Publish an original data asset: AEO Academy

What you will leave with

A transparent first-party benchmark with at least one finding competitors cannot claim.

You do not need 10,000 survey responses. You need a question, a reproducible method, honest limitations and a finding useful enough that another author would prefer citing you over repeating an opinion.

Example: support-ticket benchmark

QuestionWhy do WooCommerce stores lose AI-attributed orders?

Sample214 support tickets, Jan–Jun 2026

InclusionConfirmed AI referral plus missing conversion link

Finding42% lost attribution after cross-domain checkout

LimitationCustomers of one WordPress plugin; not all stores

Turn the study into a source page

Lead with the finding
State the number, sample and period together.
Show the method
Explain collection, exclusions and how categories were coded.
Use native HTML
Put results in a table and text. A chart can support the data but must not be the only place it exists.
Expose limitations
Trust increases when readers can see where the finding should not be generalized.
Offer reuse
Provide a downloadable CSV, chart embed or citation line.

Example ticket causes

Cross-domain checkout42%

Referral stripped27%

Consent mismatch18%

Other13%

If you have no customer dataset

Run a teardownScore 50 public category pages with a disclosed rubric.

Interview expertsAsk the same five questions and publish areas of agreement and disagreement.

Run a controlled testChange one page element and track crawl/citation results over a fixed period.

Do the work

Field assignment

Scenario

You have no proprietary “big data,” but you do have 200 customer support tickets and 40 sales calls.

Choose one question the records can answer consistently.
Define inclusion rules and code the observations into categories.
Publish the method, sample, limitations, table and downloadable data.

Definition of done

A transparent first-party benchmark with at least one finding competitors cannot claim.