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.

1. © BSI – We grow businesses
AN EXPLORATIVE APPROACH TO
IMPROVED USER MANIPULATION
WHAT IS PHRASING?
Brand Science Institute, January 2019

2. AGENDA
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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
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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
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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
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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
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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
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9. RESULT TYPE II STRUCTURE RECOGNITION TOPIC FIELDS
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10. THANK YOU
XIÈXIE
CHOKRANE
HVALA
VIELEN DANK
TAK
MERCI TÄNAN
DANK U WEL
KÖSZÖNÖM
DZIĘKUJĘ
ARIGATÔ
GRAZIE
СПАСИБО
TERIMA KASIH
TESEKKUR EDERIM