Artifacts Gallery | Dimension Labs

Text Dimensionality

Structure for the 95% of data that has none

Why traditional B.I. tools can't analyze Unstructured Data

Exploring the intersection of artificial intelligence and creative design systems. How machine learning algorithms are reshaping the future of digital product development and user experience optimization.

How we help you work with Unstructured Data

We automate the extraction pipeline — no hand-tagging, no prompt engineering per project. Dimensions aren't fixed: you can adjust the underlying logic as needs evolve, and those changes propagate consistently across your full dataset.

How Text Dimensionality is used

Dimensions are the schema layer for unstructured data. Once text has dimensions, they behave like any structured field — queryable, filterable, joinable — which is what makes Artifacts (reports, dashboards, and monitors) possible on top of raw conversations. Every output stays traceable to the source record.

Why traditional B.I. tools can't analyze Unstructured Data

Structured data has shape: rows, columns, schemas. Unstructured data (calls, chats, tickets, surveys) has none — no consistent fields to filter, trend, or build metrics on. We call that missing structure text dimensionality: the stable attributes inside every conversation, waiting to be extracted.

How we help you work with Unstructured Data

We automate the extraction pipeline: no hand-tagging, no prompt engineering per project. Dimensions aren't fixed: you can adjust the underlying logic as needs evolve, and those changes propagate consistently across your full dataset.

How Text Dimensionality is used

Dimensions are the schema layer for unstructured data. Once text has dimensions, they behave like any structured field (queryable, filterable, joinable) which is what makes Artifacts (reports, dashboards, and monitors) possible on top of raw conversations. Every output stays traceable to the source record.

What we're learning about language

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Examples of dimensions being used

Examples of dimensions in use

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Dimensions

All

Sentiment & Emotion

Intent & Journey

Experience & Operations

Product & Features

Pricing & Value

Revenue & Growth

Risk, Trust & Compliance

Competitive & Market

People & Segmentation

AI & Automation

Verbatim & Summaries

How strongly the person feels, independent of whether it's positive or negative — surfaces your highest-passion and highest-risk voices.

Grievance Severity

The stakes behind a complaint — from mild annoyance to serious harm — as framed by the customer.

Overall Sentiment

The true feeling expressed in the words themselves — extracted from the prose, not the star rating or survey score.

Predicted CSAT

A modeled 1–5 satisfaction score inferred purely from the qualitative text of an interaction.

Predicted NPS Band

The likely promoter / passive / detractor classification read from language, even when no score was given.

Customer Intent

The primary reason the person reached out or showed up.

Effort Level

How hard the customer had to work to get value or resolution.

First-Time vs. Repeat

Whether this is a new or returning customer, read from the narrative rather than a CRM flag.

Interaction Type

Whether the exchange is a complaint, question, praise, cancellation, or sales inquiry.

Lifecycle Stage

Where the person sits in their journey with you — prospect, new, onboarding, active, at-risk, or churned.

Purchase Motivation

The dominant reason the customer bought or visited.

Resolution Status

Where the issue stands by the end of the interaction — resolved, pending, or unresolved.

Transaction / Visit Type

The kind of transaction the text is about — sales vs. service, purchase vs. return, dine-in vs. delivery.

Use Case

The specific business or personal use case the person references.

Accessibility & Courtesy

How well specific needs were accommodated and the courtesy shown.

Atmosphere & Ambiance

The energy, mood, and sensory experience of the venue.

Core Quality Verdict

The customer's assessment of the core product or offering — food, course, device reliability.

Digital & App Experience

Experience with the app, online ordering, or self-service surfaces not visible in structured data.

Facility & Cleanliness

The physical condition and cleanliness of the space.

Order & Service Accuracy

Whether the order or request was fulfilled correctly.

Primary Friction

The single most operationally important thing that went wrong.

Primary Topic

The single dominant subject of the conversation.

Service Recovery

What happened when the customer raised an issue or asked for help.

Service Speed & Wait

What the customer says about timeliness and wait time.

Staff Interaction Quality

The character of the human or service interaction, from exceptional to hostile.

Engagement Mechanic Response

How the customer reacts to gamification and engagement features — streaks, rewards, notifications.

Feature Discussed

The specific feature or capability the person engaged with.

Feature Request

A specific improvement, fix, or missing capability the customer asks for.

New-Launch Feedback

Early signal on a newly launched or updated product — critical for catching launch-quality issues fast.

Product / Module Referenced

Which product, model, brand, or module the text is about.

Emotional Intensity

How strongly the person feels, independent of whether it's positive or negative — surfaces your highest-passion and highest-risk voices.

Grievance Severity

The stakes behind a complaint — from mild annoyance to serious harm — as framed by the customer.

Overall Sentiment

The true feeling expressed in the words themselves — extracted from the prose, not the star rating or survey score.

Predicted CSAT

A modeled 1–5 satisfaction score inferred purely from the qualitative text of an interaction.

Predicted NPS Band

The likely promoter / passive / detractor classification read from language, even when no score was given.

Customer Intent

The primary reason the person reached out or showed up.

Effort Level

How hard the customer had to work to get value or resolution.

First-Time vs. Repeat

Whether this is a new or returning customer, read from the narrative rather than a CRM flag.

Interaction Type

Whether the exchange is a complaint, question, praise, cancellation, or sales inquiry.

Lifecycle Stage

Where the person sits in their journey with you — prospect, new, onboarding, active, at-risk, or churned.

Purchase Motivation

The dominant reason the customer bought or visited.

Resolution Status

Where the issue stands by the end of the interaction — resolved, pending, or unresolved.

Transaction / Visit Type

The kind of transaction the text is about — sales vs. service, purchase vs. return, dine-in vs. delivery.

Use Case

The specific business or personal use case the person references.

Accessibility & Courtesy

How well specific needs were accommodated and the courtesy shown.

Atmosphere & Ambiance

The energy, mood, and sensory experience of the venue.

Core Quality Verdict

The customer's assessment of the core product or offering — food, course, device reliability.

Digital & App Experience

Experience with the app, online ordering, or self-service surfaces not visible in structured data.

Facility & Cleanliness

The physical condition and cleanliness of the space.

Order & Service Accuracy

Whether the order or request was fulfilled correctly.

Primary Friction

The single most operationally important thing that went wrong.

Primary Topic

The single dominant subject of the conversation.

Service Recovery

What happened when the customer raised an issue or asked for help.

Service Speed & Wait

What the customer says about timeliness and wait time.

Staff Interaction Quality

The character of the human or service interaction, from exceptional to hostile.

Engagement Mechanic Response

How the customer reacts to gamification and engagement features — streaks, rewards, notifications.

Feature Discussed

The specific feature or capability the person engaged with.

Feature Request

A specific improvement, fix, or missing capability the customer asks for.

New-Launch Feedback

Early signal on a newly launched or updated product — critical for catching launch-quality issues fast.

Product / Module Referenced

Which product, model, brand, or module the text is about.

Product vs. Service Attribution

Whether dissatisfaction stems from the product itself or from how it was serviced.

Reliability & Defect Type

The specific hardware or software failure, and where in the lifecycle it occurred.

Billing Dispute

The specific billing or charge dispute described.

Dollar Amount Referenced

Exact monetary amounts named in the text — disputes, fees, promises, refunds.

Fee & Premium Change

The direction and size of a price, fee, or premium change the customer calls out.

Price–Value Perception

How the customer frames what they got for what they paid.

Pricing & Paywall Friction

Reaction to subscriptions, paywalls, ads, and monetization changes.

ROI & Value Realization

The concrete business outcome the customer credits to your product.

Account Health Score

A composite health read inferred from all the signals in a message.

Buying Signal

Positive purchase intent and where the deal sits in the sales process.

Churn & Cancellation Risk

Language suggesting the customer may leave, not renew, or switch away.

Expansion & Adoption Signal

Language pointing to more seats, new use cases, upsell, or deeper adoption.

Loyalty Signal

An explicit loyalty-program or brand-loyalty stance — the retention stake.

Objection

The concern or hesitation blocking the deal.

Recommendation Signal

Whether the person would recommend you — or actively warns others off.

Return & Refund Signal

Whether the customer returned, refunded, or is considering it.

Actionability Tier

The operational owner who could act on the feedback — the routing tag that turns voice into a task.

Compliance Flag

Language or situations that should be routed for compliance review.

Data & Account Loss

Reports of lost data, progress, or access.

Escalation Risk