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What is phrasing - An explorative approach to improved user manipulation

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As part of the content development of digital contact points such as websites, blogs and social media hubs, content is developed, prepared and published exclusively from the internal perspective of the companies. Ideally, in close cooperation with different departments, content development focuses on identified keywords and factual insights. Companies try, if at all, to put themselves in the position of the user in order to increase the demand for the corresponding content. As a result, it can be stated that companies see what they want to see.

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What is phrasing - An explorative approach to improved user manipulation

  1. 1. © BSI – We grow businesses AN EXPLORATIVE APPROACH TO IMPROVED USER MANIPULATION WHAT IS PHRASING? Brand Science Institute, January 2019
  2. 2. AGENDA © BSI – We grow businesses 2019 | Seite: 2 Core Issue Procedure Model Phrasing
  3. 3. © BSI – We grow businesses 2017 | Seite: 3 “IT AIN’T WHAT YOU KNOW THAT GETS YOU INTO TROUBLE. IT’S WHAT YOU KNOW FOR SURE THAT JUST AIN’T SO.” Mark Twain
  4. 4. SEARCH FOR RELEVANCE IN THE LONG-TAIL Short Head:  General Keywords  High search volume  High competition  Low conversion rate Long-Tail:  Specific keywords (chains)  Low search volume  Low competition  Higher conversion rate © BSI – We grow businesses 2019 | Seite: 4
  5. 5.  On the basis of identified keywords and logical findings, chains of words are formed and it is thought that the user can put himself in a position to do so. We see what we want to see...  The learned procedure is therefore highly inefficient and leads to numerous problems:  We don't know which question the user really asks us.  We don't know what his (deep psychological) motive is.  We do not know which structures arise from millions of questions per year.  We don't know which topics from the user's questions are really relevant.  We do not know how the questions and topic areas are connected. Depth psychological and structural drivers from search behavior PROBLEM WE DO NOT CREATE SUSTAINABLE RELEVANCE © BSI – We grow businesses 2019 | Seite: 5
  6. 6. MODEL PHRASING 1 - EXPLORATORY DATA CUSTOMER 2 - ITERATIVE KEYWORD TEST 3 - TESTING KEYWORDS QS 4 - SCRAPING PHRASES Structuring of screening contents of the customer Iterative testing of keywords mediumKeyword Search Tools & Testing for stable synonyms Explorative Testing aller Keywords in Search Suggest Methods Google Identification of dominant phrases in relevant markets (Scraping) Clustering relevant topic areas Extraction of related keywords / synonyms Primary test of granular questionnaire components and their composition Test for stability of extracted questions using Search Suggest Scraper Extraction keywords & preparation for analysis Derivation of first relevant question modules Drilling Question building on Keyletters questions Summary & evaluation of the most relevant questions 5 - QUANTITATIVE PATTERN 6 - QUALITATIVE MOTIVE 7 – RELEVANT QUESTIONS Identification of structures (patterns) in extracted questions Analysis of question structure data on underlying motives Clustering Topics Phrases Evaluation of structures (Patern)& expressiveness for content building alternatives Identification of basic emotional states and dominant motives Descriptive presentation of relevant issues Explanation of Pattern Analysis Plot to clarify relevant question structures Comparison & evaluation of motifs in intra brand competition Derivation of recommendations from phrasing for motif users, content creation, etc.. 8 – VERIFIZIERUNG STRUCTURE Checking structures with the help of semantic networks Checking the validity of identified clusters and topic areas Identification of relationships between topic areas and clusters © BSI – We grow businesses 2019 | Seite: 6
  7. 7. RESULT TYPE I MOST RELEVANT QUESTIONS  welches xxx bei  welches xxx für  welches xxx bei  welches xxx hat am meisten  welches xxx bei  welches xxx schmeckt  welches xxx hat am meisten  welches xxx hat viel  welches xxx für  welches xxx ist gut bei  welches xxx hat viel  welches xxx für  welches xxx ist gut  wo kommt unser xxx her  wo kommt xxx vor  xxx wo kommt es her  das gesündeste xxx der  das beste xxx für  das richtige xxx  das beste xxx still  das beste xxx ohne  das beste xxx medium  das teuerste xxx  das gesündeste xxx  das beste xxx  das xxx der  das xxx mit den meisten  welches xxx für  welche xxx haben viel  welche xxx sind unbedenklich  welche xxx sind basisch  welche xxx wurden getestet  welche xxx sind nicht verunreinigt  welche xxx gehören zu  welche xxx gibt es in  welche xxx haben viel  welche xxx sind verunreinigt  welche xxx sind für geeignet  welche xxx sind natriumarm  welche xxx enthalten  welche xxx für  welche xxx sind für geeignet 7. xxx 7.4 xxx bei 7.1 xxx ohne 7.2 xxx mit 7.3 xxx für 7.5 xxx gegen 7.6 Mixed © BSI – We grow businesses 2019 | Seite: 7
  8. 8. ERGEBNISTYP II ABLEITUNG PSYCHOLOGISCHER MOTIVE Within the sections, different types of questions and techniques were used: 1. General Associations 2. Query of positive and negative associations 3. Selective control of questions and matching Question clustering after multiple iterations Analytical techniques Psychology – Meaning of Words Analysis of the emotional significance and underlying motives through the creation of emotional perceptual spaces and the derivation of meaningfulness: 1. Analysis of the questions on the basis of individual words and breakdown of word frequencies along different language dimensions 2. Derivation of multidimensional motif structures of over 8 million content components and spaces of meaning 3. External validation of analysis results by sampling and experimental comparisons  Which question clusters arise in general?  How large are the clusters in terms of volume and degree of differentiation?  Which patterns can be identified from the questions asked?  How can initial motives be derived from mere manual classification?  How are the questions related to each other and how large is the intercorrelation between the questions?  … WC Sixltr Dic Negate Assent Affect Posemo Posfeel Optim Negemo Anx Anger Sad Swear 1073 30,75 68,59 3,91 0,47 7,46 5,13 0,47 0,37 2,33 0 1,49 0,37 0 1282 25,59 66,46 3,51 0,94 4,91 1,64 0,23 0,23 3,28 0,31 1,64 0,47 0,08 690 38,55 66,52 1,88 0,43 6,38 4,35 0,14 0,72 2,03 0,43 1,3 0,14 0 197 32,99 59,9 1,52 1,52 4,57 3,05 0 0 1,52 0 1,02 0 0,51 377 36,07 64,72 3,18 1,59 4,51 0,8 0 0 3,71 0 2,92 0,27 0 847 29,04 66,82 3,19 0,47 4,72 3,54 0,24 0,71 1,18 0 0,35 0,24 0 833 31,45 64,95 3,84 0 8,16 4,2 0,12 0,6 3,96 0,48 2,4 0,12 0 221 28,51 71,04 1,81 0,9 7,24 4,07 0,9 0,9 3,17 0,45 1,81 0,45 0 855 27,49 69,24 3,39 0,47 4,21 2,92 0,35 0,58 1,29 0 0,82 0,12 0 18 22,22 72,22 11,11 0 5,56 0 0 0 5,56 0 5,56 0 0 © BSI – We grow businesses 2019 | Seite: 8
  9. 9. RESULT TYPE II STRUCTURE RECOGNITION TOPIC FIELDS © BSI – We grow businesses 2019 | Seite: 9
  10. 10. THANK YOU XIÈXIE CHOKRANE HVALA VIELEN DANK TAK MERCI TÄNAN DANK U WEL KÖSZÖNÖM DZIĘKUJĘ ARIGATÔ GRAZIE СПАСИБО TERIMA KASIH TESEKKUR EDERIM

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