Do ChatGPT and Google use the same words for brands?

A description term is a word or short phrase used to characterize a brand, such as reliable, open source, or easy to use. ChatGPT Search and Google AI Mode shared no exact description term in 59,707 of 78,167 same-prompt, same-brand comparisons. The exact rate was 76.4%.

A visibility check on one engine cannot show how another engine frames the same brand. Compare the same prompts and brands across both engines before treating one answer as the market narrative. BrightEdge's 61.9% brand-recommendation disagreement statistic measures which brands appear. This study measures the exact language after the prompt and brand are held constant.

The matched comparisons contained 971,326 description uses after combining both engines and removing duplicate matches. Only 26,376 of those uses appeared on both engines, or 2.7%. That share is the pooled exact overlap. The engines used exactly the same set of description terms in 100 comparisons.

The headline is not caused only by short answers with one missing word. Even across the full language pool, exact agreement is limited. This does not mean the engines contradict each other because different words can express the same idea.

Positive descriptions accounted for 526,337 of 567,463 Google AI Mode description uses, or 92.8%. They accounted for 461,491 of 560,854 ChatGPT Search uses, or 82.3%. The difference was 10.5 percentage points.

An aggregate sentiment score can hide a platform difference in how brands are framed. The result is descriptive and does not show that either engine's wording was more accurate.

Exact adjective overlap was 6.1%, based on 19,405 shared uses among 316,962 combined uses. Positioning claims overlapped at 1.7%, with 847 shared among 49,663. Other phrases overlapped at 0.79%, with 3,743 shared among 476,583.

Agreement is highest on compact labels and lowest on fuller descriptions. Audit the exact claims and phrases around a brand, not only its headline sentiment.

Excellent was shared in 1,133 matched comparisons, open source in 785, best in 737, recommended in 623, and strong in 583. No shared phrase appeared in 1,200 comparisons.

The language that carries distinctive positioning is less likely to match exactly than broad evaluative words. Treat shared generic praise as a starting point, not proof of consistent positioning.

Strong appeared only on the ChatGPT Search side in 6,423 matched comparisons and only on the Google AI Mode side in 2,044. Robust showed the reverse pattern: 392 ChatGPT-only comparisons and 4,707 Google-only comparisons. Highly recommended appeared in 34 ChatGPT-only comparisons and 2,390 Google-only comparisons.

Build an engine-specific message map from the words attached to your brand and competitors. A shared brand ranking does not imply shared positioning language.

Among brands with at least 50 matched comparisons, Etsy had the highest pooled exact overlap at 6.6%, with 53 shared uses among 803 combined uses across 68 comparisons. PayPal was at 5.5% and Supabase at 5.2%. At the other end, Remote was at 0.39%, QuickBooks at 0.71%, and Chase at 0.82%.

Use the brand table to identify where to inspect the actual wording. A low exact-overlap rate does not by itself show inaccurate, negative, or contradictory descriptions.

Across 17 industries with at least 1,000 matched comparisons, Consumer Goods had the highest pooled exact overlap at 3.4% across 1,161 comparisons. Food and Beverage followed at 3.2%, while Professional Services was at 2.2% and Artificial Intelligence at 1.9%.

The cross-engine language gap is not confined to one market. Compare brands within their industry, but do not assume a sector benchmark explains a specific wording difference.

Requiring at least 90% confidence in the extracted term produced no exact overlap in 60,698 of 76,910 comparisons, or 78.9%. Requiring at least three description terms on each engine produced 27,039 of 42,580, or 63.5%. Also requiring similar numbers of terms on each engine produced 19,263 of 30,799, or 62.5%.

The main study kept descriptions extracted with at least 80% confidence. It excluded 10,911 description uses that could not be tied to a known brand, 5,545 below the confidence minimum, and 762 that were empty after cleaning. Fuller descriptions create more chances for one exact match, so their zero-overlap rate is lower. The result still applies only to literal wording and should not be reported as disagreement about meaning.

The engines shared no exact wording in 76.4% of 78,167 matched comparisons, and pooled exact overlap was 2.7%. The brand, industry, and description-term tables show where those differences concentrate.

Track the same buyer prompts on ChatGPT Search and Google AI Mode. Save the exact words attached to your brand and competitors. Separate selection, sentiment, and wording in the audit. Investigate material differences in claims, but do not label synonyms as contradictions without reviewing the full answers.