Mailchimp to Kajabi Migration
List migration, re-segmentation and deliverability for a member-based organization
Context
A member-based organization was moving its email operation off Mailchimp onto Kajabi. The list had grown organically for years with no consistent schema: 10,299 raw contacts spread across overlapping exports, with duplicates under multiple spellings, syntactically invalid and undeliverable addresses, aged cohorts dating back years, and a block of contacts with no recoverable interest or consent signal at all.
A flat export-import would have replayed that entropy into the new platform: engagement metrics dragged down by dead addresses, sending reputation exposed against the Gmail/Yahoo bulk-sender thresholds, and a team still unable to answer the only question that matters in a CRM, "who exactly should receive this campaign?". The engagement covered the full arc: forensic list hygiene, a segmentation architecture designed before anything moved, a verifiable cohort-by-cohort import, the automation layer that keeps the structure alive, and authenticated sending validated before the first campaign left the building.
The Challenge
- No single source of truth: the 10,299 rows came from overlapping lists and historical exports, so identity resolution had to happen before any quality judgment could be made.
- Unknown consent provenance on a whole block of contacts, mailing them blind would invite complaints; silently dropping them would burn real members.
- Kajabi and Mailchimp model audiences differently: Mailchimp audiences/groups/tags had no one-to-one destination, so the taxonomy had to be redesigned, not translated.
- The migration could not pause operations, the organization kept communicating with members while the move was prepared.
- Deliverability had to be provable on day one: fresh platform, fresh sending infrastructure, zero tolerance for landing in spam during the first sends.
Scope and Approach
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01
Export forensics and identity resolution
Consolidated every source export, normalized encodings, casing and formats, then de-duplicated on deterministic keys, 10,299 raw rows resolved to 5,306 unique identities. Merge rules were written down before running: which field wins on conflict, how name variants reconcile, what happens to contacts present in multiple lists with contradictory states.
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02
Three-tier address validation
Ran every address through syntax, MX and mailbox-level verification and bucketed the output into deliverable, risky and dead tiers: 4,862 contacts survived as verified deliverable. Risky addresses (catch-all domains, timeouts) were quarantined for re-permission rather than imported as active, and dead addresses never left the staging file. Suppression state, unsubscribes and hard bounces, migrated first, flagged so they could never be re-mailed.
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03
Segmentation architecture
Designed a 21-segment taxonomy across four orthogonal axes: 4 main subscription lists, 4 regions, 3 engagement-recency tiers and 10 event-interest tags. The axes compose by intersection, "list A, region B, engaged, interested in topic C" is a two-condition query, not a new list, which is what makes the model maintainable as the organization grows.
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04
Offline transform, cohort import, reconciliation
Applied the full taxonomy to the cleaned dataset offline, where transformations are testable and reversible, then imported into Kajabi cohort by cohort with tags applied at import time. After each cohort: count reconciliation against the staging file, so any drift between "sent to platform" and "visible in platform" surfaced immediately instead of months later.
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05
Forms, templates and tagging automations
Built the reusable email template set and interest-capture forms, each wired to one of 5 tag-application automations. New signups self-segment on entry: the form declares the interest, the automation applies the taxonomy, and no human ever has to remember the tagging convention.
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06
Sending authentication
Configured and verified SPF, DKIM and DMARC for the new sending setup and confirmed alignment before the first campaign, the Gmail/Yahoo bulk-sender baseline treated as an entry requirement, not an afterthought.
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07
Zero-party recovery of the unknown block
The 261 contacts with no recoverable interest signal got a dedicated broadcast pointing to a preference landing page. The form arrived pre-filled, email and known attributes hydrated from URL parameters by JavaScript, so a member confirmed in seconds: 4 list checkboxes, 2 profile/region selects, 5 automations tagging each response into the taxonomy. Non-responders aged into suppression instead of polluting engagement metrics.
Architecture flow
Technical Deep Dive
Why validation has three tiers, not two
Binary valid/invalid validation is how migrations quietly poison new platforms. The middle tier, catch-all domains, greylisting timeouts, role accounts, is where judgment lives: import them as active and they depress open rates and inflate bounce rate on a fresh sending reputation; delete them and real members disappear. Routing the tier to re-permission preserved both the reputation and the members.
Taxonomy before transport
The segmentation model was designed and applied to the data while it was still local. Importing first and segmenting later, the common order, means the platform state and the plan drift apart from day one, and nobody can verify the import actually carried the structure. Local-first made the import itself the verification: every cohort landed with its tags, and counts had to match.
The pre-filled preference page
Recovery campaigns die on friction. The landing page removed almost all of it: the broadcast link carried the contact identity in URL parameters, JavaScript hydrated the form fields on load, and the member only ticked interests and pressed submit. Every submission flowed through the same 5 tagging automations as a fresh signup, one pipeline, no special cases, and produced declared, zero-party interest data instead of inferred guesses.
Suppression as a first-class dataset
Unsubscribes and hard bounces were exported, preserved and loaded before any active contact. Losing that file during a platform move is how organizations end up re-mailing people who opted out, a compliance exposure under CAN-SPAM/GDPR and a guaranteed complaint spike. Treating suppression as the first data load makes the failure mode impossible.
Engineering Decisions
Rebuild the taxonomy instead of translating Mailchimp groups
Mailchimp audiences and groups encoded history, not strategy. Translating them one-to-one would have preserved years of accumulated inconsistency. The four-axis redesign cost one workshop-grade decision up front and made every future campaign a composition instead of a new list.
Quarantine the risky tier rather than import-and-hope
Importing risky addresses as active would have been invisible for a week and expensive for a quarter, engagement dilution on a new platform compounds. Re-permission converts the recoverable slice and lets the rest expire without ever touching the sending reputation.
Per-cohort import with reconciliation over one bulk push
One 5,000-row import that "mostly worked" is an audit nightmare. Cohort-sized imports with a count check after each made every discrepancy local, attributable and fixable in minutes.
Results
- From 10,299 raw contacts to 4,862 validated, de-duplicated members, a reconciled migration, not a copy of the entropy.
- A 21-segment, four-axis taxonomy the team composes audiences from, instead of one undifferentiated list.
- Interest-capture forms and 5 tagging automations keep the taxonomy self-maintaining as new members arrive.
- Suppression integrity preserved end to end, no opted-out contact ever re-entered the mailable base.
- Authenticated, aligned sending verified before the first campaign, bulk-sender compliant from send one.
- The 261 unknown-consent contacts resolved through pre-filled zero-party preference capture, not guesswork.
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