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Product and app usage dashboard

What the Product and app usage dashboard in Kontala Analytics shows: feature adoption, first-visit paths, friction and page speed, its filters and every tile on it.

Product and app usage treats every page type and click type as a feature, and shows how widely and how often each is used, which first-visit paths and features go with coming back, where visitors struggle, and which pages are slow.

Use it for product decisions: what to promote, what to fix and what nobody uses.

Good to know

  • Features are your page and click types, so the more of your site is typed, the more this dashboard can see.
  • The Feature filter picks one feature for the lower half of the Features tab.
  • The Friction and Speed tabs need friction capture turned on for the property, as struggle signals describes, and only count visitors who consented.
  • The Paths tab keeps its own 90-day range of first visits.

At a glance

Which features visitors use, how widely and how often, and who uses each; how new visitors' first visits unfold and which paths and features go with coming back; where visitors struggle, with errors, rage, dead and error clicks and quick backs; and which pages are slow.

Filters

The filters across the top apply to every tile they can, unless a tile says it has its own range.

  • Date range: the last 30 days, today included. It does not apply to 11 tiles on the Usage and Paths tabs.
  • Device type: not set when the dashboard opens, so it keeps everything until you pick a value.
  • Allowed origin: set to true, so tiles count only the origins your property allows. Clear it to see every origin the tag ran on. It does not apply to 27 tiles on the Usage, Features and Paths tabs.
  • Feature: not set when the dashboard opens, so it keeps everything until you pick a value. It does not apply to 47 tiles on the Usage, Features, Paths, Friction and Speed tabs.

Date zoom is turned off on this dashboard, because its charts already set their own time grain.

Tabs

Usage

TileKindWhat it shows
Active visitorsNumberVisitors with a visit on an allowed origin in the date range, each once.
Features per visitorNumberHow many different features the average active visitor used in the date range: page types they viewed and click types they clicked.
Visits with a typed page or clickNumberThe share of visits that viewed a page or clicked something Kontala gives a type: how much of what visitors do this dashboard can see. From the Visits explore.
Back within 7 daysNumberThe share of new visitors of the last 90 days who came back within 7 days of their first visit, over the first visits at least 7 days old. From the First visits explore.
Visits with frustrationNumberThe share of measured visits that met an error click, a rage click, a dead click or a quick back. From the Visits explore.
Good page viewsNumberThe share of measured page views whose LCP, INP and CLS, of those they measured, were each good: the Core Web Vitals' pass rate. From the Page views explore.

What do people use, and how often?

TileKindWhat it shows
Engagement matrix: how many use each feature, and how oftenMatrixEach feature by the share of active visitors who used it in the date range and how many days a week they did, split at the medians into core, power, one-off and underused features.

How to read this dashboard

A feature is a page type or a click type: viewing a page of a type, or clicking something of a type, as the Page types and Click types pages classify them. Unclassified and Other are no feature, so the more of a site Kontala classifies, the more this dashboard sees; Visits with a typed page or click says how much it sees now.

Adoption is the share of the active visitors in the date range who used a feature, and Days a week how many days of a week those who used it did. The matrix splits both at their medians: core features many use often, power features a few use often, one-off features many try once, underused the rest.

Back within 7 days and the other first-visit figures read the last 90 days' first visits, whatever the date range. A visitor is a device: Safari and iOS forget it after 7 days.

Which features reach the most visitors?

TileKindWhat it shows
Adoption by featureBar chartThe share of active visitors who used each feature in the date range, the fifteen used most on top.
Features per visitor by weekLine chartHow many different features the average active visitor used in each complete week of the date range.

Features

Who uses which feature, and how often?

TileKindWhat it shows
Feature scorecardTableEach feature used in the date range: who used it, how widely, how often, how much of it is a habit, and how soon new visitors found it.

Who uses each feature?

TileKindWhat it shows
Adoption by new and returning visitorsBar chartFor the twelve features used most, the share of new visitors who used each on their first day against the share of returning visitors who used it on a later one.
Adoption by device typeTableFor each feature used in the date range, the share of active visitors on a phone, a desktop and a tablet who used it.

How is one feature doing? Choose it with the Feature filter

TileKindWhat it shows
Visitors who used itNumberActive visitors who used the chosen feature in the date range.
AdoptionNumberThe share of active visitors who used the chosen feature in the date range.
Days a weekNumberOn how many days of a week those who used the chosen feature in it used it, on average.
Weeks on 3+ daysNumberOf the weeks a visitor used the chosen feature in, the share they used it on 3 days or more.
First-time usersNumberVisitors who used the chosen feature for the first time ever in the date range.
Days to first useNumberHow many days after their first visit those who first used the chosen feature in the date range typically did.
The chosen feature's adoption by weekLine chartThe share of each complete week's active visitors who used the feature the Feature filter chooses.
The chosen feature: weeks by days usedColumn chartThe weeks visitors used the feature the Feature filter chooses in, by how many days of each week they used it.

About features

Every active visitor is counted against every feature, used or not, so each feature's adoption has the same visitors below it and features compare like with like. Days a week and Weeks on 3+ days count the weeks a visitor used a feature in; a week cut by the date range counts its days in it. First-time users used a feature for the first time ever in the date range, and Days to first use is how long after their first visit that came. New visitors are on the day of their first visit and returning on a later one. Every figure counts visitors whose first visit was on an origin the property allows. Choosing one feature with the Feature filter fills the numbers above; it leaves the rest of the dashboard as it is.

Paths

TileKindWhat it shows
New visitorsNumberVisitors whose first visit, on an allowed origin, was in the last 90 days. From the First visits explore.
Back within 7 daysNumberThe share of new visitors of the last 90 days who came back within 7 days of their first visit, over the first visits at least 7 days old. From the First visits explore.
Back within 30 daysNumberThe share of new visitors of the last 90 days who came back within 30 days of their first visit, over the first visits at least 30 days old. From the First visits explore.
Typed first visitsNumberThe share of the last 90 days' first visits that viewed a page or clicked something Kontala gives a type. From the First visits explore.
Strongest first-visit signalNumberThe feature whose use in a first visit goes most with coming back within 7 days, and how many times more often those who used it came back. From the First visits explore.

How do the last 90 days' first visits unfold, and who comes back?

TileKindWhat it shows
First visits, step by step, and whether they came backFlowThe last 90 days' first visits at least 7 days old, flowing through their first four features, numbered from the first, to whether the visitor came back within 7 days: the 40 busiest links. From the First-visit paths explore.

Which first-visit features go with coming back?

TileKindWhat it shows
First-visit features against coming backTableFor each feature, the share of the last 90 days' new visitors who used it in their first visit, how often those who did and did not came back within 7 days, the lift and the correlation. From the First visits explore.

Is there an aha moment?

TileKindWhat it shows
Back within 7 days by features in the first visitColumn chartThe share of the last 90 days' new visitors who came back within 7 days, by how many different features their first visit used. From the First visits explore.
Back within 7 days, used it or notBar chartFor the ten features most new visitors used in their first visit, the share who came back within 7 days among those who used it and those who did not. From the First visits explore.

Which first-visit paths bring people back?

TileKindWhat it shows
First-visit paths and how they didTableThe commonest paths of the last 90 days' first visits: how many took each, and how often they came back within 7 and 30 days and converted. From the First visits explore.

About paths

A path is the features a first visit used, in order: a repeat of the one before is one step, Unclassified and Other are left out, and the flow shows the first four steps, then whether the visitor came back within 7 days, along its 40 busiest links; the paths table holds every path. Lift divides how often the new visitors who used a feature in their first visit came back by how often the rest did, and needs 20 first visits at least 7 days old on each side. It says what goes with coming back, not what causes it: visitors who use more of a site were keener to begin with, so a strong signal is where to look, and an experiment is how to know. For sign-ups and the action that keeps them, see the Retention dashboard's Activation tab.

Friction

TileKindWhat it shows
Visits with frustrationNumberThe share of measured visits that met an error click, a rage click, a dead click or a quick back. From the Visits explore.
Error-free visitsNumberThe share of measured visits with no JavaScript error, as Sentry's crash-free sessions count a browser's. From the Visits explore.
Rage clicksNumberThe share of measured visits with three clicks or more within a second of each other, in one spot. From the Visits explore.
Dead clicksNumberThe share of measured visits with a click on something that looked clickable that nothing answered within a second. From the Visits explore.
Error clicksNumberThe share of measured visits in which a JavaScript error came within a second of a click. From the Visits explore.
Quick backsNumberThe share of measured visits in which the visitor went back from a page within 10 seconds. From the Visits explore.

Is friction going down?

TileKindWhat it shows
Visits with frustration by weekLine chartThe share of each week's measured visits that met an error click, a rage click, a dead click or a quick back. From the Visits explore.
Error-free visits by weekLine chartThe share of each week's measured visits with no JavaScript error. From the Visits explore.

What does friction cost?

TileKindWhat it shows
Conversion rate by the friction metColumn chartThe share of measured visits that converted, by the most telling friction each met, None first. From the Visits explore.
First visits back within 7 days, by the friction metColumn chartThe share of measured first visits followed by another visit within 7 days, by the most telling friction each met. From the Visits explore.

Where does it happen?

TileKindWhat it shows
Friction by page typeTableEach page type's measured page views, and the share of them with an error, a rage click, a dead click or a quick back. From the Page views explore.
The most frustrating elementsTableThe elements visitors rage clicked, dead clicked or met an error clicking, on the page each was on, with the visits that met them. From the Friction explore.

Which errors reach the most visits?

TileKindWhat it shows
JavaScript errors by the visits they reachedTableEach JavaScript error, grouped by name and normalised message, with the visits and visitors it reached, its error clicks, its pages and when it was last seen. From the Friction explore.

About friction

Friction is measured where a property turned it on, from the visits whose visitors consented, and every rate here is over those measured visits: it says Not captured where there are none. An error click is a JavaScript error within a second of a click; a rage click three clicks or more within a second of each other, in one spot; a dead click a click on something that looked clickable that nothing answered within a second; a quick back a page left for the one before within 10 seconds. A visit counts once, for the most telling friction it met. Errors are grouped by their name and message, with numbers, addresses, ids and quoted text other than a name taken out, and an error thrown in another site's script, such as a tag manager's or a widget's, is marked so. Dead clicks are a lower bound on pages that change by themselves, and a rage click on a quantity button is usually no frustration: in the Friction explore, Nothing answered the burst tells the two apart. Friction going with fewer conversions shows where to look; visitors who try harder also meet more of it.

Speed

TileKindWhat it shows
LCP, 75th percentileNumberLCP at the 75th percentile of measured page views, with its rating at web.dev's thresholds. From the Page views explore.
INP, 75th percentileNumberINP at the 75th percentile of measured page views, with its rating at web.dev's thresholds. From the Page views explore.
CLS, 75th percentileNumberCLS at the 75th percentile of measured page views, with its rating at web.dev's thresholds. From the Page views explore.
Good page viewsNumberThe share of measured page views whose LCP, INP and CLS, of those they measured, were each good: the Core Web Vitals' pass rate. From the Page views explore.

How many page views are fast, on mobile and on desktop?

TileKindWhat it shows
LCP by device typeStacked barsThe share of each device type's measured page views whose LCP was good, needed improvement or was poor. From the Page views explore.
INP by device typeStacked barsThe share of each device type's measured page views whose INP was good, needed improvement or was poor. From the Page views explore.
CLS by device typeStacked barsThe share of each device type's measured page views whose CLS was good, needed improvement or was poor. From the Page views explore.

Is it getting faster?

TileKindWhat it shows
LCP by week, 75th percentileLine chartLCP at the 75th percentile of each week's measured page views, against web.dev's thresholds. From the Page views explore.
INP by week, 75th percentileLine chartINP at the 75th percentile of each week's measured page views, against web.dev's thresholds. From the Page views explore.

Where is it slow?

TileKindWhat it shows
Speed by page typeTableEach page type's LCP, INP, CLS and TTFB at the 75th percentile, a cell that needs improvement tinted amber and a poor one red, and its share of good page views. From the Page views explore.
The slowest pagesTableThe pages with the slowest LCP at the 75th percentile, with their INP and CLS, a cell that needs improvement tinted amber and a poor one red. From the Page views explore.

Does speed cost conversions?

TileKindWhat it shows
Conversion rate by landing page speedColumn chartThe share of visits that converted, by their landing page's LCP rating. From the Visits explore.

About speed

Speed is rated as web.dev and the Chrome UX Report rate it: at the 75th percentile of measured page views, so three in four were at least that fast, Good, Needs improvement or Poor at web.dev's thresholds, and only once 20 page views measured it. In the tables a cell is tinted amber where it needs improvement and red where it is poor.

LCP, FCP and TTFB are a page load's, and a route change's only where Chrome reports soft navigations (from Chrome 151). INP needs an interaction. CLS is measured by Chromium browsers alone, and every browser on an iPhone or iPad is Safari's engine, so mobile INP and CLS lean on Android. Good page views were good on all three Core Web Vitals they measured.

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