Industries · Hedge Funds, Banks & Quant Funds · Hedge funds · Quant funds · Banks · Credit unions · Private equity

Hedge funds, banks and quant funds, from one sample of tickers to the graph in your warehouse.

A bank's marketing team wants the households in its footprint researching a refinance, a HELOC or an auto loan this week, with current customers kept out of the spend. A fund wants a daily count of the people in market for a brand, a category or a competitor, mapped to tickers and delivered as a series it can backtest. Both read the same graph: roughly every US adult, 120M businesses and 2 trillion intent signals a day.

Daily intent series mapped to tickers for funds, in-market lending and deposit audiences for banks, customer suppression and enrichment, and the graph licensed into the warehouse.

Book a free demo Start at rung one

Funds get aggregates, never a person. Banks get marketing data, never a consumer report: nothing here is used for credit, insurance, employment or housing decisions.

Daily intent on 65K topics, brands and competitors by name, aggregated by geography, income band and age for research, or kept at the household for marketing.
Household and finance fields on roughly every US adult: income band, home value, net worth band, credit-range band, vehicles and liens, new movers and life events.
Delivery the way a data team wants it: Snowflake share, S3 drops on a schedule, the API at volume, with a proof of concept on your own tickers or your own customer file first.

Enterprise · Daily intent series · 24 tickers · delivered to s3://fund-poc/

SeriesRefinanceAuto loansBrand vs competitor · 6 pairsHELOC

Cut byDMAIncome bandAge bandDaily since start

Coverage240M adults · aggregatedNo person-level rows

DeliverySnowflake shareS3 · weekly history fileAPI

Download the sampleScope the licenseMap the tickers

240 million+consumer profiles

120 million+business profiles

2 trillionintent signals a day

400+fields per profile

What the graph holds for funds and banks

The bundles a fund or a bank reads first.

Four of the sixteen bundles, picked for this industry. See everything in the graph →

Household & financeIncome, home value, net worth and credit bandsModeled income, home value, net worth band, credit-range band, mortgage and refinance flags on roughly every US household: the fields a bank segments on and a fund aggregates.Open this table in the data dictionary → Intent & linkages2 trillion signals a day, 65K topicsDaily scores by topic, brand and competitor, joined to the household for marketing or rolled up to a series by geography and demographic band for research.Open this table in the data dictionary → Vehicles & propertyWhat they own and oweMake, model and year, purchase dates and lien flags, home ownership and value: demand signals for auto, lender and homebuilder names, and lending audiences for banks.Open this table in the data dictionary → Business person & company120M businesses, and the people in themOwners, finance leads and headcount for business banking, and firmographic demand signals for software and services tickers.Open this table in the data dictionary →

The ladder · simplest to largest

Five rungs, from a bank's first mailer and a fund's first sample to the graph in the warehouse.

Banks climb the marketing rungs; funds start at rung two with a sample and spend the rest of the ladder on history, coverage and delivery. Both arrive at rung five: the graph licensed into the warehouse.

Rung 1 · Day one

A community bank, a credit union, a regional lender, one footprint

Mail the households in your footprint shopping for a loan this week, and keep your customers out of it.

US Consumer Data builds the segment: households in your counties researching a refinance, a HELOC, an auto loan or a new checking account this week, with the income and home-value bands you lend to.

US Consumer Data builds the segment: households in your counties researching a refinance, a HELOC, an auto loan or a new checking account this week, with the income and home-value bands you lend to. Direct Mail prints and mails it with postage included and matches the responses back. Smart Exclusion keeps current customers out of the spend, hashed before anything leaves your systems.

Build the in-market segment in US Consumer Data by county, product and income band; the count shows before anything is pulled.
Mail it through Direct Mail; the responses match back to the mailed file.
Load your customer file into Smart Exclusion so current customers never see acquisition offers.

US Consumer Data Direct Mail Smart Exclusion

Rung 2 · First month

A bank with a media budget and a website, or a fund analyst with a hypothesis

Advertise to the in-market households, name the visitors on the rates page, and pull the first sample of tickers.

For the bank: Ad Audiences turns the same in-market households into hashed audiences on Meta, Google and CTV, and Website ID names the companies and people who visited the rates and business-banking pages. For the fund: a sample through Enterprise: daily counts of the people in market for twenty-four brands and categories over ninety days, mapped to tickers, next to the results those companies reported, so the analyst sees whether the series leads.

Bank: build footprint audiences in Ad Audiences by product and income band; the match rate per platform shows first.
Bank: put Website ID on the rates, mortgage and business-banking pages.
Fund: name twenty-four tickers; the sample comes back as daily series by DMA and income band, with the brand-to-topic map written out.

Ad Audiences Website ID Enterprise

Rung 3 · First quarter

A bank with a CRM and a call center, or a fund running a trial

Enrich the customer file, watch it for intent, and run the proof of concept on your own tickers.

For the bank: Enrich appends household, finance, vehicle and life-event fields to every customer and lead, written back through Integrations, and Pulse watches the book for the week a customer starts researching a competitor's mortgage or a new auto loan. For the fund: a scoped trial through Enterprise: your ticker list, your geographies and demographic bands, daily delivery to S3 or a Snowflake share, with the history that exists at signing stated in writing, so the backtest runs on real data, not a sample.

Bank: enrich leads and customers with Enrich; the fields land in the CRM or the warehouse.
Bank: put the book on Pulse; the record flips the week a customer shops elsewhere, and the branch calls first.
Fund: a written scope, the data-provenance and consent questionnaire answered, a trial priced to credit against the license.

Enrich Pulse Enterprise Custom Intent Feeds

Rung 4 · First year

A quant fund, a multi-manager platform's data team, a bank with a modeling team

License the daily series with history, point in time, and build the models on it.

The fund licenses the aggregated series through Enterprise: daily counts by topic, brand, competitor pair, DMA and demographic band, delivered on a schedule with a documented point-in-time convention and a brand-to-ticker map you can audit, plus Custom Intent Feeds for a custom universe of topics no catalog has. The bank's modeling team takes the household fields and the intent history to score propensity for every product it sells, refreshed monthly by API or through the MCP server.

Fund: scheduled delivery of the full series with history, a point-in-time file per day, and the ticker map under version control.
Fund: a custom topic universe through Custom Intent Feeds for the brands and categories the catalog does not cover.
Bank: propensity models scored monthly against the whole footprint by API or through the MCP server; audiences and mail pulled from the scores.

Enterprise Custom Intent Feeds US Consumer Data Ad Audiences

Rung 5 · At scale

A national bank, a multi-manager platform, a private equity firm with a portfolio

License the graph into the warehouse, resolve every brand and channel to one customer, and run the portfolio on it.

Enterprise delivers the graph on a schedule to the bank's warehouse, resolves every brand, product and channel to one customer key, and runs matching with media partners in a Clean Room.

Enterprise delivers the graph on a schedule to the bank's warehouse, resolves every brand, product and channel to one customer key, and runs matching with media partners in a Clean Room. A fund platform licenses the aggregated series across every pod with one contract and one data-sourcing review. A private equity firm runs the same products across its portfolio companies, one sub-account per company, the way an agency runs its clients, and reads the series for diligence on targets.

Proof of concept: the customer file or the ticker list against the graph, with match rate, coverage and history reported in writing.
Scheduled warehouse delivery; one customer key across brands and channels; clean-room matching with media partners.
Platform and portfolio licenses: one contract, sub-accounts per pod or per company, redistribution terms written down.

Enterprise Custom Intent Feeds Smart Exclusion Ad Audiences

What funds and banks teams use it for

What funds, banks and portfolio teams run on the graph.

Demand nowcasting by ticker

Daily counts of the people in market for a brand or a category, mapped to tickers and delivered as a series with history.

Enterprise Custom Intent Feeds

Share shift, brand against brand

Competitor-pair series: one retailer against another, one lender against another, week by week.

Enterprise Custom Intent Feeds

B2B software demand

Research on CRM migration, data platforms and pricing pages by company size and industry, as pipeline signals for software tickers.

Custom Intent Feeds B2B Data

Autos, housing and lending deltas

Vehicle purchases by make, new movers by ZIP, refinance and HELOC interest, as demand series for auto, lender and homebuilder names.

Enterprise US Consumer Data

In-market deposit and lending audiences

Households in the footprint researching a refinance, an auto loan, a HELOC or a new account this week, by income and home-value band.

US Consumer Data Ad Audiences

Acquisition mail with matchback

Account and rate offers mailed to in-market households, postage included, matched back to the accounts that opened.

Direct Mail

Customer suppression

Current customers hashed and excluded from acquisition media on every platform, refreshed as accounts open.

Smart Exclusion

Customer and lead enrichment

Household, finance, vehicle and life-event fields appended to every record in the CRM or the warehouse.

Enrich

Attrition and refinance watch

The week a customer starts researching a competitor's mortgage or auto loan, flagged in the CRM for the branch to call.

Pulse

Business banking prospecting

Owners and finance leads at the 120M businesses in the footprint, with validated emails and phones.

B2B Data Chrome extension

Private-markets diligence

Brand-level demand series on a target, read by the deal team before the letter of intent.

Enterprise

Portfolio-wide licensing

One license across portfolio companies, one sub-account each, for audiences, suppression and enrichment.

Enterprise Agency DaaS

Use it right

Aggregates for funds, marketing data for banks, and the lines that are never crossed.

What applies when the buyer is a fund or a bank. Your counsel decides; this is how the data behaves.

No consumer reports. The graph is marketing and research data, not a consumer report. It is never used for credit, insurance, employment or housing eligibility, and the license says so.
Funds get aggregates. Research deliveries are counts and series by geography and demographic band, never a person, a household or an identifier.
Public behavior, not inside information. Intent is read from behavior across the open web and aggregated; it is not company data, customer data or anything under a non-disclosure agreement.
Your customer data stays yours. Customer files used for suppression, enrichment or a proof of concept are hashed and matched, never added to the graph; GLBA-covered data never leaves your side unhashed.
Calling, texting and mailing rules apply. Phones carry do-not-call and line-type flags; TCPA, CAN-SPAM and UDAAP compliance is yours, and the data supports it.
Diligence answered in writing. Provenance, consent and opt-out handling, panel stability and the ticker map are documented for your data-sourcing and compliance review.

Questions

Questions a data-sourcing lead or a bank marketer asks first.

Can a fund get person-level data?

No. Research deliveries are aggregated daily series by topic, brand, geography and demographic band. Person-level data is for marketing uses by the business that owns the customer relationship.

How is a brand mapped to a ticker?

A brand-to-topic map over the 65K topics and the custom feeds, built with you on the proof of concept, versioned, and delivered with every drop so it can be audited.

How much history is there?

Whatever exists at signing is stated in writing before the trial, and every day after is archived under your license with a point-in-time file per day.

Is this FCRA data? Can we use it for underwriting?

No, and no. It is marketing and research data. It is never used for credit, insurance, employment or housing decisions, and the license prohibits it.

How is it delivered?

Snowflake share, S3 or GCS drops on a schedule, or the API at volume; marketing uses also run in the app and over MCP. A proof of concept on your own tickers or your own customer file comes first.

Other industries

The same graph, a different ladder.

Financial Services Insurance Technology Marketing Agencies All industries

Book a free demo

Bring twenty-four tickers or one footprint. We scope the sample on the call.

Thirty minutes with a person who knows alternative data and bank marketing: a fund gets a sample series for its tickers scoped, a bank gets this week's in-market households counted in its counties, and both leave with the next rung written down.

Book a free demo See how it works

Thirty minutes, live on your own data. A person who knows the products and this industry runs the call. By continuing you accept the DataMoon terms.