: Accurately size dollar value initiatives, only spend time and resources on things that impact.

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:

25 million
restaurant-specific reviews
3 million
annotated restaurant data points
15+ years
historic restaurant data
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.

A visual timeline of five customer reviews with corresponding insights extracted. The reviews cover various experiences, like perfect soup temperature and warm beer, with insights highlighting service and atmosphere. Ratings and icons from review platforms are shown.

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

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?
A speaker with long blonde hair (Mary Hamill), dressed in a black blazer and jeans, stands on stage at the Best Practices Conference. They hold a microphone and gestures while smiling in front of a blue and yellow conference backdrop.

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.

Get a Demo

See restaurant-trained analytics in action