Method and appendix

The figures are based on 351 brands analysed in brandvju as of October 2026, all measured with the same method. The base is not a representative sample of Danish business. The base grows continuously with new analyses, so the figures here are a snapshot. We refer only to aggregated figures and never single out the measurements of named brands. Examples are anonymised: quotations are verbatim, and brand names are left out. Percentages are rounded.

What is measured, and on what basis

ArticlenMeasurementParticular caveat
What Danish business looks like340 (colour), 275 of 348 (typeface)Primary colour, typeface and logo type machine-read from the brands' websitesWebsites that refuse reading are included with reduced certainty or left out
The friendly neighbour with no sense of humour351Archetype and tone on five scales from 1 to 5Machine-identified from the brand's own channels
The word everyone uses297Word search on fifteen terms, Danish and EnglishCounts use, not frequency
Purpose297Purpose, sender and responsibility machine-classified from front page and about-us textsMeasures communication, not whether the purpose is lived
The ten commandments3491,744 values clustered into ten meaning groupsThe groups are our choice and can be tested
Values they do not say out loud351Declared and implicit valuesSample of 20 brands (102 values). The group without declared values is small (33)
Sustainability297The place of sustainability in the communicationMeasures communication, not behaviour or climate footprint
The hero297The main role in the story, tied to verbatim quotationsBrands with very little text are left out
Reflection and self-image331The prism's two facets scored from 0 to 10Clarity in the communication, not customers' feelings
Identity and relationship351Disciplines scored from 0 to 100, mediansMeasures what is visible externally
Employer brand350Employer brand and sub-scoresJob portals and channels behind a login are not included
The half distinctive asset351Strong distinctive assets, buying situations, scale 0 to 10Strong distinctive assets count only assets that are both distinctive and consistently used
The logo is protected351The chain of distinctive assets, scale 0 to 10Imagery is assessed on the material available
Position351Clarity and separation, scale 0 to 10Relationship is co-variation
Friction350 (1,104 points)Friction points sorted into ten typesFixed list of types, can be tested
The average brand351Middle of the field and marked deviationDefined from the field's own spread
The best351 (87 per quartile)Gap between top and bottom quartileStability checked on a thousand subsamples
The anatomy of strength351Co-variation between a discipline and the othersStability checked on a thousand subsamples
C2524 companies against 351The index's overall figuresNever individual companies

AI technology and quality assurance

Texts, values, purpose and customer segment are read and classified by AI technology (language models) from the brands' own publicly available texts and channels. The classifications are spot-checked, and the check is described under "How we measured" in each article. Scores and figures are calculated by the platform, and the graphics are drawn directly from the data. The report's text is edited and approved by the editor, Martin Ove Rasmussen, founder, brandvju. A full overview of the AI technology used is available in brandvju's privacy policy.

Literature

  • David Aaker, Managing Brand Equity (1991).
  • Byron Sharp, How Brands Grow (2010), and Jenni Romaniuk, Building Distinctive Brand Assets (2018), Ehrenberg-Bass Institute.
  • Al Ries and Jack Trout, Positioning: The Battle for Your Mind (1981).
  • Jean-Noël Kapferer, Brand Identity Prism (1992, revised 2008).
  • Tim Ambler and Simon Barrow, The employer brand, Journal of Brand Management (1996).
  • Douglas Holt, How Brands Become Icons (2004), and Jim Stengel, Grow (2011), on values and purpose.
  • Margaret Mark and Carol S. Pearson, The Hero and the Outlaw (2001).
  • Joseph Campbell, The Hero with a Thousand Faces (1949), and Gustav Freytag (1863).
  • Kate Moran, Nielsen Norman Group (2016), tone-of-voice dimensions.
  • Semiotics: Ferdinand de Saussure, Charles Sanders Peirce and Roland Barthes.

Use, copyright and AI technology

Copyright and quotation

© 2026 brandvju. This article from The Brand Field, 2nd half of 2026, is protected by copyright. You are welcome to quote from the article and reproduce individual figures and graphics, provided the source is clearly stated and the quotation does not distort the content. Reproduction of larger parts, adaptation and commercial use require written permission. Enquiries: info@brandvju.com.

Text and data mining

The content may not be used to train or fine-tune AI models without a written agreement. brandvju reserves its rights to text and data mining, cf. Article 4(3) of EU Directive 2019/790 on copyright in the Digital Single Market.

Use of AI technology and the EU AI Act

The analyses are built on brandvju's technology platform, which uses AI technology (language models) to read and classify the brands' own publicly available texts and channels. The classification is spot-checked but may contain errors. Parts of the text have been prepared with the help of AI technology. Content, figures and conclusions have been reviewed and approved by the editor, who holds editorial responsibility. This disclosure is made in line with Article 50 of the EU AI Act. The graphics are drawn directly from data and are not generated by AI technology.

Scope and limits

The content is a basis for decisions and not advice. It describes the brands' visible expression, not the companies' culture or quality, and it does not name the measurements of individual brands. Names and marks mentioned belong to their respective owners, and brandvju has no affiliation with them. Danish law applies.

Responsible editor: Martin Ove Rasmussen, founder, brandvju.

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