Library
Use cases
What investment, data, sales and marketing teams build on firmographic, technographic, hiring and intent data.
50 pieces
- Adding company signals to lead scoringA lead score knows what a person did, not what the company is or is about to do. Here is how to add company features to it without double counting or leakage.
- Adding technographic filters to a prospecting toolA technology filter is a set of definitions before it is a dropdown. What "runs it now", "first seen" and "recently added" should mean, and the datasets and indexes that serve them.
- Benchmarking pay and talent demand for workforce planningA workforce plan needs the pay employers advertise for a role and how many of them are competing for it. Here is how to build both from job postings.
- Benchmarking sales compensation from advertised payQuartiles of advertised base pay and on-target earnings for sales roles, by country and week. Here is how to place a plan against them and how to read the result.
- Building a company knowledge graph from identifiers and eventsA company graph answers questions that span datasets. This guide gives the node and edge tables, the join that finds a brand's listed parent and the way to link your own records.
- Building a point-in-time company dataset for back-testsA back-test is only as honest as the dates in its data. This guide shows how a dated, write-once record lets you key company signals by when they were known and query as of a date.
- Building account-based marketing segments from company signalsA segment is a rule that names accounts and says why they are on the list. Here are recipes that combine fit with timing, the tables behind each and how to keep them current.
- Building company change alerts into your productAn alert is a dated event shown to someone who follows a company. This guide covers the tables to read, the schema to store, how to dedupe and what each message may say.
- Building thematic baskets from technology adoption dataA basket of adopters is only as good as its membership rule. Here is how to build one from website technology data, rebalance on dated events and test it.
- Catching companies as they enter a new marketA new market shows up in a company's site, its job board and its newsroom, each at its own moment. Here is how to join them into one dated timeline per country.
- Commercial due diligence on a target with public signalsBefore the data room opens, public signals can show where a target is hiring, selling and announcing, and how it compares with its competitors. Here is the method.
- Company data as context for AI agents and copilotsDesign the tools, the result format and the tests for an agent that answers questions about companies from dated, sourced rows instead of scraped pages.
- Company signals in credit research and counterparty monitoringPublic signals can flag a borrower under strain before the next report. This guide builds a watchlist from them and shows how to read each trigger beside your own credit file.
- Defining an ideal customer profile from dataDescribing your customers is not enough: a profile has to show what separates them from the market. Here is how to enrich won accounts, measure lift and test the result.
- Detecting go-to-market changes from pricing and key pagesThe key pages of a company website show how it sells. Here is how to turn changes to them, and to its markets and currencies, into a dated watch.
- Detecting restructuring early from postings and announcementsA restructuring leaves a pattern on a company's job board before it reaches a disclosure. Here is the pattern, the announcements that confirm it and the false alarms.
- Enriching company records in your data productEnrichment starts with a match and ends with a licence. Here is how to match records on domain, which fields to add, how to refresh them and what to settle for embedding.
- Event-driven research with Form 8-K filings and newsroomsA company tells you what it has done in two places, its newsroom and its Form 8-K. Here is how to join them into one dated calendar and where the labels stop.
- Expansion signals for account managementCustomers often show growth in public before they ask for more. Here is how to read it from their websites, job boards and announcements, and rank the accounts worth a call.
- Finding accounts by the technology they runThree list patterns on the marketing stack datasets, what account ids add to them, and the checks that keep a technology list from sending a rep to the wrong company.
- Following private funding with SEC Form D filingsForm D is one of the few primary records of private fundraising. This guide explains what it holds, how to read its amounts and dates, and where the record stops.
- Keeping a warehouse in step with incremental API syncA daily sync that resumes after a failure, runs twice without harm and notices a period that arrives late. The design, table by table, with the keys and the checks.
- Mapping a partner ecosystem from technology co-occurrenceCo-occurrence on company websites shows whose audience overlaps yours. A worked method with the datasets, the lift measure and the checks that separate partners from rivals.
- Mapping alternative data to a security masterJoining company data to securities is a many-to-many problem. This guide covers the identifiers every listed company carries, the join order, parents and brands, delistings and check digits.
- Measuring AI adoption across listed companiesNo single public signal measures AI adoption. Here is how to read three of them from company data, combine them into a score you can audit and avoid keyword traps.
- Measuring an installed base and its weekly movementPrevalence per 100 websites, adds, removals and net change for any recognised technology, with the checks that keep coverage growth out of the result.
- Measuring remote and hybrid work trends by industryThe share of new postings that state remote or hybrid work can be read every week by industry and country. Here is what it counts, how to pull it and how to read it.
- Monitoring supplier and vendor risk with public company signalsPublic signals tell a procurement team where to look in a supplier list. Here is how to read announcements, hiring and site changes, and how to turn them into a review queue.
- Personalising campaigns by technology stack and growth stageKey campaign variants on what an account runs, how fast it is hiring and what it announced last week. A rule set, a query and the guardrails that keep copy accurate.
- Portfolio company monitoring for private equity teamsPublic signals give an operating partner a weekly outside view of each portfolio company and its competitors. Here is how to build the watchlist and design the digest.
- Powering account scores in a sales platform with licensed signalsFor product teams that put a score beside each account: what a weekly row carries, the three states a score can be in, how to survive a version change and what to settle in the licence.
- Prioritising accounts with company-level intent scoresA weekly ranking of target accounts from company-level intent scores, with the join to fit, the evidence a rep can read, and the test that shows whether the ranking earns its place.
- Producing market research from weekly aggregate seriesA weekly series is only as good as its footnote. Here is how research and media teams pull the Fokals Market Series, test a number before it is printed and cite it.
- Reading a competitor's strategy from its hiringFunctions, seniority, locations and tools named in a competitor's postings show where it is investing before the product does. Here is a monthly brief built from them.
- Reading technology adoption as a signal of vendor revenueFor a vendor whose product shows on its customers' websites, installs and net adds are a dated proxy for customer growth. Here are the measure, the query and how to read it.
- Recruiting intelligence: finding companies that are hiring nowA company that is hiring is a prospect for a recruiter or an HR-tech seller. Here is how to find them by role and place, rank them by growth and avoid false leads.
- Redistributing company data to your customers under licenceA working list for platforms and product teams that deliver licensed company data onward: what the data carries, what you can promise customers and which questions to put in writing.
- Retrieval-augmented generation over structured company signalsMost questions about companies ask for a count, a date or a list, which a database answers exactly. This guide shows what to embed, what to filter and what to leave to SQL.
- Running competitor displacement plays from technology changesA rival tool leaving a company website is a dated, public change. How to read added and removed events, tell a swap from a flicker, and measure whether the plays work.
- Sector hiring trends for macro and thematic researchA thematic view is a claim about a sector, not one company. Here is how to read hiring series that hold their company cohort fixed, and how to test a theme across industries.
- Sizing a total addressable market with technographic countsCount the companies that run a technology, state how many of your list the data can see, and multiply by your own price. A worked method with its traps.
- Sourcing private companies for venture capital with growth signalsTurn public signals into a short, repeatable list of private companies worth a first call, with the query, the thresholds to start from and how to read what comes back.
- Spotting churn risk when a customer removes your technologyWhen a customer's website stops loading your tag, the record is dated and public. Here is how to turn removals and competitor additions into a churn alert you can test.
- Territory planning with firmographic and hiring dataEqual account counts hide unequal opportunity. How to weight accounts by fit and hiring momentum, balance territories on that weight and check each cell against Market Series.
- Timing outreach with hiring signalsA posting names what a company is about to build and often the tools the role needs. Six hiring signals, where to read each one, the play it supports and how to test the play.
- Tracking competitor launches and partnerships at the sourceA competitor's newsroom, feeds and site changes show what it launches and with whom, in its own words and dates. A watchlist method with the datasets, event types and queries.
- Tracking sales team build-out as a sign of growth plansSales capacity is hired before it produces revenue. Here is how to read a company's sales postings as a weekly record of what it plans to sell, to whom and where.
- Training and evaluating models on dated company signalsA model on company signals is only as honest as its feature table. This guide builds one as of each date, splits by time and names the properties of the record that keep it safe.
- Trigger events for outbound: funding, leadership and launchesA trigger event is a dated change that gives a seller a reason to write now. Here are the 13 event types in company announcements and regulatory disclosures, and how to rank them.
- Using hiring data in equity research between earningsA company reports four times a year and hires every day. Here is how to turn its job postings into a research signal you can test and trust.