Verified against ChatGPT · 2026-08-14
Position an ad offer with a price-framing check that catches when the anchor doesn't actually make sense
Drafts offer positioning copy for an ad, including how price or value is framed and anchored, with an explicit check that the anchor comparison is honest and would hold up if a skeptical buyer looked closely at the math.
The prompt
Ready to copy — highlighted parts are example details you can swap.
Position an ad offer for $29/month meditation app subscription, annual plan billed as $299/year., including how the price or value should be framed, and explicitly check whether the framing's math would hold up if a skeptical buyer actually did the comparison themselves rather than just feeling the vibe of the framing.
OFFER
$29/month meditation app subscription, annual plan billed as $299/year.
ACTUAL PRICE AND WHAT'S INCLUDED
$299/year covers unlimited sessions, offline downloads, and one linked family account.
WHAT THIS IS BEING COMPARED AGAINST (real anchor, if one exists)
One in-person therapy session locally averages $120-150, per publicly available local directory pricing — not a claim we've independently verified nationally.
TARGET BUYER'S PRICE SENSITIVITY
Price-sensitive enough that a $299 annual charge upfront causes hesitation, even though the monthly-equivalent is low.
Write the offer positioning in two parts. Part 1: the framing approach — decide whether this offer is better positioned around an anchor comparison ("less than the cost of X"), a per-unit breakdown ("just $Y per day/use"), a bundled-value framing (listing what's included and its combined worth), or a straight price-transparency framing (stating the price plainly because the offer is strong enough not to need dressing up) — and justify the choice based on the target buyer's stated price sensitivity, not just pick whichever framing sounds most persuasive by default. Part 2: the actual ad copy using that framing. Then, run an honesty check: if using an anchor or per-unit comparison, verify the math actually works as stated (e.g., if claiming "less than a cup of coffee a day,� confirm the daily-equivalent price is genuinely in that range, not a stretch) and flag explicitly if the comparison only works with a generous rounding or an unstated assumption a skeptical buyer would catch. Do not invent a comparison anchor not given to you (a made-up "average cost of X" statistic) — if no real anchor was provided and one is needed for the framing to work, say so and either request the missing figure or default to a different framing that doesn't need one.
OUTPUT: framing approach chosen with justification, the ad copy itself, and the honesty check confirming the math holds or flagging exactly where it's a stretch.Customize
Optional — swap in your own details for the highlighted parts above.
Why this works
Price-anchoring and per-unit framing ("less than a cup of coffee a day") are common enough in ad copy that a model asked to position an offer will reach for one by default regardless of whether the underlying math is actually honest, and this is a specific, well-documented weak point in AI-generated pricing copy — the model is optimizing for a framing that sounds persuasive, not one that survives a skeptical buyer doing the arithmetic themselves, which is exactly the gap the explicit honesty-check step closes by forcing the model to state and verify the actual calculation rather than assert the comparison and move on. Requiring the framing choice itself to be justified against the buyer's stated price sensitivity, rather than picked because it's the most conventionally persuasive option, matters because the right framing genuinely differs by buyer: a price-sensitive buyer facing a large upfront annual charge benefits from a per-unit breakdown that makes the daily cost feel small, while a buyer who already trusts the value proposition may find an anchor comparison to an unrelated purchase (coffee, another subscription) feel like a manipulation tactic rather than useful information, and defaulting to one framing style regardless of context misses that distinction entirely. The instruction against inventing a comparison anchor addresses a concrete accuracy problem: an ad claiming a product costs "less than the average cost of X" is making an implicit statistical claim, and if that statistic wasn't actually provided or verified, the ad is asserting something as fact that the advertiser has no basis for defending if a regulator, competitor, or simply a skeptical customer ever asks for the source. Explicitly flagging when a comparison only works via generous rounding or an unstated assumption gives the person using this prompt a chance to either fix the framing or accept the risk deliberately, rather than discovering after the ad is live that a customer did the math publicly and the framing didn't hold up.
What you get back
Framing chosen: per-unit breakdown, justified by stated price sensitivity to the upfront $299 charge. Ad copy: "$299/year works out to about 82 cents a day — unlimited sessions, offline downloads, one family seat included." Honesty check: $299/365 = $0.819/day, rounds cleanly to "about 82 cents" without a stretch — math holds without generous rounding.
Verified against
ChatGPT GPT-5.1 · 2026-08-14
Changelog
- 2026-08-14 — Initial publish, verified against ChatGPT GPT-5.1.
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