For AI Products

Every abandoned prompt, incomplete generation, and unused AI feature is a missed opportunity.
DeepSync shows you why.

Building a great AI product isn't just about model quality — it's about delivering an experience users trust. DeepSync helps AI teams understand how people actually use copilots, chatbots, AI search, agents, and generative applications so they can continuously improve adoption and retention.

Prompt journey analyticsAI conversation replayFeature adoption insightsEnterprise-ready in under 5 minutes
Conversion funnel showing where users drop off across an AI product's onboarding

The challenge

Your AI might be brilliant. That doesn't mean users know how to use it.

Users experiment with prompts, regenerate responses, upload files, switch models, compare outputs, and explore features before deciding whether your product is worth paying for.

One prompt and gone

Usage numbers can look healthy while most users generate a single response and never come back.

Features nobody discovers

Modern AI products ship dozens of capabilities, and most users find only a fraction of them.

Regeneration hides a real problem

Users repeatedly regenerating instead of accepting a response usually means something is broken, not that they're just picky.

Paywalls that stop the wrong users

A usage limit hit before someone experiences real value looks like monetization, but it's usually lost retention.

The solution

Where DeepSync helps

DeepSync helps AI product teams understand every interaction — from the first prompt to long-term adoption — using Session Replay, Heatmaps, Journey Analytics, and AI-powered behavioral insights.

Prompt-to-Response Journey

Every successful AI interaction starts with a prompt

Replay user sessions to understand how people write prompts, refine instructions, regenerate responses, and decide whether the output solved their problem. Identify where conversations fail and improve prompt success rates.

  • See how users refine or abandon prompts mid-conversation
  • Identify where responses trigger repeated regeneration
  • Understand which prompts most often lead to a completed task
Session replay of a user writing and refining an AI prompt

AI Onboarding

Most users decide whether an AI product is valuable within minutes

DeepSync reveals where users abandon onboarding, ignore suggested prompts, skip tutorials, or become confused before generating their first response. Optimize activation using real behavioral data, not assumptions.

  • See where first-time users hesitate before their first prompt
  • Find where suggested prompts and tutorials get ignored
  • Measure time to first successful generation
Heatmap of an AI product's onboarding screen

Feature Discovery

Most users discover only a fraction of what you've built

File uploads, voice input, agents, image generation, memory, custom assistants — heatmaps and journey analysis reveal which features users adopt, ignore, or struggle to find.

  • See which AI features get used and which stay hidden
  • Measure adoption after a new capability ships
  • Prioritize surfacing features with the clearest usage gap
AI chat interface with an unused feature panel

On the ground

What this looks like in a real week.

AI Products & Copilots scenarios DeepSync teams run into — and how each one gets fixed.

01

Everyone writes one prompt and leaves

An AI writing assistant attracts thousands of new users every day. Analytics show that 72% of users generate only one response before leaving. Session replay reveals many users expect a continuing conversation but instead see a blank editor after the first generation, with no suggested follow-up.

The product team introduces contextual prompt suggestions and conversation starters; next-day retention increases 21%.

02

The AI isn't slow — users think it is

A coding copilot receives complaints about slow generations. Replay sessions reveal users clicking 'Generate' multiple times because nothing appears to happen during model inference.

An animated progress indicator and streamed responses dramatically reduce rage clicks and duplicate requests.

03

Nobody finds image generation

An AI productivity platform launches image generation. Three months later, usage remains low. Heatmaps show that most users never notice the image generation tab hidden inside a dropdown menu.

After redesigning navigation and surfacing image generation in onboarding, adoption nearly triples.

04

The paywall stops the wrong users

A conversational AI platform limits free users to ten messages. Journey analysis reveals that most users encounter the paywall before receiving meaningful value.

The company adjusts free usage limits to let users complete a typical workflow first; paid conversions increase without a proportional rise in infrastructure cost.

05

AI summary finds the real problem

An AI meeting assistant notices declining engagement after a product update, with nothing unusual in dashboards. DeepSync AI identifies that users repeatedly abandon during file uploads because drag-and-drop silently fails on Safari.

Engineering reproduces the issue in minutes and ships a fix the same day.

06

Prompt templates nobody uses

A legal AI assistant introduces dozens of prompt templates. Replay sessions reveal users scrolling past templates and typing their own prompts because template names don't clearly explain their purpose.

The product team redesigns templates around common tasks instead of categories; template usage doubles.

07

Voice input creates confusion

An AI mobile app launches voice conversations. Session replay shows users repeatedly tapping the microphone because recording starts automatically without clear feedback.

A redesigned recording interface reduces abandoned conversations and improves feature adoption.

08

Enterprise users never invite their teams

An AI knowledge platform closes enterprise deals, but adoption remains low. Journey analysis shows administrators successfully onboard themselves but never invite colleagues because team management is buried inside settings.

The feature is surfaced during onboarding, increasing workspace adoption across enterprise accounts.

What leadership tracks

KPIs this team already reports on.

First prompt success rate

Share of new users whose first prompt produces a response they act on.

Time to first value

How long it takes a new user to get a result worth coming back for.

Feature adoption rate

Share of active users who use a given capability, like file upload or voice input.

Free-to-paid conversion

Share of free users who upgrade to a paid plan.

Average conversations per user

A proxy for whether users are returning, not just trying the product once.

Weekly retention

Share of active users who return the following week.

Who uses it

One tool, every team, different questions.

Product

Understand how users interact with prompts, conversations, agents, and AI workflows to improve activation and retention.

AI Engineering

Identify UX issues around generation, latency, file uploads, and conversation flows that affect user satisfaction.

Growth

Measure which acquisition channels bring users who actually become active subscribers, not just signups.

Design

Optimize onboarding, conversation interfaces, prompt suggestions, and premium experiences using real behavioral data.

Customer Success

Replay customer sessions to quickly resolve onboarding issues and improve enterprise adoption.

Marketing

Learn how visitors evaluate AI features, pricing, and use cases before starting a trial or subscribing.

Leadership

Receive AI-powered summaries highlighting product friction, feature adoption, and opportunities to improve customer retention.

Fits your stack

Works with the tools you already run.

StripeSegmentMixpanelAmplitudePostHogIntercomHubSpot
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FAQ

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