A use-case of how NVALUE Analytics can help your segment your twitter followers into personas based on text analytics

1. NVALUE
WORDS, TWEETS &
PERSONAS

2. NVALUE: THE PROCESS OF ADDING VALUE
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ADDED
VALUE

3. NVALUE: THE PROCESS OF ADDING VALUE
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Rough diamond Polished diamond
Data Insights

4. Some examples of how we
can your data
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5. Cross-sell well Cross-sell poorly
CROSS SELLING ANALYSIS
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IDENTIFY CROSS-SELLING PATTERNS AND OPTIMIZE THE STRATEGY (BUNDLING,
CO-MARKETING, RECOMMANDATION, ETC.)
Sales data
SAP, Webshop
eCommerce, etc.
Business Reports
& Dashboards
Operational focus
Cross-sell
Matrix
Strategic focus

6. CAMPAIGN PERFORMANCE ANALYSIS
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IDENTIFY WHICH PARAMETERS PREDICT BETTER CONVERSION RATE IN ORDER TO
OPTIMIZE YOUR CAMPAIGNS MID-RUN
Campaign data
CRM, Marketing
automation, etc.
Business Reports
& Dashboards
Operational focus
Conversion
Analysis
Strategic focus

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GROUPING OF FOLLOWERS BASED ON WORDS
ANALYSIS
SEGMENT YOUR TWITTER FOLLOWERS TO IDENTIFY “PERSONAS” TO TARGET
WITH YOUR MARKETING MESSAGE
Social media data
Twitter, Facebook,
LinkedIn, etc.
Social Media
Dashboards
Operational focus
Semantic
clustering
Strategic focus

8. AND MUCH MUCH MORE
 Basket analysis
 Clustering of customer based on buying patterns
 Competitors data analysis
 Trade-fairs/events analysis
 …
All aiming to your data
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9. NVALUE
WORDS, TWEETS &
PERSONAS

10. KEY CONCEPT:
The words we choose when
communicating paint a picture of
ourselves, even if we don’t realise it
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Like all the best families, we
have our share of eccentricities,
of impetuous and wayward
youngsters and of family
disagreements
YO wen u gettin da ps4 tings in
moss side? Ain’t waitin no more.
Plus da asian guy whu works
dere got bare attitude
#wasteman
I'm not even thinking of
weddings, cause obviously I'm
not divorced from the 'tranny' yet
WHO SAID WHAT?

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Like all the best families, we
have our share of eccentricities,
of impetuous and wayward
youngsters and of family
disagreements
YO wen u gettin da ps4 tings in
moss side? Ain’t waitin no more.
Plus da asian guy whu works
dere got bare attitude
#wasteman
I'm not even thinking of
weddings, cause obviously I'm
not divorced from the 'tranny' yet
WHO SAID WHAT?

13. SIDE EFFECTS:
By looking at the words people choose we
can:
Learn about them
Group them
Engage them by using their language
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GROUPING OF FOLLOWERS BASED ON WORDS
ANALYSIS

15. HOW IT WORKS: DATA RETRIEVAL
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COLLECT FOLLOWERS DESCRIPTION AND STORE THEM IN A
TABLE

16. HOW IT WORKS: WORD FREQUENCY ANALYSIS
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TRANSFORM EACH DESCRIPTION INTO A TABLE OF WORD-
FREQUENCIES

17. HOW IT WORKS: SEMANTIC CLUSTERING
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COMPARE THE WORD-FREQUENCIES OF EACH FOLLOWER IN
ORDER TO GROUP TOGETHER PEOPLE WHO USE SIMILAR
WORDS

18. HOW IT WORKS: CREATION OF PERSONAS
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FOR EACH GROUP CREATE AN EXAMPLE “PERSONA”
Avg. #Followers: 350
Avg. #Following: 675
Avg. #Tweets: 2300
Avg. #Followers: 2000
Avg. #Following: 8500
Avg. #Tweets: 17K
Avg. #Followers: 680
Avg. #Following: 3200
Avg. #Tweets: 1500

19. Some examples of how to use
the results
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DESIGN SPECIFIC MESSAGES
DESIGN RELEVANT CONTENT/MESSAGES FOR THE IDENTIFIED
PERSONAS TAILORING TOPICS, WORDING, POSITIONING, ETC.

21. QUANTIFY AND PRIORITISE
PRIORITIZE CATEGORIES WITH BETTER CHANCE TO SPREAD YOUR
MESSAGE AND MONITOR FOLLOWER ACQUISITION
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22. SELECT ADVOCATES
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ENGAGE WITH DIGITAL ADVOCATES ONLINE (@MENTION) AND
OFFLINE (EVENTS, PARTNERSHIPS, PRESS RELEASES, ETC.)

23. REGIONALISE STRATEGY
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OPTIMISE REGIONAL ACTIVITIES IN THE LIGHT OF
GEOGRAPHICAL DISTRIBUTION OF FOLLOWERS

24. Want to discover more?
Get in touch
Mail: igor@nvalue.net
Twitter: @NValueAnalytics
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