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© BSI – We grow businesses
AN EXPLORATIVE APPROACH TO
IMPROVED USER MANIPULATION
WHAT IS PHRASING?
Brand Science Institute, January 2019
AGENDA
© BSI – We grow businesses 2019 | Seite: 2
Core Issue
Procedure Model Phrasing
© 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
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
 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
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
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
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
RESULT TYPE II STRUCTURE RECOGNITION TOPIC FIELDS
© BSI – We grow businesses 2019 | Seite: 9
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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What is phrasing - An explorative approach to improved user manipulation

  • 1. © BSI – We grow businesses AN EXPLORATIVE APPROACH TO IMPROVED USER MANIPULATION WHAT IS PHRASING? Brand Science Institute, January 2019
  • 2. AGENDA © BSI – We grow businesses 2019 | Seite: 2 Core Issue Procedure Model Phrasing
  • 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. 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.  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. 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. 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. 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. RESULT TYPE II STRUCTURE RECOGNITION TOPIC FIELDS © BSI – We grow businesses 2019 | Seite: 9
  • 10. THANK YOU XIÈXIE CHOKRANE HVALA VIELEN DANK TAK MERCI TÄNAN DANK U WEL KÖSZÖNÖM DZIĘKUJĘ ARIGATÔ GRAZIE СПАСИБО TERIMA KASIH TESEKKUR EDERIM