Scrape.do gives developers one place to collect public web data at scale. Its Web Scraping API handles proxies, headers, CAPTCHAs, and JavaScript rendering, while its Ready APIs return structured JSON for popular sites in a single request.
That simplicity is the product promise. The measurement layer behind it needs to be just as focused.
Scrape.do uses tinyanalytics to understand how developers discover the product, which pages help them evaluate it, and how those visits progress toward signup and product use—without turning analytics into another system the team has to maintain.
One site, several high-intent journeys
A visitor might arrive looking for a general-purpose scraping API, a pre-built endpoint, pricing details, or an answer to a technical question. Each route signals a different need.
tinyanalytics brings those journeys into one view. Shared date ranges, filters, segments, and comparisons help the team move from a top-level traffic change to the pages and channels behind it without rebuilding the analysis in another tool.
From first visit to first API request
For an API product, a signup is only part of the story. The more useful question is whether a developer reaches a successful first request.
With pageviews and custom events in the same event model, Scrape.do can follow the path from a landing page to account creation and product activation. Funnels make each step visible, so the team can see where developers continue and where the journey needs a clearer explanation.
This keeps marketing and product teams focused on the same outcome: helping the right visitor get to working data faster.
Keeping automated traffic in context
Scrape.do operates in a world shaped by bots, crawlers, and automated requests. Treating every hit as a person would make acquisition reporting harder to trust.
tinyanalytics separates bot activity from human analytics. That gives the team a cleaner view of real visitor behavior while keeping automated traffic available for its own analysis.
Seeing how AI discovery grows
Developers increasingly discover tools through ChatGPT, Claude, Perplexity, Gemini, and other assistants. tinyanalytics identifies visits from AI assistants and reports AI crawlers separately from people.
For Scrape.do, that means AI discovery is measurable instead of being folded into a generic referral bucket. The team can compare landing pages, trends, and downstream behavior to understand which visits turn into meaningful product exploration.
Privacy-friendly by design
Scrape.do removes infrastructure work from web data collection. tinyanalytics follows the same practical principle for measurement: one small tracking script, no analytics cookies, no raw IP storage, and no cross-site profile.
That gives the team useful traffic and product insight while limiting the visitor data it has to manage. When a signed-in journey needs stable identity, Scrape.do can deliberately send its own customer ID through identify() rather than relying on a hidden browser profile.
Analytics that can grow with the product
Scrape.do already spans a flexible Web Scraping API and Ready APIs, with more tooling planned around proxies and browser-based scraping. As those product lines grow, the team can keep acquisition, activation, revenue, and reliability signals in one platform.
The result is a measurement setup that matches the product itself: simple at the first request, deep enough for the work that follows.
Ready to connect acquisition, product journeys, and revenue in one clear view? Start free or talk to our team to see how tinyanalytics can help.