How do you handle reputation during M&A activity?

M&A activity reveals whether the digital infrastructure on both sides of a deal actually reflects current reality. Diligence teams now query search results, AI engine responses, Wikipedia, and structured data signals on both companies and their key executives; inconsistencies between those layers and the deal narrative can slow the process or influence price perception. Reputation work on a transaction therefore runs in two phases.

Pre-announcement phase

1. Entity hygiene. We audit and correct Wikidata entries, schema.org Organization markup, and sameAs links on both the acquirer and target. Wikidata’s structured statements model explicit parent-subsidiary and predecessor-successor relationships, which means an uncleaned entry can carry stale ownership or leadership data into every downstream system that reads from it. Google Search Central’s Organization structured data documentation confirms that accurate markup helps Google disambiguate an organization in search results.
2. AI engine accuracy. AI engines frequently carry incorrect descriptions of a company’s ownership, scope, or leadership, sometimes confidently and persistently. Pre-announcement is the window to identify and address these errors before they enter the due diligence workflow.
3. Wikipedia currency. Wikipedia feeds the Google Knowledge Graph and is heavily used as a reference source by AI engines. Articles on both the acquirer and target need to reflect current, sourced facts before deal-related searches intensify.

Post-announcement phase

1. Entity updates with deal facts. Once the transaction is public, Wikidata, schema markup, and Wikipedia are updated with deal facts as they become available and verifiable. Wikidata’s parentOrganization and subOrganization properties (and their Schema.org equivalents) are the structural mechanism for reflecting new ownership accurately.
2. AIQ tracking of deal narrative. AIQ monitors how the eight major AI engines: ChatGPT, Copilot, Gemini, AI Overview, Perplexity, Grok, Claude, and Google AI Mode, absorb and represent the deal narrative over time, flagging engines where the old description persists or where inaccurate framing appears.
3. Owned integration content. During the period when stakeholders are actively researching the combined entity, owned content covering the integration story fills the gap that structured data and Wikipedia cannot yet reflect in full.

Buy-side and sell-side

This work applies on both sides of a transaction. Buy-side mandates focus on ensuring the acquirer’s own digital footprint is authoritative and that the target’s signals are accurate before close. Sell-side mandates focus on presenting the target correctly and ensuring the deal narrative benefits the seller’s positioning in the market.