How do you handle reputation during M&A activity?

M&A activity tests whether the digital record on both sides of a deal matches current reality. Diligence teams now query search results, AI engine responses, Wikipedia, and structured data signals on both companies and their senior executives, and gaps between those layers and the deal narrative can slow the process or shape how price is perceived. Reputation work on a transaction 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 record explicit parent-subsidiary and predecessor-successor relationships, so 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 often carry incorrect descriptions of a company’s ownership, scope, or leadership, sometimes confidently and repeatedly. Pre-announcement is the window to find and fix these errors before they reach 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 pick up.

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 how new ownership gets reflected 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. While stakeholders are 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 making the acquirer’s own digital footprint authoritative and confirming the target’s signals are accurate before close. Sell-side mandates focus on presenting the target correctly and making the deal narrative work for the seller’s position in the market.