Each use case below describes the problem, the workflow in the product and the plan that fits. All of them rest on the same thing: a corpus of 128,867 recorded sales from 28 May 2021 to 28 May 2026, each with its venue, date and a link to the public report it came from.
Pricing a name before an expired auction closes
The problem
An expired auction gives you hours, sometimes minutes, to decide how high to go. Gut feel and a registrar's automated number are a poor basis for a bid, because neither shows which sales the number rests on. Overpay once and the margin on that name is gone.
The workflow
Enter the name, for example crons.ai. The engine describes it (5 letters, .ai, plural, developer term) and finds sales that share meaning and traits, not only letters. Set the venue tier to wholesale, because the people bidding against you are investors, not end users. You see comps such as server.ai at 29,400 USD (Namecheap, 25 February 2025), kernel.ai at 14,599 USD (Dynadot, 8 October 2024) and webhook.ai at 2,424 USD (Namecheap, 8 October 2025), each with a relevance score and reasons. The estimate gives a wholesale figure, a range and a confidence level. Your maximum bid sits below the wholesale figure, with room for the resale.
The plural matters too. The rationale flags that plural forms usually sell for less than the singular, which is often the difference between a sensible bid and an expensive one. More on this in wholesale vs retail domain prices.
Which plan fits
Pro (150 searches a month) suits a part time investor who bids on a few names a week. Investor (750 searches a month) suits daily auction work. One avoided overpay at auction can cover a year of Investor at $888.
Setting buy now prices across a portfolio
The problem
A portfolio of hundreds of names usually has prices set years ago, by rule of thumb, or not at all. Names priced too high never sell. Names priced too low leave money with the buyer. Pricing them one by one takes weeks.
The workflow
Upload a bulk appraisal list on the Investor plan (up to 200 names per list) or the Broker plan (up to 1,000 names per list). Each name gets the same treatment as a single search: comps, a range, a wholesale and a retail figure and a confidence level. The portfolio view puts every name and its estimate in one table, which you can sort by confidence or value and export to CSV for your marketplace.
For buy now pricing, the retail figure is the anchor, since buyers on end-user marketplaces pay retail. The same name can sell at very different levels: mega.app sold for 1,350 USD on Sav.com (22 July 2023) and then for 50,000 USD on Spaceship.com (30 June 2025). Names with Low confidence or no comps above 1,000 USD are the ones to price by hand, or to drop at renewal.
Which plan fits
Investor for portfolios up to a few hundred names a month (each name counts as a search, 750 a month). Broker for larger portfolios, with 3,000 searches a month and lists up to 1,000 names. See for investors.
Answering an inbound offer with a white label report
The problem
A buyer sends a five figure offer for a client's name. The client wants to know whether to take it, and the buyer wants to know why the counter is higher. A number without evidence starts an argument. A report with dated, sourced sales ends one.
The workflow
Run the name, filter to the extension and the date range that make sense, remove comps you would not defend, and save the report. On the Broker plan, export it as a white label PDF with your logo: the comps, the estimate, the rationale that cites sales by name, price and date, and the source link for every sale. Send it to the client to agree a floor, and to the buyer to support the counter. The audit log records who exported which report and when.
Retail comps carry the argument with an end user. For a .ai name, sales such as law.ai at 350,000 USD (Sedo, 16 August 2025) or os.ai at 150,000 USD (Afternic, 12 March 2025) show what end users have paid for short, meaningful names, while the rationale explains how your name compares.
Which plan fits
Broker: white label PDF reports, 250 reports a month, 5 seats with roles in a shared workspace, invoices with company details and the export audit log. See for brokers and how brokers justify a domain price.
Justifying a domain purchase inside a company
The problem
A founder has found the right name for the product, and the seller wants 40,000 USD. The CFO, the board or a co-founder asks the fair question: what is this name worth, and how do we know? A registrar estimate cannot answer it, because it does not show the sales behind the number.
The workflow
Search the name and save a report. The report shows the comps, the low, likely and high values, the retail figure (the one that applies to a company buying from a seller), the confidence level and a rationale in plain English. It also lists what would raise or lower the value, which is useful when negotiating. Attach the PDF to the purchase request. Anyone reading it can open the source link of each sale and check it.
If the asking price sits far above the high value, you have a reason to negotiate. If it sits inside the range, you have a reason to approve. Either way, the decision is documented. The estimate is a data-backed opinion, not a certified appraisal, and the report says so.
Which plan fits
For a one-off decision, the one full report you get after signing up may be enough. For a team that buys several names a year, Pro covers 10 saved reports a month with PDF and CSV export.
Suggesting listing prices on a marketplace through the API
The problem
A marketplace or portfolio platform wants to show sellers a suggested price when they list a name, and buyers a few comparable sales next to it. Building and maintaining a comps engine is a project of its own.
The workflow
Call GET /api/v1/comps?domain=<name> from your server. The response contains comps with relevance, reasons, venue, date and source link, plus the estimate with low, likely and high values, wholesale and retail figures, confidence and rationale. Show the suggested range to the seller, and show a few comps with their venue and source link to the buyer, as the attribution rule requires. Filters for TLD, price, date, tier, style and length let you match your marketplace's audience.
Which plan fits
Broker, the only plan with the REST API, at 5,000 calls a month counted as usage. Details are on the API page.
Which plan for which use case
| Use case | Plan that fits | Why |
|---|---|---|
| Expired auction bids | Pro or Investor | Searches per month, wholesale filter, source links |
| Portfolio buy now prices | Investor or Broker | Bulk lists of 200 or 1,000 names, portfolio view, CSV |
| Inbound offer for a client | Broker | White label PDF, audit log, seats |
| Internal purchase approval | One-time report, then Pro | Cited report as PDF |
| Marketplace price suggestions | Broker | REST API, 5,000 calls a month |
How SoldComparables supports each case
Every use case relies on the same engine: semantic comps instead of keyword matching, a relevance score and reasons for every sale, a range split into wholesale and retail, and a rationale that cites real sales. How it works is set out in the methodology.
Run a search on the domain appraisal tool with a name you are working on, or compare plans on pricing.