The mistakes that kill your progress

Most GEO strategies don't stall from a lack of knowledge but because of a handful of recurring mistakes: content that's too generic, giving up too early, relying on a single engine, neglecting the technical side. Fixing them one by one is often enough to unblock progress that looked stuck.

Producing generic content instead of precise answers

The most common mistake is publishing content that looks like ten competitors' content: a general definition, a list of tips already seen elsewhere, no proprietary data. Generative AIs favor sources that give a specific, verifiable answer to a precise question, not ones that rephrase an already widely available consensus.

The simple test: if your content could have been written by any competitor in the sector, it won't set you apart in AI answers. A figure drawn from your own experience, a detailed real-world case, an answer that takes a clear position on a point where opinions diverge — that's what gives a model a reason to cite you rather than someone else.

Giving up after two or three weeks

GEO almost never produces visible results before several weeks, sometimes several months for the most competitive keywords. Many teams run a first audit, publish two or three pieces of content, don't see their score move, and stop. This is the costliest mistake, because it happens right when the effort is starting to pay off behind the scenes: the AIs still need to crawl the new content, index it, and associate it with the right queries before it shows up in answers.

That's why a weekly workflow kept up over time is more effective than an intense sprint followed by a stop. A modest but continuous pace over six months beats one month of intense effort followed by abandonment.

Tracking only one AI engine

Focusing all your attention on ChatGPT because it's the most used is a classic mistake. Perplexity works differently (more search-oriented, with direct source citation), Claude and Gemini have their own logic for selecting sources, and the split between these engines varies by audience and sector. A brand can be well positioned on Perplexity and nearly absent on Gemini, and you won't see it if you only look at an aggregated score.

Tracking the four engines separately, even at a basic level, prevents you from building a strategy optimized for a single channel that could lose relevance or change behavior overnight.

Ignoring the technical side in favor of content alone

Publishing good content isn't enough if it stays hard to crawl, poorly structured, or blocked for generative AI robots. Many teams pour all their effort into writing and neglect the technical foundations: whether AI crawlers can access the content, clear page structure, no unintentional blocks. Excellent content that's invisible to crawlers has the same effect as content that doesn't exist.

A visibility score can shift from one week to the next without any of your actions being the cause: providers regularly update their models, which sometimes changes how sources are selected, without a detailed advance announcement. Reading every variation as the direct consequence of your latest publication leads to the wrong conclusions either way: crediting an action that had nothing to do with it, or doubting a strategy that was actually working well.

Good practice means telling apart one-off swings, which may come from a model update, from trends confirmed over several consecutive weeks, which more likely reflect a real effect of your work. This is one of the reasons regular weekly measurement matters more than reacting to a single isolated number.

Another frequent mistake is running GEO in isolation, disconnected from SEO, existing content, and acquisition channels already in place. The off-site signals that matter for GEO largely overlap with those that matter for classic SEO: domain authority, external mentions, backlink quality. Treating the two separately doubles the work and weakens each channel instead of reinforcing them together. This topic is developed further in this module, in the lesson on GEO as an acquisition channel.

Never checking what competitors are doing

Finally, moving forward without ever checking who's capturing citations in your place deprives your strategy of an essential signal. Regularly analyzing competitors in AI answers helps you understand why a score is stalling: often it's not that your content is bad, it's that a competitor answered the same question better, with a more authoritative or more recent source.

One last, quieter mistake is measuring your progress by comparing yourself right away to the biggest players in the sector, the ones who've been publishing content for years and already have well-established domain authority. Against that benchmark, any real progress looks negligible, which wrongly leads to the conclusion that the strategy isn't working.

It's more useful to track your own trajectory over time and compare yourself to competitors of a similar size, before aiming at the sector leaders. A visibility score that doubles in three months is a positive signal, even if it stays far behind that of a long-established player. It's this relative progress, week after week, that shows whether the pace of work you've put in place is working.

What to remember

None of these mistakes is irreversible. They share one thing in common: they all come from a lack of consistency or a lack of overall perspective. Fixing just one of them, without changing the rest of the strategy, often already produces a visible unblock within a few weeks.