Northline ResearchAlso Northline Labs

AI visibility research

What shows up when someone asks an AI.

Northline Research studies how brands are named, cited, and recommended in answer engines. We publish methods first, then findings.


Focus

What we research

01

Citation selection

How answer engines attach sources, and how that differs from simply naming a brand in the prose.

02

Share of voice

How to count mention, citation, and recommendation as separate events inside a defined prompt panel.

03

Prompt design

How a question set becomes a sample frame, and how branded prompts distort an audit if they are mixed in.

04

Platform change

How to observe Google AI Overviews and chat engines without treating every interface shift as a new law.

Method

Research approach

Services and methodology

Frame

Write the question before the prompt

Every study starts with a user job: learn, compare, select, verify, or operate. Prompts come second. If we cannot state the job, we do not collect yet.

Sample

Build a panel you can run again

We version prompt panels, separate branded from unbranded items, and keep the list small enough to repeat. Novelty is not a design goal.

Code

Score events, not vibes

Mentions, citations, and recommendations are coded on separate fields with a written codebook. Disagreement between readers is recorded.

Limit

Report what the method cannot say

We do not convert answer text into traffic or revenue. We do not blend engines into one pie. If a claim needs a number we did not collect, it stays out.


Contact

Briefings, studies, and methods questions

If you want a competitive landscape study, a visibility benchmark, a prompt panel, or a vendor evaluation, write to us. There is no form.