See how repair shop staff value used smartphones, tablets and notebooks at the counter with Fixh AI: a fixed condition questionnaire, an AI-calculated price suggestion, and a direct handoff to the used device purchase flow.
Used device trade-in valuation with Fixh AI is the tool repair shop staff use at the counter when a customer brings in a used smartphone, tablet or notebook and asks how much it is worth for trade-in or direct purchase. It lives in the Shop section of the back office, under "Used device valuation" (path /shop/trade-in), and it is built to be used by the staff member while the customer is still standing at the counter: it takes just a few minutes to identify the device, answer a standardized condition questionnaire, and get a price proposal calculated by artificial intelligence, backed by a written justification. It is not a self-service storefront for the end customer: it is a co-pilot for the people working in the shop, replacing a rough eyeballed guess with a repeatable, logged and consistent method from one staff member to the next.
Why it matters for a repair shop
Anyone running a repair shop knows how delicate the moment is when a customer brings in a used device and asks for a price: offering too little risks losing the purchase, and the resale or spare-parts value that comes with it, to a competitor; offering too much erodes margin and can create unfair differences between customers if different staff members with different experience are doing the valuing. Trade-in valuation with Fixh AI standardizes that moment: the condition questions are always the same for a given device category, no matter who is asking them, and the suggested price accounts for both general second-hand market rules and the shop's own real purchases of the same model in recent weeks. For a repair shop it is also an acquisition channel: a customer who gets a quick, transparent valuation for an old phone is more likely to come back to have their current phone repaired, or to buy a refurbished one from the shop's own showcase. Finally, it sets the shop apart from competitors who value used devices by guesswork: being able to show the customer a freshly generated, written justification for the offer increases the perceived transparency and professionalism of the shop.
How it works in practice
The flow is organized in three guided steps. In the first step, the staff member identifies the device in one of two ways: scanning or typing the device's 15-digit IMEI, which calls the same lookup service already used in "New repair" and automatically fills in brand, model and category, or manually searching brand and model with an instant-search field. The device category, smartphone, tablet or notebook, is proposed automatically based on the selected model but can still be changed by hand.
Once the device is identified, the staff member generates the condition questionnaire: it is important to be precise here, because these questions are not produced on the fly by artificial intelligence — they are a fixed catalog, configured per device category in the database (storage capacity; screen condition, whether original and whether pristine, scratched or cracked; body condition; CE marking; whether the cameras work; SIM tray for smartphones and tablets; buttons and ports; biometric unlock; account/carrier lock status; included accessories; whether the battery is original or replaced and, only for Apple and Samsung devices, the battery health percentage band), plus a free-text field for any other wear notes. Some questions adapt to the device: the 64GB storage option, for example, only appears if the model is more than five years old, since on a recent model that capacity is no longer commercially relevant.
Once every question has been answered, the staff member requests the valuation: this is the only point where Fixh AI, built on Google's Gemini, comes into play. The system builds a prompt including the brand, model, category, release year and calculated age of the device, the company's currency and country, every answer to the condition questionnaire and, when available, real purchases of that exact same model made by that same shop in the last thirty days: this history is explicitly flagged to the AI as the more reliable signal, to be preferred over its general knowledge whenever the two disagree. The model is instructed to be cautious whenever confidence is low, to treat a non-original screen or battery as a significant defect rather than a minor one, and to factor in how many newer generations of the product have launched since the device came out. The structured response returns a minimum-maximum price range, a suggested price within that range, and a short justification written in the company's configured language. Every valuation, device, answers, price range and justification, is permanently saved to the history log, with an "estimated" status.
From the result screen, the staff member can start over or register the purchase: doing so moves the valuation to "converted" status, and the system automatically opens the Used device purchase module, pre-filled with brand, model, suggested price and a text summary of the declared condition, ready to collect the seller's personal details and generate the actual purchase document together with the matching warehouse stock entry. Trade-in valuation with Fixh AI, on its own, therefore does not produce a tax document or a stock movement: it sets the stage so the used device purchase module can do that in the next step, without retyping brand, model and price.
Quick guide
- Go to Shop > Used device valuation.
- Select the shop location you are working at from the top selector.
- Scan or type the device's 15-digit IMEI to auto-fill brand, model and category, or search brand and model manually.
- Check and, if needed, correct the proposed category (smartphone, tablet or notebook).
- Generate the condition questionnaire and answer every question based on the device's real state.
- Request the valuation: Fixh AI calculates the price range, the suggested price and a written justification.
- Show the result to the customer and decide whether to proceed.
- If the customer agrees, select "Register purchase": the valuation is marked as converted and the pre-filled Used device purchase module opens.
- Complete the seller's personal details there to generate the final document and the warehouse stock entry.
- Check the history at the bottom of the page any time to find past valuations again.
Real use cases
A customer brings in a four-year-old iPhone with an intact screen but a visibly worn battery, and asks whether it is worth repairing or selling. The staff member identifies it via IMEI, answers the questionnaire flagging a non-original battery at 85-90% health, and Fixh AI proposes a cautious price justified by the battery defect: the customer decides to sell it as-is instead of paying for the repair.
A multi-shop company notices that two different staff members, in two different shops, value the same smartphone model in similar condition very differently. Switching to valuation with Fixh AI makes the suggested price consistent regardless of who runs it, because it is based on the same questionnaire and the same purchase history.
A regular customer of the repair shop brings in a notebook they no longer need, having recently bought another device from the same shop: answering that the keyboard, ports and battery all work normally, they get a price proposal that accounts for the shop's own recent purchases of similar notebooks, and close the sale by registering the purchase straight from the result screen.
Tips and best practices
Answer the questionnaire as precisely as possible: every question affects the final price, and a rough answer about the screen or the battery can meaningfully shift Fixh AI's proposal away from the device's real value. Use the IMEI lookup whenever it is available: besides being faster than a manual search, it reduces the risk of accidentally selecting a similar but different model. Keep in mind that the suggested price automatically accounts for your own shop's recent purchases of the same model: if you feel a model has recently been overpaid, address that upstream rather than expecting a single valuation to fix it on its own. Show the customer the written justification Fixh AI generates alongside the price: it helps explain why the offer is what it is, especially when the price is lower than the customer expected.
Common mistakes to avoid
The first mistake is skipping or randomly answering some questionnaire questions just to reach the price faster: the result is a less reliable estimate that can lead to paying more, or less, than the device is actually worth. Another mistake is confusing this tool with the Used device purchase module: valuation with Fixh AI only produces a price proposal and a searchable history entry, not a tax document or a stock movement, which remain the job of the purchase module the valuation hands off to. Also avoid treating the suggested price as a fixed, non-negotiable figure: it is a starting point, deliberately calculated with caution to leave room for negotiation, not a binding price list. Finally, do not forget to select the correct shop location before starting a valuation, especially in multi-shop companies: the selected shop affects which recent purchases the AI uses as a reference.
Frequently asked questions
Who uses the trade-in valuation with Fixh AI, the customer on their own or does it need staff? It is a staff-facing tool, not a self-service storefront for the customer: a staff member runs it at the counter during the conversation with the customer bringing in the used device.
Do the questionnaire questions change every time, or are they generated by AI? They are always the same for a given device category, drawn from a catalog configured in the system: the AI does not generate the questions, it only comes into play to calculate the price based on the answers given.
What exactly does Fixh AI (Gemini) do in the valuation? It receives the brand, model, device age, every questionnaire answer and, when available, the shop's own recent purchases of the same model, and returns a price range, a suggested price and a short written justification, staying cautious whenever there is uncertainty.
What happens after getting a valuation? You can start over or register the purchase: doing the latter marks the valuation as "converted" and automatically opens the Used device purchase module, pre-filled with the device data and the suggested price, where you complete the seller's details to generate the final document and the warehouse stock entry.
Can I look up past valuations? Yes, at the bottom of the page there is a searchable history by brand or model, with date, category, suggested price, status and the staff member who ran it, plus a detail view showing every answer given and Fixh AI's justification.
Is the questionnaire the same for every device? It is specific to each category (smartphone, tablet or notebook), and some questions, like battery health percentage or the 64GB storage option, only appear for certain brands or older models.
