Mailchimp Leads Database | $3/1K | Website Contacts

Mailchimp Leads Database

Find website prospects across compatible datasets using Mailchimp saved technology matches and original source-dataset membership, filter by country and available business contacts, and export deduplicated domains as CSV, Excel or JSON. Use the results for reviewed business research, CRM preparation and API workflows.

$3 per 1,000 delivered results on every Apify plan, plus $0.00005 per start event per GB of allocated memory, minimum one event. Apify platform usage is additional. The default export can deliver up to 10,000 rows ($30 in result fees at that volume). An explicit 10-row preview costs $0.03 in result fees. Check the Pricing tab for the effective rates on your plan.

Evidence and inventory

Coverage snapshot — 8 November 2026	Value
Search scope	Indexed Mailchimp website records
Matching source rows with default evidence mode, no email filter	1,353,572
Default export	Up to 10,000 domains with stored emails
Result price	$3 per 1,000 delivered domains

Counts are before domain deduplication.

A complete read-only audit found 554,346 exact saved-token source rows, including 434,802 outside the original named group. These are overlapping rows, not distinct websites. The additional Tech Detected Stack field is considered where available. Missing fields are unknown. This is saved evidence, not live detection.

Default export includes original Mailchimp dataset rows plus exact saved-technology matches from other datasets. Original dataset membership alone does not verify the technology for each row. Set requireStoredTechnology to true to require an exact saved token on every returned row. Matching checks CMS Platform, eCommerce Platform, Marketing Automation Platform, CRM Platform and Tech Detected Stack where present. Strict mode can return a small or empty audience.

The original named dataset was counted at 918,773 source rows on 8 November 2026. This is not the number of unique qualified domains, available emails, confirmed installations or active businesses. Filters and domain deduplication reduce the exported audience. Every compatible source table is searched. Original named-dataset membership is distinguished from exact saved-technology matches found in other groups. Domain deduplication applies across sources.

No live website requests, account cookies or external API keys are required from you. Stored fields can be old or missing. No deliverability, phone reachability, current platform installation or consent to receive outreach is implied.

Quick start

1. The Console starts at 10,000 rows with stored emails. Set maxItems to 10 for a small preview. The example below uses that explicit preview size.
2. Optionally select countries, a literal domain/company keyword or field filters.
3. Run the Actor. Read SUMMARY and ERRORS, then export the Dataset.

{"workflow":"export","hasEmail":true,"maxItems":10,"outputPreset":"contacts"}

For a matching-volume preview:

{"workflow":"count","hasEmail":false}

Count-only creates no lead rows or result events, but start and platform usage still apply. The total measures matching source rows before domain deduplication.

Useful workflows

Goal	Input	Result
Review contact prospects	hasEmail: true, maxItems: 10	Rows with a populated stored email field
Build a regional list	country: ["US", "GB"]	Stored country codes match the selection
Require a phone	hasPhone: true	Nonempty stored phone field
Find a company or domain	keyword: "example"	Literal substring in domain/company, not search-engine results
Preview volume	workflow: "count"	Matching source-row count, without paid Dataset rows
Continue an export	Complete saved resumeInput	Next page in the selected source context
Select CRM columns	outputPreset: "custom", columns	Requested fields plus evidence fields

Inputs and limits

Input	Default / limit	Meaning
workflow	export or count	Export rows or preview counts
hasEmail, hasPhone	true, false	Require nonempty stored fields
country	No filter	ISO-2 codes, normalized to uppercase
requireStoredTechnology	false	Require exact saved target token on every row; otherwise original dataset rows also qualify
keyword	No filter, up to 100 characters	Literal domain/company substring
phoneCode	No filter	Stored phone prefix such as +44; formatting affects matches
maxItems	10,000; range 1–10,000	Maximum delivered domains
outputPreset	contacts	contacts, sales, full or custom
filters	No extra filters	Allowed field comparisons combined with AND
sortBy, sortDesc	Schema default	Allowed-field ordering and direction
offset	0; up to 1,000,000	Skip eligible domains; prefer full continuation
sourceSession, exportCursor	Omitted	Copy saved continuation without editing
parallelReaders	Schema default	Bounded read parallelism; same result price

Allowed filters: equals, not_equals, contains, not_contains, starts_with, ends_with, in_list, not_empty and empty. These compare stored fields. Unknown fields are rejected, including requests to override the Actor with another platform. Private source configuration cannot be supplied by callers. Traffic enrichment is not offered here.

Output and exports

One paid result is one delivered domain after filters and within-run deduplication. Available fields include Root Domain, Company, Emails, Telephones, Country, State, City, Vertical, social links and stored technology/business signals. Values can be empty. Revenue, employee and spend values are stored signals or estimates, not independently audited facts.

Output	Interpretation
Root Domain	Domain identity for deduplication
Emails, Telephones	Stored values, not delivery/reachability verification
CMS Platform, eCommerce Platform	Stored technology strings; empty does not prove absence
Marketing Automation Platform, CRM Platform	Related stored tools, where present
Tech Detected Stack	Additional saved technology evidence where present
_platform	Public source-cohort label, not a live detection result
_platformEvidence	stored-technology when that row has an exact saved match; otherwise source-dataset
_storedTechnologyMatch	Exact target-token match in selected stored fields; null for mixed websites

Illustrative output shape, not a guaranteed or real lead:

{"Root Domain":"example.org","Company":"Example","Emails":"contact@example.org","Country":"US","_platform":"Mailchimp","_platformEvidence":"source-dataset"}

Synthetic examples are never inserted into Dataset results. Legacy source timestamps are not exposed by this export policy, so per-row freshness is unknown. The inventory-count date is not the date each website was collected.

Count, errors and continuation

SUMMARY records status, completeness, rows and performance. evidenceMode reports the active selection rule in both SUMMARY and COUNT_SUMMARY: stored-technology-only (an exact saved match is required) or source-dataset-or-stored-technology (the original dataset also qualifies). ERRORS is empty on clean runs. Count mode writes COUNT_SUMMARY; its total counts eligible source rows before cross-segment domain deduplication. It is not a distinct-domain or verified-contact count.

After a limit or budget stop, open EXPORT_CONTINUATION and copy the complete resumeInput into a new run. Keep source session, export cursor, filters and sort together. You may change maxItems for the next page. The source context is pinned but tables are live, so concurrent changes can affect pagination. Unrelated exports start at offset 0 without another export's cursor. Within-run deduplication does not suppress older exports unless their saved continuation is used.

An empty result can be legitimate. Source failures are recorded instead of producing fake rows. Read isComplete before treating partial results as a full audience count. Validation inside an already-started run can incur start/resources even when no lead is delivered. A successful build alone does not prove source availability.

API and integrations

Start an asynchronous run, wait for its terminal status, then read the run's Dataset and key-value store:

curl --request POST \
  'https://api.apify.com/v2/acts/apivault_labs~mailchimp-leads-database/runs' \
  --header "Authorization: Bearer $APIFY_TOKEN" \
  --header 'Content-Type: application/json' \
  --data '{"workflow":"export","maxItems":10,"hasEmail":true}'

Read https://api.apify.com/v2/datasets/DATASET_ID/items?format=csv with the authorization header, or select format=json / format=xlsx. Output links lead to Dataset rows, summary, count preview, errors and continuation.

Use an n8n HTTP Request node or the official Python Apify client. A dedicated published package or community node for this Actor has not been verified; no unpublished integration is advertised. See the Apify API documentation for run and storage endpoints. You can save your own private input in Console; no public Tasks are required for these examples.

Result fees

Delivered rows	Result fees
10	$0.03
100	$0.30
1,000	$3.00
10,000	$30.00

Add memory-weighted start and Apify compute/storage/transfer usage. A charge cap can stop delivery before maxItems, even when more rows match. Empty/count-only runs have no delivered-row charge but still use resources. These examples are result fees, not a fixed total run cost. Check the actual run charge breakdown.

FAQ

Is this a live list of websites using Mailchimp?

No. It is an indexed historical cohort. Exact saved-token mode, where available, checks stored fields only and does not revisit websites.

Does every row have an email and phone?

Only when both corresponding filters are enabled and matching data exists. Missing fields remain empty. Stored contact data does not establish deliverability.

Is the inventory count the number of unique prospects?

No. Preview your filters and inspect the deduplicated output. Source segments can overlap.

Can I request another platform or all 73M+ records here?

You cannot select unrelated platforms. This Actor searches all compatible tables but returns only original dataset rows or exact saved technology matches. The general database offers unrestricted source selection.

Why can continuation return fewer rows?

Filters, deduplication, a charge cap, source changes or errors can reduce delivery. Read summary, errors and continuation instead of assuming only that many websites exist.