The real business value of social media lies in integrating social media data with other company datasets, such as sales and web analytics. Ever wanted to know more about how social media activity connects to purchase? How to measure social data and ROI? Which demographics give brands the best chance of social influencing sales? Here is the powerpoint slides from the webinar on September 25th.

1. www.facegroup.com
www.pulsarplatform.com
SOCIAL SALES STUDY
How social media activity connects to concert ticket sales
by Jessica Owens & Sameer Shah

2. What we did
We partnered with an events company to demonstrate how levels of social media activity can predict ticket sales. The hypothesis: social media drives awareness that can contribute to increased sales. We used Pulsar, our proprietary Social Data Intelligence platform, to track the social media discussion around three specific concerts. We analysed the entire online ecosystem, including Twitter, Facebook, Tumblr, YouTube, as well as forums, blogs and news sites. We explored the correlation between the volume of social media messages about concerts and ticket sales for these events. Our method then used R- squared statistical tests on data normalised logarithmically to control for irregular distributions.:
UK tour of a top female pop artist (female audience, aged 18-24)
A 1970’s rock band (predominantly male audience, 30s-50s)
A 2014 rock festival
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www.pulsarplatform.com

3. The rock festival: The daily level of social media activity spikes dramatically when acts are announced
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messages
3rd announcement of acts
2nd announcement of acts
1st announcement of acts, plus early-bird tickets notification
Source: Festival 2014 data, Date range: 14 Oct – 31 Dec 2013
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www.pulsarplatform.com

4. We then compared social media activity against ticket sales & website visits, and showed the data on a log scale to see the correlation better
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Social media messages
Ticket sales
Website visits
Source: Festival 2014 data, Date range: 14 Oct – 31 Dec 2013
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www.pulsarplatform.com

5. Plotting each day's "pair" of social volumes & ticket sales shows there is a 53% correlation between ticket sales and social media conversation
R² = 0.5259
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Social media messages (log)
Ticket sales (log)
Source: Festival 2014 data,
Date range: 14 Oct – 31 Dec 2013
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www.pulsarplatform.com

6. To put this in context… Social media activity links to ticket sales almost as strongly as visits to the ticket sales website (61% correlation)
Source: Festival 2014 data,
Date range: 14 Oct – 31 Dec 2013
61%
53%
Website visits
Social media messages
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www.pulsarplatform.com

7. To put it in plain English: Each 9 extra messages link to a +1 rise in seat sales
Source: Download Festival 2014 data,
Date range: 14 Oct – 31 Dec 2013
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www.pulsarplatform.com

8. The rock festival: Although Twitter drives most social media volume, public Facebook messages have the highest correlation with ticket sales
Source: Festival 2014 data,
Date range: 14 Oct – 31 Dec 2013
38%
52%
17%
Twitter
public Facebook
News & blogs
Share of total volume
88%
11%
1%
Total: 60,756 posts
Correlation with ticket sales
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www.pulsarplatform.com

9. Who contributes to the conversation?
Source: Festival 2014 data,
Date range: 14 Oct – 31 Dec 2013
Share of total volume
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Fans
(60%)
Based on coding of random sample of 100 messages
Media
(10%)
Promoters
(10%)
Artists & Festival official account
(20%)

10. Depending on the event, the predictive power of social can vary
Date range: 14 Oct – 31 Dec 2013
UK tour of a world- renowned female pop artist
A 1970’s rock band
A 2014 rock festival
Volume predicts 53% of sales
Volume predicts 49% of sales
Volume predicts 22% of sales
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www.pulsarplatform.com

11. Reason 1: Relevance
Social media discussion has to be tightly focused on the event itself
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All discussion about the rock festival is about the concert event. There's no other way people can mention it. So this even saw the strongest correlation with sales figures (53%).
But for our pop artist, initial analysis of all social media buzz about the artist found no correlation with UK tour sales at all.
It's only when we narrowed the social data down to specific mentions of the tour by name, and in the UK only, that the strongest relationship with social media data emerged.

12. Relevance may explain the results of other social-to-sales studies too
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Measuring: overall social buzz vs. sales
"We didn't see any statistically significant relationship between our buzz and our short-term sales." (Ad Age, March 2013)
Measuring: negative sentiment vs. sales
"The consulting firm found bad buzz for an unnamed telecom client hurt signups by 8%, offsetting their entire TV spend." (Ad Age, June 2013)

13. Reason 2: Demographics
Social predicts sales best for a younger audience who use it more
Source: Kantar & TNS Omnibus study for eMarketer, 2013
Age 65+
26% use social networks
6% use Twitter
Age 18-24
95% use social networks
39% use Twitter
Social media demographics by age:
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14. In the case of the 1970’s rock band, news visibility is the most predictive factor – still indicating that awareness is still key to sales
Source: A 1970s Rock band data,
Date range: Date range: 13 Nov – 15 Jan
R² = 0.298
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UK visibility (log)
Ticket sales (log)
The older audience is less present on social networks like Twitter or Facebook – news may be a more relevant channel. News sites tend to have high visibility, Pulsar's proprietary metric for establishing content's influence and reach.
While social media volumes correlated only 22% with sales, that rises to 30% when using visibility, which weights the impact of the media most relevant to this audience more highly.
www.facegroup.com
www.pulsarplatform.com

15. Other studies have also found stronger relationships when they look beyond just social media volume
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Measuring: social media shares vs. sales In the UK:
A Facebook share generates £2.25 in additional gross ticket sales
Twitter - £1.80
LinkedIn - £1.24 (Techcrunch, April 2012)
Measuring: influencers' messages vs. sales
"The number of overall Twitter mentions is a poor predictor of box office sales [for Hollywood films]. What did correlate to box office success was the number of tweets from influential tastemakers." (Readwrite.com, Dec 2012)

16. Takeaways
1.Social media buzz and sales can correlate strongly – over 50%
2.The type of social media activity that can predict sales may vary between brands
3.We saw stronger results for products aimed at a younger audience who use social media more
4.The social data you're measuring needs to be specifically about the product in question – results are weaker for general "brand buzz"
5.We see stronger results where social can provide a direct path to purchase (e.g. event tickets)
6.Finding a relationship between social & sales takes exploration of different aspects of social and different aspects of sales
www.facegroup.com
www.pulsarplatform.com

17. THANK YOU
Research team: Jessica Owens (@hautepop)
Sameer Shah (@thesquidboylike)
If you want to find out more about this study or about our research in general, please get in touch at info@facegroup.com.