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David Phillips
         2010
Why do Evaluation
 What to learn today:
   All PR methodologies include Evaluation
       Who?
   When should evaluations be done?
   What is your experience?
   Techniques
   Future
Things to Measure
 volume and favourability of coverage
 delivery of key messages, issues and trends
 key publications & journalist tracking
 full intelligence on competitors media presence
 breakdown by brands / services / products / business areas
 impact achieved
 media type
 opportunities to see,
 regional & socio-economic profile
 reach & frequency of coverage in terms of actual number of
  people against tightly defined core target audiences
 concise summary of entire report
 full qualitative analysis in easy to understand explanatory text
Things that are hard to measure
 Reach
 Tone
 Impact
 Effect
 Meaning
 Curation
 Big Data
Who does this sort of stuff?
 Dead Tree analysis
   http://www.amecorg.com
          Early authors: Linda Hon, Phillips 1992, J. E. Grunig, 1977 b,
           1983; J. E. Grunig & Hickson, 1976; Suchman, 1967; Wright,
           1979, Dermot McKeone 1995
 Digital analysis
    http://www.radian6.com/
    Http://kleaglobal.com
 Is that enough?
    Socio, economic, share, etc
    http://www.brandwatch.net
Next generation
 All the web
 Real Time Web
 Real time correlation
 Computerised
 Also real time location, etc etc
 New aproaches
        http://bit.ly/bXARaG
        Towards Relationship management
A process for management
 There is the opportunity to mix and match the
  knowledge and experience of the practitioner.
 Perspectives
   Subject areas
   What is important
   What is positive
What more is there to know?
The code is
invisible
A quick look at semantics
Finding meaning using semantics
 I Love Lucy
I      Lucy
I      Lucy

 http://users.aber.ac.uk/dgc/Documents/S4B/
Teach software to curate
Many
applications
A lot of outcomes
A working example
PR meets Big Data and Semantics
 We saw what big data looks like for the PR practitioner
 We saw how we can get information and turn it into
  data
 You learned how to inject professional insights into
  Big Data .
 You now know how to get a competitive advantage.
Why do Evaluation
 Did we learn today:
   All PR methodologies include Evaluation
       Who?
   When should evaluations be done?
   What is your experience?
   Techniques
   Future

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Monitoring And Evaluation

  • 2. Why do Evaluation  What to learn today:  All PR methodologies include Evaluation  Who?  When should evaluations be done?  What is your experience?  Techniques  Future
  • 3. Things to Measure  volume and favourability of coverage  delivery of key messages, issues and trends  key publications & journalist tracking  full intelligence on competitors media presence  breakdown by brands / services / products / business areas  impact achieved  media type  opportunities to see,  regional & socio-economic profile  reach & frequency of coverage in terms of actual number of people against tightly defined core target audiences  concise summary of entire report  full qualitative analysis in easy to understand explanatory text
  • 4. Things that are hard to measure  Reach  Tone  Impact  Effect  Meaning  Curation  Big Data
  • 5. Who does this sort of stuff?  Dead Tree analysis  http://www.amecorg.com  Early authors: Linda Hon, Phillips 1992, J. E. Grunig, 1977 b, 1983; J. E. Grunig & Hickson, 1976; Suchman, 1967; Wright, 1979, Dermot McKeone 1995  Digital analysis  http://www.radian6.com/  Http://kleaglobal.com  Is that enough?  Socio, economic, share, etc  http://www.brandwatch.net
  • 6. Next generation  All the web  Real Time Web  Real time correlation  Computerised  Also real time location, etc etc  New aproaches  http://bit.ly/bXARaG  Towards Relationship management
  • 7. A process for management  There is the opportunity to mix and match the knowledge and experience of the practitioner.  Perspectives  Subject areas  What is important  What is positive What more is there to know?
  • 9. A quick look at semantics
  • 10. Finding meaning using semantics  I Love Lucy I Lucy I Lucy  http://users.aber.ac.uk/dgc/Documents/S4B/
  • 13. A lot of outcomes
  • 15. PR meets Big Data and Semantics  We saw what big data looks like for the PR practitioner  We saw how we can get information and turn it into data  You learned how to inject professional insights into Big Data .  You now know how to get a competitive advantage.
  • 16. Why do Evaluation  Did we learn today:  All PR methodologies include Evaluation  Who?  When should evaluations be done?  What is your experience?  Techniques  Future