Lingo marketing

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Lingumarketing describes an approach that applies the findings from corpus linguistics to a corresponding (online) communication situation with specific language data in order to initiate or optimize a possible marketing strategy . These are mostly language data in the form of weakly structured text networks, which are characterized by the variables size, indeterminacy and (thematic) diversity (a variant of Big Data ). This concerns u. a. the channels social media , blog , free text field on homepages or rating / user forum . Lingo marketing can be seen as an interdisciplinary research area in the field of market research , at the interface between linguistics and marketing , similar to neuromarketing .

Assumptions

Lingumarketing assumes that language processing is largely unconscious and that language creates reality , based on the epistemology of constructivism . Language is based on its own laws, which is why it is difficult to measure with conventional, numerically oriented methods and does not fit well into the rational-economic thought structures of the classic marketing mix . Speech data are not unambiguous numbers and therefore cannot simply be converted into such, as they contain additional semantic information ( connotation , contextual knowledge , etc.).

Methods

Lingumarketing uses methods of qualitative-hermeneutic text and discourse analysis (including analysis of semantics , collocation , isotopic or metaphor ) in combination with semi-automated techniques of linguistic text mining , computer linguistic and statistical analysis methods to discover hidden meanings in large amounts of text. These are u. a. Clustering method using the parameters keyword , co-occurrence , topic discovery and tracking , part-of-speech tagging , named-entity recognition or sentiment analysis . The sentiment analysis records assessments and polarities (positive, negative, neutral) of the target groups.

Questions

Lingo marketing is often used for open questions such as: B.

  • How did campaigns or services arrive with target groups?
  • What do target groups think about X or X's services ( image )?
  • What is rated well by target groups and what is rated badly?
  • What are the wishes and problems of the target groups (topic discovery and tracking)?
  • How do X's competitors act?
  • How do X's markets look now / in the future?
  • How do your own employees rate X?

With the methods of lingo marketing, full-text analyzes (online) can provide realistic feedback more quickly and cost-effectively. H. in-depth knowledge and understanding of the target groups are advanced, and in the end performance or image are modified accordingly. For example, not only auto semantics (nouns, verbs and adjectives) provide information about the topic (e.g. delivery reliability or trust ); small (negation) particles and distance markers such as actually, of course, none refer to jointly assumed knowledge, to goals or systems of norms, proximity and distance of the target groups. This information is essential in order to offer marketing that is (linguistically) adapted to the target group's wishes / emotions , e.g. B. react to a negative image or adapt the product portfolio etc.

aims

Lingo marketing makes implicit information explicit; H. utterances or arguments indicating evaluation, and thus new and potentially useful knowledge gained. Target groups such as customers or employees are turned into linguistic idea generators in a knowledge circulation process ( hermeneutic circle ) and performance / image adjustments are made via actual feedback ex post (without simulations in focus groups or questionnaires ). In the end there are new patterns and a better understanding of all communication participants, which is based on a secure data situation. The specific effects of lingo marketing on the performance of companies can be seen in the long term in reduced sales costs, increased efficiency in general correspondence, image improvements, more convincing presentation of products, longer-term customer loyalty and better customer interaction.

Web links

Individual evidence

  1. ↑ R. Reichert: Big Data: Analyzes on the digital change of knowledge, power and economy. Bielefeld: transcript Verlag, 2014. p. 10
  2. ↑ Hans-Georg Häusel: Neuromarketing: Findings from brain research for brand management, advertising and sales. Haufe textbook, 2014.
  3. ^ Siegfried Schmidt: Cognitive autonomy and social orientation. Constructivist remarks on the relationship between cognition, communication, media and culture. Frankfurt am Main: Suhrkamp, ​​1996.
  4. ↑ Christina A. Anders, Markus Hundt, Alexander Lasch: The linguistic appearance of listed companies from the energy and financial services sector - personnel recruitment through language. Trends and tendencies in the linguistic design of career websites (KIMATEK 2010) Kiel 2011: Personal communication Schelenz / promerit.
  5. ^ Simone Burel : Identity positioning of the DAX 30 companies. The linguistic construction of self-images in representational texts. Berlin / Boston, 2015.
  6. ↑ Bianka Trevisan, Eva-Maria Jakobs: Linguistic Text Mining. In: Bernhard Keller, Hans-Werner Klein, Stefan Tuschl (eds.): Future of market research. Development opportunities in times of social media and big data. Heidelberg, 2015. 167-185.
  7. ↑ Manfred Klenner: Sweet trepidation and painful ecstasy: Automatic sentiment analysis in the works of Eduard von Keyserling. In: C. Chiarcos (Ed.): From form to meaning: processing texts automatically. 2009. pp. 91-97.
  8. ↑ Joachim Ballweg: Modal Particle. In: Ludger Hoffmann (Ed.): Handbook of German parts of speech. Berlin, 2009. 547-553.
  9. ↑ Gerlinde Mautner: Language, trade, language trading: On the importance of language in management. In: Jonas F. Puck, Christoph Leitl (ed.): Foreign trade in change. Festschrift for Reinhard Moser's 60th birthday. Heidelberg, 2011. 3–12.