How DEL GEO audits your data and sets the baseline for GEO and generative SEO

If you’re thinking “why does ChatGPT not mention us?”, you’re not alone. If you’re thinking “why is the answer wrong?”, that’s the scary one. If you’re thinking “we do SEO, why isn’t that enough?”, welcome to the GEO era. We do DEL GEO work because search behaviour moved from clicks to answers, and you need to be present in answer engines, not just search engine results pages.

This is generative engine optimization (GEO) and search engine optimization (SEO) working together, not competing. GEO means your brand shows up inside AI-generated answers on generative search engines, not just in search engine results pages (SERP). And yes, this is GEO/SEO generative engine optimization in plain English.

Business Meeting presenting data.

Why we start with an audit and baseline

There is no “ChatGPT Console”, so guessing is what most SEO players do. We don’t guess. We baseline. Baseline means we measure what the answer engine says about you today, then we prove change with the same tests next month. That’s how we avoid random SEO activity and focus on metrics that tie to search visibility. If you want the quick overview of our GEO audit, start here: DEL GEO audit overview.

Step 1: We get the “keys” and map your source stack

First, we need access to what we can actually change. That includes your site, plus the places AI-driven search engines pull “verification” from.

We audit your source stack across the web, including:

• Your website tech basics like robots.txt and llms.txt, so AI-powered search can read the right pages first.

• Your Google profiles and major listings, because google and google search still feed a lot of search results.

• Your authority pages like Wikipedia or Wikidata, because generative engines love consensus.

• Community sources like Reddit and Quora, because answer engines trust real discussions.

• Dev channels like GitHub and Stack Overflow, if you’re technical, because coding assistants exist too.

• Visual channels like YouTube transcripts, because images and video need text for retrieval.

Step 2: We run an “Entity Consistency Audit”

This is where search engine optimization meets generative engine optimization. We check if your company facts match across your site, google listings, directories, and any knowledge sources.

We build a simple “facts template” and push it into places machines actually read, like your About page, footer, and schema. Example facts we standardise: founded date, HQ, service area, offering, support hours, contact, last updated. This is boring on purpose. Boring is how you reduce hallucination risk.

Step 3: The AI Visibility Test (this is the baseline)

Now we test how the generative artificial intelligence systems describe you today. We run a zero-shot and few-shot prompt audit across major models like ChatGPT, Perplexity, and google ai (Gemini). We use prompt sets like:

• “Who is [Brand]?”

• “What does [Brand] do?”

• “Who are the top providers of [category]?”

• “Best [solution] for [use case]” prompts, because that’s where prompt rankings show up.

Then we score the baseline with clean, repeatable metrics:

• Citation frequency, how often you’re mentioned in a fixed set of 50 to 100 queries.

• Share of Voice, how often you show up versus competitors in the same prompt set.

• Sentiment analysis, whether the model frames you as reliable, expensive, or risky.

• Source gap analysis, which websites the answer engines cite, and where you’re missing.

• Search results referral signals in analytics, like traffic from chat tools where we can see it.

This baseline is what makes generative SEO success measurable.

Step 4: We turn the baseline into an action map

We take the audit results and build a Topic Graph, which is an entity map, not a keyword list.

This is where geo describes strategies that classic search engines never needed. We map keywords to real questions, because generative engines work on natural language, not just short phrases.

We split it by platform, because platform-specific optimization is real, and each search environment behaves differently. If you want the deeper “how we write” side, here’s the playbook: Generative SEO strategies.

Step 5: We lock your baseline into a dashboard we can beat

We set a monthly dashboard, so your baseline becomes a line we can move. We track the same prompt set, so we can prove improvement without gaming the numbers. We also spot common GEO mistakes early, like poor site architecture, mobile optimization neglect, and over-optimization that breaks readability. Yes, we still do technical SEO, but we do it with a generative SEO lens.

That includes schema, llms.txt, and making sure google AI overviews can lift clean chunks without losing context.

A quick example, over coffee

A client came in convinced their SEO wasn’t working. In the baseline, they had decent rankings on traditional search engines, but zero presence in answer engine results. Worse, the AI-generated answer invented a feature they don’t offer. We fixed the facts, tightened entity consistency, added schema, and rebuilt key pages for passage retrieval. Next month, citation frequency moved, sentiment stabilised, and the hallucination stopped showing up in our prompt set. That is artificial intelligence search engine optimization in the real world.