AI recommendations: your 5-star rating is no longer enough, and here’s why

Just like your business, your competitors are very likely showing off a high rating. Today, a 4.8 is no longer a standout achievement, but simply an “entry ticket” to be considered, by both people and AI.

When the average rating of well-ranked businesses sits somewhere between 4.8 and 5 stars, the gap is not significant enough for a user, and even less so for a LLM.

You can no longer win on your rating alone. But don’t panic: Partoo is here to help you understand where you stand when it comes to AI recommendations from LLMs!

What are AI recommendations really based on?

An average rating is no longer enough to sum up the quality of a business. AI knows perfectly well that ratings and reviews can be outdated, biased or even manipulated. That’s why LLMs now go much further: they analyse how recent, emotionally charged and detailed reviews are before forming a recommendation.

In other words, AI doesn’t just look at how highly rated you are. It also looks at what your customers have said recently, how much detail they went into and how strongly they felt.

Among the three main signals that algorithms scrutinise, you’ll find:

How recent the latest reviews are

For AI, review recency is a direct sign of reliability.

A business with an excellent rating but no new reviews for several months sends a weak signal, as the data may be seen as potentially outdated. By contrast, a company with a slightly lower rating but very recent reviews is considered a more accurate reflection of the current reality.

AI therefore thinks in terms of “living proof”: recent reviews suggest ongoing activity, and ongoing activity means the customer experience is still relevant today!

A steady stream of reviews, even imperfect ones, often carries more weight than a flawless score that has stood still over time.

The sentiment expressed

AI never assesses you in isolation. It systematically compares you with local alternatives.

If several businesses have similar ratings, it will try to understand what actually sets you apart. To do so, it analyses the recurrence of certain strengths, such as speed of service, cleanliness or value for money, but also the sentiment conveyed through tone and emotionally loaded wording, such as “highly recommend”, “warm welcome” or “huge disappointment”.

What matters is not being perfect on every factor, but being better than your competitors on specific, visible aspects.

That is what allows AI to generate both fairly objective recommendations, such as: “this hotel is often mentioned for its quick check-in”, and more subjective ones like: “this restaurant is praised for its delicious dishes”.

How rich the reviews are

Not all reviews carry the same weight in the eyes of AI.

A comment like “Great, I recommend” gives it very little to work with. By contrast, a detailed review containing concrete information about the product, service, context, experience and perceived sentiment becomes a genuine source of insight.

AI favours richer reviews because they help it:

• understand the customer experience precisely
• identify potential perception gaps between what is promised and what is actually experienced
• extract tangible proof points
• generate contextualised recommendations

For example, a review such as: “Very welcoming staff, less than five minutes’ wait and the product matched the description” will have far more impact than a simple 5-star rating with no explanation!

The more specific detail your reviews contain, the more material AI has to recommend you, and the greater your chances are of appearing in its answers.

Is your brand ready for AI recommendations? Take the test!

You’ve got it: your business can have a 4.9-star rating… and still be completely invisible to AI.

In just one minute, you can check whether you’re a “Leader”… or a “Ghost”.

Step 1: Ask AI about your business

Go to the LLM of your choice and ask this exact question:

“Which [business category] would you recommend in [your city] right now?”

Step 2: Fill in your scoring grid

Then identify your profile:

• Ghost (0 pts or less): AI does not have enough evidence to recommend you, regardless of your rating or actual quality.
• Present (1 to 2 pts): You exist in the dataset, but without anything recent or distinctive. You’re not convincing AI yet.
• Reference (4 pts): You’re mentioned spontaneously, with concrete and recent details. You’re sending the right signals, at the right pace. Well done!

Whatever your profile is, keep in mind that a low score is almost never a quality issue. It’s a data issue… AI doesn’t lack confidence in you: it simply lacks proof!