Knowing who matters: discovering and analysing influence online
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A presentation at the very well organised and run Social Media Monitoring 2009 conference in London. Hope it makes interesting reading!
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Knowing who matters: discovering and analysing influence online
- 1. Knowing who matters Discovering and analysing influence
- 2. Identity online is dispersed
- 3. '...we are buried beneath the weight of information, which is being confused with knowledge...' Tom Waits
- 4. #1 Prior Preparation Prevents Poor Performance
- 5. #2 Think like an analyst and an anthropologist
- 6. Combine quantity with quality
- 7. "I keep six honest serving-men (They taught me all I knew); Their names are What and Why and When And How and Where and Who" - Rudyard Kipling
- 8. #3 Look for the actionable insights
- 9. #4 Make context king …and Twitter the court jester
- 10. “The demolition... oops, sorry, 'conservation' of our listed Marina Restaurant here in Ramsgate has caused a right royal rumpus. Now it transpires that our council's own Heritage Development Advisor has written to English Heritage asking for their support, and inviting them to make a site visit in the 'near future'.” - eastcliffrichard.blogspot.com
- 11. #5 Track the flow of information
- 12. …flaming on to macnn, Mac Daily News & Infinite Loop
- 13. All publicity is good publicity …at least for a while
- 14. Influence is sentiment agnostic
- 15. Thanks for your time @timcallington tim.callington@edelman.com
Editor's Notes
- Make sense and make use of dataGauge influence of groups/individuals online Understand the dynamics of communities to plan your comms strategyShare some thoughts based on experience that will hopefully be of help to people
- People are active in a wide range of placesHuge variety of tools and services to use and that’s only the platformsWe need to focus on people and the topics not the technology (can’t base all measurement around this)
- Have means to collect a massive amount of data from a variety of sourcesChallenge is in distilling that down to something that’s relevant and meaningfulThat tells you about the importance of the communities you want to engage
- First step before you begin monitoring is make sure you have a clear goal for what you want to achieveClear business goal, whether planning to inform a comms campaign, or issues and crisis relatedThis sets the context for the monitoring you want to achieve and will help to provide a framework for how you interpret the data you collect and point you to a relevant outcome
- To determine influenceUnderstand the data and the platforms and the limits of what they can provideYou also need to be an anthropologist too, understand how people are behaving, what’s motivating them – the insights that will help you answer the question, what do I want to achieve
- To put it another way, combine quantitative analysis with qualitative analysisLook at data from a range of perspectives(Swap “Influence” for “Profile”) Sentiment and Content stands apart – key qualitative measure
- Analysing the data by those criteria is fine, but you need to make it relevant to the context, the situation you’re inIt’sabout people rather than data, people creating the content you are looking atSo you need to look at it in human terms: who, what, where when, why and how
- That will lead you to the actionable insight That clear direction on what you need to do in the context of your business and communications objectivesBased on how people are discussing your brand or behaving onlineConclusion you draw from your analysis that points to a particular course of action you need to take to address your original goal.The insight may support or complement your business goal but it may also be an indirect answer which requires you to think more creatively about applying it to you campaign
- That will help you analyse your data and determine what course of action to takeBut in determining who then to engage with, based on influence, thinking about context is absolutely essentialJust focusing on how they rank on a particular social media platform isn’t sufficient, need to look at their position within in a particular community or the part they play in setting the agenda on a particular issue
- For example listing and conservation issuesPeople coalesce around specific issues then disperse, conversations highly localised.No absolute influencer active on social media, they will emerge when a particular planning issue arisesIt is more a matter of understanding how people gather rather than who the specific influencers are, so that when a community forms you can very quickly know how to act to deal with the situation, whether its an issue that’s arisen or an opportunity for your brand.
- In any given situation to understand where the influence lies, you need to look at the flow of informationTypically it will begin with an influence, not necessarily high profile, but expert in their fieldThey will be picked up by amplifiers, who have the profile and contacts to spread the message, for it to be picked up by the target audienceCitations, references and the content (opinions and attitiudes)
- For example, Daring Fireball is a Mac Developer blogRespectable audience, but not huge, but because of the writers expertise, much of his content gets picked up on the major Mac news sitesIn the long term it also sets the editorial agenda of the news sites
- One tricky ingredient to take in to account when measuring influence is sentimentWhat you tend to find though is that all publicity is good publicity, whether positive or negative the simple exposure tends to give the subject more influence over the target audience (as long as it’s not overwhelming negative)But not necessarily in the long term, gradually credibility is damaged
- So despite Nick Griffin’s performance on Question Time being roundly dismissed, he still managed to assert some influence, at least short termThe survey found that 22 per cent of voters would “seriously consider” voting for the BNP and the BNPreported 3,000 new applicationsHopefully this though is justlies, damn lies and statisticsLet’s hope 90% of statistics are made up