Navigator
Startup
Product & Usage Analytics

Session Analysis: Understanding the User Journey

Tracking how users move through your product—and what session patterns reveal about engagement.

• Navigator Team
session analysis user journey engagement behavior

A user logs into your product.

They click around for 3 minutes.

They leave.

That’s a session: A single, continuous usage of your product.

Session analysis tracks what users do during sessions: Which pages they visit, how long they stay, where they drop off.

What Is a Session?

A session is a period of continuous activity by a user.

Session definition:

  • Starts when user logs in (or lands on the site)
  • Ends when user logs out, closes the browser, or is inactive for 30 minutes
  • Can include multiple pages, clicks, actions

Example session:

  • User logs in
  • Views dashboard (30 seconds)
  • Clicks to analytics page (2 minutes)
  • Clicks to export report (1 minute)
  • Downloads CSV
  • Logs out
  • Session duration: 3.5 minutes, 4 pages visited

Session Metrics

Session length:

  • How long are users in the product each time they use it?
  • Longer = more engaged (or more confused and searching)

Pages per session:

  • How many different pages do they visit?
  • More pages = exploring (or struggling to find what they need)

Bounce rate:

  • % of sessions where user visits 1 page and leaves
  • High bounce rate = user didn’t find what they wanted, or landing page is wrong

Return frequency:

  • How many sessions per user per week?
  • More frequent = habit-forming (good)
  • Less frequent = optional (at-risk for churn)

Session Length Patterns

Session length varies by product type:

Social media (Twitter, TikTok):

  • Average session: 15-30 minutes
  • Multiple short sessions per day (users check throughout the day)
  • High engagement = long sessions

Productivity tools (email, Slack):

  • Average session: 5-20 minutes
  • Multiple sessions per day
  • High engagement = frequent sessions (not necessarily long)

Analytics/reporting tools:

  • Average session: 5-15 minutes
  • 1-3 sessions per day
  • High engagement = regular check-ins

E-commerce:

  • Average session: 2-5 minutes
  • Bounce rate high (40-50%)
  • High engagement = quick decision (user knows what they want)

If your session length is declining, engagement is declining.

If session length is increasing, either engagement is improving, or users are struggling to find what they need (and taking longer to complete tasks).

Bounce Rate Analysis

Bounce rate is high when:

1. User lands on the wrong page

  • They searched for “feature X” and landed on “feature Y”
  • Solution: Improve page titles/descriptions so people land on the right page

2. Page takes too long to load

  • User gets impatient and leaves
  • Solution: Optimize performance

3. Value isn’t clear

  • User lands on page, doesn’t understand what it does or why it matters
  • Solution: Better messaging, clearer value prop

4. Page is broken

  • Something doesn’t work, user leaves
  • Solution: Fix bugs

5. User is just window shopping

  • They’re exploring, not committed to buying (or signing up)
  • Solution: This is partly normal; some bounce is expected

Normal bounce rate varies:

  • Blog posts: 50-70% (people read, leave)
  • Landing pages: 40-60% (people exploring options)
  • Product pages: 20-40% (people more committed)
  • User dashboards: 5-15% (logged-in users are engaged)

High bounce rate on user dashboards (>30%) is concerning. Users are logging in but leaving immediately.

Session Flow Analysis

Track the path users take through your product:

Typical path for analytics tool:

  1. Login (100%)
  2. View dashboard (95%) — 5% bounce
  3. Click on metric (75%) — 20% drop
  4. View detailed report (60%) — 15% drop
  5. Export or share (40%) — 20% drop
  6. Logout (100% of remaining)

This tells you:

  • Step 2-3 is the biggest drop (20%). Why are people not clicking into details? Is metric name confusing? Is button hard to find?
  • Step 4-5 has a 20% drop. Many users view the report but don’t act on it. Why? Is export button unclear?

Fix the biggest drops first.

Session Analysis by Cohort

Different user cohorts have different session patterns:

New users (first week):

  • Session length: 8-10 minutes (exploring, trying things out)
  • Pages per session: 6-10 (bouncing around)
  • Bounce rate: 20% (but many of these become engaged)

Returning users (week 2-4):

  • Session length: 4-6 minutes (knowing what they want)
  • Pages per session: 3-4 (more focused)
  • Bounce rate: 10% (they know where to go)

Power users (month 3+):

  • Session length: 3-5 minutes (very efficient, quick actions)
  • Pages per session: 2-3 (direct path)
  • Bounce rate: <5% (know exactly what they’re doing)

This is the ideal pattern: Users get more efficient over time.

If returning users have longer session times than new users, something is wrong (they’re struggling, not learning).

The Engagement Gradient

Session patterns reveal engagement level:

Highly engaged:

  • Sessions: 3+ per day
  • Session length: 15+ minutes
  • Pages per session: 5+
  • Low bounce rate: <5%

Moderately engaged:

  • Sessions: 1-2 per day
  • Session length: 5-10 minutes
  • Pages per session: 2-3
  • Bounce rate: 10-20%

Lightly engaged:

  • Sessions: 2-4 per week
  • Session length: 2-5 minutes
  • Pages per session: 1-2
  • Bounce rate: 30-50%

Disengaged (at-risk):

  • Sessions: 0-1 per week
  • Session length: <2 minutes
  • Pages per session: 1
  • Bounce rate: >50%

Users in the “lightly engaged” and “disengaged” categories are at high churn risk.

Using Sessions to Diagnose Problems

Problem: High bounce rate on onboarding flow

Session analysis reveals: New users land on “Create Account” page, 60% bounce.

Options:

  • Page is slow (fix performance)
  • Form is too complex (simplify form)
  • Value isn’t clear (add messaging explaining why they should sign up)
  • They landed by mistake (improve landing page keywords)

Problem: Users not reaching “activation” page

Session analysis reveals: Users visit 3-4 pages, but 40% bounce before reaching “create first project” (your activation point).

Options:

  • Path is unclear (users don’t know how to get there)
  • They’re not ready yet (they need more education first)
  • They gave up (flow is too long)

Solution: Add navigation or tutorial that guides them directly to activation.

Problem: High session length, but low retention

Session analysis reveals: Users spend 20 minutes in product, but 50% don’t come back.

This suggests:

  • Users are struggling (long sessions because they’re confused)
  • Product is complicated (users are learning)
  • They didn’t find value (spent time exploring but didn’t achieve their goal)

Solution: Simplify product, add better guidance, or improve onboarding to get them to value faster.

Temporal Session Patterns

Session patterns vary by time of day/week:

During business hours (9 AM - 5 PM):

  • More sessions from business users
  • Shorter sessions (quick check-ins during work)

Evening/weekend:

  • Fewer sessions from business users
  • Longer sessions if they happen (more focused work)

Monday morning:

  • Spike in sessions (people catching up)

Friday afternoon:

  • Drop in sessions (people winding down)

This is normal. Don’t compare Monday to Friday; they’re different animals.

When analyzing session changes, compare same time periods (Monday to Monday, not Friday to Monday).

The Takeaway

Sessions reveal how users actually move through your product.

High session length + high frequency = engaged Low session length + low frequency = disengaged

Analyze session flows to find where users drop off.

Fix the biggest drop-off points first.

Track sessions by cohort. Different user types have different patterns (and that’s expected).

Use session analysis to diagnose onboarding problems, feature confusion, and engagement issues.

We help you analyze session data, identify drop-off points, and diagnose engagement problems.