Tag Archives: social media

Watch our webinar: How Social Media Predicts Ticket Sales

Thanks to everyone who joined me last Thursday for my webinar on How Social Media Predicts Concert Ticket Sales. With over 50 attendees we had a great global audience and some really good questions at the end – I had to think on my feet! Feedback’s been really positive, so thank you all for attending.

If you missed it, no need to miss out – the full webinar can be downloaded here with slides and audio for the full experience. The webinar runs for 30 minutes, with an additional 5 minutes for questions.

Alternatively here’s our presentation ready to read:

If you liked that…

...Why not check out some of our other research studies, such as How Stuff Spreads, my webinar with Francesco D’Orazio on viral videos Gangnam Style and Harlem Shake – or some big thinking on The Future of Social Media Research.

…Or if you’d like to get in touch to talk about how the learnings might apply to your own business, or explore doing a similar study yourself, just send me an email at Jessica@Facegroup.com.

…If you’d like to learn more about our social data research platform Pulsar that powered this project, head on over to PulsarPlatform.com or email Info@Pulsarplatform.com and our team will get back to you right away.

Does social media drive sales? A research review

As social media research matures, the big question on everyone’s lips is “How can we connect this to other data?” More particularly, how can we connect it to what really matters to our business: sales?

Last week I gave a webinar on exactly this topic, sharing the results of our research study mapping social media buzz for 3 music events against ticket sales. You can find that presentation here on Slideshare, and download the full recording from this link.

In this blog, I want to put our work in context and map the wider industry thinking on this issue by summarising 5 other key social-to-sales research studies. There are a number of different ways that social media activity and sales can be compared, and I hope it’s useful to provide a summary and outline some of the key differences:

1. Buzzkill: Coca-Cola Finds No Sales Lift from Online Chatter
March 2013

Presenting at the Advertising Research Foundation’s Re:Think 2013 conference, Coke’s Eric Schmidt reported that “We didn’t see any statistically significant relationship between our buzz and our short-term sales.” (AdAge.com)

Note that Coke are still big believers in social media’s effectiveness as part of an integrated campaign: said Wendy Clark, “It’s the combination of owned, earned, shared and paid media connections – with social playing a crucial role at the heart of our activations – that creates marketplace impact, consumer engagement, brand love and brand value.”

IEDGE-cocacola-social-media-strategy-2

[image created by Coca Cola, via iEdge.eu]

But this study is evidence that overall social media buzz – the number of brand mentions – doesn’t necessarily correlate with sales. What might?

2. McKinsey Finds Social Buzz Can Affect Sales — Negatively, Anyway
June 2013

“The consulting firm initially couldn’t find any connection between social-media buzz and sales, either when looking at overall data changes or even by applying an algorithm to assign sentiment to the buzz. But McKinsey found the relationship between negative buzz and a decline in sales when it “hand tabulated” sentiment in social-media comments.” (AdAge.com)

This negative sentiment hurt signups by 8%, “offsetting their entire TV spend,” McKinsey principal Jonathan Gordan said at the Advertising Research Foundations Audience Measurement 8.0 conference in New York. Why? Because the negativity was primarily driven by complaints about the sign-up process and call-centre workers at the telecom provider. 

This shows how a relationship between social and sales can become visible when you drill down into more specific aspects of social data. Brand volumes didn’t impact telecoms sign-ups - but complaints about the sign-up process did.

3. Eventbrite: Facebook Drives More Ticket Sales Than Twitter And LinkedIn Across US And UK
April 2012

A different metric here – not social media volumes (aka the number of messages mentioning a brand), but the number of shares:

“The company says that Facebook is the king of all social networks when it comes to ticket sales. In the UK, if a person shares an event on Facebook, it generates an average of £2.25 ($3.60) in additional gross ticket sales. A share on Twitter, meanwhile, drives an average of £1.80 ($2.90), and an event shared on LinkedIn generates an average of £1.24 ($1.99) in additional event revenue.” (TechCrunch.com)

Eventbrite’s reason for why Facebook is bringing in more sales is good sense: “The connections we have on Facebook most closely represent the people we actually know and spend time with offline,” its researchers write.

Eventbrite facebook

4. Why Twitter Buzz ≠ Movie Ticket Sales
December 2012

“140 Proof looked at 25 major Hollywood films released in 2012, compiling data on each movie’s social media activity (mentions and hashtags) two weeks before, and two weeks after the release. It found that the number of overall Twitter mentions is a poor predictor of box office sales (unlike tweet volume and TV ratings). What did correlate to box office success was the number of tweets from influential tastemakers” (Readwrite.com)

Again, the relationship between social and sales doesn’t show up when you just look at raw volumes – but it is still there. Pulsar’s range of influencer metrics such as visibility and Klout filters can enable deeper analysis of how influence relates to sales, going beyond “number of tweets from tastemakers” to understanding how influence levels and sales-power scales.

5. Vision Critical: “From Social To Sale”

A totally different methodology – they’re not mapping activity in social media, or measuring clickthroughs from social channels, but rather surveying 5,657 people asking them to report whether they’d ever bought anything they’d seen on Twitter, Facebook or Pinterest.

This is worth doing because, “68% of Facebook users  are “lurkers” who post only rarely, so the influence of  social on their purchasing will not be visible from social  media analytics alone.” It’s a good reminder to think about social media users as much as an audience as content-creators - and that the path to purchase is more complex than old-fashioned sales funnel models, or simple ‘last-click’ attribution.

social-media-selling-for-un-sexy-brands

[image via Digital Information World]

Five studies, two key take-aways for understanding how social and sales connect:

1. Think about your user journey. How do people make a decision to buy your product – who or what might influence them? How  do people consume your product – is it particularly social, like something you would want to do with friends, or something worth boasting and sharing on Twitter and Facebook? Is it something people can purchase quickly online, or a more considered purchase?

2. Think about what aspect of social media to measure. It may not be simple volumes of brand messages that correlate with sales, but something more specific – such as influence, sentiment, or specific topics. Or perhaps it’s not messages at all but behaviours such as sharing. Most of all, remember to measure all of social media, not just owned channel activity: you’re looking for consumer behaviour, not just reactions to your own!

As these studies from a diverse range of brands show, social media does often connect to sales – not all of the time, but often with some statistical smarts & a deep knowledge of social, a link can be found.

Note that we’re saying “connect”, not “cause” - correlation can be assessed using relatively simple stats such as R-squared tests, but unpicking causation (Was it social media activity that made someone buy, or a price promotion, or TV advertising?) is a challenge for regression analysis and a bigger topic than we can discuss here.

And sometimes the relationship between social and sales can go both ways – not only “I buy a concert ticket because I saw the news on Twitter”, but also “I bought a concert ticket for my favourite band and I’m so excited, I want to tell everybody!” Perhaps brands can even hope for a virtuous circle of social driving sales, which drives further social activity, which drives even more sales… Fingers crossed!

Found this interesting? Read our social to sales study: get the presentation here on Slideshare, or download the webinar recording from this link. Thanks!

FACE’s ALS Ice Bucket Challenge

This week the inevitable happened. FACE became the next in a long line that has been nominated for ALS’ Ice Bucket Challenge. Yes, the social media phenomenon reached us in our London Office; we have Brightsource to thank for that!

ALS is a disease that many had never heard of or understood before the Ice Bucket Challenge; it has brought a huge amount of awareness to the charity and many similar non-profits who are trying to fight the cause.

The challenge represents more than just throwing iced cold water over your head. It shows us the incredible power of social media, and how quickly content can go viral.

We would like to thank Brightsource for the nomination. Our nominations go to Extendi, Sennep and Sensum. You have 24 hours – considering it’s a Friday we’ll give you until Monday.

Please donate what you can to the following links:

ALS in the US here:
https://secure2.convio.net/alsa/site/…

Or to the UK’s Motor Neurone Disease Association here:
http://www.mndassociation.org/news-and-events/Latest+News/the-mnd-ice-bucket-challenge

Find out more about ALS (known more commonly as Motor Neurone Disease in the UK or Lou Gehrig’s disease):

http://www.alsa.org/about-als/what-is…

Meet us at… Corporate Researchers Conference

Cat V Dog FLYER A5 FRONT

Corporate Researchers Conference (September 17-19, Chicago) is one of the only conferences created for and by corporate researchers, and FACE cannot wait to be there.

We will be putting you to the ultimate test with our Internet cats vs. Internet dogs battle, just like we did at Marketing Week Live in the UK. There, the more dominant force has been Internet cats. Now with the test going transatlantic for the first time, will the US be any different?

If you’re familiar with our experiment then you’ll know that everything we do at FACE is about understanding people. Once again we have teamed up with our friends at Sensum who specialise in mobile solutions for capturing, visualising and reporting engagement. Using Sensum’s proven biometric technology (yes, we are taking this seriously) we will measure people’s emotional reactions to one cat and one dog YouTube Buzzfeed video and solve this old-age debate once and for all.

 Although everyone already knows whether they’re a cat or dog person in real life, things may be a little different in the digital sphere. So when it comes to Internet pets, which one do people like more? If you’re attending Corporate Researchers Conference in September please come over and take the test to see not only which pet will win YOUR heart, but who is the winner overall. 

And while you’re there, please say hello to Andrew Needham (our CEO), Job Microsoft (UK MD), and Marc Geffen (US Research Manager) who are very much looking forward to meeting you.

Do you want to know how to identify top influencers within your category? Interested in the ingredients of a successful co-creation project? Or what it takes to become a socially intelligent business? Then come to our booth at stand 202 in the Vista Lounge, we’d love to tell you all about it.  We’ll also present our social data intelligence platform Pulsar which enables you to go beyond keyword tracking to map brand audiences, track how content spreads, and manage your teams to engage effectively with your customers in social media. 

Thank you to Buzzfeed for kindly allowing us to use their content for this experiment.

10 tactics for rigour in social media market research

Last week I went to the MRS Connected World conference, a really excellent event gathering together an inspiring crowd to talk about new technologies and consumer behaviours. Not just to listen – though listening was great! I was also putting forward the FACE point of view on a panel with Tom Ewing of Brainjuicer and Paul Edwards of Working Plural & JKR.

Our topic: “cutting through the noise”. Digital media & technology has generated a dramatic shift – for the first time in history, there’s not a shortage of information but an excess. But how to make sense of it all? How to find the insight amid the flood?

Our session was kindly written up by Research Live, so I won’t go into the details here. Instead, I want to pick up on a really smart question from an audience member – How do you do social media research with real rigour?

Great question. How do you move beyond a set of observations made on a vast and potentially rather amorphous dataset, to get to something we might actually call research? On the spot I came up with 3 ways  - but on reflection, there are more.

Here’s my top 10 ways to make your social media research rock solid:

1. Capture the complete universe

If the dataset’s incomplete (and especially if you don’t know what’s missing), you can’t say anything about how your findings relate to the wider universe. Tweets found directly through Twitter search are really no more than anecdote until you can contextualise them within a meaningful totality of everything that’s going on in social.

figure13

Image source: Mapping The Global Twitter Heartbeat: The Geography of Twitter, by Kalev H. Leetaru et al., 2012

So make sure you’re using a social media research tool that’s built on top of Twitter Firehose (the 100% data API) and robust blog, forum & news data collection.

Of course there’s still a gap between “everything said in social” and “everything people think”. But that’s true for every research method – this is a risk we can only minimise, never remove entirely.

2. Your search strategy is critical

Great data sources aren’t enough on their own – you’ve got to set them up right. If you’re searching for a particular category (e.g. haircare), you need to be confident you’ve collected the whole category – every possible way people can talk about hair, from products to styles and stylists, and verbs & adjectives as well as nouns. Just searching for all mentions of “hair” won’t cut it – you’re not capturing a meaningful totality.

How to build good search syntax: Brainstorm. Then test it in Twitter & Google search, then iterate to add in new words & phrases that come up. Analyst experience is key here to build a search strategy that’s both comprehensive and focused.

3. Qualify your quant insights

Social data is qual data at a mass scale, says Francesco D’Orazio, our chief technologist.

Numbers on their own aren’t insights. Positive sentiment is 20% – so what? What are people saying? What are the needs and emotions driving that figure, and why is it higher for one brand than another? Read, synthesise, code. Quote the actual messages, show the verbatim. Keep the people visible in how you tell your insights.

4. Quantify your qual insights

Say you’re doing an innovation project, find out that fighting frizz is the most important consumer haircare need. Your immediate client might love the depth of qual insight you can build from beauty blogs and forums… But she’s also got to communicate that insight around a larger organisation & to lots of people who won’t ever read your full deck.

So quantify that qual insight and rank it against other needs. Savvy use of Boolean search strings – NEAR operators & smart exclusion terms – can give you sensible approximate volumes for almost any concept. You’ll not capture every nuance, to be sure – but it’ll help support that qual insight as a really solid finding.

puggit pug AND rabbit

(Ok, not really an example of quantifying qual insights – but a very cute example of Boolean syntax!)

5. Can another analyst find the same insights?

Classic research methods such as data coding still can have a key role to play in turning social media data into insight. It provides a structured template for content analysis that helps iron out bias from the analyst’s own preconceptions. Instead you’ve got a random sample of 200 messages and a structured grid, and it’s easy to review across team to help standardise what you mean by particular categories and concepts.

6. Benchmark

Is this finding real? How much does it actually matter? Display your research findings contextualised against other brands, other categories, or as share of voice – so your reader can get a sense of proportion.

7. State what you don’t know, or can’t prove

  • e.g. “This visualisation is based on Twitter data, a channel used by 26% of the UK population.”
  • “Social media messages almost never identify a store by its exact street address, and only 1.6% of tweets have geolocation. Consequently we cannot locate the se complaints to specific store, only town or region level.”
  • “Social media data includes only information that is publicly available on the web, and not private email or text message data” (yes we get this one!)

Make the gaps explicit. It shows you know what you’re talking about – and helps ensure your insights are interpreted accurately. Overclaim isn’t rigorous!

8. Test hypotheses. Test a null hypothesis.

Having hypotheses makes your data useful – instead of just drawing a picture of the landscape, you’re trying to find out something specific. But in the spirit of scientific enquiry, proving a hypothesis isn’t just going out looking for data that supports it. It’s also about looking for data that supports the null hypothesis – the counter-possibility that nothing is happening, or the opposite. Look for both – and if all the evidence really falls on one side, then you can be confident that your finding is really robust.

Null hypothesis cartoon aliens socks

Testing the null hypothesis or counter-factuals  is also a great way to find interesting things you weren’t expecting (see point 10!)

9. Triangulate against other data sources

Extract everything you can from your client, from sales figures to  qual research to semiotics decks.  Turn these into hypotheses. Is your research supporting these? Building on them? Taking them a new direction? Or disagreeing entirely? All are legitimate outcomes – and putting your insights in this context makes them much easier for your client to use.

10. Don’t do social media research if it’s not the right way to answer your question

A contrarian point for closing – but here at FACE we’re honest about the fact that social media data can’t answer all research questions. Its genius is that the data we’re analysing is largely spontaneous and unprompted, making it a great way to find “unknown unknowns’ – the things you didn’t even know you wanted to know, or needed to ask.

Unknown-Knowns-invert-657x600

But sometimes you’ve got really specific questions to answer – how far are consumers prepared to trade off price vs. quality, perhaps, or whether a different shade of blue would make a better bottle top. And I’m afraid people just aren’t talking about bottle cap colours in social media… So you’d need to ask them directly: time for a focus group! Not social.

*

So that’s 10 ways to make your social media research really robust. Any more to add? Get in touch with us on Twitter – we’re @FaceResearch – and tell us your top tips! I (Jess) do a bunch of tweeting for FACE, so let’s keep the conversation going.

Or if you’ve got a really thorny research problem and you’re looking for a rigorous solution, get in touch with my colleague James on James.Hirst@Facegroup.com – we’d love to talk it through with you.