Integrations

Your tools finally talk to each other

UX Connection pulls insights from every layer of your design operation—then synthesizes them into patterns no single tool can see.

FigmaGA4AmplitudeHotjarGitHubJiraMixpanelLinear+ 10 more
The Difference

Individual tools vs. connected intelligence

FIGMA ALONE
Before

Button component used 847 times

With UX Connection

Button component used 847 times, correlates with 23% faster task completion, and teams using it ship 2.1 days faster than teams going custom

GA4 ALONE
Before

Conversion rate: 3.2%

With UX Connection

Conversion rate: 3.2%, up from 2.4% baseline, attributable to checkout redesign with 94% confidence, representing $2.3M annual revenue lift

HOTJAR ALONE
Before

Rage clicks detected on checkout page

With UX Connection

Rage clicks on checkout traced to specific Figma component (card-payment-v2), affecting 12% of sessions, estimated $47K monthly revenue impact

GITHUB ALONE
Before

142 commits this sprint

With UX Connection

142 commits, 67% touched design system components, average PR cycle 2.1 days (vs 4.7 for custom code), correlating with 34% fewer production visual bugs

The insight isn't in any single tool.
It's in the connections between them.

Design Tools

Where your designs live

Figma

Live
What we pull:
  • Component usage across files and teams
  • Version history and iteration velocity
  • Design-to-handoff time
  • Comment sentiment and resolution rates
  • Style guide adoption
  • + 2 more
Insight example:

Teams using your button component ship 2.3 days faster than teams going custom.

Sketch

Live
What we pull:
  • Library symbol usage
  • Document version frequency
  • Shared style adoption
  • Plugin usage patterns
  • Export frequency by format
Insight example:

Symbol detachment increased 34% this quarter—design system drift detected.

Adobe XD

Live
What we pull:
  • Component state tracking
  • Prototype interaction paths
  • Share link engagement
  • Design spec views by engineering
  • Asset export patterns
Insight example:

Engineers viewed checkout specs 12x more than other flows—complexity signal detected.

Analytics Platforms

Where your metrics live

Google Analytics 4

Live
What we pull:
  • Conversion events and funnels
  • User flow paths
  • Engagement metrics (time, depth, frequency)
  • Audience segments
  • E-commerce transactions
  • + 2 more
Insight example:

Users who encountered your new onboarding flow convert at 23% higher rate with 94% confidence.

Amplitude

Live
What we pull:
  • Behavioral cohorts
  • Retention curves
  • Feature adoption rates
  • Funnel conversion
  • Path analysis
  • + 2 more
Insight example:

Feature adoption correlates with 3.2x higher 12-month retention for users in the redesigned segment.

Mixpanel

Live
What we pull:
  • Event streams
  • Funnel performance
  • Cohort retention
  • User property distributions
  • Signal detection
  • + 1 more
Insight example:

Rage click events dropped 67% after the form redesign shipped—friction eliminated.

Heap

Live
What we pull:
  • Auto-captured events
  • Session recordings metadata
  • Conversion paths
  • Effort score calculations
  • Retroactive funnel analysis
Insight example:

Average clicks-to-checkout dropped from 8.3 to 4.1 post-redesign.

Behavior & Research

Where your insights live

Hotjar

Live
What we pull:
  • Heatmap density data
  • Scroll depth percentages
  • Click maps
  • Rage click locations
  • Dead click detection
  • + 2 more
Insight example:

47% of users never scroll past the pricing table—content hierarchy issue detected.

FullStory

Live
What we pull:
  • Frustration signals (rage clicks, error clicks)
  • Session metrics
  • Conversion funnels
  • Page performance impact
  • Search behavior
  • + 1 more
Insight example:

Error click rate on mobile checkout is 4.2x higher than desktop—responsive issue flagged.

Maze

Live
What we pull:
  • Usability test completion rates
  • Task success metrics
  • Misclick rates
  • Time on task
  • Path analysis
  • + 1 more
Insight example:

Prototype B had 89% direct success vs 54% for A—clear winner before development.

Dovetail

Live
What we pull:
  • Interview insight tags
  • Theme frequency
  • Sentiment analysis
  • Highlight reels metadata
  • Research project velocity
  • + 1 more
Insight example:

'Confusing navigation' tagged in 34 of 50 interviews—top user pain point confirmed.

Development & Code

Where your designs ship

GitHub

Live
What we pull:
  • Commit frequency by component
  • PR review time
  • Design file references in commits
  • Component import statements
  • Breaking change detection
  • + 1 more
Insight example:

Design system components average 2.1 day PR cycle vs 4.7 days for custom implementations.

GitLab

Live
What we pull:
  • Merge request metrics
  • Pipeline success rates
  • Component usage in codebase
  • Design token adoption
  • Issue-to-merge velocity
Insight example:

Teams using design tokens ship 34% fewer visual bugs to production.

Bitbucket

Live
What we pull:
  • Pull request analytics
  • Branch patterns
  • Code review cycles
  • Deployment frequency
  • Component traceability
Insight example:

Frontend deploys increased 23% after design system v2 adoption.

Project Management

Where your work is tracked

Jira

Live
What we pull:
  • Issue cycle time
  • Story point velocity
  • Bug density by component
  • Design-tagged ticket flow
  • Sprint completion rates
  • + 1 more
Insight example:

UX-tagged tickets resolve 1.8 days faster when design specs are attached.

Linear

Live
What we pull:
  • Cycle metrics
  • Project progress
  • Issue relationships
  • Label analytics
  • Team velocity
  • + 1 more
Insight example:

Design QA issues dropped 45% after component library standardization.

Asana

Live
What we pull:
  • Task completion rates
  • Project timeline adherence
  • Workload distribution
  • Custom field analytics
  • Goal progress tracking
Insight example:

Design review bottleneck identified—average 3.2 day wait for approval.

Data Warehouses

Connect to your source of truth

Snowflake

Live
What we pull:
  • Custom metric queries
  • Revenue attribution data
  • Customer lifetime value
  • Cohort definitions
  • Any structured business data
Insight example:

Direct connection to your source of truth—no data discrepancies between tools.

BigQuery

Live
What we pull:
  • Custom SQL queries
  • Event stream data
  • Cross-platform user matching
  • Revenue and transaction data
  • Custom attribution models
Insight example:

Query your entire data warehouse with attribution context automatically applied.

“We could build this ourselves”

You could. Here's what it takes:

18
API integrations to build and maintain
47
Distinct data points to normalize
6-9 mo
Estimated build time
$180K+
Estimated engineering cost

Or $299/month. Connected in 15 minutes.

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