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Customer storyHow the voice AI company Futuro grew its traffic3×AI traffic in 60 days

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Data and research

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Open dataWhere AI sends people, across more than 6,000 sites

Compare your share of
AI answers.

Bring your own data. No live model calls. Processed locally.

Calculate shares from answers you already collected. Inspect the comparison set, then choose how much position should count.

Add your answer checks

CSV, TSV or TXT · Up to 5 MB

UTF-8 text. Read locally, never uploaded.

Build a complete comparison

Required: prompt, platform, brand, position.
One row for every prompt × platform × brand.

Position 0 means checked and absent.

Missing rows are not zeros. Add at least two brands. Optional recommended and cited columns must be complete for every row, or omitted.

Runs locally. No live model calls.

Position weights

An optional view of prominence. These weights do not change whether a brand was mentioned.

Choose position weights

Use 0–10 in descending order. First position must be greater than 0. Results update as you edit.

Add data to begin

Your data stays on this device.

Files are read locally. Refresh or reset clears the analysis. Usage analytics record summary metadata, never file names or contents. Only the first 50,000 rows are analysed.

A fair comparison.
Visible math.

Mention share = brand mention units ÷ all tracked brand mention units × 100.

Position-weighted share = brand position score ÷ all brand position scores × 100. Weights affect prominence, not whether a mention happened.

Use the same prompts, models, date, geography and tracked brands. The tool measures only the answers you supply; it does not estimate prompts you did not run or models you did not include.

Position and citations show prominence and evidence. They do not tell you whether the wording was positive, correct or likely to convert.

Read the complete AI share of voice guide for the difference between mention share, citation share, recommendation share and absolute visibility.

Turn one calculation into a trend.

Trakkr runs real buyer prompts across AI platforms, keeps the answer evidence and shows how your position changes against competitors over time.

Monitor real prompts

Before you
use the number.

Mention share divides one brand’s mention units by mention units for every tracked brand. Recommendation share and citation share use their own event totals. The optional position-weighted share scores first, second, third, and later mentions separately, then divides each brand’s score by the combined score.