Data Driven Social Media Marketing - Social Fresh Baltimore 2011
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The document presents data and analysis from social media marketing campaigns run by Argyle Social. Various metrics are shown comparing the performance of posts distributed via RSS versus manually, the impact of including hashtags, and how promoter, balanced, and curator type accounts differ in their engagement and conversion rates. Key findings indicate that timeliness impacts clicks and revenue, posts with hashtags do not consistently outperform, and curator type accounts have the highest conversion rates with balanced accounts in the middle and promoters the lowest.
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Data Driven Social Media Marketing - Social Fresh Baltimore 2011
- 1. Presented November 30, 2011 at Social Fresh Baltimore @argylesocial
- 4. In God we trust. All others must bring data. W. Edwards Deming @argylesocial
- 6. The Elements of Statistical Learning, 2nd Edition, Preface Hastie, Tibshirani, Friedmand @argylesocial
- 7. • • • @argylesocial
- 8. • • • @argylesocial
- 9. Clicks by Posting Method Revenue by Posting Method 30 $300 25 $250 20 $200 Revenue Clicks 15 $150 10 $100 5 $50 0 $0 RSS Manual RSS Manual Posting Method Posting Method @argylesocial
- 10. Clicks by Posting Method Revenue by Posting Method 30 $300 25 $250 20 $200 Revenue Clicks 15 $150 10 $100 5 $50 0 $0 RSS Manual RSS Manual Posting Method Posting Method @argylesocial
- 11. Timeliness vs. Traffic Timeliness vs. Influenced Revenue 25 $400 $350 20 $300 Influenced Revenue $250 15 Clicks $200 10 $150 $100 5 $50 0 $- Posted Immediately Scheduled for Later Posting Timeframe Posting Delay @argylesocial
- 12. Timeliness vs. Traffic Timeliness vs. Influenced Revenue 25 $400 $350 20 $300 Influenced Revenue $250 15 Clicks $200 10 $150 $100 5 $50 0 $- Posted Immediately Scheduled for Later Posting Timeframe Posting Delay @argylesocial
- 13. How Effective are Posts with Relative Performance of Hashtag vs Non- Hashtags? Hashtag Posts 25 # of Twiter Accounts 20 26% 15 53% 21% 10 5 Posts with Hashtags Underperform 0 -70% -30% 10% 50% 90% No Significant Difference Posts with Hashtags Outperform Performance Increase (Decrease) of Posts with Hashtags @argylesocial
- 14. How Effective are Posts with Relative Performance of Hashtag vs Non- Hashtags? Hashtag Posts 25 # of Twiter Accounts 20 26% 15 53% 21% 10 5 Posts with Hashtags Underperform 0 -70% -30% 10% 50% 90% No Significant Difference Posts with Hashtags Outperform Performance Increase (Decrease) of Posts with Hashtags @argylesocial
- 15. Sample Promoters: link to their own site more than 50% of the time. Breakdown Balanced: link to their own site between 25% and 50% of the time. Curators: link to their own site less than 25% of the time. Clicks Per Post Click To Conversion Post Conversion Rate Promoters Promoters Promoters Balanced Balanced Balanced Curators Curators Curators 0 20 40 60 0.0% 1.0% 2.0% 3.0% 0.0% 50.0% 100.0% 150.0% @argylesocial
- 16. Sample Promoters: link to their own site more than 50% of the time. Breakdown Balanced: link to their own site between 25% and 50% of the time. Curators: link to their own site less than 25% of the time. Clicks Per Post Click To Conversion Post Conversion Rate Promoters Promoters Promoters Balanced Balanced Balanced Curators Curators Curators 0 20 40 60 0.0% 1.0% 2.0% 3.0% 0.0% 50.0% 100.0% 150.0% @argylesocial
- 17. B2C Facebook Engagement B2C Facebook Engagement by Weekday/Weekend by Saturday/Sunday 100% 50% 100% 50% 90% 40% 90% 40% Engagement Rate Variance Engagement Rate Variance 80% 30% 80% 30% 70% 20% 70% 20% % of Brand Posts % of Brand Posts 60% 10% 60% Significant! 10% 50% 0% 50% 0% 40% -10% 40% -10% 30% -20% 30% -20% 20% Significant! -30% 20% -30% 10% -40% 10% -40% 0% -50% 0% -50% Weekday Weekend Saturday Sunday Posts Engagement Posts Engagement @argylesocial
- 18. B2C Facebook Engagement B2C Facebook Engagement by Weekday/Weekend by Saturday/Sunday 100% 50% 100% 50% 90% 40% 90% 40% Engagement Rate Variance Engagement Rate Variance 80% 30% 80% 30% 70% 20% 70% 20% % of Brand Posts % of Brand Posts 60% 10% 60% Significant! 10% 50% 0% 50% 0% 40% -10% 40% -10% 30% -20% 30% -20% 20% Significant! -30% 20% -30% 10% -40% 10% -40% 0% -50% 0% -50% Weekday Weekend Saturday Sunday Posts Engagement Posts Engagement @argylesocial
- 19. • • • @argylesocial
- 20. Do or do not. There is no try. ~Albus Dumbledore Slides at ar.gy/socialbaltimore Thank you very much. Eric Boggs @ericboggs http://argylesocial.com @argylesocial
Editor's Notes
- Eric doing the intro.
- Eric doing the intro.
- 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.
- 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.
- 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.
- 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.
- Eric quickly explains the data source for the next few slides.
- 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.
- 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.
- 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
- 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
- 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.
- 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.
- 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.