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Analytics part 2

Driving Adoption & Accessibility of Analytics with Conversational AI

Driving Adoption & Accessibility of Analytics with Conversational AI

Simplifying data access and empowering users of all technical levels to query, create, and share insights effortlessly.

Simplifying data access and empowering users of all technical levels to query, create, and share insights effortlessly.

Company context

Ambient.ai

Enterprise SaaS, Physical Security, Computer Vision

Security monitoring is overwhelming.

Ambient.ai alerts customers of notable activity by watching 1,000s of camera footage so security professionals don't have to.

Project overview

Role

Design lead

Stakeholders

10

Timeline

4 months

Problem context

Analytics platforms often have high barriers to entry making it difficult for non-technical users to generate & share insights.

Users need

A simplified way to query, create, share, and understand insights.

Team Lead

Create & share charts to communicate progress; need to easily generate insights with stakeholders.

Executive

Understand high-level metrics by understanding visualizations at a glance; need dashboard summaries.

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Starting point

business context

Drive adoption of the Analytics platform by addressing the needs of both technical and non-technical users.

Design objective

How might we

Design an AI-powered analytics solution that empowers users—regardless of technical expertise—to easily query, create, and share actionable visualizations, while providing transparency and control.

Simplify visualization workflows.
Foster trust using AI experiences.

Design & development

ITERATION 1

We wanted to validate whether a conversational AI interface embedded within the dashboard would simplify users’ ability to generate insights.

We wanted to validate whether a conversational AI interface embedded within the dashboard would simplify users’ ability to generate insights.

user feedback & Iterations

Input Output Improvements

A blank messaging box was too open-ended.

A blank messaging box was too open-ended.

Customers want responses as visualizations.

Customers want responses as visualizations.
AI Trust & Transparency

Customers wanted clarity on how insights were being generated.

Customers wanted clarity on how insights were being generated.
Feature Placement
Insights need to live where users work—at both the dashboard and data levels.

Dashboard only data analysis

Dashboard only data analysis

Cameras page data analysis

Cameras page data analysis

Alerts page data analysis

Alerts page data analysis

TYING THE PRODUCT TOGETHER

Allow customers to create AI insights wherever to ultimately add it to and share from a dashboard.

Allow customers to add AI created charts to dashboards.

Allow customers to add AI created charts to dashboards.

ITERATION 2

Impact & outcome

improved chart creation time

10 minutes

10 minutes

Seconds

Seconds

increase in created charts

30%

reduced support tickets

20%

Key Learnings & Takeaways

Guidance matters

Providing dynamic input suggestions reduces friction and helps users get started.

Transparency builds confidence

Explaining how AI works fosters trust, which is essential for adoption.