Does Building Backlinks to One Page Boost Others?
Does Building Backlinks to One Page Boost Others?
One of the biggest unanswered questions in off-page SEO is whether building backlinks to one page can boost SERP rankings to other pages on the same site. The idea has been floating around since the early 2000s, way before John Mueller aired out “link juice” like Jay-Z did to Nas.
At Citation Labs, we call this idea Impact Radius, and we’ve been studying it for some months now.
Essentially, our thought here is that a rising tide lifts all boats and some of that sweet page rank will naturally flow from one page on a domain to others as links are built.
What does that mean?
If links to one page on a domain affect another, it could change how we build links and structure our campaigns.
For example…
- We could direct backlinks to “hub” pages to benefit “spoke” pages for clients who structure their content that way, effectively multiplying efforts in a single campaign.
- We could also use an impact radius metric to forecast ROI more accurately, even for pages we don’t directly build links to.
- It could also give SEO stakeholders an opportunity to take credit for something we’ve all thought was happening, but never had solid data on. That means more feathers in your proverbial cap.
Our Study
So, how can we study this phenomenon? As with assessing impact in any SEO campaign, there are so many moving parts. So, we had to get tactical. Our first idea was that any boost that was passed from page-to-page could be related to internal links.
With that, we set up a data study with help from the data of our biggest clients:
Hypothesis
Pages on a domain that are internally linked to a backlink target URL will see improved keyword rankings compared to pages with no internal link to that target.
Methodology
Study Design
We studied three major clients from January 2024 to August 2024. We built backlinks to target pages (or “campaign pages”) for each client, then tracked how these backlinks affected their other pages. We divided pages into three groups:
- Campaign Pages (40 total) – These pages received backlinks.
- Internally Linked Pages (341 total) – These pages were linked to from campaign pages.
- Unlinked Pages (293 total) – These pages were topically-relevant, but had no links from the campaign pages.
Data Collection
We used SEMRush to pull all ranking keywords for every page in our dataset. We then calculated an “average position” for each page based on all the keywords it ranked for. We repeated this monthly to capture changes over time. At the end of the eight-month window, we compared the average positions for Month 1 and Month 8.
Internal Linking Identification
We ran a Screaming Frog crawl on each client’s domain. That crawl told us which pages were linking to the campaign pages. Site structures differed across the three companies, so the internal linking setup was unique to each domain.
Analysis
We grouped pages based on their internal linking status. We compared the change in average keyword positions from Month 1 to Month 8. We considered any upward movement in ranking as an improvement. We did not exclude any pages or filter out possible confounding factors like domain authority or content type. We also did not account for seasonality, competitor campaigns, or on-page changes that clients might have made.
Limitations and Confidentiality
We kept client identities private. The dataset was modest, so further studies are needed for stronger statistical significance. We plan deeper segmentation, including vector embedding, to analyze anchor text relevance. While external SEO events (e.g., competitor campaigns, algorithm updates) may have influenced results, we did not control for them in this phase of our study.

Key Findings
Client domain pages that were internally linked to from the target page saw an increase in average page rank than pages that weren’t linked. One client even saw ranking boosts for linked pages of up to 33% versus unlinked pages.
This early data is promising. It suggests there’s something to this Impact Radius, and we’re going to keep at it to find out more.

Bringing in Vectors
With AI and large language models driving many of the SEO conversations these days, we also wanted to understand if topical relevance had anything to do with the impact radius phenomenon.
To study that, we used a slightly-altered version of Everett Sizemore’s visionary workflow to identify internal linking opportunities with Screaming Frog and ChatGPT’s vector embedding API to understand if topical relation (identified through vector analysis) was the conduit for impact radius, instead of internal links.
While there are likely confounding variables to explore and we are in the process of expanding our initial dataset, we have not yet noted a lift in rankings due exclusively to semantic overlap. This is something we will continue to explore.

Next Steps
First off, we want to build a bigger dataset and statistical significance. We also plan to explore questions like:
- Does link placement matter for impact radius? Is a nav link enough to pass that boost?
- How important is anchor text relevance for passing juice internally?
- Does anchor text relevance matter for impact radius? How can we implement vector embedding to assess this?
There’s a lot more to discover here, for sure. We look forward to sharing more soon.
In the meantime, it may be worth testing this on your own domains. If you find anything interesting, tag us on LinkedIn!