Every opportunity scored, with the reasoning attached
A list of a thousand prospects is not a strategy. Sightivo scores each opportunity, tells you the action to take, and shows you why it ranked where it did.
What is link opportunity scoring?
Link opportunity scoring is the practice of ranking potential backlink targets by their likely value before you spend any outreach effort on them. Rather than treating a prospect list as a queue to work top to bottom, scoring assigns each opportunity a number based on how relevant the source is to your category, how much authority it carries, and how realistically you can earn a place on it.
The reason it matters is that link building effort is roughly constant per prospect while link value is not. Researching a contact, writing a personalised email and following up costs about the same whether the placement turns out to be worthless or category-defining. Scoring is how you spend a fixed budget of attention on the opportunities that actually move the needle.
Sightivo scores on relevance, authority and — distinctly — whether the source is one that AI assistants already cite when answering questions in your category. A high-authority page that no assistant ever reads scores lower than a mid-authority page that ChatGPT pulls from every time. Each score comes with the reasons behind it and the specific action to take.
What goes into a score
Three signals, weighted for what you are actually trying to win.
Topical relevance
A mention on a site that covers your category is worth more than a higher-authority mention somewhere unrelated. Sightivo weights how closely the source’s subject matter sits to yours.
Authority and reach
Domain-level strength still matters for Google. Sightivo factors it in without letting it dominate — authority alone is what produces prospect lists nobody can act on.
AI citation likelihood
Some sources get pulled into ChatGPT and Claude answers constantly; most never do. Sightivo weights the ones assistants already cite in your category, because that is where a mention compounds.
The action to take
A score without a next step is trivia. Every opportunity names what to actually do — pitch a guest post, submit a listing, reply to a roundup, ask for an inclusion in an existing article.
Sorting by DA vs. scoring an opportunity
Why the standard approach produces lists nobody works through.
| Sorting an export by DA | Sightivo opportunity scoring | |
|---|---|---|
| What gets ranked highest | The biggest sites, regardless of fit | The most relevant sites you can realistically earn |
| Relevance | Judged by hand, prospect by prospect | Scored automatically against your category |
| AI answer impact | Not considered at all | Weighted by whether assistants already cite the source |
| Next step | You work it out yourself | Named on the opportunity — pitch, submit, or request inclusion |
| Why this one | Opaque | Reasoning shown on every score |
Frequently asked questions
How should you decide which backlinks are worth pursuing?
Weigh three things: how topically relevant the source is to your category, how much authority it carries, and how likely you are to actually earn the placement. Relevance should outrank raw authority — a mention on a site covering your exact subject typically does more for both rankings and AI citation than a stronger link from an unrelated site. Sightivo scores all three and shows its reasoning on each opportunity.
What does the opportunity score out of 100 mean?
It is a relative priority signal, not an absolute quality grade. A 98 means this is among the best opportunities available to you right now given your category, your current backlink profile and what AI assistants are citing. The same source could score differently for a different company, which is the point — the score is about fit, not about the site in isolation.
Is domain authority still a useful metric?
It is useful but badly overweighted in most workflows. DA is a third-party estimate of ranking strength, not a Google metric, and it says nothing about topical fit or whether an AI assistant will ever read the page. It belongs in a scoring model as one input among several rather than as the sort order.
Why does AI citation likelihood affect the score?
Because a growing share of buying research now happens inside an assistant rather than on a results page. A mention on a source that ChatGPT and Claude repeatedly cite in your category keeps paying out every time someone asks a relevant question, while a mention on a page no assistant reads only ever works through traditional search.
Last updated August 3, 2026