[[FIG:kb-0065]]

How the partnership operates day to day

Bidirectional data sharing

IMPACT™ and AIQ™ outputs go to the PR firm’s account leads so they have a live read on search and AI representation. In return, the firm’s media plans and proactive narrative work come to Five Blocks so source-layer interventions line up with what is being placed and pitched.

Coordinated timing

Announcements, owned content publication, and proactive Wikipedia work are timed so the earned, owned, and entity layers move together. The engines then get a consistent picture instead of a fragmented one.

Joint calls

Five Blocks attends the joint calls and treats the PR firm’s account leads as peers rather than gatekeepers. Senior advisors are present when strategy is set, not only during execution.

Clean division of work

Media relations and storytelling sit with the PR firm. Entity optimization, Wikipedia strategy, search management, and AI source-layer work sit with Five Blocks. The lines are explicit at the start of every engagement and revisited when scope expands.

Why the structure matters

When these disciplines run in silos, each team executing without visibility into the other, the engines get conflicting signals and both workstreams lose leverage. The shared data flow and clean division of labor are what let the partnership do more than either side working alone.

The post How does Five Blocks manage the relationship between a client’s PR team and reputation strategy? appeared first on Five Blocks.

GeoSearch lets the team run a query the way a real searcher would see it in any of hundreds of specific locations, instantly, without the overhead of VPNs and proxy chains.

[[FIG:kb-0111]]

Where we use it

• Checking whether a critical article dominates the results in a single market.
• Validating Wikipedia visibility country by country.
• Diagnosing why an investor in Tokyo sees a different narrative than one in London.

Why no VPN is needed

The usual way to check a foreign SERP is to chain VPNs and proxies, which is slow, unreliable, and easy to get wrong. GeoSearch removes that overhead: results come back as a real local searcher would see them, on demand. The data also feeds into IMPACT™ for clients whose programs need geographic depth.

The post How does GeoSearch help with managing search results across different locations? appeared first on Five Blocks.

[[FIG:kb-0015]]

Four phases of evolution

1. 2003 to 2007, e-commerce and online marketing. The firm began as a search company, helping clients be found by customers.
2. From 2007, the pivot to reputation management. The same search expertise was applied in the other direction, to help clients shape what was being found about them. Reputation management has been the sole focus since.
3. The 2010s: Wikipedia, Wikidata, and entity optimization. As Google moved toward the Knowledge Graph and away from a pure ten-blue-links results page, the work grew to cover Wikipedia, Wikidata, and entity signals.
4. From 2023, AI reputation management. Tracking and influencing what AI answer engines say about clients: ChatGPT, Gemini, Copilot, Perplexity, Claude, Grok, Google AI Overviews, and Google AI Mode. Five Blocks built AIQ in-house for this work, the same way IMPACT™ was built for the search era.

The post How has Five Blocks evolved over the years? appeared first on Five Blocks.

[[FIG:kb-0115]]

What gets tracked

For every keyword in scope, IMPACT™ captures the full results page and records each ranking URL along three dimensions:

Ownership

Whether the result is client-owned, earned media, third-party, or hostile.

SERP feature

Where the result sits on the page: organic, AI Overview, People Also Ask, knowledge panel, image, video, or news.

Topic

The subject the result speaks to, so coverage can be read by theme rather than only by keyword.

Coverage at a glance

• 500 cities with city-level SERP tracking (via GeoSearch).
• 69 countries of geographic coverage.
• 23 languages.

Benchmarking and history

The platform records peer rankings against named competitors and stores the full time series. A client’s position can be tracked as it moves and compared against rivals rather than against a fixed threshold. Across the active client base this amounts to roughly 100 million data points per day.

The post What data does the IMPACT platform track? appeared first on Five Blocks.

The underlying risk is documented: large language models mishandle broad classes of human names even in short text because the linguistic cues are ambiguous. Weak entity infrastructure, no Wikidata entry, no schema markup, no clean disambiguation, makes that conflation far more likely.

[[FIG:kb-0064]]

The disambiguation infrastructure

1. Wikidata entity record

   Five Blocks creates or completes a distinct Wikidata item for the client with full disambiguating attributes: date of birth, current employer, prior employers, and notable affiliations. Each item carries a unique Q-identifier that machines use to tell this person apart from any namesake. Where a Wikipedia article exists, it is linked as a sitelink on the same item.

2. Owned bio page with schema.org Person markup

   The client’s bio page on the company site is marked up with schema.org/Person and carries sameAs links pointing to the Wikidata Q-item, LinkedIn profile, Wikipedia article (where applicable), and any other authoritative identifiers. Schema.org defines sameAs as “URL of a reference Web page that unambiguously indicates the item’s identity”, which is the disambiguation signal engines rely on. This page becomes an anchor in the client’s identity graph.

3. Third-party citations with disambiguating context

   Third-party coverage, press mentions, bylined articles, industry profiles, is steered toward sources that use the client’s disambiguating context (title, employer, credential) alongside the name. Each citation that does so raises the engine’s routing confidence.

4. Wikipedia (where notability supports it)

   Where the client meets Wikipedia’s notability threshold, a Wikipedia article is the strongest single disambiguation signal available. Wikipedia’s own disambiguation system uses dedicated disambiguation pages and unique identifiers to resolve conflicts between subjects who share a name. An article linked to the Wikidata item ties all the layers together.

How the signals compound

Once the infrastructure is in place, search engines and AI engines route the client’s queries to the client rather than to a namesake. Person schema with verified sameAs links helps engines build an identity graph and gives them biographical disambiguation anchors. The disambiguation gets stronger as the entity signals deepen and more citations adopt the consistent context.

The post How does Five Blocks handle reputation management for individuals with common names? appeared first on Five Blocks.

[[FIG:kb-0012]]

The training pathway

1. Structured technical curriculum, new account managers work through search algorithms, Wikipedia editing standards and Notability guidelines, schema markup and Wikidata, AI engine behavior, and the use of IMPACT™ and AIQ as analytical tools.
2. Shadowing senior account managers, after the curriculum, they shadow senior account managers on real client engagements, not practice exercises.
3. Supervised independent responsibility; they are then given independent responsibility for a client, and even then work under a dedicated team leader for their first set of accounts.

The result

This gives us a deeper bench than most agencies our size. When a senior advisor is unavailable on a Friday afternoon, the next person on the call has been through the same training and works from the same playbook.

The post How does Five Blocks train and develop its team? appeared first on Five Blocks.

[[FIG:kb-0018]]

How engagements typically start

Most clients engage us first for a specific situation: a crisis, an audit, a Wikipedia article, or a contested executive narrative. They then continue on retainer once that work is stabilized.

The post What services does Five Blocks offer? appeared first on Five Blocks.

[[FIG:kb-0016]]

Feeder backgrounds

People join from a wide range of disciplines:

• Technology
• Academia
• Communications
• Public relations
• Law
• Journalism

The post What types of professionals work at Five Blocks? appeared first on Five Blocks.

[[FIG:kb-0176]]

The trajectory

People increasingly put the questions they once typed into Google to ChatGPT, Gemini, Perplexity, Copilot, and the other major engines, especially for informational and research questions where they want a synthesized answer rather than a list of links. Google is doing the same thing: its AI Overviews now place an AI-generated answer at the top of the standard results page, often before any blue-link result, for queries the system judges warrant a summary. Reputation work follows wherever people read the answer, so Five Blocks expects the emphasis to keep moving toward the sources the engines rely on most.

The three disciplines that come to the front

• Source quality. Search and AI engines judge sources by credibility, so a citation from an authoritative, independent outlet shapes an answer more than adding more of your own pages does. As the engines do more of the assembling, the quality of the sources they trust becomes the primary lever.
• Entity precision. The engines rely on structured knowledge sources such as Wikidata and the Google Knowledge Graph to resolve who or what a query is about. When that entity infrastructure is weak, engines can confuse or conflate distinct subjects that share a name, so getting the entity record right matters more than it did for ranking alone.
• Multi-model narrative monitoring. The same question can return materially different answers across the major engines, so tracking them in parallel becomes routine work rather than an occasional spot check. A problem can surface in one model before the others.

Why Five Blocks built ahead of the curve

You can’t edit what an AI model says directly, so the leverage in all three disciplines is in the sources and entity records the engines read, not the engine itself. That is what the emerging practice of Generative Engine Optimization (GEO), a category that formed in 2024, works on. Five Blocks built its AIQ platform to monitor it: AIQ polls the eight major AI engines (ChatGPT, Gemini, Copilot, Perplexity, Claude, Grok, Google AI Overviews, and Google AI Mode) for how they represent a brand, its executives, and its narratives, so a program can be managed across models rather than tuned for any one of them.

The post What does Five Blocks predict for the future of AI in reputation management? appeared first on Five Blocks.

One article, three discovery surfaces

• Search results. For branded queries, the Wikipedia article usually appears at the top of Google’s results, often the first detailed reference a searcher reads.
• Knowledge Panel. Google draws the description and facts in its Knowledge Panel from Wikipedia and Wikidata, so the article shapes the entity card shown beside the results.
• AI answer engines. Wikipedia is among the most heavily weighted and most-cited sources the major AI engines use when they summarize a subject, so it helps set the narrative those engines deliver.

[[FIG:kb-0163]]

Why accuracy matters

Because the same article feeds all three surfaces, a single problem rarely stays contained. Inaccurate, incomplete, or negatively framed Wikipedia content can damage a client’s entire digital presence and persist across platforms, since the search result, the Knowledge Panel, and the AI answer can all repeat the same flaw. Google’s own guidance makes the point: Knowledge Panel descriptions cannot be edited directly and update only once the underlying source is corrected. Fixing the article is the upstream correction that carries everywhere downstream.

The post What is Five Blocks’ perspective on Wikipedia’s role in digital reputation? appeared first on Five Blocks.