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Data Driven Social Media Webcast
This document discusses using data to drive social media marketing efforts. It provides insights from analyzing social media data from over 70,000 posts across 381 organizations. Key insights include that RSS automation is as effective as manual posting, scheduled posts generate clicks but not conversions, hashtag stuffing does not work, and Facebook influences more purchases than Twitter. The document also discusses measuring social media marketing efforts using a funnel to track awareness, interest, and actions. Metrics discussed include fans, clicks, and conversions to evaluate success.
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Data Driven Social Media Webcast
- 1. Data Driven SocialMedia ManagementUsing data, process, and iteration to turn your social media marketing into a revenue-generating machine.August 4, 2011
- 2. Who are thesepeople talking to me?Eric BoggsCEO, Argyle Social@ericboggsericboggs.comJason Falls@jasonfallssocialmediaexplorer.com(We’re smarter than we look. Hopefully.)
- 3. DetailsJason will leadQ/A at the end of the call.Tag your tweets/questions with #datadriven.We’re recording this shin dig.We’ll send an email follow up to everyone.Eric is @ericboggs.Jason is @jasonfalls.
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- 5. 15-second commercial:EricSocial ReviewWhitepaperhttp://ar.gy/reviewDo you have the fans you want?
- 6. What content resonateswith you audience?
- 7. How do youdrive more value through social?Using Data to Generate Insights
- 8. Data SourceA sliceof aggregate, anonymous Argyle user data.December 2010 through May 201170k+ posts381 organizations; all industries, all sizes
- 9. Insight #1 RSSAutomation WorksRSS automation is just as effective as manual posting at driving clicks and conversions.
- 10. Insight #2 ScheduledPosts Generate Clicks, Not ConversionsScheduled posting is a great tool if your goal is traffic, but not if you’re attempting to drive conversions.
- 11. Insight #3Hashtag StuffingDoesn’t WorkDon’t target content to hashtags.Target hashtags to content when relevant.
- 12. Insight #4Facebook InfluencesMore Purchases Than TwitterSource: Edison Research
- 13. Data-Driven Social MediaMarketingPracticing
- 14. The Social MediaMarketing FunnelYour goal as a marketer is to move people down the funnel.Key Insight: every step is measurable.Awareness: FansInterest: ClicksAction: Conversions
- 15. Measuring Awareness: FansRawnumbers and trends are easy but not very instructive. Compare with something real to make judgments:B2BCompare total fan count to lead count. Aim for 1:1 ratio.Consumer ProductsCompare fan count to customer count. Aim for 1:1 ratio.Newspapers & BlogsCompare fan count to website uniques. Aim for 15%.How many fans do you have?Fan count is important, but it’s just one of many numbers that lead to success in social media marketing.Fan / Follower counts are important for normalizing other social media marketing metrics!
- 16. Measuring Awareness: FansWhoare they?When it comes to your social audience, quality is just as important as quantity.Demographics—target and actual“Like Sources” and “External referrers”Fan churn (% of fans who unlike you)
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- 20. Response rateKey QuestionsWhatcontent drives interest?
- 21. What are youposting?
- 22. How are youposting it?Measuring Interest: ClicksMetrics in ActionIncrease in clicks is driven by increase posting frequencyIncrease in clicks is driven by more engaging contentDecrease in clicks is driven by less engaging contentDecrease in posts is drive by fewer posts—easy to fix!
Editor's Notes
- #2 Eric doing the intro.
- #3 Eric introduces himself, then introduces Jason.Point out that DJ Waldow is in the photo behind Jason…and took the photo of Eric.
- #5 Jason quick promo of his site and book.
- #6 Eric quick promo of whitepaper.
- #7 Intro slide – Eric frames the presentation.Examples of insights that we’ve gathered from customer data that might change the way you manage social…and as a prelude to a conversation to how you can use data from your own social media marketing efforts to make smarter marketing decisions.
- #8 Eric quickly explains the data source for the next few slides.
- #9 Eric – explain context of the data.Jason – suggest the action: use a service to automate posts via RSS. (Note: most RSS posts publish immediately, are not scheduled. Might need to delineate in the next slide.) if possible, schedule homegrown content to post multiple times. consider publishing content from other RSS feeds, can filter by tag or category.
- #10 Eric – explain the graph.Jason – explain the takeaways:Timeliness premium when it comes to transactions. The further into the future Argyle users scheduled posts, the less influence the posts had on revenue.Suggests a few things:- Marketers aren’t scheduling posts with a strong call-to-action- Followers are less responsive to “planned” content.- Time-sensitive call-to-action is compelling
- #11 Eric – explain slide.Jason – commentary:Data suggests that posts with hashtags rarely outperform posts without hashtags.Scenarios that work:- Moderately sized, well-targeted conferences – SocialFresh…not SXSW- Charitable causes- Highly engaged groups and chatsScenarios that don’t work:- Huge conferences- Generic tags- Trending topic spamRemember that your followers are your primary source of attention.
- #13 Eric - We’ve walked through a few examples that illustrate how data can drive social media marketing performance and – more importantly – marketing decisions. But we’re just talking about aggregates. The story gets more interesting when you start to look at your data in a similar fashion.
- #14 Eric - Social media marketing is a specialized version of marketing. Marketing is a business function. Business functions to drive outcomes. So by the transitive property you learned in 7th grade algebra, social media marketing is ultimately about driving business outcomes.Jason - Every step is measurable. You can’t optimize a two-step process - by breaking your social audience into segments, you can more easily move people down the funnel and measure your efforts.
- #15 Eric – audience size is the obvious place to start, but follower counts are often a polarizing metric.Jason – commentary re: follower counts, importance of quality, ratios as a smart way to normalize and benchmark follower data.
- #16 Let’s say you ran a contest last month. In this contest, you promised one lucky winner a free iPad. All that entrants had to do was like you on Facebook and post your contest to their wall. The contest was a huge success — in one week you doubled your fan count. Huzzah!In the following weeks, you’ve posted several links and a couple of offers. You were hoping to see a doubling of clicks on your links and conversions on your offers, but that didn’t happen. What’s going on?This is a straightforward example showing that raw fan / follower count isn’t very mean- ingful by itself — you also need to evaluate who your fans and followers are.