The short answer
How do you measure cybersecurity link building success?
Measure each batch of placements as a cohort: how many are still live, indexed and relevant at 90, 180 and 365 days, and what you paid per link that survived. Counting links hides the losses. Ahrefs (2022) found that at least 66.5% of links to a sample of 2,062,173 sites had rotted since January 2013, so the number that matters is durable links, not links placed. Rankings, referral traffic and pipeline then tell you whether the durable links did anything.
What is link building success in security?
A successful placement meets six conditions: it sits in editorial context on a page that covers your subject, the publisher is clean, the page is live and indexed, the link points to the right URL, real technical readers can reach it, and it supports a target page you have chosen. The first two are checked before you buy (see how to qualify a publisher). The rest are measured afterwards, and that is what this article covers.
What should you measure, and in what order?
| Layer | Metric | Question it answers | When to check |
|---|---|---|---|
| 1. Placement | Live, indexed, link intact, correct target URL | Did we get what we paid for? | At placement, then 90, 180 and 365 days |
| 2. Quality | Topical fit (five layers), publisher indexation and organic visibility, anchor and position | Is it a link an editor and a buyer would respect? | Before purchase, audited quarterly |
| 3. Profile | Net new referring domains, lost referring domains, link velocity, anchor distribution | Does the whole profile look like steady editorial growth? | Monthly |
| 4. Search | Rankings, impressions and clicks for each target page | Did the target page move? | Weekly rankings, monthly review |
| 5. Business | Qualified referral visits, demo requests, trials, pipeline touched | Did it matter commercially? | Monthly, with a longer lag |
Work from layer 1 upwards. A ranking gain on a page whose links are rotting is a borrowed result.
How do you measure durability by cohort?
A cohort is the set of placements acquired in one period, say one quarter. For each cohort, record at 90, 180 and 365 days how many placements are still live, how many of those pages are indexed and how many still link to the right URL.
Formulas.
- Live rate at checkpoint = placements live / placements acquired.
- Durable link yield = placements live, indexed and correctly linking at 365 days / placements acquired.
- Cost per durable link = total cohort spend / placements live, indexed and correctly linking at 365 days.
Worked example. Illustrative numbers, not benchmarks. A cohort of 20 placements cost $10,000. At 365 days, 15 are live, and 14 of those are indexed and linking correctly. Durable link yield is 14 / 20 = 70%. Cost per placement was $500, and cost per durable link is $10,000 / 14 = $714.
Link cohort scorecard
Enter one cohort of placements. The defaults are the illustrative example in the article. No external benchmark is applied.
- Live rate at 90 days
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- Live rate at 180 days
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- Live rate at 365 days
- -
- Durable link yield
- -
- Cost per placement
- -
- Cost per durable link
- -
Text version of the scorecard. Enter the cohort size, total spend, and how many placements are live at 90, 180 and 365 days, plus how many of the 365-day survivors are indexed and linking correctly. The scorecard returns the live rate at each checkpoint, the durable link yield, cost per placement and cost per durable link. It applies no external benchmark.
What the external data does and does not tell you. Ahrefs’ link rot study (2022) counted 66.5% of links to its sample as rotted and 74.5% as lost for SEO purposes. Of the lost links, 47.7% sat on pages Ahrefs dropped from its index and 34.2% sat on live pages that no longer linked.
The sample is links to random sites over about nine years, so it shows that decay is the default. It does not give you a target rate for purchased editorial links, and nobody publishes one. Claim strength: measured by Ahrefs, 2022, updated 2024.
What we see in our own tracking. Placements we track tend to stay live beyond 365 days, which is not common across the market. That is an internal observation, not a benchmark, and we publish no figures for it. Claim strength: observed, qualitative only.
How do you judge a single placement?
Use DR as a floor and read the page. DR is a filter: a high-DR site with declining traffic or off-topic content adds little. Check these on the specific page:
- Indexed and visible. The URL appears in search and ranks for something.
- On topic. It covers your threat, technology, sector, framework or role. Our relevance triage scores this.
- Editorial context. The link sits inside body text, not in an author bio, sidebar or footer.
- Anchor fit. Branded, URL and descriptive anchors dominate. Repeated exact-match commercial anchors create a footprint.
- Link attributes. Check whether the link is followed, nofollow, sponsored or UGC. A sponsored placement should carry rel=“sponsored” or rel=“nofollow”, which Google’s spam policies (2026b) allow.
A natural profile has a mix of attributes. Do not chase a followed-link ratio.
How do you connect links to results?
- Assign every link a target page before outreach, and record the page’s baseline rankings, impressions and organic visits.
- Tag referral links with UTM parameters where the publisher allows it, and watch engagement, movement to product pages and conversion events in GA4.
- Read Google Search Console for impressions and clicks on the target page after each cohort goes live.
- Keep the timeframe honest. Links affect search over weeks and months, and rankings also depend on content, intent match and site health. We do not publish a typical delay because we found no reliable benchmark. Set review dates and judge by leading indicators: indexation, referring-domain growth and impressions.
In B2B security, audience fit matters more than visit volume. Ten visits from CISOs who read the page to the end beat a hundred from readers who bounce.
What about AI answer engines?
Include mentions, not just links. Ahrefs’ December 2025 study of 75,000 brands (Linehan, 2025b) found that branded web mentions (0.656 to 0.709) and YouTube mentions (about 0.737) correlated with AI brand mentions far more strongly than link metrics, which Ahrefs calls very weak. This is correlation, not cause. The measurement implication is simple: log where your brand is named in publications and videos even when no link exists, and review it next to the link report.
How do you handle harmful links?
Run a quarterly audit for lost links, broken redirects and low-quality domains pointing at you. If an unwanted link can be removed, ask the site owner to remove it (how link removal requests work). Disavowing is a last resort for a clear pattern of manipulative links you cannot get removed. We give no step-by-step instruction here, and you should read Google’s current disavow guidance before acting. Claim strength: opinion.
Key takeaways
- Judge a campaign by **durable link yield**: placements still live and indexed at 365 days, divided by placements acquired.
- Track **cost per durable link**, not cost per placement. A cheap link that disappears in four months is the most expensive one you bought.
- Ahrefs' rot figure comes from a random sample of sites over nine years. It is not a benchmark for your cohort, so compare each cohort with your own previous ones.
- Domain rating (DR) is a screening filter. Page-level indexation, topical fit and the context of the link say more about one placement.
- For commercial results, connect each link to a target page, and watch that page's rankings, qualified visits and conversions.
- Nobody can promise a ranking or a timeline. Report what you measured and label what you inferred.
References
- Ahrefs (2022) 'At least 66.5% of links to sites in the last 9 years are dead', Ahrefs Blog, 29 April (updated 2 February 2024). Available at: https://ahrefs.com/blog/link-rot-study/ (Accessed: 20 October 2026).
- Google (2026b) 'Spam policies for Google web search', Google Search Central, last updated 28 August. Available at: https://developers.google.com/search/docs/essentials/spam-policies (Accessed: 20 October 2026).
- Linehan, L. (2025b) 'Top brand visibility factors in ChatGPT, AI Mode, and AI Overviews (75k brands studied)', Ahrefs Blog, 12 December (updated 12 August 2026). Available at: https://ahrefs.com/blog/ai-brand-visibility-correlations/ (Accessed: 22 October 2026).
