Relevant local experience
Sales of homes like yours — same neighborhood or micro-market, same property type, same price band — over the last 12–24 months. A great agent two price bands away is still the wrong agent.
Methodology
The Agent Match Scorecard
We publish exactly how agents are compared. Use it with us, or take it into your own interviews — the point is that the decision gets made on evidence.
The six dimensions
Pricing outcomes, in context
Sale-to-list ratio and days on market, read with judgment: over-asking results can come from systematic underpricing, and a fast sale can be the market, not the agent. Raw statistics never stand alone in our reports.
What the fee actually includes
Staging, photography, video, floor plans, open houses, digital advertising, print — itemized per candidate, so a 3% proposal and a 2.5% proposal can be compared on substance instead of headline rate.
Team structure and access
Who does the work after the listing agreement is signed — the agent you interviewed, a partner, or a junior team member. Big-name teams often hand referred clients down; we ask directly and verify with references.
Communication and fit
Cadence, channel, and style — an aggressive negotiator who texts at 10pm suits some sellers and exhausts others. Fit is subjective, so we report what we observed and let you weigh it.
Reputation and references
Online reviews across platforms, plus direct reference calls with recent sellers. We look for patterns, not star averages — and we flag anything that would make us hesitate.
What a comparison looks like
An illustrative excerpt — fictional agents, the real format. Numbers are always paired with interpretation, and no candidate is reduced to a single ranking score.
| Metric | Agent A | Agent B | Agent C |
|---|---|---|---|
| Similar homes sold nearby, 12 mo | 2 | 8 | 3 |
| Avg sale-to-list | 99.5% | 100.8% | 101.2% |
| Median days on market | 15 | 12 | 20 |
| Listing fee, as proposed | 3.0% incl. partial staging | 3.5% full service | 3.0% basic package |
| Staging | 2 rooms included | Whole home included | Seller pays |
| Who you'd work with | Solo agent | Principal + partner | Solo, no admin |
| Communication | Weekly calls | Bi-weekly text/email | Email only |
The written read matters more than the grid. In this example, Agent B has the most relevant nearby sales and the deepest prep package; her fee runs 0.5% higher, which on a $1.6M sale is roughly $8,000 — a real cost, weighed against whole-home staging and broader marketing that can return more at sale. Agent C's over-asking average partly reflects lower list prices. That interpretation — not a single score — is what you decide from.
How the candidate pool is built — and why visibility isn't fit
Before any scorecard runs, candidates have to come from somewhere. We source from transaction evidence, brokerage networks, professional referrals, public reputation, independent research — and, deliberately, from what AI systems and search engines recommend, treated as one more signal to investigate rather than an answer to repeat. Recommendation engines reward the agents with the strongest digital footprint: better websites, more citations, richer machine-readable evidence. That correlates with quality sometimes, and only sometimes — the most visible agent isn't always the best-fit agent, and an exceptional specialist can be nearly invisible to the exact query they're best qualified for.
So we investigate in both directions: the agents algorithms surface get verified rather than assumed, and the field is checked for qualified agents the algorithms missed — transaction concentration in the actual micro-market, demonstrable experience with your specific situation, independent corroboration beyond the agent's own marketing. Every claim in a report is distinguished by its source: verified against records, independently reported, or self-reported by the agent. The full argument: can an algorithm choose the right Realtor?
Where the method comes from
Before residential real estate, Jens spent years in the energy industry helping clients evaluate competing solar contractors through normalized RFP processes — the same discipline applied here: multiple qualified vendors, identical criteria, fees restated against actual scope, strengths and weaknesses in writing, and a recommendation the client could interrogate. Agent selection isn't a new problem; it's a vendor-selection problem that real estate has escaped by habit. This scorecard is that habit, corrected.
Assignment addenda. Some purchases add dimensions the core six don't cover. The first published addendum: the Lot / Spec / Rebuild Addendum — eight additional criteria for vacant land, fire-rebuild parcels, specs, and builder contracts.
Why the fee can't pick the agent
Every candidate we present operates under the same standard referral arrangement — fixed in writing before candidates are chosen, identical across the field. A matching service whose recommendations track its economics isn't an advisor; it's a directory with better fonts. Holding the fee uniform removes the incentive to steer, and on the flat-fee Evaluation Report we're paid the same no matter whom you choose.
And to answer the question skeptics rightly ask: the referral fee is paid out of the hired agent's side of the commission — it is not added to yours. You negotiate your rate directly with the agent you hire, exactly as you would if you'd found them yourself. Referral fees are a standard client-acquisition cost agents already carry, which is why experienced agents accept them without repricing the client. If the strongest agent for your home won't work on referral terms, we tell you that too — you can hire them directly, and the comparison is still yours.
Let's talk.
Straight answers, no pressure, no obligation. You'll hear back within one business day.