Short answer: a replication study for internal linking in finance needs to test whether a more coherent graph reduces orphaning, stale paths and ownership ambiguity on a different set of products, not just whether traffic increases after a change. Proper design defines hypothesis, control, intervention, observation window, stop criteria and confounders before rollout.

Hypothesis

For comparable product families, a linking structure based on page roles, product ownership and user tasks will reduce orphan rate and critical-path failures compared to the existing structure.

External traffic and ranking are secondary outcomes, not primary proof.

What is replication

Don't repeat the exact same URLs. Apply the same logic to a different population, for example another product family or another market, keeping the evaluation criteria.

If the result only occurs in the first set, the tactic may be context dependent.

The experimental unit

Use product family or topic family, not each individual link. A graph is a system intervention.

Stores product IDs, page roles and lifecycle states.

The intervention group

The treatment receives clear ownership, defined routes and contextual links to owner pages. Anchor text must describe the task and the target.

Don't simultaneously introduce massive copy rewrites if you want to isolate graph change.

The control group

The control retains the current structure, but receives the necessary factual fixes. Don't keep links to wrong pages just for the purity of the experiment.

Marks contamination when a product lifecycle event occurs.

The baseline

Saves orphan rate, stale-link rate, path completeness, incoming contextual links, canonical state and redirect chains.

For each metric keep numerator and denominator.

Primary outcome 1: orphan rate

Eligible pages without incoming contextual links from the total of eligible pages.

Exclude utility pages intentionally isolated.

Primary outcome 2: critical-path completeness

Define task paths such as concept -> product -> fees',product -> eligibility' and `support -> policy'.

It measures how many can be completed without a dead end.

Count links to retired, wrong-market, outdated or semantically wrong targets.

A technically valid 200/301 redirect can also be a weak target.

Primary outcome 4: owner consistency

For material claims, check if contextual links converge to the appropriate source owner.

This is important in finance, where fees, eligibility and disclosures can have different owners.

Secondary outcome: crawl observations

You can track crawl frequency or indexed coverage within the limits of available tools, but don't turn this into evidence of `topical authority'.

Graph quality must be demonstrated internally.

Observation window

Use at least one full release cycle and a period that includes actual product updates. A week without lifecycle events can overestimate stability.

Keep the period identical for treatment and control.

Stop criteria

Stop if:

  1. links sent to the wrong product owner;
  2. disclosures are becoming harder to find;
  3. redirect chains grow materially;
  4. the rollout produces duplicate links with no value;
  5. a rebrand changes the majority of the population;
  6. the control receives the same intervention;
  7. technical incident contaminates both cohorts.

Confounder 1: product repricing

Pricing updates can trigger many link changes and different traffic. Notes events and excludes naive interpretations.

Keep effective dates.

Confounder 2: campaign traffic

A campaign can increase visits for treatment families. External traffic can no longer be attributed only to the graph.

Use internal outcomes as primary evidence.

Confounder 3: content rewrite

If treatment pages also receive new copy, separating the effects becomes difficult.

Document change scope and if possible keep copy stable.

Confounder 4: product retirement

A retired product may lose links on purpose. Without lifecycle state, the orphan rate may appear to degrade or improve artificially.

Segment active and retired.

How do you compare the results

Report delta in raw counts and rates for treatment and control. Don't stop at `-20% orphaning' without population.

For small samples, show each experimental unit.

Positive replication

If the same logic reduces orphaning and path failures in two different populations, you have better operational evidence that the tactic is robust.

It does not automatically extrapolate to the ranking.

Null replication

If the second population does not change, check if the baseline was already good or if the page roles are different.

The null result may indicate the limit of applicability.

Negative replication

If links increase, but task completion decreases or users reach the wrong owner, the intervention must be reviewed.

More links does not mean better graph.

Maturity criterion

The tactic is robust enough for wider rollout when primary outcomes improve in replication, stop criteria are not triggered and maintenance cost remains acceptable.

Keep regression checks after rollout.

Acceptance criteria

The study is valid when:

  1. the hypothesis is predefined;
  2. intervention and control are comparable;
  3. the baseline has a numerator and a denominator;
  4. page roles are versioned;
  5. observation window is fixed;
  6. stop criteria are applicable;
  7. confounders are logged;
  8. external outcomes are secondary;
  9. replication uses a different population;
  10. the verdict can be `not replicated'.

Claim ledger

  • FACT/EVIDENCE: Google recommends crawlable links and descriptive anchor text in Search Central.
  • FACT/EVIDENCE: Search Essentials does not define a universal topical authority score.
  • PRACTITIONER GUIDANCE: financial linking experiments must include lifecycle, disclosures and source ownership.
  • INFERENCE: replication on different populations can increase confidence that a graph intervention is robust.
  • NOT PROVEN: that internal linking produces direct ranking, revenue or AI citations.

Conclusion

A replication study for internal linking in finance must demonstrate that the same logic works in more than one context. Orphaning, critical paths, stale links and owner consistency are auditable outcomes. External traffic can be tracked, but the main value of replication is that it separates a robust tactic from an accidental result in a single cluster.

Sources reviewed

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