How does Five Blocks approach a brand in the middle of an M&A process?
Five Blocks structures M&A reputation work around the deal timeline: a confidential diligence-grade audit pre-announcement, daily AIQ monitoring of both target and acquirer narratives during the deal window, Wikipedia/Wikidata updates prepared for the day of close, and post-close entity integration to unify the combined entity's digital infrastructure.
M&A work has a different cadence than standard reputation engagements because the deal timeline drives everything. Five Blocks structures each engagement across four phases, aligned to how deal communications actually unfold.
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Pre-announcement: Confidential audit
Before anything is public, Five Blocks runs a diligence-grade assessment of the target’s digital footprint. This covers the Wikipedia article state, Wikidata entity record, AI narrative profile across major engines, and any contested or legacy content that could surface during the deal window or complicate post-close positioning. The work is scoped and delivered under confidentiality.
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Deal window: Daily AIQ monitoring
Once the deal is active, AIQ™ runs daily monitoring on the target, the acquirer, and the emerging combined-entity narrative. AI engines often begin producing combined-entity descriptions before the official communications strategy has settled on what those descriptions should say, making real-time visibility into what each engine is saying (and why) a practical operational need during this phase.

Five Blocks structures M&A reputation engagements across four deal-aligned phases, from confidential pre-announcement audit through post-close entity integration. -
Day of close: Wikipedia and Wikidata update
Wikipedia and Wikidata edits are prepared in advance so the structural updates land cleanly the day the transaction closes, rather than accumulating slowly in the weeks after, during which the public record would be inconsistent with the new corporate reality.
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Post-close: Entity integration
After close, work shifts to integrating the entity infrastructure under the new corporate structure and addressing any residual narrative drift across AI engines, ensuring the combined entity is consistently represented as it intends to be.
Last reviewed: 19/05/2026