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Building an effective analytics program
Mark Farmer, Ryerson University – July 29, 2013
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Return on investment
!= “Return on engagement”
(Gain from investment - cost of investment) /
cost of investment
...





It‟s immeasurable
You shouldn‟t measure
You need to find the dollars
ROAS (Return on Ad Spend) equivalent is what...



Reach
Engagement
◦ Conversation




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Influence
Traffic
Conversion
◦ …to sale


Facebook
◦ Page impressions
◦ Stories created
 Comments
 Shares

◦
◦
◦
◦

Likes
Fans
Reach
People talking about this
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Twitter
◦
◦
◦
◦

Mentions
Retweets
Impressions
Clicks


YouTube
◦
◦
◦
◦
◦
◦

Views
Minutes watched
Subscribers
Likes
Shares
Favourites
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LinkedIn
◦ Shares
◦ Comments
◦ Views


Benchmark!
1.
2.
3.
4.

Previous effort
The competition
Phone-a-friend
Going forward


Engagement & Reach
◦ Twitter
 Retweets
 Favourites

◦ Facebook
 Likes
 “Talking about this” index

◦ YouTube
 Like...


Pure Reach
◦ Facebook




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Likes
Views
Organic & viral reach
Virality
Frequency of visits per user

◦ Twitter

 ...
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Influence
◦ Top influencer reach in Radian6 / Sysomos
◦ Interaction rate of top influencers
◦ Number of stories picked ...


Sentiment
◦ Net sentiment in Radian6
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Traffic
◦ Total social mentions, filtered by sentiment
◦ Social traffic to website & blogs


Many of the metrics listed above depend on a
variety of inputs. Because of this, digital
media practitioners shouldn‟t ...


For example, sentiment is a key metric
because it‟s a proxy for consideration: if
people think of you favourably online...


However, sentiment is influenced by many
different sources around an institution, which
are completely separate from di...


Therefore, although net sentiment can be
benchmarked for specific posts or digital
media channels, digital media succes...






Radian6
Sysomos Heartbeat
SproutSocial
HootSuite
Google Analytics / Adobe Site Catalyst /
Webtrends / etc.


Facebook Insights
Google+ ripples



(sort of)



(ok, not really)




LinkedIn
◦ “Whose viewed your updates”
 Being “rolled out”
http://christinehueber.com/2013/your-new-morepersonalized-l...


Other
◦ Tumblr - statcounter
◦ WordPress - Google Analytics / Adobe Site Catalyst


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Twitter
Why?
$
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
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Hashtracker
TweetReach
Searchhash.com
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

Excel
Pivot charts
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How do we turn this into money?
◦ You don‟t - it‟s part of a marketing funnel
◦ “You set „em up - we knock „em down”

...


http://www.smartinsights.com/social-mediamarketing/facebook-marketing/what-is-thevalue-of-a-facebook-fan-a-case-study/



Twitter reach:
http://www.unmarketing.com/2012/04/15/
when-we-exaggerate-our-size-everyoneloses/








Olivier Blanchard - Social Media ROI:
http://www.amazon.ca/dp/0789747413
Beth Kanter - Measuring the Networked...


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ca.linkedin.com/in/markfarmer64
twitter.com/markus64
http://digitalheresy.tumblr.com
Social media monitoring & metrics - Ryerson University lecture
Social media monitoring & metrics - Ryerson University lecture
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Social media monitoring & metrics - Ryerson University lecture

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Monitoring & Measuring social media - a lecture given at Ryerson University, Toronto, 2013. Talking about the most popular, most useful metrics for the various platforms (Facebook, Twitter, LinkedIn, etc.), monitoring dashboards such as Radian6 and Sysomos Heartbeat, and specific metrics such as reach, engagement, etc.

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Social media monitoring & metrics - Ryerson University lecture

  1. 1. Building an effective analytics program Mark Farmer, Ryerson University – July 29, 2013
  2. 2.     Return on investment != “Return on engagement” (Gain from investment - cost of investment) / cost of investment In other words, you want to get out more then you spend
  3. 3.     It‟s immeasurable You shouldn‟t measure You need to find the dollars ROAS (Return on Ad Spend) equivalent is what matters
  4. 4.   Reach Engagement ◦ Conversation    Influence Traffic Conversion ◦ …to sale
  5. 5.  Facebook ◦ Page impressions ◦ Stories created  Comments  Shares ◦ ◦ ◦ ◦ Likes Fans Reach People talking about this
  6. 6.  Twitter ◦ ◦ ◦ ◦ Mentions Retweets Impressions Clicks
  7. 7.  YouTube ◦ ◦ ◦ ◦ ◦ ◦ Views Minutes watched Subscribers Likes Shares Favourites
  8. 8.  LinkedIn ◦ Shares ◦ Comments ◦ Views
  9. 9.  Benchmark! 1. 2. 3. 4. Previous effort The competition Phone-a-friend Going forward
  10. 10.  Engagement & Reach ◦ Twitter  Retweets  Favourites ◦ Facebook  Likes  “Talking about this” index ◦ YouTube  Likes  Favourites ◦ Specific interactions (likes, shares, etc.) for other media such as Tumblr, Pinterest, Instagram, etc.
  11. 11.  Pure Reach ◦ Facebook      Likes Views Organic & viral reach Virality Frequency of visits per user ◦ Twitter  Tweet reach ◦ YouTube  Subscriptions ◦ Traffic metrics from other sources such as Tumblr, Pinterest, Instagram, etc. ◦ Total monthly mentions in Radian 6 / Sysomos segmented by sentiment
  12. 12.  Influence ◦ Top influencer reach in Radian6 / Sysomos ◦ Interaction rate of top influencers ◦ Number of stories picked up by mainstream media via digital sources
  13. 13.  Sentiment ◦ Net sentiment in Radian6
  14. 14.  Traffic ◦ Total social mentions, filtered by sentiment ◦ Social traffic to website & blogs
  15. 15.  Many of the metrics listed above depend on a variety of inputs. Because of this, digital media practitioners shouldn‟t be held solely responsible for moving these metrics; such metrics are impacted by many different inputs above and beyond the digital media channels available to an institution.
  16. 16.  For example, sentiment is a key metric because it‟s a proxy for consideration: if people think of you favourably online, we can safely assume (and correlate quantitatively, if needed) that they will consider buying from you / interacting with you in a desirable fashion.
  17. 17.  However, sentiment is influenced by many different sources around an institution, which are completely separate from digital media.
  18. 18.  Therefore, although net sentiment can be benchmarked for specific posts or digital media channels, digital media success can‟t be based on net sentiment for an institution. Digital media might only contribute a small part of an institution‟s overall net sentiment and perception.
  19. 19.      Radian6 Sysomos Heartbeat SproutSocial HootSuite Google Analytics / Adobe Site Catalyst / Webtrends / etc.
  20. 20.  Facebook Insights Google+ ripples  (sort of)  (ok, not really) 
  21. 21.  LinkedIn ◦ “Whose viewed your updates”  Being “rolled out” http://christinehueber.com/2013/your-new-morepersonalized-linkedin-homepage-by-christinehueber/ ◦ Corporate page analytics   Instagram Pinterest
  22. 22.  Other ◦ Tumblr - statcounter ◦ WordPress - Google Analytics / Adobe Site Catalyst
  23. 23.    Twitter Why? $
  24. 24.    Hashtracker TweetReach Searchhash.com
  25. 25.   Excel Pivot charts
  26. 26.  How do we turn this into money? ◦ You don‟t - it‟s part of a marketing funnel ◦ “You set „em up - we knock „em down”      Change over time Sentiment - proxy Social care Social CRM SWOT analysis
  27. 27.  http://www.smartinsights.com/social-mediamarketing/facebook-marketing/what-is-thevalue-of-a-facebook-fan-a-case-study/
  28. 28.   Twitter reach: http://www.unmarketing.com/2012/04/15/ when-we-exaggerate-our-size-everyoneloses/
  29. 29.     Olivier Blanchard - Social Media ROI: http://www.amazon.ca/dp/0789747413 Beth Kanter - Measuring the Networked NonProfit: http://www.amazon.ca/MeasuringNetworked-Nonprofit-UsingChange/dp/1118137604 Katie Delahaye Paine - Measuring What Matters: http://www.amazon.ca/Measure-What-MattersUnderstanding-Relationships/dp/B00D821V28 Avinash Kauishik – Web Analytics 2.0: http://www.amazon.ca/Web-Analytics-2-0Accountability-Centricity/dp/0470529393
  30. 30.    ca.linkedin.com/in/markfarmer64 twitter.com/markus64 http://digitalheresy.tumblr.com

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