A fund that buys alternative data about what companies do on the web can use it only once every record is mapped to a ticker, or to an identifier that outlives a change of ticker. This comparison sets four providers of company-level web data side by side, Thinknum, Similarweb, LinkUp and Fokals, on four points: what each observes, how a record is tied to a listed security, how the history is dated and how the data is delivered. After it you can read any provider's documentation against the same four points and test its ticker mapping on a sample of names.
Every statement about a provider comes from its own pages, read on 7 October 2026 and linked where it is used. Where those pages do not cover a point, the text says that we found no statement on the pages read, which describes the pages and not the product. No provider is ranked. Nothing here is investment advice, and nothing here claims that any dataset predicts a share price or an investment result.
Which alternative data providers deliver company-level web data mapped to tickers?
Thinknum, Similarweb, LinkUp and Fokals each document company-level web data tied to listed securities. Thinknum's datasets are queried by ticker, Similarweb maps tickers to domains and apps, LinkUp describes a dated ticker reference file, and Fokals carries ticker, MIC, ISIN, LEI and share-class FIGI on every listed company.
An observation is made on a website or an app, and the columns of the table say which security stands behind it, by which identifiers, and with which dates. Together they decide how much work the join to your security master will be, and whether a back-test sees point-in-time data.
| Provider | Observed on the web | Tie to a listed security | Dating and history | Delivery |
|---|---|---|---|---|
| Thinknum | Datasets that include job listings, store locations, products and discounts by vendor, and Apple App Store ratings | A query names a dataset and a list of tickers, each written as a market and a symbol. A ticker search returns the entities under each ticker. The company metadata example shows a security entry with a CUSIP and an ISIN | A Historical API for a dataset's history or a daily update feed, in daily files combined into a monthly file. Each record has a unique identifier column for syncing additions and updates. On whether the history is point-in-time we found no statement on the pages read | An API with results as JSON, CSV, XLS or XLSX, and software with queries, charts and alerts by email |
| Similarweb | Web, app and user engagement trends on public and private companies: visits and bounce rate for domains, average users for apps | A ticker mapping that connects domains and apps to a company. Tickers are mapped to ISINs, with a synthetic ISIN standing in for a missing code, and the data is aggregated by stock | Point-in-time mapping: a start and an end date for events on each subsidiary and brand, reviewed monthly. On whether the metrics are point-in-time we found no statement on the pages read | Dashboards, an API, and files through Amazon S3 or Snowflake |
| LinkUp | Job listings sourced directly from company hiring websites | A company ID on every job record. A company ticker reference with ticker, exchange, exchange country and a primary flag, and reference files for ISIN, CUSIP and SEDOL mapped through a FactSet concordance | A job record carries the time it was first observed, last changed, last seen and last not found. The ticker and company references are point-in-time, with a start and an end date on each row | Snowflake, AWS, Azure, GCP, FTP, Databricks and Google BigQuery |
| Fokals | The technologies each company website runs and every dated change to them, every role a company publishes, company announcements and regulatory disclosures by event type, stated headcount and the monthly traffic tier of each website | One stable company ID. Ticker, MIC, ISIN, LEI and share-class FIGI on every listed company, and its SEC CIK where it has one. A brand or subsidiary carries the identifiers of its listed parent | Each record carries the time it was observed. Daily and weekly datasets are written once, after the period closes, and are never revised | A REST API in JSON with cursor pagination, bulk exports as JSON, JSON Lines or CSV with a manifest, and a signed-in dashboard |
The rows rest on these pages.
- Thinknum. Its dataset catalogue, home page and About page, and in its documentation the Query API, the Company API, the Historical API and the page on saving a query as a file.
- Similarweb. Its Stock Intelligence page and its article on ticker mapping, dated 23 September 2024.
- LinkUp. Its RAW product page and the data dictionary of the RAW feeds, last updated on 9 June 2026.
- Fokals. The data dictionary, the methodology and the page for investors.
Ticker mapping for web traffic, pricing, job postings and app data: what Thinknum, Similarweb and LinkUp document for investors
Among providers that document a ticker mapping, Similarweb covers web traffic and app engagement, Thinknum covers product pricing, store locations and job listings, and LinkUp and Fokals cover job postings, with website technologies and company announcements also in Fokals. AlphaSense and YipitData are outside this comparison only because their documentation was not read for it.
| Data type | Documented by | What its pages say is observed |
|---|---|---|
| Web traffic | Similarweb | Total visits, unique visits and bounce rate for domains |
| Web traffic | Fokals | The monthly traffic tier of each company website |
| App data | Similarweb | Monthly, weekly and daily average users for apps |
| App data | Thinknum | Apple App Store data that includes release date, ratings and pricing |
| Pricing | Thinknum | Pricing and average discount by vendor, by product and by location |
| Store locations | Thinknum | Store location data for tracking store growth |
| Job postings | Thinknum | Job listings filtered by title, location, type, category and date of posting |
| Job postings | LinkUp | Job listings from company hiring websites, each dated when first observed |
| Job postings | Fokals | Every role a company publishes, labelled by job function and seniority, with daily open, new and closed postings for each company |
| Website technologies | Fokals | The technologies each company runs, each with its first-seen and last-seen dates, and a dated event for every adoption and removal |
| Announcements | Fokals | Company announcements and regulatory disclosures, classified by event type |
The data type decides what a mapping has to hold: the domains and apps behind each security for traffic and app data, the careers sites of each employer and its listed parent for job postings, and the retailers or vendors of each listed company for prices and store locations.
What each provider documents about the tie to a security
Each section goes one level deeper than the table.
How Thinknum ties company web data to a ticker as alternative data
Thinknum's API documentation keys its datasets to tickers. A ticker is written as a market and a symbol, a query names a dataset with a list of tickers, and a ticker search returns the entities filed under each one. The company metadata example carries a security entry with a CUSIP and an ISIN.
The Query API page shows the convention in the form nasdaq:aapl, and a query with an empty ticker list returns the whole dataset. The example of a ticker search shows two named entities under one ticker, so a ticker can stand over more than one entity. The Company API lists companies as pairs of ticker and name and can be searched by domain, which gives a second way in from a website.
The Historical API is described as the route for clients who download a daily feed, and the unique identifier column on each record lets a store be kept in step with additions and updates. The guide to Thinknum alternatives covers the application and other sources of the same kind.
What Similarweb says about stock tickers and company web data as alternative data
Similarweb's Stock Intelligence pages describe web, app and user engagement trends on public and private companies, with a ticker mapping that connects domains and apps to a company. Its article on the mapping, dated 23 September 2024, describes tickers mapped to ISINs, start and end dates for subsidiary and brand events, and data aggregated by stock.
In the article, parent, subsidiary and regional domains are brought into one database with the ticker and the subsidiary names. Tickers are mapped to ISINs, and a synthetic ISIN stands in where a code is missing. Each subsidiary and brand receives a start and an end date for point-in-time events, and the article says Similarweb's research analysts review the file each month.
A synthetic ISIN is a detail to raise before a join: ask how one is marked, so that it is never matched against a real code in your master.
LinkUp: job postings with a point-in-time ticker reference
LinkUp's RAW page says it sources job listings directly from company hiring websites. Its data dictionary defines four times on a job record: when the job was first observed, when a change to it was last observed, when it was last seen and when it was last looked for and not found.
The same document describes a company ticker reference that holds point-in-time ticker information for each company ID. Every row has a start date and an end date for joining point-in-time information, the exchange and its country, and a flag for the primary ticker. Further files hold point-in-time ISIN, CUSIP and SEDOL, described as mapped through a FactSet concordance. A point-in-time company reference holds the company's name, its website, a legal entity identifier and an open PermID on dated rows, and the dictionary says it can be joined to job records to understand a corporate change such as a change of name. The guide to LinkUp alternatives sets other sources of job data beside it.
Fokals: security identifiers on every row of a listed company
Fokals delivers firmographic, technographic, hiring and intent data on public and private companies, collected from first-party company sources and public records and processed in-house. Every company has one stable company ID. A listed company carries its ticker, MIC, ISIN, LEI and share-class FIGI, and its SEC CIK where it has one. A brand or subsidiary carries the identifiers of its listed parent, so a record observed on a brand's website arrives with the parent's security on the row.
The hiring and marketing stack pages describe the datasets, and coverage describes the companies.
A worked example: testing a ticker mapping on a sample of names
The test runs on any provider's sample. This example is illustrative: Acme Robotics is an invented listed company, and every figure is invented.
Assumptions:
- Your sample request names 50 listed companies from your security master, each with an ISIN, a ticker and a MIC.
- Acme Robotics is one of the 50. It owns a consumer brand with a website of its own, and it changed its ticker once inside the sample period.
- From your own records you know 15 websites that belong to 10 of the 50 names.
- The sample's reference file gives each ticker a start and an end date.
Step 1: the key ladder. Try the strongest key first and record which key matched each name. The ISIN comes first: the Association of National Numbering Agencies describes ISO 6166 as the global standard for identifying financial instruments uniquely, and the last of its 12 characters is a check digit, so a mistyped code can be caught before the join. A ticker comes next, tried with its market identifier code, the ISO 10383 code that identifies an exchange, a trading platform, another market or a trade reporting facility as a source of prices.
| Key tried | Names tried | Result | Names left |
|---|---|---|---|
| ISIN | 50 | 43 matched | 7 |
| Ticker with MIC | 7 | 4 matched | 3 |
| Ticker alone | 3 | 1 with one candidate, 1 with two candidates | 1 |
Of the 50 names, 47 match on an identifier with no review (43 + 4), which is 94%. Two go to review, which is 4%, and one has no match, which is 2%. List the three by name and send them to the provider.
Step 2: the websites behind each security. For the 10 names whose websites you know, count how many of the 15 websites the sample ties to the right security. Here it is 12 of 15, or 80%. One of the three misses is the website of Acme Robotics' consumer brand, whose records arrive under a key of their own. Ask whether the brand is mapped to its parent and from which date.
Step 3: the dates. Acme Robotics is one of the four names matched on ticker with MIC. It has 120 records in the sample, 45 dated before its change of ticker and 75 after it. A join on the ticker your master holds today finds the 75, which is 62.5% of the 120. A join made as of each record's own date, with the start and end dates of the reference file, finds all 120. If a sample carries one current ticker on every row instead, the first join finds all 120, and the question moves to ownership: the date from which a brand's records count towards its parent.
Report the three figures together: 94% of names matched on an identifier, 80% of known websites tied to the right security, and 120 of 120 records joined across a change of ticker once the dates are used. The use case on mapping alternative data to a security master gives the join in full, with delisted names and check digits, and ISIN vs LEI vs FIGI covers the standards behind the keys.
Questions the pages leave to a conversation
Put the same questions to each provider and keep the answers with the sample.
- The key. Which key is permanent on the provider's own records?
- The reference. Which identifiers arrive on the row and which in a reference file, and does that file carry start and end dates?
- The web assets. Which domains, apps or careers sites stand behind each security, and who reviews the list?
- Changes to history. Is a delivered record or a closed period ever changed, and how is the change flagged?
- The sample. Can it be cut for the names you hold, over a period that contains a change of ticker?
Fokals publishes the documents these questions start from: the data dictionary defines every identifier column, the sourcing statement sets out what is collected and how, and sample data for the companies you name is sent on request. The guide to building a point-in-time dataset for back-tests shows what to do with the dates once the sample has passed.
Frequently asked questions
Which alternative data providers offer web scraping data mapped to stock tickers for hedge funds?
Four providers compared here document company-level web data keyed to listed securities. Thinknum indexes the data trails companies leave online and keys its datasets to tickers. LinkUp sources job listings from company hiring websites, with a point-in-time ticker reference. Similarweb maps tickers to domains and apps. Fokals carries ticker, MIC, ISIN, LEI and share-class FIGI on every listed company.
Does Thinknum map its datasets to tickers?
Yes. Thinknum's API documentation writes a ticker as a market and a symbol, and a query names a dataset with a list of tickers. A ticker search on a dataset returns the entities filed under each ticker. The example response of its Company API shows a security entry with a CUSIP and an ISIN, and companies can be searched by web domain.
Does Similarweb map websites and apps to stock tickers?
Yes. Similarweb's Stock Intelligence page describes a ticker mapping that connects domains and digital assets to a company. Its article on the mapping, dated 23 September 2024, describes tickers matched to domains and apps and mapped to ISINs, with a synthetic ISIN standing in for a missing code, a start and an end date for events on each subsidiary and brand, a monthly review by its analysts, and metrics aggregated by stock.
Is LinkUp's ticker mapping point-in-time?
LinkUp's data dictionary describes a company ticker reference that shows point-in-time ticker information for each company ID. Each row has a start date and an end date for joining point-in-time information, the exchange and its country, and a flag for the primary ticker. Further point-in-time files hold ISIN, CUSIP and SEDOL, described as mapped through a FactSet concordance.
Which identifiers does Fokals carry on a listed company?
Every company has one stable Fokals company ID. A listed company carries its ticker, MIC, ISIN, LEI and share-class FIGI, and its SEC CIK where it has one, and a brand or subsidiary carries the identifiers of its listed parent. Each record carries the time it was observed, and daily and weekly datasets are written once and never revised.
How do I test a provider's ticker mapping before licensing the data?
Ask for a sample for the names you hold and run three counts. First, the share of names that match on ISIN or on ticker with MIC, with no review. Second, the share of the websites you know that the sample ties to the right security. Third, for a name that changed its ticker, the share of its records that join as of each record's own date.
What this page says about the products it names was checked against their public documentation on 7 October 2026. Product and company names are trademarks of their owners. Fokals is not affiliated with them or endorsed by them.