6. Beacons: Working with Unstructured Data

Traditional analytics platforms excel at processing structured data—numerical values, categories, and predefined metrics. However, unstructured data—such as customer reviews, call transcripts, support tickets, and social media comments—remains an untapped resource for many businesses.

Beacons are our cutting-edge mechanism that leverages Generative AI to extract insights from unstructured data, transforming raw text into meaningful, actionable intelligence.

Unlike other analytics platforms, Infinity allows users to not only analyze structured data but also extract deep insights from free-text content. This provides a powerful, competitive advantage—enabling businesses to understand customer sentiment, identify recurring themes, and uncover hidden trends that traditional analytics tools cannot capture.

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Use Case: Extracting Sentiment & Themes from Disneyland Reviews

Imagine you have a dataset named disneyland_reviews containing the following columns:

review_id	reviewer_name	date	rating	comments
1	Alice	2024-02-20	5	Loved the rides, but food was overpriced.
2	Bob	2024-02-21	3	The wait times were unbearable, but the staff was friendly.
3	Charlie	2024-02-22	2	Food was terrible, and the roller coasters broke down.
4	Daisy	2024-02-23	4	Great shows, but too crowded to enjoy properly.
5	Eve	2024-02-24	1	The worst experience! Staff was rude, food was cold, and long lines everywhere!

The Problem with Traditional Analytics

Most analytics platforms can only plot numerical ratings, such as: 📉 Average Rating Over Time 📊 Ratings by Month or Reviewer

However, these insights lack context. Why did a customer give 1 star? Was it due to bad food, rude staff, or broken rides? Traditional tools cannot extract themes or sentiment from the reviews themselves.

How Beacons Solve This Problem

With Beacons, Infinity automatically processes commentary data to extract: ✅ Sentiment Analysis (Positive, Neutral, Negative) ✅ Key Themes (Food complaints, Ride issues, Wait times, Staff friendliness, etc.)

Beacon-Generated Insights

review_id	sentiment	themes extracted
1	Positive	Good rides, Overpriced food
2	Neutral	Long wait times, Friendly staff
3	Negative	Bad food, Ride malfunctions
4	Positive	Great shows, Crowded
5	Negative	Rude staff, Cold food, Long lines

Integrating Insights with Other Data

Once Beacons process the reviews, users can: 🔗 Merge the sentiment data with structured tables (e.g., CRM or sales data) 📊 Plot trends over time (e.g., complaints about food increasing over summer) 📉 Analyze correlations (e.g., do negative reviews correlate with staff shortages?)

For example, if you merge the review insights with CRM data, you can see if unhappy customers had previous complaints, lower lifetime value, or requested refunds.

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Why Beacons Are a Game-Changer

🚀 No other analytics platform on the market can automatically extract themes and sentiment from unstructured text and make that data usable in traditional BI workflows.

📈 With Beacons, Infinity users can unlock hidden insights and transform unstructured data into actionable business intelligence—without requiring manual tagging, complex NLP models, or external AI tools.

This is the future of analytics—beyond numbers, into the realm of understanding and prediction.