I recently gave a talk on current trends and likely future developments in social media monitoring. I promised to upload the slides. So here there are. The presentation outlines how social media monitoring moves from social listening to social insights and further to social intelligence. After a short introduction with reference to all the main trends, the presentation puts spotlights on the in my view essential developments along the way.

1. Gregor Hopf
Slideshare November 2016
Trendsand likely Future Developments
of Social Media Monitoring

2. SOCIAL LISTENING
TO SOCIAL INSIGHTS
TO SOCIAL
INTELLIGENCEreal-time
Machine
Learning
BigData
Prof. Dr. Gregor Hopf - November 2016

3. Social Media measurement should not be
an afterthought left solely to software
platforms auto-generating fancy graphs
and charts. Done properly it should be
tailored to your organization’s objectives,
with emphasis on what has changed as a
result of your work.
Richard Bagnall, 2013.
Then: Managing Director and Co-Owner of Metrica
Now: CEO of Prime Research UK
Then and now: Chair of the social media measurement group of the International
Association for the Measurement and Evaluation of Communications (AMEC)
OUTPUT – OUTTAKE – OUTCOME
Prof. Dr. Gregor Hopf - November 2016

4. Main Trends & Developments
INTEGRATION
One Dashboard to rule them all
Break-upofSilos
Across Departments
and Disciplines
CUSTOMER
JOURNEY
DATA PROTECTION
INFLUENCER
Detractors
Virality Mapping
SOCIAL SELLING
PERFORMANCE
SOCIAL LISTENING
TO SOCIAL INSIGHTS
TO SOCIAL
INTELLIGENCE
real-time
Machine
Learning
BigData
IMAGE ANALYTICS
WITH SENTIMENT ANALYSIS
financial
ROI
SOCIETAL
MONITORING
NEW USER
SEGMENTATION
MESSENGER
CHATBOTS
VIDEO
Prof. Dr. Gregor Hopf - November 2016

5. Trends
• Integration
• Customer Journey
• Influencer
Future Developments
• Image Analytics
• Messenger & Chatbots
• New User Segmentation
Agenda
Prof. Dr. Gregor Hopf - November 2016

6. Publishing &
Engagement
Metrics &
Clipping
CRM
Measuring, Reporting, Monitoring
Social Listening
Third
Party
Data
#1: INTEGRATION
Analytics
Prof. Dr. Gregor Hopf - November 2016

7. One Dashboard to
Rule Them All
Example: Hubspot
• Tool Integration
• Data Integration
• Across Departments,
Disciplines and Data-
/Information-Silos
New & better functions:
• Competitor Monitoring /
Benchmarking
• Visualisations
• Real-time, customizable
but automated reporting
across the organization,
up to the C-Suite
#1: INTEGRATION
Prof. Dr. Gregor Hopf - November 2016

8. One Dashboard to Rule Them All
Example: Hubspot
From monitoring of your social-media presence (owned media)
to monitoring your presence in social media (owned, earned and
bought) and beyond.
#1: INTEGRATION
Prof. Dr. Gregor Hopf - November 2016

9. Full Funnel Monitoring: From Promise to Reality
Currently:
mostly aggregated data about the organization,
its products and brands on each step of the journey,
e.g. share of voice, sentiment, review monitoring,
response rates.
Near Future:
Integration of all touchpoints on an individual level to
allow for personalized (automated) communication
at decisive points along the journey:
• social media touchpoints (hashtags, social media
activity , tracking links etc.)
• online data (e.g. tracking cookies)
• further CRM data (e.g. service or customer centre,
email- or ad-campaigns)
• reliable context analysis (semantic analysis)
• personal data (e.g. geo-location, in-app activity,
messenger communication)
• likely preferences based on profiles.
#2: CUSTOMER JOURNEY
David Rogers:
The Network is Your Customer;
Yale University Press, 2011.
www.davidrogers.biz
Prof. Dr. Gregor Hopf - November 2016

10. Gain insights not only about
what is being said
but who is saying it,
who is not (detractors)
and how influential are they
(virality mapping).
#3: INFLUENCER
Example: Sproutsocial
Example: Talkwalker
Prof. Dr. Gregor Hopf - November 2016

11. Example: Sproutsocial
Prof. Dr. Gregor Hopf - November 2016

12. #3: INFLUENCER
Sources: www.youtube.com and www. guardian.couk
Prof. Dr. Gregor Hopf - November 2016

13. #3: INFLUENCER
Example: Talkwalker
Prof. Dr. Gregor Hopf - November 2016

14. From Trends to
likely Future Developments
Prof. Dr. Gregor Hopf - November 2016

15. Identify influencers and group
users along metrics that matter
to them – not (only) along their
demographics:
Casestudy: Cambridge Analytica
Claims to have collected 5000
data points on over 220 million
Americans for the purpose of
strategic communication during
the electoral process. Every
person is assigned one of five
personality traits:
• Openness to Experience
• Conscientiousness
• Extraversion
• Agreeableness
• Neuroticism
Plus further information about
demographics and likely position
on individual political topics.
 Who is most likely our customer?
 Where is he/she?
 What interests him/her?
 How does he/she like to be
approached?
 When is he/she willing to talk to us?
Analysis of untapped potential, e.g.
topics the user is most likely interested
in in other platforms such as Spotify,
travel booking platforms etc.
Ability to communicate at scale yet
still individually
#4: NEW USER SEGMENTATION
Prof. Dr. Gregor Hopf - November 2016

16. #5: IMAGE ANALYTICS (incl. Sentiment)
Prof. Dr. Gregor Hopf - November 2016

17. From Image Recognition to
Image Analytics
Example: Logograb
Social media listening and
analysis is still largely text based
while the communication has
moved on to pictures and
videos.
#5: IMAGE ANALYTICS (incl. Sentiment)
Prof. Dr. Gregor Hopf - November 2016

18. Access to digital
Walled Gardens
1 Billion Whatsapp User
900 million FB-Messenger
850 million QQ Mobile
700 million WeChat
300 million Skype
Statista, April 2016, monthly users
Snapchat is the most
important social network
for US teens (28%),
followed by Instagram
(27%), Twitter (18%) and
Facebook (17%)
Statista, February 2016
#6: MESSENGER & CHATBOTS
Sources:
Background picture: :Flickr „Walled Garden at Cowdray“ by Russel James Smith (cropped and superimposed)
Snapchat Logo; Snapchat.com; WhatsApp Logo: Whatsapp.net
Prof. Dr. Gregor Hopf - November 2016

19. And all the machine-reading
based analytics we can get…
#6: MESSENGER & CHATBOTS
Source: WhatsApp.net
Voice Recognition
Video Analytics
And a little bit of text
Semantic Image
Recognition
Geo-Location
Prof. Dr. Gregor Hopf - November 2016

20. +
Machine
Learning
2016
Trends Perspectives
Monitoring Social Listening Social (Media) Intelligence
WHAT – SO WHAT – NOW WHAT
Publishing &
Engagement
Metrics &
Clipping
CRM
Social Listening
Third
Party
Data
Analytics
Supply Chain
Real-time
Marketing
Data-driven
Social Selling
Yield-
Management
Predictive Crisis
Management
…
+
Big
Data
+
User
Profiling
+
Access
to
Messenger
Prof. Dr. Gregor Hopf - November 2016

21. FROM MEASURINGTO INSIGHTS TO DECISIONS
Summary
SOCIAL LISTENING
TO SOCIAL INSIGHTS
TO SOCIAL
INTELLIGENCErealtime
Machine
Learning
BigData
Any Questions?

22. Gregorhopf.de
kontakt@gregorhopf.de Find me on:
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Any Questions?
Prof. Dr. Gregor Hopf - November 2016