An Open Letter to Anyone Frustrated by Social Listening

I spent nine years at top social listening platforms—Talkwalker, Brandwatch, and Crimson Hexagon. During that time, I witnessed customers drowning in data but starved for insights.

Despite all the dashboards, word clouds, and various approaches to sentiment, the social listening industry remains unable to answer two fundamental questions:

What do I need to know?
And what should I do?

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When I was offered the chance to join a small team of data scientists building a new solution from scratch—right as my wife and I were expecting our first child—I knew it was a risk. But it was also the greatest opportunity of my career. And now 18-months later that gamble has paid off.

Can you imagine a text analytics platform that doesn’t include a single word cloud? We did it.

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Dimension Labs offers an entirely new way to identify themes that are both hyper relevant and highly targeted.

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Identifying posts relevant to personal patient experiences among those with diabetes.

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We're an analytics solution that integrates with any existing social listening tool or can be used as a stand-alone solution. Here are the biggest problems we've solved: 

1. Relevant Data Only

• Automatically filter down to posts about the customer experience for any brand or topic.
• No Boolean, ever.

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2. Accurate Sentiment
• Target brand-based and entity-based sentiment.
• A more precise satisfaction rating that goes beyond “positive” or “negative.”
• Dynamic issue labels that bake sentiment into the underlying analysis, making it truly actionable.

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3. Automated Trend Detection

• Use AI to spot trends with no context window limitations
• Goal-based insights aligned with any business function; identify problems tied to the digital experience or discover emerging themes in conversations about frozen foods.

How do we do it?

We invented a new approach for analyzing unstructured text. It’s called ‘Text Dimensionality’ and the premise is simple: every piece of text contains many different aspects of meaning. 

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Moving from unstructured to structured in seconds; what patients talk about when they talk about diabetes.

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Consider the sentiment on the following example post:

“After trying this new spiced caramel latte at Dunkin Donuts I don’t know if I’ll ever go back to Starbucks again. Sooo good!”

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Dunkin Donuts - Positive

Starbucks - Negative

You need a solution that can understand sentiment from the point of view of the person doing the analysis.

We use AI to identify the meaning that is relevant to your brand, line of business, or even a specific role. The output are custom sentiment, organic themes, and actionable insights relevant to your specific needs using an automated approach that requires no keyword searches. 

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How are we fundamentally different? 

In traditional social listening, you might rely on a GPT plugin or the platform’s built-in AI—only to hit context-window limits, miss brand nuances, or struggle to both identify and track categories over time across the full dataset. 

With Dimension Labs, you can:

— Process thousands of posts in minutes—like having a human read and categorize each one.

— Automatically detect new themes and categories as they arise.
— Create a category map and track changes over time

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If you only take one thing away from this it should be this: 

The promise of our solution is simple: whatever business objective you have, we identify and rank the problems you need to address as told to you by your customers.

In this way text dimensionality is the biggest leap forward in text analytics in more than a decade. It is time to completely reimagine what’s possible.

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Yours truly,

Jason Potteiger (jason@dimensionlabs.io) 

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Learn How Dimension Labs' next-gen text analytics goes beyond traditional social listening.