[Alain Stevens – Petfood Advisor]

Hello everyone,

Many pet owners have probably noticed something confusing while browsing Facebook groups or pet nutrition communities: the exact same kibble can appear in a “Top Recommended” chart in one group and then show up as a “Bad Choice” in another ranking a few days later.

This leaves many consumers wondering who to trust and whether these scoring systems are actually reliable.

One of the biggest reasons behind these contradictions is that every ranking system uses different evaluation methods. Some charts focus heavily on protein percentages, while others concentrate almost entirely on estimated carbohydrates. Certain groups penalize specific ingredients automatically, whereas others prioritize marketing claims such as “grain-free” or “high meat content.”

As a result, two people can analyze the same product using completely different criteria and end up with opposite conclusions.

Another issue comes from incomplete or estimated data. Pet food labels rarely provide every nutritional detail needed for precise analysis. Many online charts rely on estimated calculations or simplified formulas, especially for carbohydrates. Depending on the formula used, the final result can vary significantly from one ranking table to another.

Recipe changes also create major inconsistencies. Manufacturers frequently modify formulas, suppliers, fat levels, additives, or mineral balances. However, many Facebook charts are never updated after publication. An old screenshot can continue circulating online for years even though the product composition has already changed.

There is also the problem of context.

A food that works well for a highly active dog may be unsuitable for a sterilized indoor cat. A product adapted to a senior animal may receive a lower score because it does not fit the criteria of a generic scoring system designed for “average” pets.

Most simplified Facebook rankings ignore these biological differences and attempt to assign one universal grade to every animal, which can quickly become misleading.

Social media itself also plays a role in amplifying confusion. Bright colors, dramatic warnings, and “best vs worst” charts generate far more engagement than detailed nutritional explanations. Emotional content spreads faster than nuanced analysis, even when the underlying methodology is weak or incomplete.

Finally, many ranking systems cannot evaluate important hidden factors such as ingredient digestibility, manufacturing quality, nutrient bioavailability, or industrial processing methods. Two products with similar analytical values on paper may perform very differently in real-world nutrition.

This is why more and more pet owners are starting to move away from simplistic ABCDE-style scores and toward more detailed educational approaches that explain products instead of reducing them to a single letter or color.

In pet nutrition, a product is rarely universally “good” or “bad.” The real question is whether it is appropriate for a specific animal, in a specific situation, with specific needs.

[Auteur]

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