##Find Out deeper consumer`s insight into China Market## Based on Digital Media and Textual Data as a way to get deeper into your consumers’ minds *ENG ver

1. © Copyright Taeltech 2020.
taeltech.com
Social
Listening

2. SOCIAL
LISTENING
Digital Media and Textual Data
as way to get deeper into your
consumers’ minds
©CopyrightTaeltech2020.

3. Collect data across all major EC & SNS Platforms
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3
We are a data analytics & research company with 50,000 active consumers
that we monitor and engage with to gain insights on brands
Sales Data
Social Media Textual Analysis
Competitor Analysis
User Survey
Product Testing
User Behaviour Assumption Testing
姨太的山口魔力
KOL endorsements,
consumer questions,
recommandations,
comparisons, etc
Collect Massive Data
from all platforms
We leverage Elo Rating,
Graph Theory, and Latent
DirichletAllocation
Analyze using Machine
Learning and in-house
algorithms
Our local specialist interpret
and make sense of the data,
and link the insights to
business objectives
Human interpretation of the
output Taeltech collects all relevant data from the web and
provides you with analytics that applies models
that are unique in the social listening space

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CEO, Co-founder
Previously worked at McKinsey & Company as a
consultant and Mead Johnson Nutrition as a Sales
director.
Alex is a graduate of London School of Economics.
BD Director, Japan
Previously director at a SoftBank-funded IT startup, Yasu
started his career in advertising and has been active in the
marketing industry for over 10 years.
Yasu is a graduate of Brown University and Tokyo
University where he completed his Masters degree.
Head of Product, Co-founder
Previously worked at Bain & Company as a consultant. Yaz
also launched an airline which now operates 30 aircraft
with +10m passengers/year.
Yaz is a graduate of London School of Economics, and
Oxford University.
Product Manager
Previously worked as a producer for CCTV. Thea is also
the co-founder of a Culture & Communication company in
Shanghai.
Thea is a current graduate student of University of
Bayreuth.
Yaz Belinskiy
Thea Xu
Alex Busarov
Yasuhiro Takayama
Who we are: Deep Social Listening Team

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Data Analyst
Experienced in data analytics for 2 years. Proficient in
Python, SQL, Excel, SPSS, Stata and R.
Jiaxian is a graduate of University College London.
Vera Huang
Zimu Li
Jonathan Ross
Who we are: Deep Social Listening Team
Jiaxian Xie
Senior Data Analyst
Data analyst with a quantitative social psychology
background (from NYU & HKU). Fluent with Python and
familiar with hypotheses testing on behavioral data.
Zimu is a graduate of New York University and University
of Hong Kong.
AI and Data Engineer
Previously worked as a data consultant for an NGO
fighting against rainforest deforestation. Experienced in
data analytics, AI, machine learning, and predictive
modelling.
Jonathan is a graduate of Virginia Tech, with coursework
from Shanghai Jiao Tong University.
Copywriter
Previously worked for beauty and video company.
Vera is a graduate of Wuhan University.

6. Our strength
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6
INSIGHTS &ACTIONS, not reports
Going beyond Data
We employ techniques from digital
hermeneutics, linguistics, and cognitive science
to map conceptual nets of actual consumers
AI andAutomation
We extensively useAI and Machine Learning to
process massive amounts of data, to bring down
the cost, and achieve superlative accuracy
BusinessAcumen
With our MBB consulting DNA, we ensure that
every piece of analysis we provide is
immediately actionable and aligned with
strategic priorities

7. How we see words, and promotions
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Consumers interpret and understand your key message only in terms of language and categories familiar to them. That
is why it is critical to constantly monitor which messages have successfully “reached” them.
Encoding Digital Media Decoding

8. The 4 areas where brands most often seek our support
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Having clear view on the 4 areas bellow, is crucial to assess your current situation and plan for the future
Share of Mind Communication Effectiveness
Decision Factors
1. What are the brands that my brand is often compared to?
2. How am I evaluated against them? (which aspect of my brand,
am I winning or losing?)
1. How do consumers see my brand based on the factors that are
important to their decision making?
2. How does the evaluation of my brand compare to my
competitors?
Trend Forecast
1. What are the messages that have successfully
resonated with the consumers?
1. What are the themes that consumers find important in
my category?

9. SOCIAL
LISTENING
Share of Mind: True Category Consideration set and
Pecking Order
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10. Why it is important
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Consumers never see a brand in isolation, but always as a member of a ‘consideration set’

11. Our approach to competition status analysis
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Pick up all
comments about
your brand
1.
Filter the comments
within that include
other brand names
2.
Decide on the origin &
destination & sentiment of
the brand comparison
3.
Map all the brands out to
visualize their relationship
to each other
4.

12. Our offering for Competition Status Analysis
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We map all links and references within the textual corpora for all brands in the category onto a graph to
delineate the existing relationships

13. Traditional KPIs
Awareness, Interest,
Sales, etc.
Use Case
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Case 1
Campaign Evaluation
Build Strategy
(Segmentation/
Positioning/Targeing)
Campaign
(KOLs, Events, Targeted
Ads)
Campaign Evaluation
Based on consumer comments, check
how many & what brands you were able
to steal share of voice from
Case 2
MarketAnalysis
Locate negative evaluation
from your rival brand
Understand what aspect of your
brand is losing in consumer
evaluation
Reconsider messaging to make sure that
the strength you communicate resonate with
your consumers
Significant volume of negative evaluation
based on juxtaposition to an irrelevant
brand
Reconsider positioning to realign
your brand with the right
competitors

14. SOCIAL
LISTENING
Decision Factors Detector: Consumer Choice Decision Matrix
& Brand's Performance
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15. Our approach to brand performance evaluation
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Establishing a set of factors that are considered in choosing a brand in your category is important in evaluating your
brand status, especially in relation to your competitors
Smell
Price
Packaging
Quality
Neural Net
Pattern Recognition
AI-based grouping of words based
on affinity & similarity
Factors based on which each
brand will be evaluated
Establish 8-10 factors that are important in
consumer’s choosing a brand in your category
SmellPackaging
Quality

16. Our offering for Brand Performance Evaluation
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We provide you with relevant factors to be monitored in terms of comment volume and sentiments and enable you to
compare your performance vs. competitors

17. How this data could be leveraged
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17
Competitive benchmarking is the best way to identify where you must be winning to be successful. Diagnosing your
current standing is essential to understand where you should be going

18. SOCIAL
LISTENING
Elo-Prism: Measuring communication effectiveness
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19. Why it is important
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Product Descriptions are subject to Rashomon effect. Consumers tend to remember the product very differently
compared to what the brand owner intended
Rashomon effect a term related to the notorious unreliability of
eyewitnesses. It describes a situation in which an event is given
contradictory interpretations or descriptions by the individuals
involved.

20. Our approach to Communication Effectiveness Analysis
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Elo Rating
Amethod for calculating
the relative skill levels of
players in zero-sum
games such as chess. We
have applied this system
to the “competition” of key
messages to win the mind
of the consumer
Messages that are ranked first simply by frequency of appearance are reranked by the Elo Rating System
based on its unique algorithm that observes the gap between the ranking on the brand side vs. the
comments corpus on the consumer side.

21. Our offering for Communication Effectiveness Analysis
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We analyze your messaging and how effectively each part of the message has resonated with the consumers
Intended Message What Consumers Remember

22. Our offering for Communication Effectiveness Analysis
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We also analyse the penetration rate of your keywords to measure the extent that each keyword in your communication
has been picked up by the consumers
Product
Description Corpus
Comments
Corpus
Top Keywords Penetration Ratio
Keywords
Keywords

23. How this data could be leveraged
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Case study: In its communication a brand is putting heavy emphasis on “Ingredients”, “Organic”, “Vegetative”, while
consumers only remember the bits about “Moisturising”, “Hair Quality”, “Restorative” messages
Intended Message What Consumers Remember
Top 10
10%
Article Keywords penetration rate**
Top 30
12%
Top 50
17%
By restructuring its communication the brand can devote more space to emphasising the product characterics that consumers care about and set the correct expectations

24. SOCIAL
LISTENING
Trend Forecast: Emergent Category Trends and User Groups
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25. Why it is important
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Aproduct may appeal to people with very different interests, who in turn often identify with different market “trends”
"I am pregnant, I wonder if I should
switch to organic shampoo?"
"I think it plays well with my
new kawaii style"
"I became vegetarian recently, I like
everything organic and natural"

26. Our offering for Category Trend Analysis
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We extract trending topics from massive Digital Media corpora as opposed to starting off with presumed categories for
messaging in order to avoid subjective bias
What is commonly done now What we offer
Functional Benefit Emotional Benefit Lifestyle
Smooth hair
Great Smell
Relaxing
Recovery
Extravagant
Healthy
Limiting your options from the outset Bleeding edge trends, as they emerge from data
Well Being
Performance
Lifestyle
Specific Need

27. Well Being
Our approach to Category Trend Analysis
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Latent Dirichlet
Allocation model
Latent DirichiletAllocation model is a generative statistical model that allows sets of observations to be explained by unobserved
groups that explain why some parts of the data are similar. We use this model to cluster words together to derive themes that are
pertinent to brands instead of applying standard categories such as “function vs. emotional,” price, lifestyle, etc.
Based on the LDAmodel, keywords are extracted and clustered based on similarity, affinity in terms of not
only meaning but contextual placements
Nurturing, Recovery, Harm
reduction, Natural, Vegetative,
Stress Relief,Aromatherapy
Well Being
Smooth Hair, Bright Colour,
Suitable, Long Lasting Effect, Looks
Great Without Conditioner
Performance
Young girl, Dashing, Beautiful,
Sparkles, Japan, Modern,
Independent
Lifestyle
Anti-dandruff, Does not itch,
Hair Loss Reduction,Anti-
cheilitis
Specific Need

28. How this data could be leveraged
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Reconsider your key product attributes based on trending themes to build message variations to be tested in the market
MessagingA Messaging B
Messaging C
Trends
Performance
Well Being
Specific Need
Key ProductsAttributes
Moisturising
Essential Oil
Natural
Smooth
Organic
Japan
Trendy
Lifestyle
Modern Woman
Modern Woman
Trendy Organic
Essential Oil
Japan
Smooth
Moisturising
Smooth
Organic

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