The Hunting Spreadsheet You Actually Need

I have seen hunters with 47-column spreadsheets who still bought a penalized domain. I have also seen hunters with a napkin sketch who built a six-figure portfolio. The difference was never the number of columns — it was knowing which signals actually predict whether a domain will perform after purchase.

The bloat usually starts with good intentions. You add a column for Moz DA, then Ahrefs DR, then Majestic TF, then CF, then a ratio of the two, then a note column, then a "gut feeling" column. Before long, the sheet becomes a project in itself. You spend more time maintaining it than actually evaluating domains.

Here is the hard truth: most of those metrics are measuring the same underlying thing, just through different lenses. Stacking them does not give you more signal — it gives you more noise dressed up as diligence.

Start With What a Bad Domain Actually Looks Like

Before deciding what to track, think about what has burned people. A DA 44 domain with zero real editorial backlinks — passed by a bulk checker that filled in demo data. A dropped domain with a clean Ahrefs profile but a Wayback history full of pharma pages from 2019. A "niche relevant" domain whose anchor text is 60% exact-match commercial terms, a footprint left by whoever bought it before you.

Those failures share a pattern: the surface metric looked fine, and nobody checked one layer deeper. Your spreadsheet should be built around catching that one layer, not accumulating more surface metrics.

The Columns That Actually Earn Their Space

Domain — obvious, but include the full string with extension. You will thank yourself at 2 a.m. when you have 80 candidates open in tabs.

Overall Score (0–100) — a single composite number that forces you to commit to a verdict. I run candidates through DomainScope for this; it pulls live backlink data, Wayback history, ICANN registration, organic traffic estimates, and penalty signals into one score with a plain-English rationale. One number, one verdict, no committee meeting required.

Referring Domains (real, not raw) — not total backlinks, not DR. The count of unique linking root domains after obvious spam and network links are stripped. A domain with 800 backlinks from 3 domains is a domain with 3 real endorsements.

Anchor Text Red Flag (Y/N) — a binary flag. If more than 25–30% of anchors are commercial exact-match terms, flag it. You do not need the full breakdown in the spreadsheet; you need the decision gate.

Wayback Category — what was this domain in its past life? Four values cover almost everything: On-niche, Off-niche, Spam/PBN, Parked/Blank. An off-niche domain is not automatically disqualified, but you need to know what you are inheriting.

Age (first registration year) — not the current registration date, which resets with every transfer. The earliest ICANN/RDAP or Wayback record. A domain "registered in 2023" that first appeared in Wayback in 2008 has a decade of history you need to read.

Traffic Estimate — even a rough organic traffic figure from Ahrefs or Semrush tells you whether Google was ever sending real users here. Zero traffic on a supposedly authoritative domain is a question, not an answer.

Price / Source — where you found it and what it costs. Sounds mundane. Becomes essential when you revisit a candidate three weeks later and cannot remember if it was GoDaddy auction, NameJet, or a direct seller who quoted you $800.

Decision — three values: Buy, Watch, Pass. Nothing else. If you cannot put it in one of those three boxes, you have not finished evaluating it.

What Deliberately Left the Sheet

No separate DA, DR, TF, CF columns. If you need those numbers, drill into the source tool. The spreadsheet is for decisions, not for housing raw data from five different platforms.

No "potential" column. I removed mine after realizing it was where wishful thinking lived. If the domain does not score well on the objective columns, no amount of "potential" notes will change the outcome after purchase.

No color-coding systems beyond the three-value Decision column. Color coding feels productive. It is not.

Keeping It Honest Over Time

Add one column you will probably hate: Outcome (90 days). Leave it blank at purchase. Come back in three months and record what actually happened — ranked, flat, tanked, flipped. Over a year, that column becomes more valuable than any SEO metric. It tells you where your own evaluation process is leaking.

Nine columns. That is the whole sheet. If you find yourself adding a tenth, ask what decision it enables that the existing nine do not. If you cannot answer that in one sentence, delete it.

The real test is not whether your spreadsheet is thorough — it is whether it makes you faster and more accurate than you were without it. Run your next ten candidates through it and check your hit rate at 90 days. That number will tell you more about your process than any column ever could.

Read next: The Domainer's Toolkit: Tools, Automation, and Daily Workflow · The Art of Domain Negotiation: First Email to Closed Deal

Want to vet a domain right now? Analyze it free on DomainScope →