Dilan Mirioğlu UX · UI · Product

UX Study — Measurement framework

Defining UX KPIs

A shared definition of what “good” looks like in numbers — 46 UX metrics organised on Google’s HEART model, each tagged with the evidence it comes from and when to instrument it.

Framework
Google HEART
Context
In-house UX practice · mobile product
Scope
46 metrics across 5 dimensions
Role
UX — measurement & analytics

Why this exists

As the team’s UX practice matured, “is the experience good?” kept getting answered by opinion. We needed one agreed scoreboard. I built this framework on Google’s HEART model — Happiness, Engagement, Adoption, Retention, and Task Success — so every metric ladders up to a question about the user, not a vanity number.

Each KPI carries two extra tags that turn a long list into a plan: where the evidence comes from (so we know which tool has to be in place) and a measurement priority (so we instrument the core signals first instead of boiling the ocean). Use the filters below to slice the catalog by either.

Measurement priority

P1

Core. The essential signal — instrument these first.

P2

Secondary. Valuable once the core loop is measured.

P3

Later. Useful context; lower urgency to wire up.

Evidence type

Analytics. Product & event data — what users actually did.

UX tooling. Heatmaps & session replay — behaviour, up close.

Survey. Asked directly — attitudes and perceived quality.

Marketing & SEO. Reach and discoverability — the outside view.

The framework at a glance

46
KPIs defined
5
HEART dimensions
27
Core (P1) metrics to instrument first
4
Evidence types feeding the model

Where measurement concentrates

KPI count per HEART dimension, split by the evidence each metric relies on. Happiness carries the most instrumentation and the widest mix of evidence; retention and task success run almost entirely on analytics.

Happiness 18
Engagement 12
Adoption 8
Retention 6
Task Success 2

The metric catalog

Every metric, grouped by its HEART dimension. Filter by evidence type or priority to focus the list.

Evidence
Priority

46 of 46 metrics

Happiness

How good does the product feel to use — satisfaction & perceived quality.

18 of 18

SEQ

P1

Single Ease Question — a post-task ease rating, averaged across users.

Survey

NPS

P1

Net Promoter Score — how likely users are to recommend the product.

Survey

System Usability Scale

P1

Standardised 10-item usability score (SUS).

Survey

CSAT

P1

Customer Satisfaction Score — overall satisfaction, asked in-survey.

Survey

Sentiment Analysis

P1

User feedback classified as positive, negative, or neutral.

Survey

Miss Click

P1

Taps landing on non-interactive areas — a sign of misleading affordances.

UX tooling

Rage Tap

P1

Rapid repeated taps in one spot — a strong frustration signal.

UX tooling

Time in Major Journeys

P1

Time to complete the key flows, defined per product.

Analytics

Devices

P1

Device types across the user base.

Analytics

OS

P1

Operating-system split — iOS, Android, or both.

Analytics

Screen Dimensions

P1

Screen sizes and resolutions users are on.

Analytics

Load Time

P1

How long the app takes to load.

Analytics

Average Usage Time

P2

Average time users spend in the product over a period.

Analytics

Support Interaction

P2

Volume of support contacts and how many get resolved.

Analytics

Permissions

P3

Share of users who grant the access permissions the app asks for.

Analytics

Error Rate

P3

Share of actions that end in an error.

Analytics

Frequency of Crash

P3

How often the app crashes.

Analytics

Total Crash Count

P3

Total number of crashes recorded.

Analytics

Engagement

How deeply and how often users engage — sessions, sharing, upgrades.

12 of 12

Register Count

P1

Number of new sign-ups.

Analytics

Daily Avg. Sessions

P1

Average sessions per user, per day.

Analytics

Monthly Avg. Sessions

P1

Average sessions per user, per month.

Analytics

Session Length

P1

Time spent within a single session.

Analytics

Session Depth

P1

Interactions performed within a session.

Analytics

Session Interval

P1

Time that elapses between two sessions.

Analytics

Upgrades

P2

Users moving up to paid tiers.

Analytics

Uninstall Trend

P2

Trend of users uninstalling the app.

Analytics

Number of Shares

P2

How often in-app content gets shared — a read on the active-user profile.

Analytics

Social Shares

P2

How often users share the app on social channels.

Analytics

Updates

P3

Adoption rate of new app versions.

Analytics

Referral

P3

User-to-user referral rate.

Analytics

Adoption

Are new users taking it up — and can they find it in the first place.

8 of 8

Mobile Downloads

P1

Number of mobile app downloads.

Analytics

Search Results

P1

How many results the brand surfaces for in search.

Marketing & SEO

User Growth Rate

P2

Rate at which the user base is growing.

Analytics

First-Week Engagement

P2

How much new users engage in their first week.

Analytics

SEO Rank

P2

The brand’s ranking position in search engines.

Marketing & SEO

Install Trend

P3

Change in install rates over time.

Analytics

Brand Awareness

P3

Share of people who recognise the brand.

Survey

Social Media Followers

P3

Follower count across social channels.

Marketing & SEO

Retention

Do users keep coming back — the core health of the product loop.

6 of 6

Retention Rate

P1

Share of users who stay active over time.

Analytics

DAU

P1

Daily active users.

Analytics

MAU

P1

Monthly active users.

Analytics

Churn Rate

P1

Share of users who leave the platform.

Analytics

Stickiness

P1

DAU ÷ MAU — how habitual usage is.

Analytics

Reactivation Rate

P2

Share of long-inactive users who return.

Analytics

Task Success

Can users complete what they came to do — and come back to do it again.

2 of 2

Total Lead

P1

Total potential customers in the marketplace.

Analytics

Repeat Purchases

P1

Rate of customers purchasing again.

Analytics