Similarweb Top Websites & App Intelligence

Every argument about where attention lives on the internet eventually needs a scoreboard. This is the scoreboard: Similarweb publishes two ranked surfaces - a Top Websites table naming the most visited domains worldwide or per country and category, and Top Apps store leaderboards naming what people are actually installing - and behind them sits a tracked universe of roughly four million apps with the quantitative layer attached.

The two halves answer different halves of one question. The website table carries behavior: rank, category, rank change, average visit duration, pages per visit and bounce rate, so you can see not just who leads but how visitors behave once they arrive. The app side splits into standings - rank and movement on the Top Free, Top Paid and Top Grossing boards of each store - and metrics: downloads, DAU/WAU/MAU, stickiness, session counts, estimated revenue and day-1/7/30 retention across 58 countries and up to 37 months of history.

As a dataset this is the attention ledger of the application software market, normalized into one flat record shape. Get a sample of this dataset and the dictionary below stops being hypothetical.

Records exactly as captured during the August 2026 verification pass:

rank        : 1
website     : google.com
category    : Search Engines
period      : July 2026, Worldwide

rank        : 5
website     : chatgpt.com
category    : AI Chatbots and Tools
period      : July 2026, Worldwide

leaderboard : Top Free Apps (Google Play, US)
columns     : Rank, Change
ranking_date: August 18, 2026

Read the middle capture twice. A conversational AI assistant sits fifth among every domain on earth, between instagram.com and facebook.com, under three years after shipping. Nothing else in the software market moves a top-five slot that fast, and this is the dataset where such movement shows up first - as a rank change, before any press release confirms it.

The app capture shows the standings layer bare: rank and movement, nothing else on the board. The downloads, sessions and revenue ride on the metric fields that join on app identity. Get a sample of this dataset filtered to your domains, apps, categories or countries and it arrives in the same shape.

Fourteen documented fields spanning both halves of the dataset - seven describing ranked websites and their visitor behavior, seven describing apps and their commercial performance. Definitions verified against live records during the August 2026 pass.

Geography - worldwide rankings plus a country dimension: website tables cut per country and category, app intelligence spanning 58 countries. Share-of-attention questions are inherently local - a productivity app that owns Germany tells you little about Brazil - so the geographic cut is where most analyses start.

Temporal - every ranking is a dated snapshot, and the archive runs deep: up to 37 months of app history and up to 7 years of web history. That depth turns a leaderboard into a longitudinal panel - rank trajectories, seasonal curves, the slow displacement of one category by another.

Granularity - per-domain and per-app records, keyed on identity so successive deliveries join cleanly. The headline boards are deliberately cut lists - the leading fifty domains per view and fifty-one apps per board - while the tracked universe beneath extends the app side to roughly four million records.

API, files, or your warehouse. Daily, weekly, or hourly.

Samples precede any commitment, and recurring deliveries land keyed on domain and app identity, so each pull joins cleanly to the last and to whatever else you already hold.

• Share-of-attention tracking - watch your category's top domains quarter over quarter: visit duration, pages per visit and bounce rate move before revenue does (competitive intel product teams x application software).
• App launch and growth analysis - downloads, DAU/WAU/MAU and retention curves for any tracked app turn a rival's launch into a measurable curve instead of a rumor (investors and quants x application software).
• Category heat maps - rank movement aggregated by category shows where consumer attention is migrating, weeks before earnings calls admit it.
• Territory and account prioritization - rank high-traffic domains and high-grossing apps by country to sequence outreach and partnerships (sales growth teams x application software).
• Benchmarking studies - engagement norms per category give consultants a defensible yardstick for client performance reviews.
• Citable market facts - "fifth most visited website on earth" is a sentence every audience already understands, sourced from the reference point the industry itself uses (journalists academics x application software).

Competitive intelligence and product teams get the market's own scoreboard: rivals' domains and apps, ranked, with behavior attached. Investors and quant researchers read downloads, usage and retention across millions of apps as bottom-up evidence for which niches compound. Market researchers and consultants benchmark clients against category engagement norms instead of vendor-supplied case studies. Sales and growth teams rank prospects by actual traffic and grossing position rather than headcount guesses. Data scientists and ML engineers get a stable, identity-keyed panel of engagement metrics suitable for trajectory modeling. Developers and data-product builders wrap domain and app rankings into dashboards their stakeholders already know how to read.

Stated plainly, because they shape the analysis:

• Headline boards are cut lists. The famous tables name the leading fifty domains per view and fifty-one apps per board; everything outside the cut lives in the tracked universe rather than the leaderboard. Depth questions route through the metric layer, not the front page.
• Figures are modeled, and disclosed as such. The publisher states its data includes estimations and extrapolations. Readings are strongest compared within the same methodology - share and trend questions - and weakest as absolute-size claims.
• Standings alone carry little. An app board row is rank and movement; the commercial story requires the joined metric fields, which is a design decision to know about before charting.
• Ranks are snapshots. Boards re-rank continuously; a stored rank is a dated observation, and time-series work means accumulating scheduled deliveries rather than reconstructing history after the fact.
• Web and app halves measure different things. Visit duration is not screen time; a domain ranking and a grossing board answer adjacent but distinct questions. Keep them labeled.

Because the raw artifact is two leaderboards that reset while you watch, and every serious question wants a table with history. Datadory normalizes both halves into the fourteen-field dictionary above, joins standings to metrics on app identity, cuts samples to your domains, apps, categories or countries, and schedules deliveries into your warehouse so thirty-seven months of app history becomes a longitudinal panel instead of a folder of screenshots. Browse the rest of the shelf on the application software data hub, the best application software datasets ranking, or the full catalog.

Application Software catalog neighbors that answer the questions this one raises. StatCounter Global Stats tracks browser, engine and platform share from measured page views - the installed base behind the traffic this dataset ranks. Apple iTunes Search API exposes catalog metadata, prices and ratings for iOS apps, the storefront facts beside the usage curves here. Chrome Web Store Extensions & Apps covers the extension economy that never touches a website ranking. G2 Software Categories & Product Pages and Capterra Software Directory hold the B2B verdict - review counts, ratings and pricing - for software bought by companies rather than downloaded by people. Together they cover the whole software market from consumer attention to enterprise procurement.