1. An elaborate costume raises the question of renting versus owning
We asked: “How should I compare renting an elaborate Halloween costume for one night with buying one?”
For that one question, we saved 48 ChatGPT answers and 16 Perplexity answers. All favored renting under the stated one-night premise, subject to costs and terms. Every answer also kept reasons to buy, including future use, customization or resale. [H1-01]
The alternatives extended beyond rent or buy-new. Secondhand options appeared in 27 of the 48 ChatGPT answers and 12 of the 16 Perplexity answers. Borrowing appeared in one ChatGPT answer and ten Perplexity answers.
For a retailer, this describes a broader competitive decision: ownership is being weighed against temporary use. Deposits and return rules enter the discussion alongside the costume itself. The finding is specific to an elaborate outfit for one night, not a general verdict that renting is better.
2. Walking comfort can make ordinary clothing the starting point
Another question asked how to choose a costume comfortable enough for a long evening of walking. For this example, we read the first saved ChatGPT answer and the first saved Perplexity answer: two answers to the same question.
Both started with familiar footwear and everyday clothing, then added recognizable details. Neither directed the reader to a named purchase destination. [H1-02]
ChatGPT described choosing clothes someone would already feel comfortable wearing on a long walk, then adding accessories or makeup. Perplexity similarly proposed ordinary clothes plus one or two details that establish the character.
A report counting only retailer names would miss much of the advice. These answers helped with wearing the costume, even though they did not name a store. We are describing those two examples, not measuring how often every response took that approach or validating the comfort claims.
3. A recognizable character can start in an existing wardrobe
We also asked: “What Halloween costumes can I make using clothes and household items I already own?” Again, this example uses one answer from each system—the first saved response to that question.
Both combined a denim shirt, jeans and a bandana into Rosie the Riveter. Both supplied other combinations of ordinary clothes and household items without directing a named purchase. [H1-03]
The useful advice was specific enough to act on: particular ingredients produced a recognizable look. A finished costume was only one possible way to get there.
For a brand team, the commercial question becomes which pieces the person still needs, if any. The study did not measure whether anyone followed the advice or spent less as a result.
4. Decorations have to fit the home—and the months after Halloween
Two questions covered practical constraints. One asked how to decorate a rental without permanent attachments or bulky props. The other asked what to check about weather, power and storage before buying a yard display.
We read the first answer from each system to each question: four answers in total. In the rental examples, removable or fold-flat pieces were central. ChatGPT added a retailer shopping table; Perplexity stayed with materials and placement. [H1-04]
For the outdoor question, both answers emphasized weather, power and packed storage requirements. The display’s size after it came down mattered alongside its effect while installed.
These examples identify information surrounding a purchase: where the item will go, how it will be used and where it will live afterward. They are saved AI advice, not verified installation instructions or evidence that adding those details to a product page will improve citations.
5. After the holiday, a familiar name can have a different job
Our post-Halloween question asked about practical ways to swap, donate or repurpose costumes. We saved eight ChatGPT answers and eight Perplexity answers to that same question.
Reading the first answer from each system showed different possible actions: keeping, swapping, donating, selling and repurposing. Goodwill was a donation destination; eBay was a resale destination. [H1-05]
We also counted names across all eight saved answers from each system. Goodwill appeared in eight ChatGPT answers and seven Perplexity answers. eBay appeared in four and eight, respectively. These wider counts establish name appearances; the two closely read examples establish the particular roles described above.
A marketplace can therefore remain visible after the original purchase while the advice concerns resale. Counting every appearance as a recommendation to buy a new costume would miss what the answer is helping someone do.
Follow the decision around the purchase
These examples extend the category from finding an outfit to obtaining, wearing, storing and redistributing it. They give marketers concrete questions to examine around their products. They do not turn repeated AI answers into evidence of shopper demand.
Methods and evidence
The corrected Halloween foundation covers 30 authored US-focused questions. The completed ChatGPT and Perplexity collections contain 612 and 556 saved answers, respectively, collected October 9, 2026. The same question was asked repeatedly; answer counts vary by question and system. These are configured API outputs, not a survey of shoppers or a recording of consumer browsing sessions.
The rental result uses all 48 ChatGPT and 16 Perplexity answers to HALLOWEEN-10-1. Walking comfort and owned-item assembly use the first answer from each system to 05-2 and 04-2. Decorating uses the first answer from each to 08-3 and 09-3. Post-holiday roles use the first answer from each to 10-3; name counts use all eight answers per system to that question. Repetition does not establish independent source discovery. Current retail terms and product claims were not checked.
H1-01–H1-05 retain their mappings to foundation claims C06, C20–C22 and C08. No AI Overview finding or new measurement is used.
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