# Propensify data sources Public-altitude guides for evidence Propensify can observe on a prospect company. This document is generated at website build from the same content as https://propensify.io/data-sources. It is not the Signal Catalogue. It does not list internal provider ids or scrape APIs. Canonical HTML hub: https://propensify.io/data-sources Compact bundle (LLM/planner): https://propensify.io/data-sources.compact.md Full bundle: https://propensify.io/data-sources.md ## Contents - [LinkedIn Ads](#linkedin-ads) — /data-sources/linkedin-ads - [Google Ads](#google-ads) — /data-sources/google-ads - [Meta Ads](#meta-ads) — /data-sources/meta-ads - [Website signals](#website-signals) — /data-sources/website-signals - [Website Ranking](#website-ranking) — /data-sources/website-ranking - [Search agents](#search-agents) — /data-sources/search-agents - [Companies House](#companies-house) — /data-sources/companies-house - [Crunchbase](#crunchbase) — /data-sources/crunchbase - [Firmographic & technographic](#firmographic-technographic) — /data-sources/firmographic-technographic - [Job openings](#job-openings) — /data-sources/job-openings - [Company workforce](#company-workforce) — /data-sources/company-workforce - [Employee voice](#employee-voice) — /data-sources/employee-voice - [Amazon Marketplace](#amazon-marketplace) — /data-sources/amazon-marketplace - [Customer reviews](#customer-reviews) — /data-sources/customer-reviews - [Company socials](#company-socials) — /data-sources/company-socials --- # LinkedIn Ads Firmographics tell you who a company is. LinkedIn Ads shows whether they’re buying attention now, how large that footprint looks, where ads send people, and what the creative mix looks like. _Data source — LinkedIn Ads signals Propensify detects: Ad Library activity, footprint, destinations, creative mix, geo reach, and stacked patterns — plus destination URL and messaging context._ HTML: https://propensify.io/data-sources/linkedin-ads Markdown: https://propensify.io/data-sources/linkedin-ads.md ## Three questions we ask of the ads 1. **Who are they aiming at?** — Job titles, seniority, and industry language in the creative — how tight the targeting story is, not a targeting-card row. 2. **What are they promising?** — Headline and description claims in the Ad Library sample. 3. **Where do they send you?** — Demo, dedicated landing page, content asset, or an opaque shortener. No matching creatives in this pass is unknown — not that they never advertise. ## Presence is a gate. Destination is the angle. ### Presence & activity Whether the company shows LinkedIn Ad Library creatives — and whether any look active now. ### Destination & creative Where those ads send people, plus format and CTA mix — demo, landing page, content, image vs document. ## How ads evidence stacks Four layers — start with whether ads look live, then scale, then where they send people, then creative and geo mix. 1. **Activity** — Live → historical 2. **Footprint** — Catalogue / impressions 3. **Destination** — Where ads send people 4. **Mix** — Creative & geo - **Activity first:** A large catalogue that isn’t active is a different conversation than ads running this week. - **Footprint ≠ spend:** Catalogue and impression bands are public Library scale — not billed spend. - **Destination is the angle:** Demo, landing page, content — where the click goes. Mix is format and geo, not organic Company socials. ## Activity Whether LinkedIn advertising looks live, recently started, or historical — read from creative date windows. Start with activity. A large catalogue that isn’t active is a different conversation than ads running this week. Live → historical ## Campaign activity Primary timing from creative start and end windows in the public Ad Library. _Live → historical_ - **Active now:** At least one creative window overlaps today — live paid pressure. - **Recently started:** New creatives in the last ~30 days — timing to engage. - **Recently ended:** Campaigns just wound down — not current pressure. - **Stale:** Historical Ad Library footprint — nothing looks active now. - **Thin dating:** Too few dated creatives to trust timing claims. ## Launch cadence Optional: how creative launches compare across recent vs prior windows. _Faster → slower_ - **Accelerating:** Launch rate up vs the prior window. - **Stable:** Steady launch cadence — neither surge nor fade. - **Decelerating:** Launch rate down vs the prior window. ## Footprint How large the Ad Library footprint looks — creative volume and reported impression bands. Bands are public ranges, not exact spend. Impression bands come from Ad Library ranges. Catalogue size prefers reported totals when pagination is incomplete. ## Catalogue Bands - **Large:** Many creatives in the public sample - **Moderate:** A meaningful set of creatives - **Small:** Few creatives visible - **Empty:** No Ad Library creatives found ## Impression Bands - **Very high:** Top public impression ranges in the sample - **High:** Material reported reach - **Mid:** Moderate reported reach - **Low:** Light reported reach - **Unknown:** No usable impression ranges ## Where ads send people Landing types the library can show. Cards map the paths. Several destination types can fire on the same account. ## Destinations - **Demo or trial:** Ads push product conversion paths. - **Dedicated landing page:** Campaign-specific pages — paid traffic into a focused URL. - **Content / PDF:** Gated or downloadable assets — content-led demand gen. - **Short-link heavy:** Many destinations are opaque shorteners — funnel hard to read. - **Sparse / unclear:** Few readable destinations in the Ad Library sample. ## Creative & CTAs Format and call-to-action mix across the fetched creatives. ## Creative - **Image-led:** Most typed ads are single-image creatives. - **Document-heavy:** Meaningful share of document / native content ads. - **Learn more CTAs:** Soft “Learn more” dominates non-null CTAs. - **CTA sparse:** Many creatives have no readable CTA. ## Geo reach Whether impression share looks concentrated in one market or spread across many. ## Geo - **Concentrated:** Impression share often skewed to one market. - **Multi-market:** Reach pattern spans several countries. - **Unknown:** Geo opaque in the fetched sample. ## When signals stack Combinations that are sharper than any single card. ## Composites - **Scaled and active:** Real LinkedIn presence that’s live — prioritize. - **Paid traffic into a landing path:** Ads buying attention into conversion-style URLs. - **Content-led demand gen:** Paid content engine, not only brand noise. - **Historical only:** They’ve advertised — but not a live “why now.” ## Context we also surface Inventory from the sample — destination URLs, headline keywords, CTA counts — not a second reading of the ads. ## Items - **Destination URL profile:** Unique landing URLs and path stems ads actually point at. - **Themes & keywords:** Keyword inventory from headlines and descriptions — recurring tokens, not a reading of the promise. - **CTA inventory:** Which calls-to-action appear, and how often they’re missing. - **Audit sample:** In deep mode: top creatives with headline, dates, and destination URL. ## What it looks like in a verified fit LinkedIn Ads evidence lands as findings on the account — with the same Fit and Signals score grammar as the product. Meridian Ops ## Findings - **Active LinkedIn ads** - **Ads into a dedicated landing path** - **Scaled and active** ## Boundaries & method - Public Ad Library sample — not Ads Manager spend or exact impression totals. - Impression fields are ranges; we use them as relative bands. - We paginate the library (default several pages) — still incomplete when totals exceed what we fetch. - Short links stay unclear until resolved — we don’t invent the landing page. - No Ad Library ads ≠ “never advertises.” Pair with Website Ranking or hiring when the ICP needs traffic floor or capacity. ## Want LinkedIn Ads on your verified fits? We’ll map activity, footprint, destinations, and creative mix to your ICP and show how they look on real accounts for your market. - [Get 10 vetted companies →](https://propensify.io/#lead) - [Book a call](https://propensify.io/book-a-call) --- # Google Ads Firmographics tell you who a company is. Google Ads shows whether they’re buying attention on Google now, how large that public footprint looks, which surfaces carry it, and where ads send people. _Data source — Google Ads signals Propensify detects: public Transparency activity, catalogue honesty, Search/YouTube/Shopping mix, destinations, offer intent, and stacked patterns._ HTML: https://propensify.io/data-sources/google-ads Markdown: https://propensify.io/data-sources/google-ads.md ## Three questions we ask of the ads 1. **Which queries and messages?** — Search copy and headlines in the Transparency sample. 2. **What offer is the click for?** — Demo, content, shopping — the intent the click is meant to start. 3. **Which URL is doing the work?** — The destination path in the sample — not assuming the homepage. No matching creatives in this pass is unknown — not that they never advertise. ## Presence is a gate. Path is the angle. ### Presence & activity Whether the domain shows public Google Transparency creatives — and whether any look recently shown. ### Path & surfaces Where ads send people, what offer shape they push, and whether that pressure is Search-, YouTube-, or Shopping-led. ## How ads evidence stacks Four layers — start with whether ads look live, then scale, then where they send people, then which Google surfaces carry the pressure. 1. **Activity** — Live → historical 2. **Footprint** — Catalogue / impressions 3. **Destination** — Where ads send people 4. **Mix** — Search · YouTube · Shopping - **Activity first:** A large catalogue that isn’t recently shown is a different conversation than ads live this week. - **Footprint ≠ spend:** Catalogue and impression bands are public Transparency scale — not billed spend. - **Destination is the angle:** Offer path and landing type. Mix is Search / YouTube / Shopping — not Website signals pixels. ## Activity Whether Google advertising looks live, recently started, historical, or too thinly dated to trust. Start with activity. A large catalogue that isn’t recently shown is a different conversation than ads live this week. Impressions may be missing even when activity is clear. Live → historical ## Campaign activity Primary timing from lastShown / creative windows in the public Transparency sample. _Live → historical_ - **Active now:** At least one creative recently shown — live paid pressure. - **Recently started:** New creative started recently — timing to engage. - **None active:** Footprint exists, but nothing looks currently shown. - **Stale:** Historical Transparency footprint only. - **Insufficient dates:** Too few dated creatives to trust timing claims. ## Launch cadence & texture How creative launches compare across windows — plus always-on vs short-flight patterns. _Faster → slower_ - **Accelerating:** Launch rate up vs the prior window. - **Decelerating:** Launch rate down — cooling, not gone. - **Stable:** Steady launch cadence — no false urgency from launches alone. - **Always-on:** Overlapping long-running creatives suggest persistent presence. - **Burst / flight:** Short flights — bursty activity, not always-on. ## Footprint How large the Transparency footprint looks — creative volume (fetched and/or public estimate) and impression bands when present. Bands are range proxies, not Ads Manager totals. Catalogue can use the public estimate when it’s larger than what we fetched. Unavailable impressions are common — not proof of low spend. Incomplete pagination means we don’t claim the full catalogue was analyzed. ## Catalogue Bands - **Large:** Large Transparency catalogue (fetched and/or estimate) - **Moderate:** Material catalogue in sample or estimate - **Small:** Limited creative catalogue - **Empty:** No creatives to size ## Impression Bands - **Very high:** Top reported Transparency impression bands - **High:** High impression band (range proxy) - **Mid:** Mid impression band (range proxy) - **Low:** Low or uncertain impression band - **Unavailable:** No parseable impression fields in the sample ## Where on Google The same “running ads” story changes depending on which Google surfaces carry the creatives. Several surfaces can fire on the same account. ## Surfaces - **Search-led:** Search carries most of the platform signal — intent-shaped GTM. - **YouTube present:** Material YouTube distribution in the sample. - **Shopping present:** Material Shopping distribution. - **Multi-surface:** Creatives span more than one Google surface. ## Where ads send people — and what they’re offering URL path and offer shape. Cards map the types. Several destination and offer types can appear together. ## Destinations - **Demo or trial:** Ads push demo/trial-style conversion paths. - **Dedicated landing page:** Campaign-style paths — paid traffic into a focused URL. - **Content / gated:** Gated or downloadable content-style destinations. - **Pricing:** Ads push pricing or plans-style destinations. - **Compliance:** Compliance / security-style destination paths. - **Homepage-heavy:** Many ads point at homepage-style URLs — shallower funnel. - **Sparse / unclear:** Funnel path poorly observable in the sample. ## Offers - **Demo or trial:** Conversion-path offer shape. - **Pricing:** Plans / pricing push in copy or path. - **Compliance:** Compliance / security-led demand intent. - **Competitive:** Conquesting-style competitive messaging. - **Content lead:** Content / lead-magnet style offers. - **Mixed:** Multiple distinct offer intents in the sample. ## When signals stack Combinations that are sharper than any single card. ## Composites - **Scaled and active:** Real Google presence that’s live — prioritize. - **Paid traffic into a landing path:** Ads buying attention into conversion-style URLs. - **Search-led GTM:** Search-shaped paid GTM on Google. - **Compliance-led demand:** Compliance angle visible in paid Google. - **Competitive conquesting:** Competitive messaging in market now. - **Homepage-heavy always-on:** Persistent presence with a shallower funnel. - **Historical only:** Footprint without current pressure. ## What it looks like in a verified fit Google Ads evidence lands as findings on the account — with the same Fit and Signals score grammar as the product. LatticeForge ## Findings - **Active Google ads** - **Search-led GTM** - **Scaled and active** ## Boundaries & method - Public Transparency sample — not Google Ads Manager spend, clicks, or exact impressions. - Impression fields are ranges and often missing; Unavailable ≠ low spend. - Catalogue may use a public estimate larger than fetched; pagination can be incomplete. - Short links stay unclear until resolved — we don’t invent the landing page. - No public Transparency ads ≠ “never advertises on Google” (non-public / login-gated ads exist). - Domain seed quality matters; multi-advertiser IDs under one domain can mix attribution. Pair with Website Ranking or LinkedIn Ads when the ICP needs traffic floor or LinkedIn-specific GTM. ## Want Google Ads on your verified fits? We’ll map activity, footprint, surfaces, and destination / offer paths to your ICP and show how they look on real accounts for your market. - [Get 10 vetted companies →](https://propensify.io/#lead) - [Book a call](https://propensify.io/book-a-call) --- # Meta Ads Firmographics tell you who a company is. Meta Ads shows whether they’re buying attention on Meta now, how large that public footprint looks, whether Instagram carries it, and where ads send people. _Data source — Meta Ads signals Propensify detects: Meta Ad Library activity, footprint, Facebook/Instagram mix, destinations, offer intent, and stacked patterns._ HTML: https://propensify.io/data-sources/meta-ads Markdown: https://propensify.io/data-sources/meta-ads.md ## Three questions we ask of the library 1. **What claim is the creative making?** — The promise in the copy and the visual — what they want the viewer to believe. 2. **What motion is the CTA?** — Shop, sign up, learn more, message — the action the creative asks for. 3. **Is the program alive or collapsing?** — A reading of the library sample. Activity continua still count live versus historical when dates exist. No ads in this pass is unknown — not that they do not advertise. ## Presence is a gate. Path is the angle. ### Presence & activity Whether the page shows Meta Ad Library creatives — and whether any look active now. ### Path & surfaces Where ads send people, what offer shape they push, and whether that pressure is Facebook-, Instagram-, or multi-surface-led. ## How ads evidence stacks Four layers — start with whether ads look live, then scale, then where they send people, then Facebook / Instagram mix plus creative and geo. 1. **Activity** — Live → historical 2. **Footprint** — Catalogue / impressions 3. **Destination** — Where ads send people 4. **Mix** — Surfaces, creative & geo - **Activity first:** A large catalogue that isn’t active is a different conversation than ads running this week. - **Footprint ≠ spend:** Catalogue and impression bands are public Library scale — not billed spend. - **Destination is the angle:** Offer path and landing type. Mix is Facebook / Instagram plus creative and geo — not organic Company socials. ## Activity Whether Meta advertising looks live, recently started, winding down, or too thinly dated to trust. Start with activity. A large catalogue that isn’t active is a different conversation than ads running this week. Default searches are often active-only — historical inactive creatives may not be in the sample. Live → historical ## Campaign activity Primary timing from Ad Library active flags and creative date windows. _Live → historical_ - **Active now:** At least one creative appears active — live paid pressure. - **Recently started:** New Meta creative started recently — timing to engage. - **Recently ended:** Campaigns just wound down — not current pressure. - **Stale:** Historical Ad Library footprint — nothing looks active now. - **Insufficient dates:** Too few dated creatives to trust timing claims. ## Launch cadence & texture How creative launches compare across windows — plus always-on vs short-flight patterns. _Faster → slower_ - **Accelerating:** Launch rate up vs the prior window. - **Decelerating:** Launch rate down — cooling, not gone. - **Stable:** Steady launch cadence — no false urgency from launches alone. - **Always-on:** Overlapping long-running creatives suggest persistent presence. - **Burst / flight:** Short flights — bursty activity, not always-on. ## Footprint How large the Ad Library footprint looks — creative/collation volume and impression bands when present. Commercial Meta ads often lack impressions; catalogue and activity carry scale then. Impression bands are range proxies, not Ads Manager totals. Unavailable is common — not proof of low spend. When ad details include reach, we also surface material vs low reach as a secondary scale check. ## Catalogue Bands - **Large:** Large Meta creative/collation catalogue in the sample - **Moderate:** Material catalogue in the fetched sample - **Small:** Limited creative catalogue - **Empty:** No creatives to size ## Impression Bands - **Very high:** Top reported Ad Library impression bands - **High:** High impression band (range proxy) - **Mid:** Mid impression band (range proxy) - **Low:** Low or uncertain impression band - **Unavailable:** No parseable impression fields in the sample ## Where on Meta The same “running ads” story changes depending on which Meta surfaces carry the creatives. Several surfaces can fire on the same account. ## Surfaces - **Instagram-led:** Instagram is the main distribution surface in the sample. - **Instagram present:** Material Instagram distribution alongside other surfaces. - **Multi-surface:** Creatives span more than one Meta surface. - **Cross-surface always-on:** Always-on presence across multiple Meta surfaces. ## Where ads send people — and what they’re offering URL path and offer shape. Cards map the types. Several destination and offer types can appear together. ## Destinations - **Demo or trial:** Ads push demo/trial-style conversion paths. - **Dedicated landing page:** Campaign-style paths — paid traffic into a focused URL. - **Content / gated:** Gated or downloadable content-style destinations. - **Ecommerce:** Commerce or product-style destinations. - **Webinar / event:** Registration-style event or webinar paths. - **Careers:** Recruiting or careers destinations. - **First-party offers:** Ads use first-party offer or marketing hosts. - **Homepage-heavy:** Many ads point at homepage-style URLs — shallower funnel. - **Sparse / unclear:** Funnel path poorly observable in the sample. ## Offers - **Content lead:** Content / lead-magnet style offers. - **Demo or trial:** Conversion-path offer shape. - **Webinar / event:** Event or webinar-style offer intent. - **Ecommerce / product:** Product or commerce-style offer intent. - **Recruiting:** Hiring-style offers — often noise for demand-gen ICPs. - **Mixed:** Multiple distinct offer intents in the sample. ## Creative & CTAs Format mix and DCO patterns across the fetched creatives. ## Creative - **Video-heavy:** Video-led Meta creative mix. - **Image-led:** Image-led Meta creative mix. - **DCO-heavy:** Dynamic creative optimization formats dominate. - **Hard conversion CTAs:** Shop / sign-up / buy-style CTAs are material. - **Learn more CTAs:** Soft “Learn more” dominates non-null CTAs. - **CTA sparse:** Many creatives have no readable CTA. ## Geo reach Whether targeting or reach looks concentrated in one market or spread across many — when ad details expose it. ## Geo - **Concentrated:** Targeting or reach often skewed to one market. - **Multi-market:** Reach or targeting spans several countries. - **Unknown:** Geo opaque without usable location or reach detail. ## When signals stack Combinations that are sharper than any single card. ## Composites - **Scaled and active:** Real Meta presence that’s live — prioritize. - **Paid traffic into a landing path:** Ads buying attention into conversion-style URLs. - **Content-led demand gen:** Paid content engine, not only brand noise. - **Always-on content:** Persistent content-offer Meta program. - **Ecommerce performance:** Product-style Meta performance pattern. - **Event-led GTM:** Webinar or event-led Meta GTM. - **Historical only:** Footprint without current pressure. ## What it looks like in a verified fit Meta Ads evidence lands as findings on the account — with the same Fit and Signals score grammar as the product. Brightline SaaS ## Findings - **Active Meta ads** - **Content-led demand gen** - **Scaled and active** ## Boundaries & method - Public Meta Ad Library sample — not Ads Manager spend, ROAS, or exact impressions. - Impression fields are often missing on commercial ads; Unavailable ≠ low spend. - Default searches are frequently active-only — inactive historical creatives may not be analyzed. - Pagination can be incomplete; we don’t claim the full catalogue was fetched. - Wrong Facebook page seed is possible — page mismatch risk means treat ads as provisional. - Short links stay unclear until resolved. Pair with Website Ranking or LinkedIn/Google Ads when the ICP needs traffic floor or other-channel GTM. ## Want Meta Ads on your verified fits? We’ll map activity, footprint, Meta surfaces, and destination / offer paths to your ICP and show how they look on real accounts for your market. - [Get 10 vetted companies →](https://propensify.io/#lead) - [Book a call](https://propensify.io/book-a-call) --- # Website signals What’s on their own site — the story they publish, the software the site loads, and how key pages look. _Data source — Website signals Propensify detects: pages they publish, software the public site loads, and visual cues when key pages are captured._ HTML: https://propensify.io/data-sources/website-signals Markdown: https://propensify.io/data-sources/website-signals.md ## Three questions we ask of their own site 1. **Who do they say they are?** — About, homepage, team, legal: B2B versus consumer, founder-owned versus subsidiary, stealth versus mid-market, charity versus commercial, entity name and jurisdiction. 2. **How do they sell, and what do they sell?** — Pricing and product language: tiers, contact-sales walls, carts, subscriptions, physical metrics, organisational features, health or clinical claims. 3. **What do they admit in the margins?** — Case studies, careers narrative, shipping and returns, privacy and FDA/HIPAA fine print, and extra pages we hunt by hypothesis when the preset families will not contain the sentence. No matching sentence in this pass is unknown — not a no. ## Lanes - **Publish** - **Load** - **Look** ## What they say. What the site loads. How it looks. ### What they say Pages on their domain — homepage, about, offer, pricing, proof, careers, legal. ### What the site loads Public front-door cues — booking widgets, marketing tags, chat, trust badges, sales paths. ### How it looks Branding and layout when pages are captured for eyes-on review. ## How website evidence stacks Four layers — bind the pages they publish, read offer cues, see what the public site loads, then nest how it looks when captured. 1. **Pages** — Families found on their site 2. **Offer cues** — Pricing · customers · team 3. **What loads** — Motion · tags · widgets 4. **Look** — Brand / layout when captured - **Pages:** Claims in copy — pitch, offer, proof, legal. - **Loads:** Hosts and tags on the public site — not a private admin audit. - **Look:** Nested, optional depth when eyes-on review helps. ## Page families Page families are the map of where we look. What we look for is above. Stack cues live in What the site loads. ## Family Chips - **Homepage:** Front-door pitch, CTAs, trust marks. - **About / story:** Mission, narrative, values. - **Team:** Leadership bios — not workforce headcount. - **Products / services:** Offer catalogue and positioning. - **Pricing:** Tiers, prices, Contact sales — absence is a signal. - **Customers / proof:** Logos, case studies, testimonials. - **Blog / resources:** Content themes and cadence cues. - **Careers (site):** Roles on their site — not the Job openings dataset. - **Legal:** Privacy / ToS entity and jurisdiction cues. - **Custom themes:** Hypothesis keywords beyond the presets. ## Pricing & commercial cues Public packaging on their pricing page when it exists — and the honest absence of public pricing when it does not. Public pricing paths also inform sales motion when we can read the site’s front door — see What the site loads. Site prices are marketing claims — not signed contract truth. ## Pricing Cards - **Pricing page present:** A pricing or plans page is found — tiers, prices, or sales CTAs may appear. - **No public pricing:** No pricing page in this pass — often a high-touch sales motion cue, not proof of no commercial model. ## Proof & team Customer proof and leadership pages when published — self-selected marketing, still useful texture. ## Proof Cards - **Customers / proof:** Logos, case studies, or testimonials on a customers-style page. - **Team / leadership:** Leadership or team bios — not a substitute for Company workforce headcount. ## What the site loads When we can read the public site, we look for booking and payment tools, marketing and email tags, ads pixels, chat, CMS cues, and how they ask people to buy — a checklist of known hosts, not every library on the page. A partial read or a quiet checklist is not proof they use none of these products. Parked or unreadable pages are coverage — not a dead company, and not “no stack.” A tag manager is not proof of which tags fire inside it. ## Load Footprint - **Domain doesn’t resolve:** The domain didn’t resolve — not proof the company is dead. - **Parked / for-sale:** A parked or for-sale page — parking ads are not their marketing stack. - **Can’t read the page:** Public HTML wasn’t usable — not proof of no stack. - **Checklist quiet:** Our checklist didn’t fire — not proof they use none of those products. ## Sales Motion Public conversion path The site may also mark itself in structured markup (organization, software, local business) — a markup claim, not a legal classification. Sales motion on the site How they ask people to buy on the public site — self-serve, published pricing, demo, booking, or a contact form. Not the real enterprise procurement motion. ## Chips - **Self-serve / try** - **Public pricing path** - **Demo / talk to sales** - **Book a time** - **Contact form** ## Stack families Shared families — recognizable products as texture, not a vendor zoo. Industry widgets appear when vertical schedulers or POS embeds show up — an embed is not proof of a paying tenant. ## Stack Families - **Booking:** Meeting or demo-booking host observed — not meeting volume. - **Payments:** Checkout or billing loader observed — not revenue. - **Marketing automation:** Marketing automation or customer-data cue — not a paid seat or volume. - **Email / SMS:** Email or SMS tool on the public site — not send volume. - **ABM / visitor ID:** Visitor-ID or ABM tag loaded — not identified-account volume. - **Tag managers:** Tag manager present — not proof of which tags fire inside it. - **Web analytics:** Page or session analytics host present — not traffic or spend. - **Ads pixels:** Paid-media pixel loaded — not ad spend, and not an Ads library creative. - **Chat:** Chat widget host — not conversation volume. - **Forms:** Form or survey widget host — not response volume. - **CMS / builder:** CMS or site-builder cue — not exclusive hosting. - **Storefront:** Commerce platform cue — not GMV or product count. - **Sales engagement:** Sales-engagement pixel on the marketing site — not sequence volume. - **Industry widgets:** Embed host observed — not proof of a paying tenant. ## Also on the public site Quieter cues — still hosts we observed, still not spend or seats. ## Stack Texture - **Product analytics & experiments:** Product, replay, or experiment snippets — not usage volume or test results. - **Publisher ads:** They sell ads on the page — not Google Ads spend, and not an Ads library. - **Cookie consent:** Consent script present — not that a banner was accepted. - **On-site reviews:** Review or UGC widget on their site — not the Customer reviews dataset. - **Login:** Auth or identity widget on a public surface — not active-user count. - **Edge / app host:** CDN or app-host cue — Cloudflare is common; not WAF spend. ## More load texture Specialist widgets when they show up — not a full library census. ## Stack Soft Chips - **Affiliate** - **Call tracking** - **Attribution** - **Site search** - **Video** - **Webinar** - **Help docs** - **Web push** - **Captcha** - **Error tracking** ## Trust & compliance cues Public trust marketing on the host — pages and badges, not attestations. ## Trust Cards - **Trust / security page:** A public trust or security page — not a SOC 2 attestation. - **Trust badge:** A trust badge on the page (for example Vanta or Drata) — not an attestation. - **UK statutory page:** A statutory page exists on this host — not filing contents. ## App & surface hints Thin cues — files and certificate names, often stale. ## App Hints - **App link files:** An app-link file was found — not install count. - **Product host on certificate:** A product-shaped name in a certificate — the host may be stale. ## Site inventory texture Optional sitemap cues — quieter than sales motion, and not traffic. ## Inventory Soft - **Sitemap size cue:** A capped URL list from the sitemap — not traffic (see Website Ranking). - **Sitemap freshness cue:** Webmaster-declared dates — often stale or fake. ## Visual signals When we capture pages for eyes-on review — branding and layout — nested here, not a separate guide. Visual cues don’t replace page copy or what the site loads. Evidence-first visual notes. We do not invent psychographics or intent theatre from a screenshot. ## Visual Cards - **Brand & layout cues:** Palette, typography, and layout density observations when pages are captured. - **Nested, not a separate guide:** Visual review rides on website page captures — not a separate guide. ## In a verified fit Northline Analytics ## Findings - **Public pricing page** - **Marketing automation on site** - **Trust page present** ## Boundaries & method - Site claims ≠ Companies House registry or enrichment truth. - Team pages ≠ Company workforce headcount series. - Careers on site ≠ Job openings dataset (→ Job openings). - Public pricing ≠ signed ACV or contract terms. - Absence of a pricing page is observational — not proof of no commercial model. - Customer logos are self-selected marketing proof. - Custom themes are hypothesis-driven — not an unbounded whole-site index. - What they publish and what the site loads are complementary — copy is not a substitute for loaded tags. - Checklist quiet ≠ they use none of these products. - Unreadable, parked, or unresolved ≠ the company is dead, and ≠ no stack. - A tag or widget host ≠ spend, seats, or revenue. - Trust badge or trust page ≠ SOC 2 or any attestation. - UK statutory page ≠ filing contents. - App-link files and certificate names ≠ installs; certificate hosts may be stale. - Sitemap size ≠ traffic (→ Website Ranking). Sitemap dates are often stale or fake. - Loaded-stack cues ≠ Firmographic technology name-lists. - Ads pixels ≠ Google Ads, Meta Ads, or LinkedIn Ads libraries. - Publisher ads (they sell ads on the page) ≠ Google Ads spend. - On-site review widgets ≠ Customer reviews dataset. - Tag manager present ≠ proof of which tags fire inside it. - CMS or edge host ≠ exclusive hosting or WAF spend. - An industry embed ≠ a paying tenant on a directory page. - We do not list every library on the page. - Visual cues are nested evidence — not a full brand audit. ## Want website signals on your verified fits? We’ll read the pages that matter for your ICP, see what the public site loads, and nest visual cues when eyes-on review helps. - [Get 10 vetted companies →](https://propensify.io/#lead) - [Book a call](https://propensify.io/book-a-call) --- # Website Ranking Firmographics tell you who a company is. Website Ranking tells you how large their public web audience looks — and whether that popularity is moving — so traffic-dependent outreach isn’t flying blind. _Data source — Website Ranking signals Propensify detects: public web audience scale bands and ranking trajectories — traffic-floor and timing without analytics access._ HTML: https://propensify.io/data-sources/website-ranking Markdown: https://propensify.io/data-sources/website-ranking.md The floor number lives here. On-the-internet-at-scale corroboration is Ads presence and Company socials; hidden pages are Search agents. - **Also read:** [Company socials](https://propensify.io/data-sources/company-socials) — public presence at scale, not the rank number - **Also read:** [Website signals](https://propensify.io/data-sources/website-signals) — pages they publish, not the floor number ## Size is a floor. Movement is prioritization. ### Audience scale Where the company’s site sits on a global popularity ladder — a coarse volume proxy for whether there’s enough public web traffic to care. ### Ranking movement Whether that popularity is improving, flat, or declining over the recent window — timing for outreach, not a substitute for analytics. ## How ranking evidence stacks Three layers — bind the audience floor, read whether popularity is moving, then combine scale and trajectory when both are in play. 1. **Scale** — Audience band 2. **Trajectory** — Improving → declining 3. **Composites** — Scale + movement together - **Floor first:** Bands are order-of-magnitude popularity — not measured monthly visits. - **Movement is timing:** Improving, flat, or declining over the recent window — outreach timing, not analytics. - **Stack when both exist:** Composites name scale and trajectory together. Do not invent extra volume bands. ## Audience scale Six bands from public global web rank. Lower global rank means a larger estimated audience. Bands are order-of-magnitude proxies — not measured monthly visits. Example domains are illustrative snapshots from public global rank — they can drift. Exact band cutoffs can be tuned per research pack. ## Volume Bands - **Very high:** Among the largest public web audiences - **High:** Large, serious public site - **Mid:** Material public audience - **Low:** Smaller public web footprint - **Thin:** Thin public rank signal - **Unknown:** No usable public rank series ## Ranking trajectories How public popularity can move over the research window. Glyphs show business direction — lower global rank is better; lines show whether popularity is rising or falling, not the raw rank number. Start with the shape. Scale tells you the floor; trajectory tells you whether to prioritize now. Improving → declining ## Public popularity movement Compared across recent vs prior windows on the available rank history. _Improving → declining_ - **Strong improvement:** Material gain in public popularity — strong “why now” for traffic-tied offers. - **Improving:** Clear upward popularity versus the prior window. - **Stable:** Avoids false urgency when nothing material moved. - **Declining:** Public popularity softened — efficiency angles, or deprioritize growth pitches. - **Strong decline:** Material loss — don’t treat as a growth-timing account. - **Volatile:** Unstable estimate — weak for timing; corroborate elsewhere. - **Insufficient history:** Not enough dated points to claim movement. ## Scale + movement together When size and trajectory agree, the story is sharper than either signal alone. ## Composites - **Scaled and growing:** Material audience and rising popularity — strongest Website Ranking timing stack. - **Scaled but declining:** Still sizable, but cooling — recovery or efficiency narratives, not growth hype. ## What it looks like in a verified fit Website Ranking evidence lands as findings on the account — with the same Fit and Signals score grammar as the product. Harborline Software ## Findings - **High audience scale** - **Improving ranking trajectory** - **Scaled and growing** ## Boundaries & method - Global web rank is a relative popularity proxy derived from public series — not first-party analytics or guaranteed visit counts. - Lower global rank means a larger estimated audience; glyphs show popularity direction, not “rank number went up = good.” - Research windows follow available history (commonly ~30 days on free coverage); longer history when the source allows. - Unknown / empty series is a coverage miss — not proof of low traffic. - Traffic is power-law distributed: compare bands, not tiny gaps between neighboring ranks. - Website Ranking does not replace ads, hiring, or firmographic sources — it is often paired with them downstream. - We prefer “insufficient data” over inventing monthly visit numbers. ## Want Website Ranking on your verified fits? We’ll map audience scale and ranking movement to your ICP and show how they look on real accounts for your market. - [Get 10 vetted companies →](https://propensify.io/#lead) - [Book a call](https://propensify.io/book-a-call) --- # Search agents Hunt for a needle in a haystack — blogs, news, pages on their site, and the wider web — by searching and reading what turns up, not only structured databases. _Data source — Search agents Propensify uses: find mentions and news on their site, in the press, and on the wider web — then read what turns up._ HTML: https://propensify.io/data-sources/search-agents Markdown: https://propensify.io/data-sources/search-agents.md ## Three questions we ask of the open web 1. **What did their nav hide?** — Unlinked PDFs, media kits, API docs, gated webinars, parked or dead domains. 2. **Who talks about them off-domain?** — Founder interviews, agency portfolios, registry crumbs, competitor case studies, title reconnaissance. 3. **What just happened in public?** — News language: layoffs, rebrands, acquisitions, budget freezes, agency-of-record appointments, launches. No result means we did not find it — not that it is false. ## Finding is cheap. Verifying is the filter. ### Find Search for pages and articles that might mention the company — on their site, in the press, and on the open web. ### Verify Keep results that look like the right company and the right topic; discard mismatches before treating them as evidence. ## How search evidence stacks Three layers — state the need, search where the answer likely lives, then decide whether a snippet is enough or a page is worth reading. 1. **Need** — What we’re looking for 2. **Where we look** — Hidden · off-domain · news 3. **Read** — Snippet vs full page - **Sample, not census:** A bounded set of results — not the whole web or every article ever published. - **Owned pages first:** Open-web search prefers pages that belong to the company when ownership matters. - **News is a feed:** Press hits are validated article samples ordered by recency — not a news archive. ## Where we look Same haystack — the jobs are the criteria. Whether this pass returned anything sits below. ## Where Chips - **Hidden pages** - **Off-domain** - **News** ## Open-web presence Whether search returns owned-page evidence for the information need — titles, snippets, and links worth following. A thin snippet can answer a simple need. It is not proof of everything on the full page. ## Open Web Cards - **Owned pages found:** Search returns pages on the company domain that match the need — sample of results, not a complete site index. - **Snippet answers:** Title or description may answer a thin question without opening the page. - **Page worth reading:** A result looks relevant enough to open and read for deeper evidence. - **Nothing found:** This search pass returned no usable matches — unknown, not proof the topic never exists online. ## News & press A recency-ordered sample of articles that cite or cover the company — standard coverage or topic-filtered when the need is specific. Empty news feed means nothing turned up in this sample — not “never in the news forever.” ## News Cards - **News hits:** Validated articles appear in the feed — sample coverage, not a complete press archive. - **Topic-filtered news:** Articles intersecting a stated topic (funding, expansion, regulation, and similar) when requested. - **No articles in sample:** No validated articles in this pass — coverage gap, not a permanent absence verdict. ## Honesty Search can retrieve the wrong company or the wrong topic. Filters reduce that risk; they do not eliminate uncertainty. ## Honesty Cards - **Wrong entity risk:** Results that fail ownership or domain checks are discarded from evidence — mismatch ≠ the topic never exists. - **Wrong topic risk:** A page can mention the company without answering the need — relevance still has to fit. ## In a verified fit Northline Analytics ## Findings - **Owned pricing page found** - **Recent press hit** - **Nothing on niche regulation topic** ## Boundaries & method - Results are a sample — not a full web index or complete news archive. - Snippet answers are thin; they are not the full page. - Owned-page preference discards many third-party mentions from open-web evidence by design. - Nothing found ≠ the topic never exists online. - Wrong-entity and wrong-topic mismatches can still occur — honesty over false certainty. - Search agents ≠ Website Ranking traffic floor. - Search agents ≠ Google Ads inventory. - Search agents ≠ Website signals page-family captures (pair those guides). - No query-syntax or vendor infrastructure details on this page. ## Want search agents on your verified fits? We’ll hunt the needles that matter for your ICP — on their site, in the press, and on the wider web — and show what is worth reading. - [Get 10 vetted companies →](https://propensify.io/#lead) - [Book a call](https://propensify.io/book-a-call) --- # Companies House Public UK registry evidence — legal identity, company status, accounts disclosure, and statutory financial lines when filings allow. _Data source — Companies House signals Propensify detects: UK legal identity, registry status, accounts disclosure, and statutory financial lines when filings allow._ HTML: https://propensify.io/data-sources/companies-house Markdown: https://propensify.io/data-sources/companies-house.md ## Two questions we ask of the filing 1. **Do they legally exist here?** — Registry identity and status language — a UK company on the register, not a credit score. 2. **Is there distress language in the filing?** — Going-concern notes, winding-up, overdue accounts as language in the document — not a new distress card wall. No filing in this pass is unknown — not that the company is empty. ## Identity is a gate. Depth is prioritization. ### Identity A verified UK company number bound to the prospect — or an honest miss / ambiguity. ### Depth Whether accounts filings exist, how rich disclosure looks, and which statutory lines we could parse. ## How Companies House evidence stacks Three rungs — bind the entity, judge disclosure, then read numbers only when they’re likely to exist. 1. **Identity** — Verified UK company 2. **Filings** — Disclosure gate 3. **Statutory numbers** — Parsed lines when present - **Always useful:** Entity bind + registry status — cheap and decisive. - **Disclosure filter:** Skip dead-end micro filings before a deep document pull. - **Magnitudes when earned:** Turnover, employees, and balance-sheet lines only when parse succeeds. ## Entity & registry status Can we safely bind a UK Companies House identity — and what does the register say about it? Incorporation age and SIC footprint can attach to a verified entity for filters — we don’t invent “startup / mature” bands on this page. ## Identity States - **Verified:** Safe UK company number bound to the prospect. - **Not found:** No safe UK bind — not “illegitimate worldwide.” - **Ambiguous:** Candidates exist; none safe to bind. ## Status States - **Active:** Register shows active — registry state only. - **Dissolved:** Closed-class status — confirm before treating as trading. - **Insolvency:** Insolvency-class status on the register. - **Other / unclear:** Non-canonical or missing status — inspect before hard gates. ## Overdue Card Accounts overdue Next accounts marked overdue on the profile — filing clock, not insolvency. ## Filings & disclosure Whether a document-ready accounts filing exists, and how rich that filing looks before any numbers are parsed. Filing found ≠ turnover known. Disclosure class decides whether a document pull is worth it. ## Filing Footprint - **Accounts filing found:** Latest accounts filing with document metadata selected. - **None found:** No selectable accounts document under current filters. ## Disclosure class How rich the selected accounts filing looks — before any numbers are parsed. _Richer → thinner_ - **Rich disclosure:** Outside the low-disclosure set — magnitudes may be worth parsing. - **Low disclosure:** Micro / dormant-style class — P&L often absent. - **Unknown:** Type unclassified — don’t assume richness. ## Filing Flags - **Paper-filed:** Digital extract less likely; OCR/PDF paths may fail closed. - **Amended:** Amended accounts may supersede an earlier filing for the period. ## Statutory numbers When disclosure allows, we parse the accounts document into statutory observations — and we say clearly when numbers weren’t available. Other statutory lines attach as magnitudes when present — we don’t invent size bands from them. ## Parse Outcomes - **Financials observed:** At least one numeric line parsed from the selected accounts. - **Low-disclosure skipped:** Filing class skipped before document fetch — saves a dead pull. - **No filing:** No selectable accounts document to parse. - **Document unavailable:** Filing meta existed; document content couldn’t be retrieved. - **Parse empty:** Document obtained; no numeric fields extracted (common on paper/PDF). ## Headline Lines - **Turnover disclosed:** Revenue line present — not profitability or buying power. - **Employees disclosed:** Statutory average employees — not live headcount confirmation. - **Net assets disclosed:** Equity / net assets observation — balance sheet only. ## Also Available Chips - Cash - Gross profit - Profit before tax - Inventories - Debtors - Creditors (≤1yr) - Tangible fixed assets - Total fixed assets - Total assets ## What it looks like in a verified fit Companies House evidence lands as findings on the account — with the same Fit and Signals score grammar as the product. Northbridge Instruments Ltd ## Findings - **UK entity verified** - **Rich accounts disclosure** - **Turnover disclosed** ## Boundaries & method - UK Companies House only — absence is not “no legal entity worldwide.” - Registry status is not commercial activity or buying intent. - Accounts overdue is profile filing metadata — not an insolvency verdict. - Filing metadata is not parsed financials; magnitudes require a successful document parse. - Low-disclosure classes often omit P&L/turnover; we may skip the document pull on purpose. - Paper-filed / PDF text paths can yield “document obtained, numbers unavailable” — we fail closed. - Statutory averages and GBP lines are observations — not credit scores or “can they afford us.” - Officers, parent-group escalation, and keyword narrative stay in deeper research — this guide covers the public-register ladder. ## Want Companies House on your verified fits? We’ll map identity, disclosure, and statutory lines to your ICP and show how they look on real UK accounts. - [Get 10 vetted companies →](https://propensify.io/#lead) - [Book a call](https://propensify.io/book-a-call) --- # Crunchbase Public Crunchbase evidence — company snapshot, funding depth, growth trends, and web / tech footprint when pages resolve. _Data source — Crunchbase signals Propensify detects: company snapshot, funding depth, growth trends, and web / tech footprint from public Crunchbase pages._ HTML: https://propensify.io/data-sources/crunchbase Markdown: https://propensify.io/data-sources/crunchbase.md ## Two questions we ask of the profile 1. **What capitalization story is on the profile?** — Stage labels, disclosed rounds, public versus private — the story the page tells, not an essay parse. 2. **What events are attached?** — Milestones and news chips on the profile — attached events, not a traffic essay. No org page in this pass is unknown — not that they are unfunded. ## Snapshot is context. Momentum is prioritization. ### Snapshot Org page facts — operating status, public/private, stage label, capital disclosure, score levels. ### Momentum What moved — funding recency, growth/heat trends, milestones, and website traffic direction. ## How Crunchbase evidence stacks One family, four depths — start with the org page, then open funding, growth, and tech when the story needs more. 1. **Profile** — Org snapshot 2. **Funding** — Rounds depth 3. **Growth** — Trends & milestones 4. **Tech & traffic** — Visits / stack - **Org first:** Identity, taxonomy, and score snapshot from the organization page. - **Funding depth:** Rounds and investors when the financials page resolves. - **Growth motion:** Trend deltas and milestone samples — not score levels. - **Tech & traffic:** Visit estimates, traffic direction, and a technology detection sample. ## Company profile Did we resolve a usable org page — snapshot facts, not a parsed essay. Employee range is a Crunchbase string — not live workforce trajectory. Pair with workforce signals when you need headcount motion. ## Profile Footprint - **Org observed:** Usable organization page extract — listing, not ICP fit proof. - **Not found:** No Crunchbase org URL resolved — not illegitimate or unfunded. - **Extract unusable:** Page sparse or extract flake — not proof of no Crunchbase presence. ## Operating - **Active:** Operating status coerces to active — CB snapshot, not legal proof. - **Closed:** Closed / defunct-style status on Crunchbase — not dissolution proof. ## Funding Status - **Public:** Funding status Public — taxonomy, not exchange verification. - **Private:** Funding status Private — not full cap-table confidentiality. ## Company Type - **For-profit:** Company type coerces to For Profit on the org page. - **Non-profit:** Company type coerces to Non-Profit on the org page. ## Stage And Funding - **Stage present:** Last-funding-type label present (e.g. Series A) — not rounds depth. - **Funding observed:** Total funding coerced to USD — disclosure parse, not audited books. - **Funding obfuscated:** Funding text present but not coercible — we won’t invent a number. ## Scores - **Growth score:** 0–100 vendor growth score snapshot — not causal growth or Hot/Warm. - **Heat score:** 0–100 vendor heat score — not buyer intent. - **CB rank:** Crunchbase rank observed — vendor prominence, not ICP priority. ## Profile Rollups - **Competitors listed:** Competitors listed on the org page — not win/loss proof. - **Founders present:** Founder names listed — sample count, not a complete roster. - **Employee range:** Employee range string on CB — not payroll headcount. ## Funding depth When the financials page resolves, we read rounds inventory and investor rollups — not a replacement for the org-page stage label. Org-page stage ≠ rounds inventory. Prefer this section when you need depth. ## Funding Footprint - **Financials observed:** Financial details page retrieved with usable extract fields. - **Not found:** No financials URL resolved — not proof the company never raised. - **Extract unusable:** No coercible rounds or investor lists — flake or sparse page. ## Rounds - **Rounds observed:** Funding rounds count ≥ 1 — inventory rollup, not per-round truth. - **No rounds listed:** Usable page with zero coercible rounds — disclosure miss possible. ## Investors - **Investors present:** Investor list length ≥ 1 — page sample, not a complete roster. - **Lead investors:** Lead investor list length ≥ 1 — sample, not exhaustive leads. ## Round Recency Latest round recency Days since latest parseable round date — extract parse, not verified close. ## Growth & milestones Trend deltas and milestone samples live here — score levels stay on the profile. Trend points are vendor snapshots — not proof of causal growth or buyer intent. ## Growth Footprint - **Growth page observed:** Growth outlook page retrieved with usable extract fields. - **Not found:** No growth outlook URL — not proof of flat momentum. - **Extract unusable:** No parseable trends or milestones — flake or sparse page. ## Trends - **Growth trend:** Signed growth-score trend points — proprietary snapshot, not causal proof. - **Heat trend:** Signed heat-score trend points — not buyer intent. ## Milestones - **Milestones present:** Recent milestones list length ≥ 1 — sample, not full chronology. - **None listed:** Empty milestones list — disclosure miss possible. - **Milestone recency:** Days since latest parseable milestone date — extract parse only. ## Tech & traffic Web visit estimates, traffic direction, and a technology detection sample — when the tech page resolves. Pair with Website Ranking when you need an independent popularity ladder — Crunchbase visits are a third-party estimate on the tech page. ## Tech Footprint - **Tech page observed:** Tech details page retrieved with usable extract fields. - **Not found:** No tech details URL — not proof of zero traffic or stack. - **Extract unusable:** No coercible visit, stack, or spend evidence — flake or sparse. ## Visits - **Visits observed:** Website visit count coerced — third-party estimate, not analytics. - **Visits unavailable:** Usable tech page without a coercible visit count. - **Visit growth:** Visit growth percent coerced — estimate, not causal audience proof. ## Traffic trend Closed-set website traffic direction from the tech page — the only continuum on this guide. _Growing → declining_ - **Accelerating:** Traffic trend coerces to accelerating — estimate label, not causal growth. - **Stable:** Traffic trend coerces to stable — not proof of flat demand. - **Declining:** Traffic trend coerces to declining — not proof of business decline. ## Stack Cards - **Stack observed:** Active technology count ≥ 1 — detection sample, not inventory of record. - **Stack empty:** Zero coercible technologies — detection miss, not confirmed non-use. ## It Spend Projected IT spend USD projected IT spend — estimate only, not budget fact. ## What it looks like in a verified fit Crunchbase evidence lands as findings on the account — with the same Fit and Signals score grammar as the product. Harborline Analytics ## Findings - **Crunchbase org observed** - **Funding rounds observed** - **Traffic accelerating** ## Boundaries & method - A Crunchbase page is a listing / AI extract — not ICP fit or complete firmographic truth. - Sparse or unusable extract ≠ the company has no Crunchbase presence. - Operating active/closed on Crunchbase is a snapshot — not Companies House or legal proof. - Public / Private are taxonomy labels — not exchange verification or full cap-table secrecy. - Total funding is USD when coercible; obfuscated means we won’t invent a number — and we don’t invent size bands. - Growth score, heat score, and rank are vendor snapshots — not buyer intent or Hot/Warm. - Growth/heat trend points and milestones are proprietary / sample observations — not causal growth proof. - Rounds and investor lists are inventory rollups — not audited raises or complete rosters. - Visits, visit growth, and projected IT spend are third-party / projected estimates — not analytics or budget fact. - Technology counts are a detection sample — not an inventory of record. Profiles / contacts depth is not part of this guide. ## Want Crunchbase on your verified fits? We’ll map snapshot, funding depth, growth, and tech signals to your ICP and show how they look on real accounts. - [Get 10 vetted companies →](https://propensify.io/#lead) - [Book a call](https://propensify.io/book-a-call) --- # Firmographic & technographic Enrichment profile for a domain — company type, size and industry footprint, technology name lists, and funding snapshot when available. _Data source — Firmographic and technographic signals Propensify detects: enrichment footprint, company type, size and industry bands, technology name lists, and funding snapshot when available._ HTML: https://propensify.io/data-sources/firmographic-technographic Markdown: https://propensify.io/data-sources/firmographic-technographic.md Industry, type, and HQ are categorical here. Stack language lives on Website signals and Job openings. - **Also read:** [Website signals](https://propensify.io/data-sources/website-signals) — stack language on their own site - **Also read:** [Job openings](https://propensify.io/data-sources/job-openings) — tooling and process language in the requisition plus category tags when present ## Firmographics bind the account. Tech shows the stack sample. ### Firmographics Whether we observe a usable enrichment profile — type, size band, industry, country, founded, funding keys. ### Technographics Whether a technology name list is present for the domain — and how rich the count looks — or an honest “unavailable.” ## How enrichment evidence stacks Three layers — bind the enrichment footprint, read the firmographic profile, then see whether a tech stack sample is present. 1. **Footprint** — Observed / miss / thin 2. **Firmographic profile** — Type · size · industry · geo 3. **Tech stack** — Names present or unavailable - **Always useful:** Observed vs not found vs thin — cheap and decisive. - **Profile keys:** Type, size band, industry, geo, funding snapshot when present. - **Stack honesty:** Names observed — or unavailable without inventing “no software.” ## Enrichment footprint First question: does this domain return a usable enrichment profile? Exactly one footprint outcome per research pass. ## Footprint States - **Profile observed:** Usable enrichment keys for the domain — firmographic lane open. - **Domain not found:** Not enrichable in this pass — not proof the company is illegitimate. - **Thin / unusable:** Enrich returned but lacked usable keys — not “no firmographics anywhere.” ## Company type When the profile parses a known type — private, public, educational, nonprofit, or government. At most one type on a pass. ## Type States - **Private:** Classified as private on the enrichment profile. - **Public:** Classified as public — optional stock fields are enrichment-reported only. - **Educational:** Classified as educational. - **Nonprofit:** Classified as nonprofit. - **Government:** Classified as government. ## Firmographic profile Size band, revenue when disclosed, industry, country, founded year, and NAICS when present. Size and revenue are enrichment range bands — not payroll or audited financials. Category tags when present on the profile — taxonomy coverage varies. ## Profile Cards - **Size band:** Employee range observed — not payroll headcount or live workforce count. - **Revenue band:** Revenue range disclosed when present — absence ≠ low revenue. - **Industry:** Primary industry label present on the profile. - **Country:** HQ country code present — may be coarse (country-level). - **Founded year:** Founding year present when coerceable. - **NAICS codes:** At least one NAICS code — coding coverage varies. ## Category Chips - B2B - B2C - SaaS - E-commerce - Manufacturing - Healthcare ## Funding snapshot Stage label, total funding magnitude, and funding-row count when the enrichment payload includes them. This is a snapshot lane — for round-by-round depth, pair with Crunchbase. ## Funding Cards - **Funding stage:** Stage label present — may not match Crunchbase stage. - **Total funding:** Numeric total when present — nulls are common for PE or bootstrapped firms. - **Funding rows:** Count of funding rows — not a complete fundraising narrative. ## Tech stack Whether vendor / technology names appear on the enrichment profile. A name list is not an exhaustive stack audit. Unavailable ≠ no software. Illustrative names when a stack sample is observed — not every tool the company runs. ## Tech States - **Stack observed:** At least one technology name in the enrichment list — count available for packs. - **Stack unavailable:** No technology names in this payload — not proof the company uses no software. ## Tech Chips - Shopify - React - Google Analytics - Salesforce - AWS - WordPress ## Discovery URLs LinkedIn and Crunchbase org URLs when reported on the profile — hops for further research. ## Discovery Cards - **LinkedIn URL:** Company LinkedIn URL reported — discovery hint; URL may be stale. - **Crunchbase URL:** Crunchbase org URL reported — discovery hint, not a CB page scrape. ## What it looks like in a verified fit Enrichment evidence lands as findings on the account — with the same Fit and Signals score grammar as the product. Northline Analytics ## Findings - **Profile observed** - **Size band** - **Stack observed** ## Boundaries & method - Third-party enrichment for the domain — not registry legal truth. - Domain not enrichable here ≠ the company is illegitimate. - A thin return means this pass lacked usable keys — not “no firmographics exist anywhere.” - Employee range is an enrichment band — not payroll headcount or live workforce count. - No revenue band on this pass ≠ low revenue. - Technology names are a sample list — not an exhaustive stack audit. - No tech names returned ≠ the company uses no software. - Stage / total / row count are enrichment snapshots — may not match Crunchbase depth. - Reported LinkedIn / Crunchbase URLs are discovery hints — they can be stale. - We do not invent size or revenue ladders beyond the enrichment bands, and this guide has no “recent raise” timing. - Headcount motion and people coverage live on the Company workforce guide. ## Want firmographic and technographic signals on your verified fits? We’ll map enrichment footprint, profile keys, and stack availability to your ICP and show how they look on real accounts. - [Get 10 vetted companies →](https://propensify.io/#lead) - [Book a call](https://propensify.io/book-a-call) --- # Job openings Public job-opening signals — active hiring footprint, listing lifecycle, function-family momentum, and mix patterns from roles we can observe. _Data source — Job-opening signals Propensify detects: hiring footprint, listing lifecycle, function-family momentum, and mix patterns from public openings._ HTML: https://propensify.io/data-sources/job-openings Markdown: https://propensify.io/data-sources/job-openings.md ## Three questions we ask of the requisition 1. **What function is this, really?** — Sales, warehouse, marketplace ops, RevOps, compliance marketing — the role nouns in the description. 2. **How is the work done?** — Tooling and process language: CRM, list-building, GTM engineering, developer tickets for web changes, 3PL, healthcare ad approvals. 3. **What motion does the copy imply?** — Enterprise versus volume, urgency, hiring freeze versus burst — including spray-and-pray or call-centre language when it appears. No openings, or a description too thin to read, is unknown — not that they never hire. - **Also read:** [Company workforce](https://propensify.io/data-sources/company-workforce) — listings ≠ headcount series plus optional keyword focus when your ICP supplies roles ## Footprint is a gate. Timing is prioritization. ### Footprint Whether we see active openings, stale opens, closed listings — or none returned for the domain. ### Timing How listings move — newly seen, long-running, closing fast or slow, and which function families are heating or cooling. ## How job-opening evidence stacks Three layers — bind the hiring footprint, read lifecycle texture, then see which function families are in motion. 1. **Footprint** — Active / none + texture 2. **Lifecycle** — New, aging, closing 3. **Function momentum** — Heating → quiet by family - **Always useful:** Active vs none — and stale/closed context when openings exist. - **Lifecycle texture:** Newly seen, long-running, quick or recent closes. - **Function motion:** Accelerating → dormant per role family in the returned openings. ## Hiring footprint First question: do we observe open roles for this domain — and what’s the open/closed texture? Active and none are exclusive outcomes for a research pass. Stale and closed can appear alongside active listings. ## Footprint States - **Active openings:** At least one listing meets active-open freshness for the domain. - **None returned:** No openings in the returned sample — not “never hires.” - **Stale open:** Still listed but aging — evergreen ATS noise or quiet hiring. - **Closed listings:** Closed in the sample — closed ≠ confirmed filled. ## Listing lifecycle How openings age and leave the board — listings can show more than one of these in the same pass. ## Lifecycle texture Fresh first-seen activity through long-running opens and recent closes — coexisting subject flags, not a single exclusive state. _Fresh activity → aging / closed_ - **Newly first seen:** Listing entered observation recently — fresh posting signal. - **Long-running open:** Visible for a long window — not proof of a hard-to-fill role. - **Quickly closed:** Short observed listing lifetime — not a confirmed quick hire. - **Recently closed:** Left the board in the recent window — motion without hire proof. ## Function momentum Per function family in the returned openings — heating, newly emerged, cooling, or quiet. Listing momentum is not headcount growth. Closure speed is observed listing lifetime — not confirmed time-to-hire. ## Category motion Exclusive states for a function family in the openings sample — packs see category as the subject. _Heating → quiet_ - **Accelerating:** Recent first-seen volume exceeds the prior window for the family. - **Recently emerged:** Family appears in recent openings after a quiet prior window. - **Cooling:** Family activity stepped down versus the prior window. - **Dormant:** No recent motion for that function family in the sample. ## Closure Velocity - **Fast closure:** Median observed listing lifetime is short for the family. - **Slow closure:** Listings linger longer before leaving the board. ## Mix & clusters Where openings concentrate — function, location, seniority, remote/hybrid, pay disclosure, and recurring titles. Clusters reflect the returned openings sample — not an exhaustive careers-site crawl claim. ## Mix Cards - **Function cluster:** Openings concentrate in one or more function families. - **Location cluster:** Roles cluster in shared locations or geos. - **Seniority concentration:** Mix skews toward a seniority band in the sample. - **Open-mix concentration:** Current opens are concentrated — thin diversity in the sample. - **Aging cluster:** A pocket of opens is aging together. - **Remote / hybrid:** Multiple openings share remote or hybrid contract types. - **Salary disclosed:** Pay bounds appear on one or more listings. - **Salary band cluster:** Enough disclosures to see a recurring band — not total-comp truth. - **Recurring title:** Same or near-same title reappears — repost or evergreen pattern. ## Keyword focus When your ICP supplies focus roles or skills, we can match openings and timing to those keywords. When your ICP supplies focus roles or keywords, we can match titles, taxonomy, and recent keyword motion — including lower-precision description-only hits. ## Keyword Chips - Role match - Title match - Taxonomy - Description-only - Open concentration - Recent - Accelerating - Long-running ## What it looks like in a verified fit Job-opening evidence lands as findings on the account — with the same Fit and Signals score grammar as the product. Brightfield Robotics ## Findings - **Active openings** - **Function accelerating** - **Remote / hybrid pattern** ## Boundaries & method - Public / observable openings for the domain — not every ATS on earth. - Open listings are visibility — not confirmed hires. - Closed does not prove the role was filled. - No openings returned ≠ the company never hires. - Stale open may be evergreen ATS noise or quiet hiring. - Long-visible listings aren’t proof of a hard-to-fill role. - Short listing lifetime isn’t a confirmed quick hire. - Function acceleration is listing observation — not headcount growth. - Clusters reflect the returned openings sample for the domain. - Salary when disclosed uses annual USD bounds — not total-comp truth. - Keyword focus only when your ICP supplies keywords; description-only matches are lower precision. - We do not invent open-role volume bands (high / medium / low headcount from listing counts). ## Want job-opening signals on your verified fits? We’ll map footprint, lifecycle, and function momentum to your ICP and show how they look on real accounts. - [Get 10 vetted companies →](https://propensify.io/#lead) - [Book a call](https://propensify.io/book-a-call) --- # Company workforce Observed headcount footprint, hiring-and-attrition motion in the series, department mix, and people-match coverage when your ICP supplies role filters. _Data source — Company workforce signals Propensify detects: observed headcount footprint, series trajectory and period shocks, department mix, and people-match coverage when filters apply._ HTML: https://propensify.io/data-sources/company-workforce Markdown: https://propensify.io/data-sources/company-workforce.md We measure mix and trajectory here. Leader names and stories live on Website signals; how work feels is Employee voice. - **Also read:** [Website signals](https://propensify.io/data-sources/website-signals) — leader names and stories on the team page - **Also read:** [Employee voice](https://propensify.io/data-sources/employee-voice) — how work feels, not the headcount series ## Presence is a gate. Motion is prioritization. ### Presence Whether we observe usable headcount for the company — or an honest empty / unusable return. ### Motion How the series moves — sustained growth or contraction, below peak, stalls, recoveries, and period shocks — plus department and people texture. ## How workforce evidence stacks Three layers — bind observed headcount, read the trajectory, then see department concentration and motion — plus role-match coverage when filters apply. 1. **Footprint** — Observed / none usable 2. **Trajectory** — Growth → below peak + events 3. **Department motion** — Mix + growth / contraction - **Always useful:** Observed vs no usable observation. - **Series motion:** Primary trajectory + texture + period events. - **Org texture:** Department dominance / thin shares / growth / contraction. ## Headcount footprint First question: do we have a usable observed headcount for this company? Exactly one footprint outcome for this lane. No usable observation is not proof of zero employees. ## Footprint States - **Headcount observed:** At least one LinkedIn-visible employee observed — not confirmed payroll. - **No usable observation:** No usable observed headcount in this return — not proof the company has no employees. ## Headcount trajectory How total observed headcount moved across the history window. Observed series change — not a confirmed hiring or layoff program. Texture can coexist with a primary trajectory. ## Primary trajectory At most one primary shape for the series — sustained growth, sustained contraction, or current level below a prior peak. _Growing → below peak_ - **Sustained growth:** Material increase across history without sustained reversal. - **Sustained contraction:** Material decrease without sustained recovery — observation, not a layoff verdict. - **Below prior peak:** Current observed headcount materially below a prior observed peak. ## Trajectory texture Stall, recovery, and volatility patterns that can appear alongside a primary trajectory. _Stall → recovery → volatile_ - **Plateau / stall:** Recent headcount largely flat after earlier movement — coverage or true stall. - **Recovery arc:** Decline to a trough then material recovery — not proof of renewed buying. - **Oscillation / volatility:** Repeated direction changes with high churn vs net — weak on small bases. ## Period events Adjacent-period shocks rolled up from the series — read with trajectory context. A single burst usually needs broader trajectory context. Contractor cycling is a niche proxy, not strategy proof. ## Event Cards - **Headcount burst:** At least one adjacent-period material total increase under signal thresholds. - **Headcount cliff:** At least one adjacent-period material total decrease under signal thresholds. - **False dawn:** A material burst mostly reversed in a short window — observation instability. - **Band crossing:** Observed employee-count range bucket changed between adjacent snapshots. - **Contractor cycling:** Unclassified headcount alternates with consistent amplitude — niche proxy only. ## Department mix & motion Where observed headcount concentrates — and which function families grew or contracted. Pattern types fire per department in the observed mix — taxonomy and coverage bias are possible. ## Department Cards - **Department dominance:** A named department is a large share of observed headcount. - **Low function share:** A monitored department is thin in the mix — not proof the function is absent. - **Department growing:** A function family increased materially vs its baseline window. - **Department contracting:** A function family decreased materially vs its baseline window. ## People coverage When your ICP supplies title, seniority, or department filters, we can see whether people matches land in the returned search page. Page sample under filters — not a full org chart. No matches ≠ no such employees exist. Illustrative mix texture when matches return — page-local counts, not a census. ## People States - **People matches:** At least one person returned under the filtered search. - **No people returned:** Empty result for this filtered search — not proof no such employees exist. - **Title query hit:** At least one match under a non-empty title query — match quality varies. - **Seniority mix:** Returned-page people share seniority values — not a company-wide census. - **Department mix:** Returned-page people share department values — taxonomy, not payroll org chart. ## People Chips - Executive - Manager - IC - Engineering - Sales - Marketing - HR - IT ## What it looks like in a verified fit Workforce evidence lands as findings on the account — with the same Fit and Signals score grammar as the product. Harborline Systems ## Findings - **Headcount observed** - **Sustained growth** - **Department growing** ## Boundaries & method - Headcount is LinkedIn-visible observation — not confirmed payroll. - No usable observation ≠ the company has no employees. - Trajectory movement is observed series change — not a confirmed hiring or layoff program. - Below a prior observed peak is not proof of distress intent. - Recovery arc ≠ renewed buying intent. - Bursts and cliffs need trajectory context; false dawn is observation instability. - Contractor cycling is a niche proxy — not proof of a contractor strategy. - Department shares use observed taxonomy — coverage bias possible; low share ≠ function absent. - People results are a filtered page sample — not a full org census. - No matches for a filtered search ≠ no such employees exist. - Title match quality varies — not a confirmed role inventory. - We do not invent headcount volume bands (large / mid / small) from observed counts. - Firmographic size bands and public job openings are sibling guides — not substitutes for this series. ## Want company workforce signals on your verified fits? We’ll map footprint, trajectory, department motion, and people coverage to your ICP and show how they look on real accounts. - [Get 10 vetted companies →](https://propensify.io/#lead) - [Book a call](https://propensify.io/book-a-call) --- # Employee voice How employees and candidates describe the company — culture, pay, benefits, interviews, and Q&A — beyond job listings. _Data source — Employee voice signals Propensify detects: workplace ratings, reviews, benefits, culture, salaries, interviews, and FAQ — beyond job listings._ HTML: https://propensify.io/data-sources/employee-voice Markdown: https://propensify.io/data-sources/employee-voice.md ## Three questions we ask of employee language 1. **Where does execution stick?** — Ops friction, tooling complaints, process that does not scale, cannot-ship language. 2. **Where is GTM unhappy?** — Quota, lead quality, marketing-sales handoff — the go-to-market complaint cluster. 3. **Is the house under strain?** — Layoffs, morale collapse, leadership distrust, would-not-recommend clusters. No reviews in this pass is unknown — not a happy workplace. ## Brands - Glassdoor - Indeed ## Workplace reputation vs compensation texture. ### Reputation Ratings, reviews, culture, and DEI cues when employees publish them on Glassdoor or Indeed. ### Compensation texture Salaries, benefits, interviews, and FAQ — directional pay and process texture, not openings counts. ## How employee voice stacks Three layers — ratings footprint, review and culture texture, then pay, benefits, interviews, and FAQ. 1. **Ratings** — Overall / categorical 2. **Reviews & culture** — Themes · DEI 3. **Pay & process** — Salaries · benefits · interviews - **Self-selecting:** Sparse volume is common — missing metrics ≠ negative facts. - **Not jobs:** Job listings live on Job openings and Company workforce — not here. - **Often empty:** FAQ, conversations, and some culture pages frequently return nothing usable. ## Ratings footprint Overall and categorical workplace ratings when the overview pages return them. ## Ratings Lanes - **Workplace ratings:** Overall or categorical ratings present — self-selecting sample, not a census. - **Ratings thin / missing:** Rating fields absent or unusable in this pass — lack of data, not a negative verdict. ## Reviews & culture Verbatim themes and culture pages when present. ## Reviews Lanes - **Employee reviews:** Pros/cons and themes from review samples on Glassdoor or Indeed. - **Culture / DEI:** Culture or DEI scores when the page exists — often empty. ## Pay & benefits Crowdsourced salary texture and benefits ratings — directional, not payroll truth. ## Pay Lanes - **Salaries:** Role-level pay ranges or approximations when enough reports exist — directional only. - **Benefits:** Benefits ratings and themes when the benefits page returns them. ## Interviews & FAQ Candidate interview experiences and employee Q&A when published. ## Interviews Lanes - **Interviews:** Interview difficulty, stages, and candidate notes when present. - **FAQ / Q&A:** Employee questions and answers — frequently empty on Indeed. ## Coverage honesty Some lanes are sparse by nature. Soft texture stays optional. ## Coverage Lanes - **Conversations:** Forum-style threads — same reading job as reviews, often empty. - **Workplace photos:** Office or amenity photo cues when present — soft culture texture. - **Employer about:** Indeed about narrative (non-hiring parts) — not firmographic truth. Job listings on Glassdoor or Indeed are not re-heroed here. Pair with Job openings for hiring footprint and Company workforce for headcount series. ## In a verified fit Northline Analytics ## Findings - **Workplace ratings present** - **Benefits themes** - **Interview process notes** ## Boundaries & method - Self-selecting / sparse samples ≠ representative workplace census. - Missing rating or empty FAQ ≠ negative workplace fact. - Salary figures are directional approximations — not payroll. - Culture / DEI / conversations / FAQ pages are often empty. - Employer about narrative ≠ firmographic or registry truth. - Job listings and hiring counts are out of scope here (→ Job openings). - Headcount series lives on Company workforce — not this guide. - Customer reviews ≠ employee reviews (→ Customer reviews). - Deep Check evidence only — no Signal Catalogue atoms for this family. - Platform defaults may be UK-biased. ## Want employee voice on your verified fits? We’ll map workplace ratings, review themes, and compensation texture — without confusing them for job openings. - [Get 10 vetted companies →](https://propensify.io/#lead) - [Book a call](https://propensify.io/book-a-call) --- # Amazon Marketplace Presence tells you a company sells on Amazon. Timing shows how the storefront is moving — so outreach can prioritize accounts with a live reason to talk. _Data source — Amazon Marketplace signals Propensify detects: review velocity, sales rank, catalogue movement, quality checks, and growth-phase patterns._ HTML: https://propensify.io/data-sources/amazon-marketplace Markdown: https://propensify.io/data-sources/amazon-marketplace.md Channel identity and attribution live here. Channel voice — returns, defects, stockouts — lives on Customer reviews and Company socials. - **Also read:** [Customer reviews](https://propensify.io/data-sources/customer-reviews) — returns, defects, felt-tricked language - **Also read:** [Company socials](https://propensify.io/data-sources/company-socials) — stockout comments and in-channel voice ## Presence is a gate. Timing is prioritization. ### Presence A validated Amazon seller, storefront, or ASIN-bearing product page attributable to the company. ### Timing Movement over a research window (typically ~90 days): reviews, rank, catalogue, and seller feedback — alone or stacked. ## How marketplace evidence stacks Four timing axes — read each alone, then stack when you want a stronger reason to reach out now. Growth-phase labels sit on the stacked reading, not on a fifth axis. 1. **Reviews** — Demand 2. **Sales rank** — Purchase 3. **Catalogue** — Footprint 4. **Feedback** — Seller activity - **Four axes:** Reviews, rank, catalogue, and seller feedback each move on their own — one clear signal can prioritize an account. - **Stack when useful:** Combine axes when you want a stronger now-reason. Do not treat every seller as in-market. - **Growth phase:** Pattern cards label the stacked reading — expanding, mixed, or contracting — not a fifth exclusive continuum. ## Timing signals Four ways a storefront can move. Each row is one axis — cards show how strong (or weak) that movement looks. One clear signal can prioritize an account. Stack a few when you want a stronger reason to reach out now. ## Review velocity Lagging demand proxy from review accumulation over the window. _Stronger → weaker_ - **Accelerating:** Demand momentum compounding — prioritize now. - **Growing:** Clear upward demand without needing acceleration. - **Decelerating:** Still growing, but cooling — sequence after true accelerators. - **Flat:** Avoids false urgency when reviews aren’t moving. - **Declining:** Cooling demand — don’t treat every seller as in-market. - **Missing:** Keeps scoring honest when history can’t support a claim. ## Sales rank Category-relative purchase momentum. Glyphs show business direction, not the raw rank number. _Improving → declining_ - **Improving:** Relative purchase momentum inside a category. - **Flat:** Prevents over-reading noise as a timing trigger. - **Declining:** Losing category position — deprioritize vs real movers. - **Missing:** Explicit coverage gap instead of a silent miss. ## Catalogue footprint ASIN count and product footprint change — a separate growth axis from reviews or rank. _Expanding → contracting_ - **Expanding:** Listing push often implies inventory and ops scale. - **Flat:** Stable footprint — no invented catalogue urgency. - **Contracting:** Portfolio reduction — don’t assume expansion. - **Missing:** Transparent when storefront history isn’t measurable. ## Seller feedback Seller-profile reputation timing — useful when fresh; de-weighted when stale. _Active → missing_ - **Momentum:** Secondary confirmation of recent seller activity. - **Stale:** Don’t treat a quiet profile as current demand. - **Missing:** Coverage honesty when profile history isn’t there. ## Checks Simple confirmations that sit alongside timing — presence, live catalogue breadth, and quality at scale — including when those checks don’t fire. ## Checks - **Presence verified:** Confirms a real marketplace operator — not a brand-name guess. - **Active ASIN cluster:** Live catalogue breadth beyond a single hero SKU. - **No active cluster:** Avoids overstating activity when the footprint looks thin. - **Quality at scale:** Momentum attached to products buyers rate well. - **Quality at scale not detected:** Surfaces weak quality evidence before you invest outreach time. ## When signals stack Combinations that are sharper than any single axis — plus a plain-English growth phase when evidence is strong enough. ## Composites - **Multi-dimensional growth:** Higher-confidence “why now” than any single axis. - **Rank leads reviews:** Momentum without review confirmation — dig deeper. - **Reviews lead rank:** Early social-proof heat that may precede rank confirmation. - **Expansion with contraction:** Portfolio rotation — not a binary growing/dying label. - **Scale without quality:** Volume growth that may not be the account you want. - **Stale seller, active products:** Weight product timing; ignore the quiet seller profile. ## Growth phase When evidence is strong enough, dimensions roll up into one phase for prioritization queues. ## Phases - **Accelerating:** Review velocity up + sales rank improving + no contraction. - **Expanding:** Velocity or rank up + catalogue/ASIN growth. - **Mixed:** At least one dimension improving and one declining. - **Sustaining:** Measured dimensions flat within thresholds. - **Decelerating:** Velocity declining/flat + rank worsening/flat + no growth. - **Contracting:** Catalogue contraction with soft velocity and rank. - **Unclear:** Insufficient evidence for a meaningful phase. ## What it looks like in a verified fit Amazon timing evidence lands as findings on the account — with the same Fit and Signals score grammar as the product. Northline Commerce ## Findings - **Accelerating review velocity** - **Sales rank improvement** - **Multi-dimensional growth** ## Boundaries & method - Timing windows follow available history (commonly ~90 days); thresholds can be tuned per ICP. - Review velocity is a lagging demand proxy — not direct GMV or unit sales. - Sales rank is category-relative; absolute meaning depends on category depth. - Catalogue expansion can reflect rotation or onboarding — not always net business growth. - Coverage states (missing, stale) are first-class — we prefer “insufficient data” over weak speculation. - Seller-level timing requires verified attribution; unattributed brand-store products may inform product demand only. ## Want Amazon timing on your verified fits? We’ll map these dimensions to your ICP and show how they look on real accounts for your market. - [Get 10 vetted companies →](https://propensify.io/#lead) - [Book a call](https://propensify.io/book-a-call) --- # Customer reviews Public customer proof from Capterra software listings and Trustpilot — ratings footprint, distribution texture, and qualitative themes when available. _Data source — Customer review signals Propensify detects: Capterra listing footprint, ratings and distribution, listing texture, and Trustpilot qualitative themes._ HTML: https://propensify.io/data-sources/customer-reviews Markdown: https://propensify.io/data-sources/customer-reviews.md ## Three questions we ask of review language 1. **Who is speaking?** — Organisational buyers versus consumers — often visible in the directory itself, and in how reviewers describe themselves. 2. **What broke or delighted them?** — Defects, returns, cancellation traps, service failure, felt-tricked-into-a-subscription language. 3. **What does the listing prove by existing?** — A B2B software directory versus a consumer review site is itself information — a proxy, not a rating. No profile in this pass is unknown — not “no customers.” ## Brands - Capterra - Trustpilot ## Presence is a gate. Texture is prioritization. ### Ratings footprint Whether we find a usable public listing with rating and review-count evidence — or an honest miss / thin extract. ### Review texture Star distribution, listing extras, and Trustpilot themes when the Deep Check lane returns them. ## How review evidence stacks Three layers — bind the listing, read rating and volume, then see distribution and qualitative texture. 1. **Profile** — Found / thin / not found 2. **Ratings & volume** — Score + review count 3. **Texture** — Distribution · themes · replies - **Self-selecting:** Ratings are not a representative quality census. - **Two lanes:** Capterra is structured checks; Trustpilot is qualitative honesty. ## Capterra footprint Do we retrieve a usable Capterra profile extract for this company? Not found is common for non-software companies — not proof of illegitimacy or zero customers. ## Footprint States - **Profile found:** Usable profile extract retrieved — not a verdict on product quality or market leadership. - **Extract thin:** A page returned but rating, count, or core fields were not usable — not proof of no listing forever. - **Not found:** No matching Capterra URL in this discovery pass — expected often outside software. ## Ratings & volume Overall rating and total review count when the observed profile returns them — snapshots, not maturity bands. ## Ratings Cards - **Overall rating:** Numeric overall rating on the listing when present — self-selecting sample. - **Review count:** Total reviews reported on the profile — volume snapshot, not an influencer tier. ## Star distribution Whether per-star counts parse from the listing — useful texture beside the overall average. ## Distribution States - **Distribution observed:** At least one star-level count parseable — still not a representative census. - **Distribution unavailable:** Star counts missing or unparseable — rating or total count may still exist. ## Listing texture Extras on the Capterra profile when disclosed — commercial and competitive cues, not contract truth. ## Listing Cards - **Pricing disclosed:** A starting-price string is shown — not an FX-normalized quote or signed contract. - **Free trial:** Profile claims a free trial — vendor claim, not proof for every segment. - **Free version:** Profile claims a free version — same vendor-claim caveat as trial. - **Reviewer demographics:** Industry, size, title, or location lists present — not a statistically valid ICP census. - **Alternatives listed:** Alternatives appear on the profile — not a competitive win/loss record. ## Trustpilot texture Themes and TrustScore when a page is found — not Signal Check atoms. Trustpilot evidence is narrative research texture. Absence of a profile is lack of data in this pass — not a negative quality verdict. ## Trustpilot Chips - **TrustScore & volume** - **Claimed profile** - **Praise themes** - **Complaint themes** - **Company replies** - **Not found** ## In a verified fit Northline Analytics ## Findings - **Capterra profile found** - **Star distribution observed** - **Trustpilot praise themes** ## Boundaries & method - Self-selecting review samples ≠ product quality truth, market leadership, or ICP fit. - Capterra not found is common outside software — not illegitimacy or zero customers. - No rating trajectory, influencer tiers, or Hot/Warm volume bands. - Pricing string on a listing ≠ FX-normalized contract value. - Free trial / free version flags are vendor claims. - Reviewer demographic lists ≠ statistically valid ICP census. - Alternatives listed ≠ win/loss outcomes. - Trustpilot themes are Deep Check narrative — not Signal Check catalogue atoms. - Trustpilot miss ≠ negative quality signal. - Customer reviews ≠ employee reviews (→ Employee voice). - Customer reviews ≠ Ad Library social proof. - G2 is not in this guide. ## Want customer review signals on your verified fits? We’ll map Capterra footprint and Trustpilot texture to your ICP and show how they look on real accounts. - [Get 10 vetted companies →](https://propensify.io/#lead) - [Book a call](https://propensify.io/book-a-call) --- # Company socials Public company profiles across LinkedIn, Facebook, Instagram, YouTube, and X — footprint, audience size, posting activity, and engagement. _Data source — Company socials signals Propensify detects: public profile footprint, audience size, posting activity, and engagement across LinkedIn, Facebook, Instagram, YouTube, and X._ HTML: https://propensify.io/data-sources/company-socials Markdown: https://propensify.io/data-sources/company-socials.md ## Three questions we ask of the profile and the posts 1. **What identity does the profile assert?** — Professional About text, industry tags, freelancer-of-one versus a real company. 2. **How do they sell in-channel?** — Links to a store, versus DM-to-purchase and unintegrated social checkout. 3. **What is the demand texture?** — Launch posts, viral spikes, stockout comments, dead silence — captions and comments, not ad targeting. No matching public profile in this pass is unknown — not proof they have no account. ## Platforms - LinkedIn - Facebook - Instagram - YouTube - X ## Presence is a gate. Activity is prioritization. ### Profile Whether we find a public company profile, page, or channel on each network. ### Posting & engagement Whether content is showing up recently, at a steady cadence, and drawing engagement. ## How social evidence stacks Three layers — bind the profile, read audience size when returned, then see posting motion and engagement on the content sample. 1. **Profile** — Found / not found 2. **Audience** — Size snapshot 3. **Posting & engagement** — Recent → stale + reactions - **Always useful:** Profile found vs discovery miss — per network. - **Scale snapshot:** Followers or subscribers when the profile returns them. - **Alive on social?:** Posting continuum plus engagement when available. ## Profile footprint Per network we check — a miss is a discovery miss for that platform, not proof they have no account anywhere. Shared gates across LinkedIn, Facebook, Instagram, YouTube, and X. We do not render five separate found/miss walls. ## Footprint States - **Profile found:** A public company profile, page, or channel is attributable on that network. - **Not found:** No matching public profile in this discovery pass — not proof they never have one. ## Audience size Follower or subscriber count when the profile returns it — a snapshot, not growth history. No invented large / mid / small influencer tiers. Count when present; silence when not. ## Audience Card Audience size Numeric followers or subscribers on the observed profile — snapshot only; not a growth trajectory. ## Audience Chips - **Followers** - **Subscribers** ## Posting activity Whether the content sample shows recent posts, a steady cadence, quiet periods, or stale activity — plus honest coverage when dates or posts are thin. Same activity ideas across networks. X may lack cadence when dated posts are thin. ## Posting continuum Shared activity shape once enough dated content is in the sample. _Recently active → stale_ - **Recently active:** Dated content in the shared recent window — the account looks live. - **Steady cadence:** Repeated dated posts at a recognizable interval when the sample supports it. - **Quiet:** Little recent dated content — still present, not obviously posting. - **Stale:** Last dated content is old relative to the shared window. ## Posting Coverage - **Content present:** At least one post, video, or tweet in the returned sample — not a full history. - **No content returned:** Sample came back empty — not proof the account never posts. - **Dates insufficient:** Not enough dated items to place the account on the posting continuum. ## Engagement Numeric reactions, likes, comments, or views on the content sample when available. Enrichment depth differs by network. Absence of an engagement atom is not proof of zero interest forever. ## Engagement Card Engagement observed Reactions, likes, comments, or views on sampled content when the platform returns them — YouTube views sit in this same lane. ## Platform texture Unique surface details that stay as chips — not five mini-guides. ## Platform Texture - **Funding on profile:** Funding disclosed on the LinkedIn company payload when present — not Crunchbase depth, not workforce headcount. - **Page ads claim:** Organic page may claim ads are running or not — that claim is not the Meta Ads Library guide. - **Reels & access:** Reels, paid partnerships, and private profiles are coverage texture — private ≠ no business. - **Shorts & views:** Shorts presence and view counts sit under the shared engagement story when returned. - **Verified & thin dates:** Verified badge when present. Cadence often deferred when dated posts are thin — honesty, not a missing product. ## In a verified fit Northline Analytics ## Findings - **LinkedIn profile found** - **Recently active on Instagram** - **Engagement observed on YouTube** ## Boundaries & method - Organic profiles ≠ Ad Library creatives — pair with LinkedIn Ads, Meta Ads, or Google Ads for paid motion. - Audience size is a snapshot — we do not invent follower growth trajectories. - No follower or subscriber “influencer tiers.” - Content sample ≠ full posting history. - Not found ≠ never present on that network. - LinkedIn funding on profile ≠ Crunchbase round depth. - LinkedIn employee fields on social payloads ≠ Company workforce series. - Facebook page ads-running claim ≠ Meta Ads Library guide. - Private Instagram ≠ no business. - X cadence may be unavailable when dated posts are thin. - Engagement enrichment cost and depth differ by network — silence is coverage, not a verdict. ## Want company socials on your verified fits? We’ll map profile footprint, audience size, posting activity, and engagement across the networks that matter for your ICP. - [Get 10 vetted companies →](https://propensify.io/#lead) - [Book a call](https://propensify.io/book-a-call)