We’re Hiring!


About us: 

The Big Boulder Initiative is an industry trade association wholly dedicated to the advancement of social data in businesses and organizations of all kinds. Our mission is to bring together representatives from companies within the ecosystem to collectively address key challenges in order to establish the foundation for the long­term success of the social data industry.

A bit about the job:

We are looking for a smart, driven, and energetic Marketing Manager to help manage and run the Big Boulder Initiative organization day­to­day. In this role, you will be responsible for the development, implementation, execution, and maintenance of a variety of projects including membership sales, member marketing and communication programs, social media content creation, conference / event coordination, and more. This position requires an individual who is passionate about marketing and possesses the ability to flawlessly manage projects from inception to completion without missing details. Ideally, this position is based in Boulder, but remote is ok as well.


Market the Big Boulder Initiative to members and prospects

  • Work closely with the Board of Directors to help manage and oversee all aspect of the
    organization to drive thought leadership and maintain a high profile in the industry
  • Develop and implement marketing campaigns to drive membership sales and overall
    member engagement
  • Drive the creation of marketing assets that clearly communicate the benefits of BBI
    membership and how to get involved
  • Create content and manage editorial calendar for the blog, Twitter, Facebook, etc. to
    develop a strong social media presence
  • Manage PR efforts including writing and releasing press releases and managing all
    press outreach and inbounds

Run events, both big and small

  • Coordinate member events including the annual Big Boulder conference, quarterly
    regional meetups and quarterly round tables

Community Management

  • Facilitate conversations and connections among our diverse member community
  • Create and deploy communication programs to drive member engagement and foster
    the development of the member community
  • Manage the Slack instance for our membership
  • Identify members of the community to drive key conversation topics
  • Promote active areas of conversation to the wider BBI membership

Run the operations of the Big Boulder Initiative

  • Identify new target members and establish engagement strategies to drive member
    conversion rates
  • Manage membership sales and renewals and maintain the membership database
  • Maintain organization website to ensure that it tells a clear, compelling story about our organization, its mission, and the benefits of BBI membership
  • Own and manage all systems and tools (website, email marketing, Slack, membership database, payments, etc.)

Who we are looking for:

We are hiring the right person, so feel free to apply. Here are some of the areas we will be looking at:

  • BA or BS preferably in marketing, communications, or business management
  • 5+ years experience in marketing, communications, and project coordination
  • Self­directed with a strong desire for professional growth through results­driven goals
  • Extreme attention to detail with strong organizational and multitasking skills
  • Professional written and verbal communication skills
  • Experience with email marketing strategy
  • Excellence PR skills including press communication and outreach
  • Prior experience in conference planning / events production
  • Expertise in business use of all major social media platforms
  • Ability to negotiate contracts and manage outside vendors
  • CMS experience a plus
  • Database development experience a plus
  • Email client (Constant Contact, MailChimp) experience a plus
  • WordPress administration experience a plus
  • Marketing Automation software experience a plus
  • CRM software experience a plus
  • Graphic design experience a plus


Interested? Send your resume to info@bbi.org




Social Data in the Fashion Industry – Recap



Fashion, Data, and Social Media: The Findings from BBI’s Latest MeetUp

Fashion is never finished and neither is the data that helps the world’s biggest fashion brands make informed decisions about their audiences and their products.

That’s why we decided to explore the topic in-depth with the help of our friends at Big Boulder Initiative (BBI). Co-hosted by Bitly and Brandwatch, experts from both organizations and Gilt came together to dig into the numbers behind some of fashion’s biggest trends in this year.

Taking Networks Seriously

An October report from Brandwatch analyzed trends, topics and audiences for Twitter and Facebook conversations surrounding top luxury brands like Chanel, Dior, Calvin Klein and more. What was the key takeaway?

99.63% of the conversation is driven by consumers, according to Paul Siegel, data scientist.

And what do we know about those consumers? They’re overwhelmingly female, for starters.

The report also breaks down the types of professions tweeting most frequently about these brands. Artists, executives, students, and journalists top the list. Brandwatch also found that these people tend to rally around other interests like music, sports, and family and parenting.


This chart looks at the type of clothing people were talking about, as well as their color preferences.

After considering the 30,000-foot view, it’s important to look at the local story, according to Siegel. Brands have to begin considering more targeted questions like: Who are the movers and shakers in the conversation? What are their spheres of influence? What content is being shared and how?

Unlocking the Power of the Link

In a survey featured on Social Media Today, 78% of respondents said that companies’ social media posts impact their purchases and 4 in 10 social media users have purchased an item online or in-store after sharing it or marking it as a favorite on Twitter, Facebook or Pinterest.

With a number of the world’s major fashion brands using our enterprise product, Bitly has access to a wealth of data like the types of devices consumers are using, what days they’re most active, and what social channels are getting the most love. And sometimes the data can surprise you.

Caitlin Rashbaum, customer success manager at Bitly, compared clicks between Black Friday and Cyber Monday for one major fashion brand. One might assume that Black Friday would see fewer clicks and more in-store purchases, while Cyber Monday would see more clicks with less brick-and-mortar activity.

However, Black Friday proved to be a much more fruitful day for digital, seeing 116,504 clicks with 104,277 uniques, versus Monday, which saw 44,710 clicks with 38,355 uniques. This simple comparison may very well impact the company’s social strategy next year and beyond.


This chart illustrates encodes (shortened URLs) and decodes (clicks on those URLs).

Caitlin also shared an analysis of all 2015 encodes (Bitlinks created to fashio brand domains) and decodes data (clicks on Bitlinks to fashion brand domains).

Overall, the fashion world saw the most social engagement during Memorial Day Weekend, Fashion Week, Black Friday & Cyber Monday, and December 1.

December 1 was the most active  day of the year when it came to social engagement, with 4.3 million links created and 152 million clicks across the top ten fashion brands using Bitly.

Visualizing the Wisdom of the Crowd

Gilt offers its members top designer labels at up to 70% off retail. Seven million members, to be exact.Igor Elbert, Gilt’s principal data scientist, gave meetup attendees a peek behind what reach like that looks like:

5 million-plus daily email distribution

  • 2,500 brand relationships
  • 5.6 million-plus mobile downloads with more than 2 million push notifications
  • 500 million-plus monthly press impressions
  • 6 million-plus unique visitors per month
  • 20-40% of sales generated through mobile
  • 1 million-plus social media participants across Twitter, Facebook, Pinterest and more

In addition, Gilt members are affluent, young and educated. A whopping 89% of them are active on social.

All of this data results in many large affinity matrices that help the team personalize algorithms for each user. Like that Louis Vuitton satchel but feel the prices are a little out of reach? You’ll get a notification that other people liked a similar bag that may be more affordable. Like these heels from Dolce & Gabbana? They might pair nicely with this little black dress. Mapping tools help organize and make sense of the data.



2016 and Beyond

There were two major themes in all three presentations: personalization and customer experience. Anticipating users’ wants and needs (especially when they might not even be aware of them), and getting them from Point A to Point B in as few steps as possible — especially on mobile — will, more than ever, differentiate good companies from great companies.

Looking Forward: Social Data and Prediction

The Social Data group on Meetup recently convened at Twitter in London for a session entitled ‘Understanding the Global Pulse using Social Data’. Following on from BBI Board Member Farida Vis’ account of their first meet up at Twitter in April, this second event gave an overview of how social data is being approached by both industry and academia. These meet ups are co-sponsored with BBI, helping to provide speakers and general support.

Social data, specifically data arising from social media, is becoming an increasingly important field for research across multiple sectors, from marketing and publishing to government and academia. Publications by Ipsos MORI, Comscore and Demos demonstrate the ways in which online public attitudes and behaviours are being analysed in order to understand not just what is happening now, but how to anticipate the future and facilitate behavioural change.

Francesco D’Orazio (@abc3d)
Opening the session was Francesco D’Orazio, VP of Product at Pulsar, and member of the Visual Social Media Lab. He spoke about a new project, which looks at the shift in public discourse on Twitter that occurred in the wake of the death of three-year old Syrian refugee Aylan Kurdi, whose body washed up on Bodrum beach in Turkey in early September. Two photographs were widely shared, including on social media, changing how these issues were discussed. As D’Orazio’s graph shows, below, the photograph’s emergence caused a sizable spike in the use of the term ‘refugee’, demonstrating that the image influenced public discussion of the wider crisis. Further results of this study will be shared by the Visual Social Media Lab towards the end of October, as part of a project on The Iconic Image on Social Media.

How a single image changed the debate on immigration

Azeem Azhar (@azeem)
Azeem Azhar, the founder of PeerIndex, discussed the growing application of AI in social media analytics, in a talk entitled: “From counting likes to teaching HAL: The future of social data”. He began by giving an overview of his background in social media research, relating to the development of tools for determining relative levels of expertise online. Azhar’s vision for the future of social data had four components: social data would become invaluable, everywhere, every larger in scale, and increasingly the domain of bots and AI. Azhar showed us two examples of AI – a rather creepy robot, and a chat bot app called XiaoIce – in which the ‘intelligence’ is the result of information aggregated from online sources. Some of the results of this are a little uncanny; almost human, but not quite.

Using an example of machine learning in the form of the site Crystal Knows, Azhar demonstrated the connection between ascertaining personality types from online data, and developing ways to communicate with them (e.g. in the form of advertising).

Analytic Value Escalator

Although this knowledge of how to approach a potential customer is of obvious use, the value of social media can be thought of using Gartner’s analytic value escalator (above), in which knowing what happened, and why, is supplanted by an ability to use datasets to predict what might happen in the future. In this field, the site Dataminr uses Twitter conversations to predict what was going to trend, and to ascertain any relationship between online discussion and factors such as future stock market performance. The future AI bot will therefore be doubly uncanny, in that it will know not just how to respond to us, but also anticipate what we might wish to discuss in advance.

Chris Austin
As the head of analytics and insight at The Guardian, Austin’s role also involved mapping a kind of ‘value escalator’, progressing from simply considering what has happened with regards to online engagement with the newspaper’s content, towards understanding why, and what this indicates for future approaches.

I was particularly struck by his diagram that mapped out several pathways for progressing through a project (below), navigating between the extremes of chaos / structure and unknown / facts. His favoured approach entailed an interconnection between logic and data, which although somewhat chaotic at times, yielded an end result that was stable and strong. I’m very much in favour of this kind of transparency, in which we get to see the process of working out what to do with data, as well as its results. As any social media researcher will know, there are often periods of outright chaos, in which the data is doing or showing something unusual. Austin’s approach encourages us to go along with the chaos, and view it as not an indicator that something is wrong, but as an integral part of the process that works to test our ideas and to validate them.


This discussion was then followed by an overview of the Guardian’s in-house monitoring software, Ophan, by Chris Moran (see screenshot below). The Ophan dashboard can present an enormous amount of data regarding individual stories and their performance, in terms of page views, engagement time, sites of referral, and geographical location of viewers.


Moran described how this kind of tracking, through social data, is used for planning future activities, in which the ‘story of the story’ indicates how to improve viewer engagement. As Moran argues, this isn’t just a question of counting page views, but rather observing which sites viewers are referred from, and how a conversation develops around what tweets feature links to the post.

Alasdair Rae (@undertheraedar)
Alasdair Rae is a senior lecturer at the University of Sheffield, in the department of Urban Studies and Planning. His talk – ‘Searching for knowledge – what can search data tell us about future trends?’ – followed on from Azhar’s discussion of analysis that yields predictive results, in that he traced the correlation between searches on Rightmove – a real estate search site –and the volume of properties sold during a given period.

To begin with, Rae gave an interesting overview of cases where correlations are found to be of little use or relevance. Using examples from Google Correlate (including the rather ingenious example of using ‘Google correlate’ itself as a search term), Rae showed the danger of overstating the importance of statistical patterns. He also demonstrated that search terms do not always entail what we might expect, in that searches for party leaders in the run up to the recent UK election did not necessary indicate who someone was going to vote for, but could simply indicate an interest (both positive and negative) in that person.

Having made this cautionary point, Rae then discussed some connections which are useful, such as that between searches for high value items such as cars, and the health of the economy more generally. Citing a number of papers (two of which are linked to below), Rae outlined some of the ways in which search patterns on Rightmove can indicate future housing market trends. He concluded with a graphic that combined user-defined search areas, in ways that showed users closely following certain features, such as the main roads into and around towns such as St. Albans. Here, the social data replicates and reconfirms the trends in the housing market, centring on desirable areas, such as the centre of London, which appears to glow white hot. Changes in these search areas, like changes in the other forms of data we were shown this evening, is a reflection of what is happening on a wider scale in the economy and in people’s tastes.


This meet up demonstrated how the commercial processes and benefits of analysing various forms of online social data can be adapted and examined within an academic context. Particularly within the field of social data studies – in which research is focused on the information generated through a multiplicity of online interactions – academics need to keep abreast of the innovations happening within industry. As this meet up showed, social data tells us not just something about society, but also about the forces that can come to shape society in future, in that predictive technologies demonstrate a desire to anticipate the market, and the consumer, in advance. Academia needs to be aware of these discussions, in order to provide a critical response to them, and to assist in developing ethical and sustainable forms of practice. But academia needs also to utilise social data, in order to gain useful insights into contemporary social issues, such as the migrant / refugee crisis discussed by D’Orazio. Events such as this one are therefore important for academics, as they are an opportunity to consider potential research techniques and topics, and a chance to collaborate with industry to develop joint approaches to the use of social data.


Choi, H., & Varian, H. (2012). Predicting the present with Google trends. Economic Record, 88 (1), pp. 2–9. http://cs.wellesley.edu/~cs315/315_PPTs/CS315-L19-CS315-L19-PredictingWithSocialMedia/Predicting-the-present-Choi-Varian.pdf

Rae, A. (2015). Online Housing Search and the Geography of Submarkets. Housing Studies, 30 (3), pp. 453­–472. http://www.tandfonline.com/doi/abs/10.1080/02673037.2014.974142#.Vg0wBLdQh1Q

About the Author

Anne Burns is a Research Associate at the University of Sheffield’s Visual Social Media lab, and is conducting an ethnography for the Picturing the Social project, that will explore the practices and forms of social media photography. Anne writes a weekly research blog, through which she will be sharing some of the findings from the ethnography. This can be found here. Anne has recently obtained her PhD from the Loughborough University School of Art. Her PhD focused on a connection between the discussion of women’s photographic practices and social discipline. Principally, Anne analysed how the devaluing of certain types of photograph (such as selfies) or behaviour (such as the pouting ‘duckface’) within popular discourse is used to classify and marginalize women. Her PhD blog, which discusses photography, social media and feminism, can be found here