Planning an exit from a long-tenured marketing automation platform without freezing marketing

The problem

The play

1. 1
   Audit everything, with an explicit keep-or-kill call

   Inventoried activities, objects, assets, integrations and webhooks with a keep-or-kill recommendation on each, so the migration carried forward what was actually used and retired the rest, rather than faithfully replicating years of accumulated debt in a new platform.

2. 2
   Sandbox before production

   Built a sandbox testing plan so the migration was validated somewhere safe before anything touched live sending.

3. 3
   Protect deliverability across the move

   Planned DKIM setup and IP warming ahead of cutover, so sending reputation carried across the platform change instead of resetting at go-live, the failure mode that quietly costs a migration its first quarter.

4. 4
   Preserve behavioural data

   Set up custom events so behavioural data survived the move and scoring did not have to start from zero on the other side.

5. 5
   Load brand assets so AI output is on-brand from day one

   Loaded brand assets, logos, colours and fonts, into the destination platform so its AI generation features produced on-brand output immediately rather than after a cleanup pass.

6. 6
   Run marketing operations in parallel

   Ran embedded day-to-day marketing ops throughout the migration: weekly pipeline and MQL reporting, an automated daily pipeline report, lead-hygiene and data-quality dashboards, event lead upload and attribution, and campaign and newsletter email builds.

7. 7
   Strategic sessions on the AI operating model

   Monthly working sessions with the head of revenue operations on the AI operating architecture, governance, operationalizing the ICP, and an evaluation of AI agent and customer-data products from platform vendors already in the stack.

What it moved

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