A local deals app fails at its basic job when a customer arrives to find that an offer has expired, applies at another branch, or excludes the item they wanted. AI can summarize an offer, but it cannot create the merchant’s permission or guarantee that a checkout will honor it.
Before developing an app, test whether you can maintain a small, trustworthy list of offers. This is a business experiment with ongoing work, not a promise of passive income or a reason to buy a large software package immediately.
Start with one useful category
Choose a defined area and an ordinary need, such as local hobby supplies or repair services. Ask potential users how they currently find offers and what makes them abandon one. Ask participating merchants what they can realistically provide and how often information changes.
A broad audience description is enough for an early test. Do not assume that everyone over 40 wants the same products or needs a discount. Let people choose categories explicitly instead of constructing a detailed personal profile.
Use a simple page or list to test the service before requiring downloads, accounts, or location tracking. If the list is not useful, adding a chatbot is unlikely to solve the underlying problem.
Make every offer a structured record
Get offers from the merchant or another source you have permission to use. Confirm whether you may display their text, images, and branding. Do not scrape a site’s restricted data or invent an exclusive partnership.
For each offer, record:
- The merchant, participating location, and original source.
- The product or service covered and the actual price or discount terms.
- Start and expiry dates, including relevant time-zone details.
- Eligibility, minimum spend, exclusions, availability limits, and redemption steps.
- When the merchant or source was last checked and who owns the update.
If a required detail is missing, flag the offer for clarification. A generated expiry date or coupon code is worse than an empty field because a customer may act on it.
Use AI to shorten, not improve, the deal
Ask: “Summarize this merchant-approved offer in plain language. Preserve all restrictions and dates. Do not add urgency, savings claims, coupon codes, endorsements, or availability. List ambiguous terms separately.”
Compare the summary with the original record. Check whether “up to” disappeared, a selected-item offer became storewide, or an introductory price became an ongoing price. These small wording changes can materially alter what a shopper expects.
Keep the full terms close to the summary and make the merchant’s destination clear. Do not claim an item is the cheapest locally unless you have appropriate current evidence for that comparison. A percentage discount alone does not establish good value.
Make expiration part of the product
Decide what happens when an offer expires, a merchant withdraws it, or the source stops updating. Build a removal or review rule into your process before publishing. “AI-powered” should not mean that old offers remain available indefinitely.
Give users a simple way to report a problem and assign someone to respond. Confirm the issue with the merchant rather than silently changing the terms. Record corrections so repeated failures can inform which offers you continue to include.
During a pilot, test awkward cases deliberately: an offer at only one branch, an unclear end date, a sold-out item, and a link that redirects to a different product. A system that handles only perfect records is not ready for everyday use.
Explain how the service earns money
If merchants pay for placement or you receive commission, make that relationship clear near the relevant offer. Do not present paid ranking as an independent assessment. Separate a sponsored listing from an editorial recommendation.
The FTC’s disclosure guidance explains the importance of making material brand relationships obvious when endorsing products. If you promote your deals service through social media, include the relevant disclosure in that promotion too. This is general information, not legal advice; obtain advice on the advertising, privacy, and consumer rules applying to your service.
Estimate costs using current quotes for hosting, messaging, development, and any data feeds, plus the time spent checking merchants and resolving problems. Revenue forecasts generated by AI are assumptions until real users and merchants demonstrate otherwise.
Keep personalization optional
Let a user select an area manually for the first version. Precise continuous location, purchase histories, and sensitive personal characteristics are unnecessary for testing whether a small offer list is useful. Explain any information you do collect and how someone can stop notifications or delete an account.
If you later add conversational search, make it retrieve from your checked records and link back to the terms. It should say when no matching verified offer exists. Ask a qualified developer to assess permissions, security, and data handling before introducing accounts or integrations.
Evaluate the pilot by accuracy, successful redemptions where verifiable, complaints, repeat use, and maintenance time. For the next development decision, see testing a small AI app before building it. Dependable local information is the product; AI is one possible tool for maintaining it.
AI disclosure: This article was written and revised with AI assistance. Sources checked September 26, 2026. See our disclaimer.
Illustrative photograph by Vinicius Brasil on Unsplash.
