Your Data: Where It Goes and What It’s Worth
An interactive, sourced map of the personal data companies collect about you, who buys and sells it, how it is used, and what it is worth over your lifetime.
Select a data type to learn more
Types of personal data companies collect
Companies documented moving personal data
What it’s worth
What your data is worth over a lifetime
One data point is worth almost nothing. A lifetime of them, connected, is worth this.
Estimated economic value your data generates from 18 to 80, in future dollars
$367,000
Just the advertising slice: $274,000. What you’re paid for any of it: $0.
Kove starts the clock at 18, legally an adult. Many children are online and generating data every day from age 10 or younger, and those years are left out. The real lifetime figure is higher; this estimate is deliberately conservative.
Economic value
what your data can generate across every commercial use
Advertising value
what it is worth specifically for ads and targeting
At age 18, one year of your data is worth about $750 economically, $750 for advertising. Economic value generated so far: $750.
| Yearly growth | 18–44 | 45–59 | 60–80 |
|---|---|---|---|
| Economic value (real) | +2.5% | +1.8% | +1.0% |
| Advertising value (real) | +2.5% | +0.15% | −0.4% |
| Inflation (both lines) | +3.3% | +3.3% | +3.3% |
The chart and figures multiply each year's real growth by 3.3% inflation, so everything is shown in future dollars.
A single record says little. Linked together over decades, they become one detailed history:
↓ a richer longitudinal profile
See how we calculated this
Research estimating the advertising value a single U.S. user generates puts Google and Meta alone at roughly $700 a year. Kove uses $750 as a conservative expanded-profile baseline, adding a small allowance for data generated across health, retail, financial, location, telecom, and data-broker systems. The optional age-13 baseline of $650 is a lower yearly figure for a younger person.
This line answers: how much economic value can your data generate over a lifetime? It covers collection, enrichment, linking, sharing, licensing, resale, analytics, and other commercial uses. Its real growth rate steps down with age: 2.5% a year through 44, 1.8% from 45 to 59, then 1.0% from 60 to 80, before the inflation adjustment below.
Research supports the principle that a richer, more connected behavioral history keeps adding commercial value. There is no market-wide study fixing that growth at exactly these rates, so Kove uses them as modeling assumptions.
This line answers: what is your data worth specifically for advertising and targeting? In real terms it rises with economic value through age 44, then nearly flattens from 45 to 59 and turns slightly negative from 60 to 80. More data does not always mean more advertiser demand: advertising research suggests commercial ad value tends to peak around 35 to 44 and fall off afterward in some markets. In the future-dollar figures shown here, inflation keeps this line rising, but it falls further behind economic value every year.
Age-based advertising values are averages and vary widely by product, income, health, location, household, and purchasing intent. They do not set the value of any one person’s data. The specific rates here are Kove assumptions.
By default, every year on both lines is also multiplied by 3.3% for long-term inflation, so the figures are stated in future dollars rather than today’s purchasing power.
3.3% is a long-term assumption. Real inflation varies year to year and can’t be predicted across a lifetime. It raises the nominal dollar figure without meaning the data itself became more useful.
Where the two lines diverge
Both lines are identical from the start through age 44. After that, economic value keeps compounding at the higher rate while advertising value’s real growth stalls, so even though inflation keeps both rising in dollar terms, the gap widens every year, and the headline (economic) ends well ahead of the advertising figure.
About this estimate
There is no universal market price for a person’s data. It is collected, combined, licensed, shared, analyzed, and monetized in many different ways, and its value depends heavily on who holds it and what they can do with it. This is a model, not a market appraisal.
It starts from published estimates of U.S. consumer advertising value tied to Google and Meta, with a small Kove adjustment for data generated elsewhere, then grows that figure each year at assumed real rates, higher early in life and lower later, along two tracks: broad economic value and narrower advertising value. By default every year is also multiplied by 3.3% for inflation, so the figures are in future dollars. Every year before the start age (18, or 13 if selected) is excluded, so the true figure is higher.
Research supports the idea that richer, more connected data improves targeting, prediction, and profiling, but the specific rates are Kove assumptions. Read this as an illustration of the potential cumulative economic value of a person’s data, not an amount anyone could sell their data for, and not a check anyone is going to write you.
Sources
- Proton - What's Your Data Really Worth?
Estimates that a U.S. person's data is worth at least $700 a year, built from Meta's and Google's own earnings (roughly $217 and $460 per American user). It is the basis for this section's $750 starting baseline.
- Proton - Google Has a Price for You. We Found It.
An analysis of more than 54,000 real ad-auction profiles, finding the average American generates about $1,605 a year in advertising value, from roughly $31 to nearly $18,000 depending on age, location, device, and household. Its age patterns inform the advertising-value line.
- FTC - Data Brokers: A Call for Transparency and Accountability (2014)
The FTC's study of nine large data brokers, documenting how they collect, combine, and sell data on nearly every U.S. household for marketing and risk scoring, with little consumer visibility or control. It supports the broader economic-value view: data is enriched, linked, and resold well beyond advertising.
- Pew Research Center - Teens, Social Media and Technology 2024
A national survey of U.S. teens ages 13 to 17 finding nearly half are online almost constantly, up from 24% a decade ago. It is the basis for the optional age-13 start, since meaningful data collection begins years before adulthood.
Curious what one piece sells for on its own? Open any data type in the sphere above and expand “What it’s worth.”
How this was put together
Each data type here is built from public reporting, regulatory filings, and company disclosures. Every named company and dollar figure links to its source in the panel that opens when you select a data type. Where a claim couldn’t be tied to a specific company, it is attributed to a category, “data brokers” or “an ad exchange,” instead of a name.
Prices are ranges because that is how this market works: the same record sells for different amounts depending on how fresh it is, how precisely it is tied to a person, and who is buying. Effects are labeled by how well they are supported, a direct effect has evidence behind it, a possible inference is something the data could enable but that we can’t show happens to everyone.
For what Kove itself does with your data, see our data transparency page. Found a mistake or a source we missed? Tell us.
Last reviewed August 2026.
Image credit: Public Domain Vectors on Unsplash.
Every type of personal data, in full
The same content as the interactive sphere above, as a plain reference: what each type of data is, who collects it, who it is sold or shared to, how it is used, how it affects you, what it is worth, and the source for every claim.
Email
Identity dataA reachable email address that acts as the key linking your other data together.
- Collected by
- Signup forms, Retailers and apps, List compilers
- Shared with / received by
- Ad platforms, List brokers, Identity graphs
- Used for
- Ad targeting, Audience matching, Marketing lists
Effects on you
- Ad retargeting. Your email lets advertisers find and re-target you on other platforms. (Direct effect)
- Cross-device profile. Matching your email to a device ID links your activity across phone, browser, and app. (Combined-data effect)
- Purchase history tied to your name. Retailers use your email to connect purchases across their own and partner systems. (Combined-data effect)
Connected data
- Phone. Email and phone are matched together as the two core contact identifiers in identity graphs. (Identity connection)
- Device ID. Hashed emails are matched to device and advertising IDs to build one cross-device profile. (Identity connection)
- Purchases and Loyalty. Your email is the index key that links your purchase history across different retailers. (Inferred connection)
Company relationships
Advertisers to Meta to Matched ad audience User-authorized connection
Data shared: email, phone. Purpose: Matching an advertiser's customer list to your account for ad targeting. When: current.
Uploading your email to a company lets that company find and target you on ad platforms.
Data brokers to Acxiom / LiveRamp to Marketers Sold to
Data shared: email. Purpose: Bulk resale of consumer email lists for direct marketing. When: current.
Your email can be bought and resold in bulk lists you never directly signed up for.
Twitter (now X) to Twitter ad system to Advertisers Used for matching
Data shared: email, phone number. Purpose: Ad targeting using contact info that users gave for account security. When: 2014-2019.
Emails and phone numbers given for two-factor login were quietly used to target ads; a $150M FTC/DOJ penalty followed.
Source: FTC / DOJ, US v. Twitter (2022)
Unroll.Me to Slice Technologies to Market researchers Sold to
Data shared: e-receipts, purchase details. Purpose: Extracting and selling receipt data from users' inboxes. When: through 2019.
An inbox tool that told users it would not touch their personal email extracted and sold their e-receipt data.
Source: FTC, In re Unrollme (2019)
What it’s worth
$0.10 - $0.40 per address in bulk lists (Recurring) Priced per thousand records; B2B lists sell for far more than consumer lists.
Phone
Identity dataA phone number used as both a contact method and a matching key across data brokers.
- Collected by
- Apps and signup forms, Wireless carriers, List compilers
- Shared with / received by
- Skip tracers, Political campaigns, Identity graphs
- Used for
- People-search lookups, Political outreach, Ad matching
Effects on you
- People-search lookups. Your phone number is a standard field in paid background-check and skip-trace reports. (Direct effect)
- Political and telemarketing contact. Political campaigns and telemarketers buy phone lists that include your number. (Direct effect)
- Cross-device identity resolution. Your phone number helps tie your email, device, and browsing activity into one profile. (Combined-data effect)
Connected data
- Email. Email and phone are matched together as the two core contact identifiers in identity graphs. (Identity connection)
- Device ID. Phone numbers are matched to mobile ad IDs inside identity-resolution graphs. (Identity connection)
- Public Record Profile. A phone number is a core field returned in nearly every people-search and background-check report. (Direct connection)
Company relationships
Political data vendors to i360 / TargetSmart to Campaigns Sold to
Data shared: phone, name, address. Purpose: Voter outreach and canvassing. When: current.
Your number can end up in a political campaign's calling and texting list without you giving it to that campaign directly.
LexisNexis / TransUnion TLOxp to Law firms and skip tracers Licensed to
Data shared: phone, address. Purpose: Locating a person for legal, collections, or investigative purposes. When: current.
Your number is retrievable through paid lookup tools by anyone with a documented permissible purpose.
Twitter (now X) to Twitter ad system to Advertisers Used for matching
Data shared: phone number, email. Purpose: Ad targeting using the phone number users gave for two-factor login. When: 2014-2019.
A phone number given only to secure an account was matched against advertiser lists; Twitter paid a $150M penalty.
Source: FTC / DOJ, US v. Twitter (2022)
What it’s worth
$0.02 - $0.09 per record in bulk offerings (Recurring) Lookup-service pricing (per-search/per-report) is separate and typically higher than bulk list pricing.
Mailing Address
Identity dataYour name and home address, sold as the base record that other fields get attached to.
- Collected by
- Retailers and catalogs, Public records, List compilers
- Shared with / received by
- Direct-mail marketers, Political campaigns, Data brokers
- Used for
- Direct mail, Voter file matching, Household enrichment
Effects on you
- Direct mail and catalogs. Your address is sold in bulk mailing lists used for physical marketing. (Direct effect)
- Household profile. Combined with property and demographic data, your address anchors a full household record. (Combined-data effect)
Connected data
- Property / Homeowner Data. Mailing address and property ownership records are collected and sold together as one household record. (Direct connection)
- Demographics. Mailing lists are commonly sold pre-bundled with demographic selects like age and income. (Direct connection)
- Political / Voter Data. Voter files use your mailing address as the primary field for matching you to other records. (Identity connection)
- Public Record Profile. Address history is a core field returned in people-search reports. (Direct connection)
Company relationships
List compilers to Direct-mail marketers Sold to
Data shared: name, mailing address. Purpose: Direct-mail marketing campaigns. When: current.
Your name and address can be purchased as part of a mailing list for a few cents per record.
Source: DataZapp / DirectMail.com mailing list pricing (2026)
Epsilon Data Management to Mass-mail fraud schemes Sold to
Data shared: name, address, modeled susceptibility scores. Purpose: Selling modeled response lists drawn from ~100M households, some to elder-fraud operations. When: 2008-2017.
Epsilon admitted knowingly selling fraud-targeting lists; a $150M DOJ resolution covered data on over 30 million people.
DoorDash to Marketing data co-op to Co-op members and downstream brokers Shared with
Data shared: name, delivery address, order history. Purpose: Trading customer lists for access to other companies' customers. When: 2020.
DoorDash put customer names and addresses into a marketing co-op with no notice or opt-out; $375K California settlement.
What it’s worth
$0.034 - $0.049 per record in bulk (Recurring) Base consumer mailing list rate; higher-touch products (labels, disk files) cost more.
Demographics
Identity dataAge, income, household size, and similar traits appended to your contact record.
- Collected by
- Retailers and surveys, List compilers, Modeling firms
- Shared with / received by
- Advertisers, Political data vendors, Lead marketplaces
- Used for
- Ad audience building, Lead scoring, Voter file enrichment
Effects on you
- Ad audience segmentation. Demographic traits are used to sort you into advertiser targeting segments. (Direct effect)
- Lead and risk scoring. Combined with financial and property data, demographics feed models that score you as a sales lead. (Combined-data effect)
Connected data
- Mailing Address. Mailing lists are commonly sold pre-bundled with demographic selects like age and income. (Direct connection)
- Purchases and Loyalty. Demographic traits are combined with purchase history to build predictive shopping segments. (Inferred connection)
- Financial Intent / Leads. Estimated income and household demographics feed directly into lead-scoring models. (Inferred connection)
- Political / Voter Data. Campaign data vendors enrich the public voter file with commercial demographic data. (Direct connection)
Company relationships
Enrichment firms to Advertisers and lead buyers Sold to
Data shared: demographics. Purpose: Audience segmentation and lead scoring. When: current.
A demographic profile built without your direct involvement can determine which offers and prices you see.
Source: DataZapp / DirectMail.com demographic append pricing (2026)
VIZIO smart TVs to Data and advertising companies Sold to
Data shared: second-by-second viewing history, appended demographics. Purpose: Selling TV viewing data with age, gender, income, and other traits attached. When: 2014-2017.
11 million TVs collected viewing history without consent; $2.2M FTC and New Jersey settlement.
Businesses and nonprofits to KBM Group / iBehavior co-op to Fraudulent mailers Licensed to
Data shared: name, address, demographics, transaction history. Purpose: Licensing pooled consumer data, including to fraud clients. When: 2012-2018.
KBM acknowledged licensing cooperative consumer data to fraud operations; $42M DOJ resolution.
Source: US DOJ, US v. KBM Group (2021)
What it’s worth
$0.001 - $0.02 per record as an append (Recurring) Priced as a per-record add-on to an existing contact list rather than sold standalone.
Device ID
Identity dataAn advertising or device identifier that stitches your activity together across apps and sites.
- Collected by
- Mobile operating systems, Apps and SDKs, Ad exchanges
- Shared with / received by
- Identity platforms, Ad exchanges, Data marketplaces
- Used for
- Cross-device matching, Ad targeting, Audience activation
Effects on you
- Cross-device tracking. A device ID links your activity across your phone, browser, and connected TV into one profile. (Direct effect)
- Location trail reconstruction. Combined with location pings, a device ID turns scattered data points into a continuous movement history. (Combined-data effect)
Connected data
- Email. Hashed emails are matched to device and advertising IDs to build one cross-device profile. (Identity connection)
- Phone. Phone numbers are matched to mobile ad IDs inside identity-resolution graphs. (Identity connection)
- Location. A device ID is how scattered location pings from one phone get tied into a single continuous trail. (Direct connection)
- Browsing and Search. Browsing and clickstream data is collected against a device identifier before being resold. (Direct connection)
Company relationships
Apps and SDKs to LiveRamp identity graph to Advertisers and platforms Processed by
Data shared: device id, email, phone. Purpose: Linking a person's activity across devices for targeting and measurement. When: current.
Your device ID is the connective tissue that turns separate, harmless-looking data points into one unified profile.
Child-directed apps and sites to OpenX ad exchange to Advertisers Processed by
Data shared: persistent identifiers, geolocation. Purpose: Passing kids' device identifiers and location into the ad exchange without parental consent. When: through 2021.
A $2M penalty followed collection of children's data and location from users who had opted out.
Source: FTC / DOJ, US v. OpenX (2021)
Jam City mobile games (21 titles) to Ad-tech partners Sold to
Data shared: mobile identifiers, game activity, data of some 13-15 year olds. Purpose: Selling or sharing mobile-game data with no compliant opt-out. When: through 2025.
$1.4M California settlement over 21 games that offered no working opt-out.
What it’s worth
A fraction of a cent per identifier in bulk; a few cents when paired with fresh location or app-activity data (Recurring) Almost never sold on its own. The value is in what it unlocks - matching one real person to every other dataset inside an identity graph.
Identity / SSN
Identity dataName, date of birth, and Social Security Number data used to verify or look up a real person.
- Collected by
- Credit bureaus, Government and court records, Data breaches
- Shared with / received by
- Background-check firms, Law firms and collectors, Employers and insurers
- Used for
- Identity verification, Background checks, Skip tracing
Effects on you
- Background checks. Employers, landlords, and lenders use your identity fields to run compliant background checks. (Direct effect)
- Breach resale. The same identity fields sell for far less on breach-fed markets, where oversupply crashes the price. (Direct effect)
Connected data
- Bank Transactions. SSN and credit-header data anchor the same financial identity that bank transaction data is tied to. (Identity connection)
- Public Record Profile. SSN and credit-header fields are the backbone of people-search and background-check reports. (Direct connection)
- Financial Intent / Leads. A verified identity combined with a declared need is what turns a record into a sellable lead. (Inferred connection)
- Military / Occupation. Military and occupation status is combined with identifiable contact and financial fields in the same broker records. (Direct connection)
- Genetic Data. A genetic profile is one more identity-linked record that can be matched back to a named person. (Inferred connection)
Company relationships
Credit bureaus to LexisNexis Risk Solutions / TransUnion TLOxp to Employers and law firms Licensed to
Data shared: name, address, date of birth. Purpose: Identity verification and permissible-purpose lookups. When: current.
Your identity fields are searchable by any business with a documented legal reason, for a per-search fee.
Payday and personal-loan sites to LeapLab and ITMedia Solutions to Non-lender marketers Sold to
Data shared: name, SSN, bank account and routing numbers. Purpose: Reselling loan applications with full identity and bank details to non-lenders. When: 2014-2022.
LeapLab sold 95% of applications for about $0.50 each; ITMedia sent 84% to non-lenders. Both settled with the FTC.
Source: FTC, In re LeapLab (2016)
What it’s worth
$1 per legitimate lookup search, versus $1 - $8 for a stolen SSN alone (One-time) The legal and illicit markets for the same fields are priced roughly 100 to 1000 times apart.
Public Record Profile
Identity dataA compiled report of your public records, addresses, and relatives, sold as a consumer lookup product.
- Collected by
- Public records, Broker contact data
- Shared with / received by
- Consumers, Investigators, Businesses
- Used for
- Background checks, Investigations, Contact discovery
Effects on you
- Public lookup by anyone. A person-search subscription lets any paying user pull your compiled record. (Direct effect)
- Errors that follow you. A mismatched name or address on a report can attach someone else's record to your profile. (Possible inference)
Connected data
- Phone. A phone number is a core field returned in nearly every people-search and background-check report. (Direct connection)
- Mailing Address. Address history is a core field returned in people-search reports. (Direct connection)
- Identity / SSN. SSN and credit-header fields are the backbone of people-search and background-check reports. (Direct connection)
Company relationships
Public records and broker data to People-search sites Sold to
Data shared: name, address, phone, relatives. Purpose: Consumer background-check and lookup subscriptions. When: current.
Anyone can pay a monthly fee to pull up a compiled report on you, whether or not you have any relationship with them.
Source: DetectiveCheck background check pricing survey (2026)
What it’s worth
$6 - $37 per month subscription; ~$30 per single report (Recurring) This is the price of the retail lookup product, not the underlying bulk data.
Browsing and Search
Activity dataWhat you search for and the sites you visit, often collected through a browser extension or antivirus tool.
- Collected by
- Browser extensions, Antivirus software, Ad-tech scripts on websites, Smart TVs and streaming apps
- Shared with / received by
- Ad agencies, Data brokers, Identity platforms
- Used for
- Ad targeting, Competitive research, Audience segmentation
Effects on you
- Re-identifiable browsing sold in bulk. Detailed browsing history has been sold to more than 100 third parties despite being marketed as anonymized. (Direct effect)
- Health and interest inference. Search and browsing patterns can reveal health concerns, religion, or financial status without a direct health disclosure. (Combined-data effect)
Connected data
- Device ID. Browsing and clickstream data is collected against a device identifier before being resold. (Direct connection)
- Purchases and Loyalty. Browsing and purchase behavior are captured together in the same retail and ad-tech pipelines. (Direct connection)
- Health. Searches and browsing activity can reveal a health condition before any health app is ever involved. (Inferred connection)
Company relationships
Avast antivirus to Jumpshot to Ad agencies and 100+ buyers Sold to
Data shared: browsing history, device id. Purpose: Resale of detailed clickstream data for advertising and analytics. When: 2014-2020.
Data from a privacy tool you installed to protect yourself was sold to over 100 companies without clear consent.
Source: FTC v. Avast, final order (2024)
VIZIO smart TVs to Third-party data and advertising companies Sold to
Data shared: second-by-second viewing history. Purpose: Selling TV viewing history without consumers' knowledge. When: 2014-2017.
Software on 11 million TVs captured what people watched from every input; $2.2M FTC and New Jersey settlement.
Disney+ / Hulu / ESPN+ to Disney ad systems to Third-party ad-tech Sold to
Data shared: account-linked device and activity data. Purpose: Selling streaming activity data across services and devices. When: through 2026.
$2.75M California settlement; data kept being shared on other services and devices after users opted out.
Sephora website and app to Advertising and analytics providers Sold to
Data shared: shopping and browsing activity, device data. Purpose: Selling browsing and shopping data despite Global Privacy Control opt-outs. When: through 2022.
$1.2M California settlement - the first major CCPA enforcement action.
Healthline.com to Ad and analytics trackers Shared with
Data shared: identifiers, article titles that could suggest a diagnosis. Purpose: Sharing health-article reading data despite user opt-outs. When: through 2025.
$1.55M California settlement - the largest CCPA settlement to date - after a consent banner that did not work as represented.
Source: California DOJ, largest CCPA settlement to date (2025)
What it’s worth
Millions of dollars per year for a bulk feed covering a large user base (Recurring) Rarely priced per person; sold as licensed datasets or activated ad audiences instead.
Purchases and Loyalty
Activity dataWhat you buy, tracked through loyalty cards, retailer accounts, and card networks.
- Collected by
- Retailer loyalty programs, Card networks, E-commerce platforms
- Shared with / received by
- CPG brands, Ad platforms, Market research firms
- Used for
- Retail media advertising, Trend research, Audience targeting
Effects on you
- Retail media ad targeting. Your purchase history is licensed to ad platforms to target you across the web, not just in one store's app. (Direct effect)
- Physical routine profiling. Purchases combined with location build a picture of your regular movements and habits. (Combined-data effect)
Connected data
- Email. Your email is the index key that links your purchase history across different retailers. (Inferred connection)
- Browsing and Search. Browsing and purchase behavior are captured together in the same retail and ad-tech pipelines. (Direct connection)
- Location. In-store purchases and location visits combine into a picture of a person's physical routine. (Inferred connection)
- Bank Transactions. Purchase-level detail is a byproduct of the same transaction feeds banks and card networks sell. (Direct connection)
- Demographics. Demographic traits are combined with purchase history to build predictive shopping segments. (Inferred connection)
Company relationships
Walmart Connect to Google Display and Video 360 / YouTube to Advertisers Licensed to
Data shared: purchase history, loyalty data. Purpose: First-party retail audience targeting and sales measurement. When: current.
Your loyalty-card purchases can be used to target you with ads on platforms outside the retailer's own app.
Source: Walmart Connect, Google DV360 integration announcement (2026)
DoorDash to Marketing data co-op to Downstream brokers Shared with
Data shared: order history, name, delivery address. Purpose: Trading customer order data into a marketing co-op. When: 2020.
$375K California settlement; DoorDash sold the data with no notice or an opt-out.
Unroll.Me to Slice Technologies to Market researchers Sold to
Data shared: e-receipts, purchase details. Purpose: Extracting and selling receipt data from users' email inboxes. When: through 2019.
The tool told users it would not touch their personal email while selling their receipt data to researchers.
Source: FTC, In re Unrollme (2019)
What it’s worth
roughly $0.10 - $0.40 per record for transaction-history segments (Recurring) Low-confidence secondary estimate - this market is usually priced as licensed audience access, not per record.
Location
Sensitive / Real-world dataWhere you go, how often, and how long you stay, collected through your phone's location permission.
- Collected by
- Mobile apps with location permission, Mobile carriers, In-store wifi and beacons
- Shared with / received by
- Data brokers, Advertising exchanges, Government agencies
- Used for
- Targeted advertising, Foot-traffic measurement, Insurance and lending risk models
Effects on you
- Ad targeting by places you visit. Visits to clinics, gyms, or dealerships can move you into ad audiences. (Direct effect)
- Inferred home and work. Overnight and daytime location clusters reveal where you live and work. (Combined-data effect)
- Insurance and lending risk scoring. Location and driving patterns can be sold into insurer risk models without a person actively opting into a specific program. (Combined-data effect)
- Stigma and physical safety risk. Location can reveal visits to reproductive-health clinics, shelters, or places of worship, raising real safety concerns. (Possible inference)
Connected data
- Driving. Trip location and driving behavior are captured together in the same telematics feed. (Direct connection)
- Device ID. A device identifier ties scattered location pings into one continuous trail. (Identity connection)
- Purchases and Loyalty. The places someone visits hint at what they buy and where. (Inferred connection)
- Political / Voter Data. Visit patterns to churches or campaign events can be used to infer political or religious affiliation. (Inferred connection)
- Health. Visits to clinics and pharmacies are a documented way location data reveals a health condition. (Inferred connection)
Company relationships
Weather / utility apps to X-Mode / Outlogic to Ad exchanges Sold to
Data shared: location, timestamps, device identifier. Purpose: Audience targeting and location analytics. When: 2017-2021.
Places visited can move a person into ad audiences without their knowledge.
Source: FTC v. X-Mode / Outlogic (2024)
Mobile apps to Gravy Analytics / Venntel to Federal agencies Sold to
Data shared: location, device identifier. Purpose: Government location tracking without a warrant. When: current.
A single location permission tap has reached 20+ companies before ending up in a government purchase, no warrant required.
Real-time ad-bidding requests to Mobilewalla to Advertising, political, and government clients Sold to
Data shared: mobile ad IDs, precise geolocation, inferred segments. Purpose: Harvesting location from ad-auction bid requests and reselling it. When: 2018-2020.
The FTC banned Mobilewalla from selling sensitive location data it had quietly pulled from bidstream traffic.
Source: FTC, In re Mobilewalla (2025)
The Weather Channel app (owned by IBM) to Advertisers and hedge funds Sold to
Data shared: precise location. Purpose: Selling location to advertisers and to hedge funds for consumer-behavior analysis. When: 2019.
The LA City Attorney sued over selling location while the app implied it was only used for forecasts.
InMarket and third-party apps to InMarket Media to Advertisers Sold to
Data shared: precise location, visit histories. Purpose: Building ad audiences from location without informed consent. When: through 2024.
FTC final order; InMarket also failed to verify that its SDK partners had obtained consent.
Source: FTC, In re InMarket (2024)
What it’s worth
under $0.01 per person in bulk; up to $1,100 for a single real-time lookup (Recurring) Over a lifetime: a few dollars per year, per broker holding the data. Bulk pricing and single targeted-lookup pricing differ by roughly five orders of magnitude.
Driving
Sensitive / Real-world dataSpeed, braking, and trip data collected through a car, insurance app, or family-safety app.
- Collected by
- Connected vehicles, Insurance telematics apps, Family-safety apps
- Shared with / received by
- Automakers' data partners, Insurers, Consumer reporting agencies
- Used for
- Insurance pricing, Risk scoring, Personalized quotes
Effects on you
- Insurance premium moves in either direction. Progressive reports about 2 in 10 telematics participants see an increase, while discount earners save an average of $328 a year. (Direct effect)
- Scored without an active opt-in. Owning a connected car can put your driving data into an insurer's risk model even if you never signed up for a specific telematics program. (Direct effect)
Connected data
- Location. Trip location and driving behavior are captured together in the same telematics feed. (Direct connection)
- Bank Transactions. Driving-behavior scores are sold into the same insurer risk-pricing pipeline as claims and credit-based insurance data. (Inferred connection)
Company relationships
GM OnStar Smart Driver to LexisNexis Risk Solutions and Verisk to Insurers Sold to
Data shared: driving behavior, location, VIN. Purpose: Insurance risk scoring. When: 2019-2024.
Driving data was sold to consumer reporting agencies and used against drivers in insurance pricing, despite a privacy policy saying otherwise.
Life360 to Arity to Participating insurers User-authorized connection
Data shared: location, driving behavior. Purpose: Opt-in personalized insurance quoting. When: current.
Opting in can lower a safe driver's quote, but Life360 says the same data can raise a high-risk driver's rate at renewal.
Source: Life360 Support, Arity (2026)
Hyundai to Verisk to Insurers Sold to
Data shared: driving behavior. Purpose: Selling connected-car driving data for insurance risk scoring. When: 2018-2024.
Hyundai sold data from about 1.7 million cars at $0.61 per car (over $1 million total), per a Senate investigation.
Honda to Verisk to Insurers Sold to
Data shared: driving behavior. Purpose: Selling connected-car driving data for insurance risk scoring. When: 2020-2024.
Honda sold data from about 97,000 cars at $0.26 per car (roughly $25,920 total).
Source: Sen. Wyden letter to the FTC, via Sherwood News (2024)
Automakers (GM, Hyundai, Honda, Kia, Mitsubishi) to LexisNexis Telematics Exchange to Insurers Shared with
Data shared: driving events, VIN-linked behavior. Purpose: Routing connected-car driving data into insurance scoring. When: current.
Multiple automakers feed driving data through the same insurance-data exchange, often disclosed only deep in a privacy policy.
Source: Kelley Blue Book, on the NYT automaker investigation (2024)
What it’s worth
$0.26 - $0.61 per car in bulk sales to analytics firms; separately, telematics scoring can move an insurance quote by tens to hundreds of dollars a year (Recurring) Automakers sold connected-car driving data to Verisk for cents per vehicle - Honda about $0.26, Hyundai about $0.61. The larger cost usually lands indirectly, as a change in insurance pricing. Buyers: Verisk, LexisNexis Risk Solutions.
Bank Transactions
Sensitive / Real-world dataYour bank and card transaction history, aggregated and licensed as a subscription data product.
- Collected by
- Banks and fintech apps, Card networks, Financial aggregators
- Shared with / received by
- Hedge funds, Investment research firms, Consumer reporting agencies
- Used for
- Investment research, Insurance underwriting, Credit and lending decisions
Effects on you
- Credit and lending decisions. Lenders use your credit report and score, built partly from transaction data, to set your interest rate and credit limit. (Direct effect)
- Insurance underwriting. Credit-based insurance scores affect auto and homeowners premiums for the large majority of insurers where state law allows it. (Direct effect)
- Investment research on de-identified data. Aggregated transaction panels are sold to hedge funds to predict company-level sales trends. (Direct effect)
Connected data
- Identity / SSN. SSN and credit-header data anchor the same financial identity that bank transaction data is tied to. (Identity connection)
- Purchases and Loyalty. Purchase-level detail is a byproduct of the same transaction feeds banks and card networks sell. (Direct connection)
- Financial Intent / Leads. Wealth and intent scores are built directly from financial and transaction signals. (Direct connection)
- Driving. Driving-behavior scores are sold into the same insurer risk-pricing pipeline as claims and credit-based insurance data. (Inferred connection)
Company relationships
Banks and fintech apps to Envestnet Yodlee to Hedge funds and researchers Licensed to
Data shared: transaction history. Purpose: Investment research using de-identified consumer spending data. When: current.
Your de-identified spending pattern helps investors predict a public company's quarterly earnings before you know it yourself.
Source: Forbes, Mastercard AmEx And Envestnet Profit From $400M Business Of Selling Transaction Data (2018)
Online tax-filing services (TaxAct, H&R Block, TaxSlayer) to Meta and Google to Ad systems Shared with
Data shared: income, refund amount, filing status, dependents. Purpose: Sending tax-return details to ad platforms via tracking pixels. When: 2022.
A Senate investigation and FTC warning found filers' financial details were sent to Meta and Google while they filed their taxes.
Source: The Markup, Tax Filing Websites Have Been Sending Users' Financial Information to Facebook (2022)
Employers and payroll systems to Equifax Workforce Solutions (The Work Number) to Lenders, collectors, and employers Sold to
Data shared: employment history, salary records. Purpose: Selling salary and employment records for verification. When: current.
About 75% of Fortune 500 companies feed employee salary data in; access is sold per pull without notice at the point of sale.
Source: Fast Company, Facebook and America's largest companies quietly give worker data to Equifax (2019)
What it’s worth
not sold per record - licensed as an aggregate subscription, reportedly $2M+/year per hedge fund client (Recurring) Individual-level pricing is not public; value is captured through subscription access to the aggregate dataset.
Financial Intent / Leads
Sensitive / Real-world dataYour identity combined with a recent, declared need, like requesting an insurance or mortgage quote.
- Collected by
- Insurance and mortgage quote forms, Comparison marketplaces, Affiliate sites
- Shared with / received by
- Lenders, Insurance agents, Home-service companies
- Used for
- Sales outreach, Underwriting prospecting, Marketing follow-up
Effects on you
- Multiple companies contact you at once. A shared, non-exclusive lead is sold to several buyers, which is why one form submission can trigger many calls. (Direct effect)
- Value drops fast. A lead's price falls sharply within days as the declared intent goes stale. (Direct effect)
Connected data
- Demographics. Estimated income and household demographics feed directly into lead-scoring models. (Inferred connection)
- Identity / SSN. A verified identity combined with a declared need is what turns a record into a sellable lead. (Inferred connection)
- Bank Transactions. Wealth and intent scores are built directly from financial and transaction signals. (Direct connection)
- Property / Homeowner Data. Homeowner and property data is a core input to mortgage and home-service lead scoring. (Direct connection)
Company relationships
Quote and comparison forms to Lead marketplaces to Lenders and agents Sold to
Data shared: contact info, declared intent. Purpose: Sale of sales leads to multiple competing buyers. When: current.
Filling out one quote form can result in your contact information being sold to several competing companies at once, unless the form says the lead is exclusive.
Payday-loan websites to LeapLab to Non-lender marketers to Ideal Financial Solutions Sold to
Data shared: name, SSN, bank account and routing numbers. Purpose: Reselling loan applications to non-lenders with no legitimate need. When: through 2016.
LeapLab sold about 95% of loan applications - including SSNs and bank details - for roughly $0.50 each.
Source: FTC, In re LeapLab (2016)
Loan comparison sites to ITMedia Solutions to Marketers and debt-relief sellers Sold to
Data shared: SSN, bank-account info. Purpose: Routing loan applications to non-lenders and resellers. When: through 2022.
84% of applications since 2016 went to non-lenders; $1.5M FTC penalty.
What it’s worth
$5 - $50 for an insurance lead; $20 - $200 for a mortgage lead depending on exclusivity (One-time) Priced per lead, not per record - value depends on freshness, exclusivity, and qualification.
Health
Sensitive / Real-world dataHealth conditions and mental-health details, often collected outside HIPAA through non-medical apps.
- Collected by
- Health and wellness apps, Telehealth platforms, Pharmacy and prescription services
- Shared with / received by
- Advertisers, Data brokers, Insurance underwriters, Employers (wellness programs)
- Used for
- Condition-based ad targeting, Life and disability underwriting, Care-management scoring
Effects on you
- Condition-based ad targeting. Being placed on a list like Anxiety Sufferers or Clinical Depression can shape which ads you see, with little vetting of the buyer. (Direct effect)
- Life and disability insurance underwriting. Prescription purchase history can be used to build a mortality-risk score outside a medical exam. (Direct effect)
- Not a factor in ACA Marketplace pricing. Health status and medical history cannot legally raise your ACA Marketplace premium, unlike life or disability insurance. (Direct effect)
Connected data
- Browsing and Search. Searches and browsing activity can reveal a health condition before any health app is ever involved. (Inferred connection)
- Location. Visits to clinics and pharmacies are a documented way location data reveals a health condition. (Inferred connection)
- Genetic Data. Health-condition data and genetic data are both handled as specialty health data outside HIPAA when sold by brokers. (Direct connection)
- Military / Occupation. Occupation-sensitive segments are sometimes combined with health attributes in the same specialty broker lists. (Inferred connection)
Company relationships
GoodRx to Facebook Google and Criteo to Advertisers Shared with
Data shared: prescription info, health conditions. Purpose: Targeted advertising using prescription and health data. When: 2017-2023.
Health app data was used to target the same users with ads related to their own medical conditions.
Source: FTC v. GoodRx (2023)
BetterHelp to Facebook Snapchat Criteo Pinterest to Advertisers Shared with
Data shared: therapy questionnaire answers, health status. Purpose: Targeted advertising using mental-health data. When: 2017-2023.
Therapy intake answers were shared for ad targeting despite a promise to keep health data private.
Source: FTC v. BetterHelp (2023)
Flo period-tracker to Facebook, Google, AppsFlyer Shared with
Data shared: menstruation, fertility, and pregnancy events, device IDs. Purpose: Sharing cycle and pregnancy data with ad and analytics platforms. When: 2016-2019.
The FTC found Flo shared fertility events despite telling users the data would stay private.
Source: FTC, In re Flo Health (2021)
Cerebral to LinkedIn, Snapchat, TikTok Shared with
Data shared: prescription history, insurance and pharmacy data. Purpose: Disclosing mental-health data for advertising. When: through 2023.
Over $7M settlement; the data was disclosed despite confidentiality promises.
Source: FTC / DOJ, US v. Cerebral (2024)
Ovia fertility and pregnancy apps to Ovia Health to Participating employers Sold to
Data shared: fertility and pregnancy data, high-risk pregnancy status, return-to-work timing. Purpose: Selling employers an aggregated view of workers' reproductive-health data. When: current.
Offered as a corporate wellness benefit; employers can see aggregate fertility and pregnancy trends among staff.
What it’s worth
$275 per 1,000 aggregated records at the cheap end, up to $15,000-$100,000+ for an annual license (Recurring) Sold with demographic overlays already attached, so one purchase usually combines several data types at once.
Genetic Data
Sensitive / Real-world dataDNA test results, which can become a transferable company asset regardless of how you consented to give them.
- Collected by
- At-home DNA testing services
- Shared with / received by
- Pharmaceutical companies, Research partners, Law enforcement
- Used for
- Drug discovery, Genetic research, Criminal investigations
Effects on you
- Sold as a corporate asset. A company holding your genetic data can sell it as part of a bankruptcy, regardless of your original consent terms. (Direct effect)
- Licensed for drug research. Consented research data can be licensed to a pharmaceutical company for target discovery. (Direct effect)
Connected data
- Health. Health-condition data and genetic data are both handled as specialty health data outside HIPAA when sold by brokers. (Direct connection)
- Identity / SSN. A genetic profile is one more identity-linked record that can be matched back to a named person. (Inferred connection)
Company relationships
23andMe to Regeneron Pharmaceuticals Sold to
Data shared: genetic profile. Purpose: Bankruptcy asset sale of the full genetic database. When: 2025.
Your genetic data can be sold as a corporate asset in a bankruptcy, regardless of the terms you originally agreed to.
Source: TechCrunch, Regeneron to buy 23andMe and its customers data for $256M (2025)
23andMe to GSK Licensed to
Data shared: consented research data. Purpose: Drug-target discovery research license. When: 2023-2024.
Data from consenting research participants was licensed to a drug company for a disclosed $20 million upfront fee.
Source: 23andMe, GSK collaboration extension and data licensing announcement (2023)
FamilyTreeDNA to FBI Shared with
Data shared: consumer genetic profiles. Purpose: Giving law enforcement search access to the consumer DNA database. When: 2019.
FamilyTreeDNA gave the FBI the same access level as a regular user, without notifying customers.
What it’s worth
roughly $17 per profile in the 23andMe bankruptcy sale (One-time) A rare directly-priced genetic-data transaction; most genetic data does not have public pricing.
Political / Voter Data
Sensitive / Real-world dataYour voter registration record, enriched with commercial data and used to target you politically.
- Collected by
- State voter files (public record), Political data vendors, Commercial data brokers
- Shared with / received by
- Political campaigns, PACs and advocacy groups
- Used for
- Canvassing and turnout targeting, Persuasion messaging, Fundraising outreach
Effects on you
- Enriched profile beyond the public record. Public voter files get merged with commercial data to add fields like religion, hobbies, and financial assets. (Direct effect)
- Persuasion and turnout targeting. The enriched file is uploaded to ad platforms to target you with specific political messaging. (Direct effect)
Connected data
- Mailing Address. Voter files use your mailing address as the primary field for matching you to other records. (Identity connection)
- Demographics. Campaign data vendors enrich the public voter file with commercial demographic data. (Direct connection)
- Location. Visit patterns to churches or campaign events can be used to infer political or religious affiliation. (Inferred connection)
Company relationships
State voter files to i360 and TargetSmart to Political campaigns Sold to
Data shared: name, address, party registration. Purpose: Voter targeting and turnout modeling. When: current.
Your public voter record can be merged with commercial data to build a profile with up to 1,800 fields about you.
Source: EFF, How Political Campaigns Use Your Data to Target You (2024)
Facebook users and their friends to Cambridge Analytica to Ted Cruz 2016 campaign Sold to
Data shared: Facebook profile data, likes, derived personality scores. Purpose: Building voter psychographic profiles from harvested Facebook data. When: 2014-2016.
Tens of millions of people were profiled - mostly friends of survey-takers who never used the app. The Cruz campaign paid about $5.8 million.
What it’s worth
official state voter-file access typically 0.5 - 1.5 cents per record; commercial rate cards vary (Recurring) Government voter-file pricing is verifiable through state election offices; the private-vendor per-record figure in this project could not be independently confirmed.
Property / Homeowner Data
Sensitive / Real-world dataHome ownership, assessed value, and mortgage details tied to your address.
- Collected by
- Public property records, Property data vendors
- Shared with / received by
- Real estate investors, Mortgage and insurance marketers, Home-service companies
- Used for
- Mortgage and insurance marketing, Investor prospecting, Wealth inference
Effects on you
- Wealth and life-stage inference. Property data is used to infer your wealth and life stage for financial marketing. (Direct effect)
- Investor and home-service targeting. Property records are sold to real-estate investors and home-service companies looking for prospects. (Direct effect)
Connected data
- Mailing Address. Mailing address and property ownership records are collected and sold together as one household record. (Direct connection)
- Financial Intent / Leads. Homeowner and property data is a core input to mortgage and home-service lead scoring. (Direct connection)
Company relationships
Public property records to Property data vendors to Mortgage and insurance marketers Sold to
Data shared: ownership, assessed value, mortgage status. Purpose: Marketing to homeowners based on inferred wealth and life stage. When: current.
Your home value and mortgage status become an inferred wealth signal used to target you with financial offers.
What it’s worth
$0.02 - $0.04 per record in bulk; $0.05 - $0.15 per record for smaller pulls (Recurring) Priced per record, similar to a mailing list, with a premium for smaller or more targeted pulls.
Military / Occupation
Sensitive / Real-world dataMilitary status and other sensitive occupation data, combined with identifiable contact and financial fields.
- Collected by
- Data brokers, Public and commercial sources
- Shared with / received by
- Marketers, Researchers, Other data brokers
- Used for
- Targeted marketing, Research, Unclear or undisclosed downstream uses
Effects on you
- Cheap bulk resale of a sensitive attribute. Military and veteran status has been observed for sale at prices falling to about $0.01 per record at scale. (Direct effect)
- Combinable with other sensitive data. This attribute can be combined with health, wealth, family, or location data in the same broker product. (Possible inference)
Connected data
- Identity / SSN. Military and occupation status is combined with identifiable contact and financial fields in the same broker records. (Direct connection)
- Health. Occupation-sensitive segments are sometimes combined with health attributes in the same specialty broker lists. (Inferred connection)
Company relationships
Data brokers to Marketers and researchers Sold to
Data shared: military or veteran status. Purpose: Bulk resale of a sensitive occupation attribute. When: current.
A sensitive personal attribute like military status can be bought in bulk for a fraction of a cent per record.
Source: Duke Sanford School, Data Brokers and the Sale of Data on U.S. Military Personnel (2023)
What it’s worth
about $0.01 - $0.20 per record depending on volume (Recurring) Price falls sharply with volume; a study observed roughly $0.20 per record in small batches down to about $0.01 at 1.5 million records.
Documented company data practices
Companies that have been documented collecting, selling, sharing, or otherwise moving personal data, drawn from regulatory orders, settlements, court filings, and reporting. Each entry is labeled by how well it is supported.
Avast / Jumpshot
Sold detailed browsing history from its antivirus software and browser extensions to over 100 buyers. Verified
Final regulatory order, 2014-2020; FTC final order June 2024. Source: FTC, In re Avast (2024)
BetterHelp
Shared email, IP, and therapy-questionnaire answers for ad targeting despite promises to keep the data private. Verified
Final regulatory order, Conduct 2013-2020; final order July 14, 2023. Source: FTC, In re BetterHelp (2023)
BMW
Flagged by Consumer Reports reporting, alongside Ford, Toyota, and Honda, for collecting consumer driving data; no confirmed enforcement action found. Reported
Research study, Reported ongoing. Source: Consumer Reports investigation and petition
Flagged for re-review - advocacy reporting, no enforcement finding.
Cambridge Analytica
Harvested Facebook profile data and likes from tens of millions of people, mostly friends of survey-takers who never installed the app, to build personality scores for voter targeting. Verified
Final regulatory order, 2014; FTC final opinion Dec 2019. Source: FTC, In re Cambridge Analytica (2019)
Cerebral
Disclosed names, prescription history, insurance, and pharmacy data for advertising despite confidentiality promises. Verified
Settled charges, Settlement filed 2024; refunds distributed 2025. Source: FTC / DOJ, US v. Cerebral (2024)
Disney (Disney+, Hulu, ESPN+)
Kept selling account-linked device and activity data across services and devices even after users opted out. Verified
Settled charges, Settlement Feb 11, 2026. Source: California DOJ, People v. Disney (2026)
DoorDash
Sold customer names, addresses, and order histories into a marketing data co-op without notice or an opt-out. Verified
Settled charges, Key transfer Jan 21, 2020; settlement Feb 21, 2024. Source: California DOJ, People v. DoorDash (2024)
Epic Games
Collected children's personal data without parental consent and used dark patterns to enable unauthorized in-game purchases by minors in Fortnite. Verified
Settled charges, Practice ~2017-2022; settled Dec 2022. Source: FTC, Fortnite Video Game Maker Epic Games (2022)
Epsilon Data Management
Admitted knowingly selling modeled susceptibility lists, drawn from a database of about 100 million households, to mass-mail fraud schemes. Verified
Criminal guilty plea, 2008-2017; deferred prosecution agreement Jan 2021. Source: US DOJ, US v. Epsilon Data Management (2021)
Equifax (via The Work Number)
Compiles employment and salary records fed in by about 75% of Fortune 500 companies and 85% of the federal workforce, and sells access to debt collectors, lenders, and prospective employers without the employee's direct knowledge at the point of sale. Documented
Investigative reporting, Ongoing since 1995; antitrust suit filed May 2024. Source: Fast Company, Facebook and America's largest companies quietly give worker data to Equifax; HousingWire on the 2024 antitrust suit (2019)
FamilyTreeDNA
Gave the FBI access to its consumer genetic database at the same level as a regular user. Documented
Investigative reporting, 2019. Source: BuzzFeed News, via Gizmodo (2019)
Flo Health
Shared menstruation, fertility, and pregnancy events tied to device and ad IDs despite representing the data would stay private. Verified
Final regulatory order, SDK sharing from 2016; final order June 22, 2021. Source: FTC, In re Flo Health (2021)
Ford
States it does not share connected-vehicle data with LexisNexis or Verisk (a documented denial, not a sale). Documented
Company statement, 2024 statement. Source: Kelley Blue Book, citing a Ford spokesperson response to the NYT (2024)
General Motors / OnStar
Sold connected-car location and driving-behavior data to LexisNexis and Verisk, which resold it to insurers, with no notice or consent. Verified
Settled charges, 2020-2024; California settlement May 8, 2026. Source: California DOJ, People v. General Motors (2026)
Also covered by an FTC final order (Jan 2026).
GoodRx
Shared prescription and health-condition data with advertisers after promising to keep it private. Verified
Final regulatory order, At least 2017 onward; order entered Feb 17, 2023. Source: FTC, US v. GoodRx Holdings (2023)
Gravy Analytics / Venntel
Kept using supplier location data after learning informed consent was absent, and sold it to commercial and government customers. Verified
Final regulatory order, Final order Jan 14, 2025. Source: FTC, In re Gravy Analytics / Venntel (2025)
H&R Block
Sent tax filers' dependent info, income type, and credit and deduction details to Meta and Google via tracking pixels. Documented
Regulator finding, 2022 practice; exposed Nov 2022. Source: The Hill, on the Warren/Wyden/Blumenthal Senate report (2023)
Healthline
Kept sharing identifiers and article titles that could suggest a diagnosis, despite user opt-outs and a consent banner that did not work as represented. Verified
Settled charges, Settlement July 1, 2025. Source: California DOJ, largest CCPA settlement to date (2025)
Honda
Sold driving data from about 97,000 cars to Verisk. Documented
Investigative reporting, 2020-2024. Source: Sen. Wyden letter to the FTC, via Sherwood News (2024)
Hyundai
Sold driving data from about 1.7 million cars to Verisk. Documented
Investigative reporting, 2018-2024. Source: Sen. Wyden press release (2024)
InMarket Media
Used precise location and visit histories for ad audiences without informed consent, and did not verify SDK-partner consent. Verified
Final regulatory order, FTC final order May 1, 2024. Source: FTC, In re InMarket (2024)
InMobi
Tracked users' locations with Wi-Fi mapping even when they denied location permission, and used it for geo-targeted ads. Verified
Settled charges, Settlement June 2016. Source: FTC, In re InMobi (2016)
ITMedia Solutions
Sent 84% of loan applications - SSNs and bank-account info - to non-lenders, marketers, debt-relief sellers, and resellers. Verified
Settled charges, Settlement Jan 2022. Source: FTC, In re ITMedia Solutions (2022)
Jam City
Sold or shared mobile-game data, including data of some 13-15 year olds, with no compliant opt-out across 21 games. Verified
Settled charges, Settlement Nov 21, 2025. Source: California DOJ, People v. Jam City (2025)
KBM Group / iBehavior
Acknowledged licensing cooperative consumer data - names, addresses, demographics, and transaction history - to fraud clients. Verified
Criminal guilty plea, ~2012-2018; deferred prosecution agreement June 2021. Source: US DOJ, US v. KBM Group (2021)
Kia
Partnered with the LexisNexis Telematics Exchange to share Kia Connect driving data for personalized insurance scores; also named as a data source in the Texas Allstate/Arity complaint. Documented
Investigative reporting, Current partnership; Texas suit ongoing. Source: LexisNexis / Kia partnership announcement; Texas AG v. Allstate/Arity complaint (2025)
LeapLab
Bought payday-loan applications and sold about 95% of them - names, SSNs, bank account and routing numbers - to non-lenders for about 50 cents each. Verified
Settled charges, FTC case 2014; final settlement Feb 2016. Source: FTC, In re LeapLab (2016)
Macromark
Pleaded guilty to knowingly brokering potential-victim mailing lists to fraud schemes. Verified
Criminal guilty plea, 2005-2016; guilty plea Sept 25, 2020. Source: US DOJ, US v. Macromark (2020)
Mazda
Named as a driving-data source in the Texas AG suit against Allstate/Arity. Reported
Lawsuit pending, Texas suit filed 2025; ongoing. Source: Texas AG v. Allstate/Arity complaint (2025)
Flagged for re-review - allegation only.
Mitsubishi
Shared driving data with LexisNexis through a Telematics Exchange-style program, alongside GM, Hyundai, and Honda/Acura. Documented
Investigative reporting, Reported 2024. Source: Kelley Blue Book, citing the NYT investigation (2024)
Mobilewalla
Harvested precise location from real-time ad-bidding requests and sold it without adequate consent verification. Verified
Final regulatory order, Major RTB collection 2018-2020; final order Jan 14, 2025. Source: FTC, In re Mobilewalla (2025)
Monument
Disclosed identifiers plus treatment-event labels such as paid therapy or medication management for ads without consumer consent. Verified
Final regulatory order, Order entered June 7, 2024. Source: FTC, US v. Monument (2024)
Nissan
Singled out in Mozilla's 2023 study for collecting unusually invasive categories per its own privacy policy, including sexual-activity data; among the 76% of studied brands that said they may sell customer data. Reported
Research study, Study published 2023. Source: Mozilla Foundation, Privacy Not Included, via Gulf News (2023)
Flagged for re-review - study analysis, no enforcement finding.
OpenX
Passed persistent identifiers and geolocation from child-directed apps and sites into its ad exchange without parental consent, and collected location from users who had opted out. Verified
Settled charges, Settlement Dec 2021. Source: FTC / DOJ, US v. OpenX (2021)
Ovia Health
Sells employers a de-identified, aggregated version of employees' fertility, pregnancy, and parenting data as a corporate wellness benefit; Activision Blizzard named as a participating employer. Documented
Investigative reporting, Ongoing since at least 2019. Source: Washington Post, The pregnancy-tracking app Ovia lets women record their most sensitive data - and their boss (2019)
Premom / Easy Healthcare
Shared reproductive-health activity, precise location, and device IDs without user consent. Verified
Final regulatory order, Before 2023; order entered June 26, 2023. Source: FTC, US v. Easy Healthcare Corporation (2023)
Reddit
Licensed real-time user post data to Google for AI model training. Documented
Investigative reporting, Feb 2024 - present. Source: Reuters / CBS News, via Lutzker & Lutzker (2024)
Confirmed licensing deal; the consent question is not the point - included as an example of user-content monetization.
Republican National Committee (RNC)
Paid contractor Deep Root Analytics to compile a 198-million-voter database for the 2016 election. Not a sale - the data was later exposed in an unsecured leak; included for the compilation cost. Reported
Investigative reporting, 2016-2017. Source: UpGuard, The RNC Files; Advertising Age (2017)
The later exposure was a leak, not a data sale - out of the strict bucket.
Sephora
Sold shopping activity and device data, and kept transmitting it despite Global Privacy Control opt-outs. Verified
Settled charges, Investigated 2021; settlement Aug 24, 2022. Source: California DOJ, People v. Sephora (2022)
Sling TV / Dish Media Sales
Shared viewing and device data with targeting attributes (age, gender, location, income) through confusing opt-outs with no usable in-app method on many TVs. Verified
Settled charges, Settlement Oct 30, 2025. Source: California DOJ, People v. Sling / Dish (2025)
Stellantis (Chrysler, Dodge, Jeep, Ram, Fiat, Maserati)
Named as a driving-data source in the Texas AG suit against Allstate/Arity, alleged to have sold driver data to Arity (Stellantis is not itself a defendant). Reported
Lawsuit pending, Texas suit filed 2025; ongoing. Source: Texas AG v. Allstate/Arity complaint (2025)
Flagged for re-review - allegation only.
Subaru
Told the NYT it sells only odometer data to data brokers, narrower than the full driving-behavior data other automakers sold. Documented
Company statement, 2024 statement. Source: Kelley Blue Book, citing a Subaru spokesperson response to the NYT (2024)
Target
Used a purchase-history algorithm to infer customer pregnancy and mail targeted baby-product coupons - in one case revealing a teenager's pregnancy to her father before she had told him. Internal use, no data sale; included as a clear documented example of what purchase data reveals. Documented
Investigative reporting, Reported 2012. Source: New York Times Magazine, How Companies Learn Your Secrets (Charles Duhigg) (2012)
TaxAct
Sent tax filers' income, refund amount, and filing status to Meta and Google via tracking pixels while people filed their taxes. Documented
Regulator finding, 2022 practice; exposed Nov 2022. Source: The Markup, Tax Filing Websites Have Been Sending Users' Financial Information to Facebook (2022)
TaxSlayer
Sent tax filers' financial data to Meta via tracking pixels; removed the pixel after being contacted by journalists. Documented
Regulator finding, 2022 practice; removed Nov 2022. Source: The Markup, Tax Filing Websites Have Been Sending Users' Financial Information to Facebook (2022)
Ted Cruz 2016 presidential campaign
Paid Cambridge Analytica for voter psychographic profiles built from about 50 million Facebook users' data harvested without permission. Documented
Investigative reporting, Jul 2015 - Jun 2016. Source: FEC filings, via Dallas Observer and The Hill (2018)
Tesla
Named the single worst offender among 25 car brands in Mozilla's 2023 Privacy Not Included study; Tesla states it does not sell personal data and uses driving data internally for Tesla Insurance. Reported
Research study, Study published 2023. Source: Mozilla Foundation, Privacy Not Included: Privacy Nightmare on Wheels, via Gulf News (2023)
Flagged for re-review - study analysis, no enforcement finding.
The Weather Channel app (owned by IBM)
Sold user location data to at least a dozen advertising sites and to hedge funds for consumer-behavior analysis. Documented
Lawsuit pending, LA City Attorney suit filed Jan 2019. Source: LA City Attorney lawsuit, via CBS News (2019)
Tilting Point Media
Collected and sold children's data through misconfigured ad SDKs in SpongeBob: Krusty Cook-Off without parental consent. Verified
Settled charges, Settlement June 18, 2024. Source: California DOJ / LA City Attorney, People v. Tilting Point (2024)
Toyota
Named as a driving-data source in the Texas AG suit against Allstate/Arity; its Connected Services program discloses sharing driving data with insurers (with consent), and a separate consumer suit alleges telematics also captured image and voice data shared with marketers and law enforcement. Reported
Lawsuit pending, Texas suit filed 2025; ongoing. Source: Texas AG v. Allstate/Arity complaint; Toyota Connected Services Privacy Notice (2025)
Flagged for re-review under a stricter evidence rule - no final consent finding yet.
Twitter (now X)
Used phone numbers and emails that users gave for account security and 2FA to target ads. Verified
Settled charges, 2014-2019; settlement May 2022. Source: FTC / DOJ, US v. Twitter (2022)
University of Chicago Medical Center
Shared hundreds of thousands of patient records with Google for predictive-analytics research, allegedly without adequate de-identification or patient consent; the lawsuit was dismissed in 2020. Reported
Lawsuit dismissed, 2017 partnership; records covered 2009-2016. Source: STAT News, via HIPAA Journal; Becker's Hospital Review (2019)
Flagged for re-review - suit dismissed.
Unroll.Me / Slice
Told users it would not touch their personal email while extracting and selling e-receipt and purchase data to market researchers. Verified
Final regulatory order, Final FTC order Dec 2019. Source: FTC, In re Unrollme (2019)
VIZIO
Collected second-by-second viewing history plus appended demographics from 11 million TVs without consumers' knowledge or consent. Verified
Settled charges, Collection from Feb 2014; settlement Feb 6, 2017. Source: FTC / New Jersey, In re VIZIO (2017)
Volkswagen
Alleged (with Ford, GM, Honda, Toyota) to have recorded vehicle occupants' text messages and call logs without consent; the class action was dismissed on jurisdictional grounds, not on the merits. Reported
Lawsuit dismissed, Dismissed Nov 2023. Source: Court record, Washington state class action (2023)
Flagged for re-review - dismissed without a merits ruling.
X-Mode / Outlogic
Sold precise latitude/longitude and mobile ad IDs, including from sensitive locations, without verifying consent. Verified
Final regulatory order, Final order Apr 11, 2024. Source: FTC, In re X-Mode / Outlogic (2024)