‹ BlogMethod · 12 Oct 2026 · 5 min read

Named, named first, linked: the states we track, and why not one score

One answer from one assistant can go six ways for your brand. Teddit draws each of them as a square instead of folding them into a number, and this is how to read the squares.

The Teddit teamWe build Teddit and run it on our own sites
The prompts list with a square per assistant per week

Three facts about every answer

When an assistant answers a buyer’s question, three separate things can happen to your brand.

  • Named. Your brand appears in the text of the answer.
  • Named first. Of the brands the answer names, counting you and the competitors you track, yours comes first.
  • Linked. The answer links to a page on your site, as a cited source or as a URL in the text.

These do not move together. An assistant can recommend you and send the reader to a review site. It can also quote your guide as a source and recommend somebody else. So Teddit records each fact on its own for every answer it stores, and the square you see is the combination.

The six states of a square

One square is one assistant’s answer to one prompt in one week. It is always in one of six states.

StateWhat the answer did
Named first + linkedNamed you before any competitor you track, and linked to your site.
Named + linkedNamed you, though not first, and linked to your site.
Named or linkedOne without the other: your name with no link to you, or a link to your page in an answer that never names you.
Not namedNeither named nor linked you, and named none of your tracked competitors either.
Competitors onlyNeither named nor linked you, but named at least one competitor you track.
Not scannedThere is no answer yet: the assistant has not answered this prompt, or its latest attempt failed.

Not named and competitors only look alike from your side, since you are absent in both. They are different problems. In the first, the assistant answered without bringing up any brand you track, which often happens with how-to questions. In the second, it did recommend brands in your space and left you out.

Not scanned is not a zero. A missing answer says nothing about your visibility, so it stays out of every rate Teddit calculates.

“Competitors only” depends on the competitors you have added. If an answer names a rival you do not track yet, the square reads “not named”. Keep the competitor list current and the squares stay honest.

Why the list shows states and not one blended score

It is tempting to turn all of this into a single number and watch it go up. We lead with the squares for three reasons.

A blended score hides a choice. To blend, someone has to decide how much a link is worth next to a mention, and how much first place is worth next to third. Those weights are opinions. Once they are inside a number, you can no longer see them or disagree with them.

A blended score hides what moved. Say a score falls from 62 to 58. You may have lost a link on one assistant. You may have slipped from first to third on several. You may have vanished from one prompt altogether. Those are three different jobs, and the number does not say which one you have.

An average hides the prompt that matters. A brand can look steady overall while its most valuable buying question flips to competitors only. In a grid that flip is a change of colour in a known place. In an average it is a rounding error.

A state is also something you can check. Open a prompt and each square leads to the answer behind it, so you can read the text and see why it was classed that way.

Reading a row and reading a column

In the prompts list each prompt carries its own small grid: one line per assistant, one square per week, oldest on the left. The last square, set slightly apart, is the latest answer.

Along a row: one assistant over time

Look for runs, not single squares. One answer is one draw, and assistants do not answer the same way every time. A single odd square inside a steady run is usually noise. A run that changes and stays changed is a finding. We wrote about why in Why the same question gets different answers.

Down a column: one week across assistants

If every assistant changes in the same week, look for a cause they share: a page of yours that changed, a new article about your category, or an edit to the prompt itself. If only one assistant changes, the cause is more likely on its side, in its model or in what its web search returned that week.

Say Brightloop, a made-up email marketing platform, tracks the prompt “Which email marketing platform is best for a small online shop?”. For six weeks one assistant’s row reads named + linked. Then it reads competitors only for three weeks, while the other rows stay as they were. One assistant, one prompt, and a change that held. Open the first square after the change and read the answer. If it now names Mailora and Quillsend and cites a comparison article that does not list Brightloop, you know where to look next.

What share of voice and tone of voice add

The squares do not say how crowded the answers are, or what was said about you. Two more measures cover that.

Share of voice

Share of voice is your mentions as a share of all brand mentions, yours plus those of the competitors you track. A brand counts once per answer, however often the answer repeats it.

An illustration: say ten answers come back. Brightloop is named in six of them, Mailora in eight, Quillsend in four and Pulsepost in two. That is twenty brand mentions, six of them yours, so your share of voice is 30%. You are present in 60% of the answers and hold 30% of the voice. The first number says you are usually in the answer. The second says you are usually sharing it.

Tone of voice

For each answer that names you, Teddit records how your brand is described: positive, neutral, mixed or negative. The judgement is about your brand, not about the mood of the whole answer. An answer can name Brightloop first and then warn that it gets expensive as a list grows. The square shows the best state. The tone says mixed.

Tone is judged by an AI model, so treat it as a pointer to the answers worth opening, not as a measurement to trust to the last digit.

The exact definitions are in Metrics and statuses.