Gilligan's Guide to Analysts as Community Managers' Best Friends
•Download as PPTX, PDF•
2 likes•12,878 views
Tim Wilson's Boston eMetrics 2012 presentation of tips and approaches that enable analysts to be highly effective and highly valued through the multi-faceted ways they support their community managers. This presentation is also available on YouTube (with voiceover) at: http://youtu.be/4kW5J8dj46k
Recommended
Recommended
More Related Content
What's hot
What's hot (20)
Viewers also liked
Viewers also liked (18)
Similar to Gilligan's Guide to Analysts as Community Managers' Best Friends
Similar to Gilligan's Guide to Analysts as Community Managers' Best Friends (20)
More from Tim Wilson
More from Tim Wilson (12)
Recently uploaded
Recently uploaded (20)
Gilligan's Guide to Analysts as Community Managers' Best Friends
- 1. The Community Manager‟s Best Friend: You @tgwilson / gilliganondata.com
- 2. Gilligan on Gilligan on an Island Data @tgwilson / gilliganondata.com
- 3. CPG RETAIL TECHNOLOGY @tgwilson / gilliganondata.com
- 4. We are a digital optimization agency. Our team helps you align quickly, test faster, fail faster, learn faster, decide faster and change faster. We get you clearheaded @tgwilson / gilliganondata.com
- 5. Community ‣ Well-intentioned and earnest Manager ‣ Likable ‣ Open to feedback @tgwilson / gilliganondata.com
- 6. The Analyst ‣ Multi-faceted ‣ Supporting the star of the show ‣ Key to delivering great ratings! @tgwilson / gilliganondata.com
- 9. The start of our 3-hour tour… @tgwilson / gilliganondata.com
- 10. The start of our 30-minute tour… @tgwilson / gilliganondata.com
- 11. What does “social media analytics” even mean? @tgwilson / gilliganondata.com
- 12. Influence Listening Data RTs Facebook Insights Monitoring Metrics Dashboards ROI Sentiment Analysis Klout Score Big Data Virality @tgwilson / gilliganondata.com
- 14. There are many different uses for the data. Analytics Performance measurement, analysis, optimization Monitoring and Moderating Facebook posts, tweets by the brand, uploaded YouTube videos Listening (and Learning) Brand mentions, trending topics among target consumers @tgwilson / gilliganondata.com
- 15. There are sooooo many tools! @tgwilson / gilliganondata.com
- 18. Channel-Provided Data Facebook Insights, YouTube Analytics Platform APIs: PageLever, Prosodic, Twitalyzer, TweetReach, Repinly, ... Social Relationship Management (SRM) Tools Vitrue , BuddyMedia, Context Optional, Shoutlet, Hootsuite, … Online Listening Platforms Radian6, SM2, Sysomos, Syncapse, … Site-Side Analytics Adobiture, Google Analytics, Coremetrics, Webtrends, ForeSee, OpinionLab, … “Influencer” Calculators Klout, PeerIndex, … @tgwilson / gilliganondata.com
- 19. Channel-Provided Analytics Data Social Relationship Monitoring and Management (SRM) Moderating Tools Listening Online Listening (and Learning) Platforms @tgwilson / gilliganondata.com
- 20. What data do we want? Will it really be actionable? Is this data “available?” No tool can violate the physics of the internet Do we already have a tool that will work? The grass is always greener… What tools are others using for this? Beth Kanter, John Lovett, Twitter, Forrester… Quick trial of the most promising tool(s) Be wary of “we don’t offer a free trial” @tgwilson / gilliganondata.com
- 21. The ROI of Social Media @tgwilson / gilliganondata.com
- 23. Two Magic Questions What do we want to accomplish? How will we know if we‟ve done that? @tgwilson / gilliganondata.com
- 27. Gaining Exposure Fostering Dialogue Promoting Facilitating Support Advocacy Generating Spurring Innovation Interaction @tgwilson / gilliganondata.com
- 28. But I have to show business value! @tgwilson / gilliganondata.com
- 29. Causal Modeling Social Media Objectives Business Outcomes XXXX included in consideration set for <category> purchases Increase the reach of the Expose target consumers who are not current XXXX brand customers to the brand Increase XXXX exposure through consumers‟ social Promote graphs Increase XXXX advocacy of the sales Increase loyalty to the XXXX XXXX brand brand for customers (by facilitating advocacy) Foster dialogue Increase brand affinity for XXXX with consumers @tgwilson / gilliganondata.com
- 31. Analysis and Optimization @tgwilson / gilliganondata.com
- 32. Community Manager‟s Question Translate to a Testable Hypothesis Determine How Best to Test Conduct the Test / Analysis Deliver (and Apply) the Results @tgwilson / gilliganondata.com
- 33. ‣ How often should we post? ‣ What days of the week are most / least effective? ‣ What times of day are most/least effective? @tgwilson / gilliganondata.com
- 34. ‣ How often should I post/tweet? ‣ When should I post/tweet (time of day / day of week)? ‣ What type of posts/tweets are most effective (videos, links, questions)? ‣ How do proactive (planned) vs. reactive (response) posts/tweets work differently? ‣ How is paid (social) media affecting my ability to “organically” reach consumers? ‣ … @tgwilson / gilliganondata.com
- 35. Friends don‟t let friends… @tgwilson / gilliganondata.com
- 36. Analysts don‟t let Community Managers… @tgwilson / gilliganondata.com
- 37. …obsess about automated sentiment analysis @tgwilson / gilliganondata.com
- 38. …obsess about automated sentiment analysis “Positive” Tweets “Negative” Tweets ‣ “goodbye to working as a cashier at ‣ “My mom says we dont have <the retailer> to working in the bakery money but yet shes at <the at <a competitor> #whatilovetodo retailer>… Thats bullshit” #excited #cantwaittostart” ‣ “When people give away <coupons ‣ “amazing rainbow at for the retailer> <<<< idiots” <the retailer> ‣ “Hate the shirt I’m wearing, going instagr.am/p/O4JUXxXxXx/” to attempt a blitz shopping trip to ‣ “So happy tomorrow is my last day at <the retailer> before school. Wish <the retailer>” me luck!” @tgwilson / gilliganondata.com
- 39. Automated sentiment analysis IS a useful way to filter @tgwilson / gilliganondata.com
- 40. Analysts don‟t let Community Managers… @tgwilson / gilliganondata.com
- 41. …obsess about finding “influencers” “We‟re going to shoot a viral video.” @tgwilson / gilliganondata.com
- 42. …obsess about finding “influencers” “We‟re going to roll out a new CRM platform that will enable 1-to-1 marketing!!!” @tgwilson / gilliganondata.com
- 43. …obsess about finding “influencers” “We‟re going to pay a company to dramatically boost our search rankings.” @tgwilson / gilliganondata.com
- 44. …obsess about finding “influencers” “We‟re going to identify „influencers‟ whose endorsements of our brand will drive members of their social graph to buy, buy, BUY!!!” @tgwilson / gilliganondata.com
- 45. Klout is a useful way to gauge “high” vs. “low” social activity @tgwilson / gilliganondata.com
- 46. Best Friends: ‣ Build and maintain a strong relationship ‣ Have a high level of mutual trust and respect ‣ Support each other through collaboration @tgwilson / gilliganondata.com
- 47. thanks @tgwilson / gilliganondata.com
Editor's Notes
- http://images.zap2it.com/images/tv-EP00001843/gilligans-island-18.jpghttp://tvlistings.zap2it.com/tv/gilligans-island/photo-gallery-detail/EP00001843/1098037
- Social media workVS Mission Control – big chunk of money…so started to become “anything that is any way related to any social media channel or social media analytics platform”
- …sometimes flustered and a bit cluelesshttp://lifeasahuman.com/2010/humor/completely-useless-mnemonics-for-your-daily-life/
- http://lifeasahuman.com/2010/humor/completely-useless-mnemonics-for-your-daily-life/
- http://www.listal.com/viewimage/2398688ConfusionUncertaintyFearhttp://www.gilligansisle.com/images/mary/mary3.jpgRespectAdmirationParadise!
- http://www.listal.com/viewimage/2398688ConfusionUncertaintyFearhttp://www.gilligansisle.com/images/mary/mary3.jpgRespectAdmirationParadise!
- http://www.gilligansisle.com/images/gilligan/gladys.jpg
- You have to get a little academichttp://www.gilligansisle.com/images/professor/prof4.jpg
- Be clear on what you’re doing (and help the community manager be clear on what they’re doing and how you’re supporting).http://www.gilligansisle.com/images/crew/lunar%20pose.jpg
- http://www.gilligansisle.com/gil.htmlhttp://blogs.suntimes.com/shinyobjects/2010/03/who_should_star_in_the_gilligans_island_movie.html
- http://www.gilligansisle.com/gil.htmlhttp://blogs.suntimes.com/shinyobjects/2010/03/who_should_star_in_the_gilligans_island_movie.html
- (You have to dive in and do the work – pragmatically)
- Be clear on what you’re doing (and help the community manager be clear on what they’re doing and how you’re supporting).http://www.gilligansisle.com/images/crew/lunar%20pose.jpg
- http://www.gilligansisle.com/images/thurston/thurston1.jpg
- http://www.gilligansisle.com/images/gilligan/buddy.jpg
- http://www.gilligansisle.com/images/gilligan/buddy.jpg
- http://www.gilligansisle.com/images/gilligan/buddy.jpg
- How many people attended John Lovett’s session earlier today?I CANNOT endorse his book strongly enough. In the context of performance management, the “six likely social media objectives” in Chapter 4 and 5 are an outstanding starting point. And, he includes pseudo-formulas for KPIs for each each of these objectives. Turning those into Twitter-specific formulas with the right tools in hand is a snap.Get the book.
- http://www.gilligansisle.com/images/gilligan/buddy.jpg
- This is an extreme example, but the reality is closer to this anecdote than you might realize. Below are some tweets flagged as “negative” through Radian6’s automated sentiment analysis related to a major retailer:“My mom says we dont have money but yet shes at <the retailer>… Thats bullshit”“Every since I started working at <the retailer> I’m good as hell at flipping percentages”“When people give away <coupons for the retailer> <<<< idiots”“Hate the shirt I’m wearing, going to attempt a blitz shopping trip to <the retailer> before school. Wish me luck!”It’s easy to see why each of these got flagged as negative, and it is easy to see how largely impossible it would be for an automated platform, with nothing else to go on than the characters in each tweet, to have done a better job. The same challenge occurs with positive sentiment. Tweets for the same retailer that were identified as having positive sentiment:“goodbye to working as a cashier at <the retailer> to working in the bakery at <a competitor> #whatilovetodo #excited #cantwaittostart #makingmoney”“amazing rainbow at <the retailer> instagr.am/p/O4JUXxXxXx/”“So happy tomorrow is my last day at <the retailer>”“Management meeting then off to B&N and <the retailer>, thank goodness everything is located on the same busy street! ”
- This is an extreme example, but the reality is closer to this anecdote than you might realize. Below are some tweets flagged as “negative” through Radian6’s automated sentiment analysis related to a major retailer:“My mom says we dont have money but yet shes at <the retailer>… Thats bullshit”“Every since I started working at <the retailer> I’m good as hell at flipping percentages”“When people give away <coupons for the retailer> <<<< idiots”“Hate the shirt I’m wearing, going to attempt a blitz shopping trip to <the retailer> before school. Wish me luck!”It’s easy to see why each of these got flagged as negative, and it is easy to see how largely impossible it would be for an automated platform, with nothing else to go on than the characters in each tweet, to have done a better job. The same challenge occurs with positive sentiment. Tweets for the same retailer that were identified as having positive sentiment:“goodbye to working as a cashier at <the retailer> to working in the bakery at <a competitor> #whatilovetodo #excited #cantwaittostart #makingmoney”“amazing rainbow at <the retailer> instagr.am/p/O4JUXxXxXx/”“So happy tomorrow is my last day at <the retailer>”“Management meeting then off to B&N and <the retailer>, thank goodness everything is located on the same busy street! ”
- http://25.media.tumblr.com/tumblr_lpub8dSF4y1qbixyoo1_1280.jpg