User Research Synthesis / [Month, Year]

# User Research
Synthesis

What we learned from 24 interviews and what it means for the product.

Research Team · [Month, Year] Round [N] · Internal
01 · Context

## Why we went back
to users

Three months after launch, retention numbers told us something the metrics couldn't.

Key Finding 03

Primary objective · Round [N] synthesis

## Users don't leave because they lose interest. They leave because they don't know what to do next.

User Behavior 04

The Pattern

## The first 48 hours determine everything

Users who complete three core actions in their first two days have a 4× higher 90-day retention rate. Most never get there.

- Onboarding drop-off peaks at step 3
- "What do I do next?" is the most common exit trigger
- Users who invite a teammate retain at 2× the rate

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Session recording review · [Month of study]

By the Numbers 05

## What the data showed

68%

of users churned within 14 days — up from 54% in cohort 2

[Analytics tool] · [Launch month]

3.2min

Average time before abandonment on the setup flow

Session recordings · n=240

4×

Higher 90-day retention for users who complete onboarding fully

Cohort analysis

Recommendations 06

What to fix

## Five changes, ordered by impact

We recommend addressing these sequentially — later ones depend on the first landing.

- Redesign the setup flow to three steps maximum
- Add a "start here" prompt on day one based on user type
- Surface the collaboration invite after first meaningful action
- Replace feature tour with outcome demonstration
- Build a 7-day email sequence that mirrors in-product progress

Current · Proposed 07
Current Onboarding

### 9-step setup, any order

Users choose their own path through setup. Most choose wrong.

- Average 3.2 minutes to first value
- Step 6 is where 41% abandon
- No adaptive logic based on user type

Proposed Flow

### 3-step guided path, adaptive

User type detected at signup. Path adjusts. First value in under 90 seconds.

- Target: 90 seconds to first value
- Eliminate decision paralysis at step entry
- Inline help triggered at abandonment signals

"I kept opening the app and then closing it again. I didn't know what I was supposed to do."

Participant 14 · 28 years old, Product Designer Interview · [Month of study]
Analysis 09

## Why onboarding problems compound over time

#### The Activation Trap

Activation is the moment a user experiences the core value of a product for the first time. When that moment is delayed or never arrives, the user's mental model of the product never fully forms. They carry a vague, unresolved impression into every subsequent session.

Each session that ends without activation reinforces the exit pattern. The user doesn't consciously decide to leave — they simply stop opening the app because it hasn't yet earned a place in their routine. The gap between download and habit is where most products lose users permanently.

Retention data confirms this: users who hit activation in session one have a 3× higher probability of returning in week two. The window is narrow. Products that front-load value creation outperform those that distribute it across multiple sessions.

#### The Network Effect Delay

Collaboration products face a compounding problem: the value of the product increases with each additional teammate, but users must cross the value threshold alone before they think to invite anyone. Most never reach the threshold.

Our data shows that the median user does not discover the invitation flow until session four — by which point 60% have already churned. The product's most powerful retention mechanism is invisible during the critical first-session window where the keep-or-leave decision is made.

The solution is not to surface the invite prompt earlier in a disruptive way, but to design the single-player experience as an explicit bridge to the collaborative one. Every solo action should feel like preparation for something that scales.

Retention Analysis 11

## 90-day retention by onboarding cohort

% retained · n=480 · [Q1 of study period]
34%
Cohort 1
41%
Cohort 2
48%
Cohort 3
67%
Proposed

Source: [Analytics tool] · Cohort analysis · Proposed target based on redesigned onboarding flow

Methodology 12

## How this research was conducted

01
Recruit
24 participants screened from the active user base. Mix of power users, casual users, and churned users within 90 days.
02
Interview
60-minute moderated sessions. Cognitive walkthrough of key flows. Think-aloud protocol throughout.
03
Analyse
Affinity mapping across 340 observations. Pattern clustering by behaviour type, not stated preference.
04
Validate
Key findings stress-tested against session recordings and support ticket data before synthesis.
Participant Breakdown 13

## Who we spoke with

Power Users 38%
Casual Users 25%
Churned Users 22%
Prospects 15%

Total participants: [N] · [Study period]

Source: Recruitment screener · [Study period]

Process 14

## From research to recommendation

[Week 1]
Recruitment

Screened [N]+ applicants, selected [N] participants across user segments.

[Week 2–3]
Fieldwork

[N] moderated sessions. Think-aloud protocol. All sessions recorded and transcribed.

[Week 4]
Synthesis

Affinity mapping across [N]+ observations. Pattern clustering by behaviour type.

[Week 5]
Validation

Findings stress-tested against [analytics tool] data and [N] support ticket samples.

Design Process 15

## The design thinking cycle

01
Empathise

Understand users in their own context. Suspend assumptions. Observe before interpreting.

→
02
Define

Reframe the problem as a point of view. One sentence. Testable. Grounded in observation.

↓
↓
04
Test

Put prototypes in front of real users. Capture what they do, not what they say.

←
03
Prototype

Build to think, not to ship. The lowest fidelity that answers the question.

Research Framework 17

Research Framework

## Analysis Hierarchy

From raw observations to strategic insight

Strategic Insight
Behavioral Patterns
Synthesized Themes
Coded Observations
Raw Field Notes

Research Team

## Questions, feedback, and next steps

[research@org.com] · [Slack #research] · Full report at [link]