Category Archives: Pulsar

Why Big Data is a human problem, not a technology one

At the beginning of October our VP of Products Francesco D’Orazio hosted a talk at the Internet & Mobile World conference in Romania. This event was focused highly on the digital transformation of businesses, aiming to highlight the online and mobile challenges they are faced with. Leading experts from the technology world gathered to share their thoughts on what’s driving forward the industry and how this translates to business.

“Big data” has been around for a few years now but for every hundred people talking about it there’s probably only one actually doing it. As a result Big Data has become the preferred vehicle for inflated expectations and misguided strategy.

As always, the seed of the issue is in the expression itself. Big Data is not so much about a quality of the data or the tools to mine it, it’s about a new approach to product, policy or business strategy design. And that’s way harder and trickier to implement than any new technology stack.

In Fran’s talk from the Internet & Mobile World, he looks at where Big Data is going, what are the real opportunities, limitations and dangers and what we can do to stop talking about it and start doing it today.

Please see below if you want to have a closer look at the slides Fran used in his presentation:

If you want to learn more about how social data can positively impact your company, get in touch by emailing: Francesco.dorazio@facegroup.com

How We Became A Software Company: 5 steps to the birth of Pulsar

“We all need to become software companies!” That’s the message from John C McCarthy in his latest Forrester Research report which in a nutshell proposes that software is a central driver of brand and financial growth.

In his post earlier this week, our CEO Andrew Needham discussed the “business of products” and how to build them, touching upon ‘Lean Startup’ methods and Marc Andreesen’s quote that “all companies are now software companies”.

The big question you are left with is how the heck do you become a software company?

At FACE, we’re now a software company (as well as a research & innovation firm). Many of you reading this will have followed our journey over the past 5 years, culminating in the 2013 launch of Pulsar, a SAAS (software as a service) social data intelligence tool.

In this blog post, I want to share how we did this.

Why? As an innovation consultancy, we’re advising brands every day on how to build products and services. Yet unlike almost every other company in this space, and even many product design firms, we have first hand experience of building products ourselves – one that’s succeeded at scale, growing seven-figure sales revenues in its first year. The story of how we built Pulsar is inscribed deep in the DNA of what FACE is as a brand, and it’s a story we want to tell much more powerfully going into 2015.

Pulsar Social Data Intelligence-01 (1)

socia_crisis5

So here’s the first installment: 5 ways we turned ourselves into software thinkers.

1. We challenged ourselves to do our jobs better 

As researchers with a passion for technology we were early users of social analytic software and we quickly learnt the limitations of the tools in the market. As part of a research innovation exercise, the team led by Francesco D’Orazio identified the key areas where we had to develop manual workarounds on client projects such as topic, network and audience analysis. A lightbulb went off when we looked at the results, which showed we could both reduce the amount of time spent on analytics and improve the quality of our work if we could automate these steps. Then we realised that no tool was offering this…

2. We became obsessed with other people’s jobs

We then looked outside of our company and our own jobs as researchers, and set about evaluating which other jobs could be improved by a tool that could automate these analyses. It was a long list: social media marketing, PR, brand management, corporate relations, advertising agencies, financial forecasting, media planning…And so on. It started to look like a viable market opportunity.

3. We started to build 

Looking outside and seeing the opportunity to improve jobs across so many industries gave us the confidence to start the pilot build of tour own social analytics product. For 18 months we built Pulsar with a small budget and team, working all the time with our clients to pilot a wide range of research projects to understand needs, features and use cases. Without having a research team in house who served as ‘internal customers’, this “listen to your users” process would have been much harder and much less powerful. To our delight, after 18 months, a lot of hard work and development, we had happy clients, happy researchers and most importantly a working product prototype – which we named Pulsar.

4. We thought BIG…

In the summer of 2012 we were so excited by the prototype of Pulsar that we started to think big. What if we scaled up the product? What if we could sell this to other companies and work with them on an ongoing basis?, What if we could sell this to lots of people all over the world doing lots of jobs? We then developed a plan to turn Pulsar into a leading platform for social intelligence. In 2013 we rolled out our big thinking by creating new teams in the company under the Pulsar brand: product, development, sales, marketing and account management. Now we really were a software company.

5. …But fought to stay Agile

After 18 months of launching Pulsar and hundreds of clients later what we have learnt about being a software company? It’s really incredibly simple: to win and keep customers as a software business, you have to be obsessed about how you can make your customers’ jobs better – and you have to keep innovating. Our development team follow Agile ‘scrum’ methodology, working on a rapid response development cycle where every aspect of development — requirements, design, and so on — is continually revisited and recalibrated to ensure it’s both deliverable and meets customer needs.

But it becomes something we’ve embraced deeper into the business too.

We’re developing continuous delivery research models, delivering social insights not just through big category landscape reports but also monthly newsletters & the Pulsar dashboard itself.

We passionately believe that “business people and developers” – that is, clients and customers, brands and consumers – have to work together to create products of value, and that’s why we still champion co-creation.

And our version of “working software” is actionable, direct recommendations that provide very specific guidance for what to do and how to change your product or brand.

So that’s how we built Pulsar – and changed ourselves as a research business in the process.

If you’d like to talk further about how we can change your business, whether that’s service design or new product development or just a difficult problem you need to solve – send me an email: Job.Muscroft@Facegroup.com

Previous post: Andrew Needham on How to Succeed in the Business of Products

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…

The Samsung vs. Apple court case shows the value of social media research

An excellent case study demonstrating the value of social media research has just emerged from an unlikely source: the Apple vs. Samsung patent dispute.

Apple-Samsung-Trial

Documents shared as part of the court case reveal some fascinating information about how the two companies were thinking about social data in 2013.

It shouldn’t still bear saying in 2014, but the messages seems slow in getting though: social media data isn’t just about “looking back” at campaigns or the last quarter’s KPIs. Samsung recognised the power of social data for “thinking forward”, for understanding customer needs strategically to feed into product innovation and early-stage comms planning. Here at FACE, we think this is an incredibly valuable and under-used use-case.

Here’s how it works:

1. Samsung used social data strategically: to attack Apple

From Neal Ungerleider in FastCo: Networked Insights Reveals How Samsung Used Social Media to Hack the iPhone:

“Samsung took on a company with the arguably most successful consumer product ever created,” Networked Insights CEO Dan Neely told Fast Company. “Samsung asked us how to use analytics to attack Apple.”

[...] Using aggregated online posts and machine learning techniques, Samsung found several specific weak spots where they could outperform Apple. Customers specifically complained about the iPhone’s comparatively poor battery life, the inefficiencies of Apple Maps, how small the screen was, unhappiness with the Lightning cable, the lack of customization, Siri, and the iPhone’s fragility. Samsung felt that it could compete with Apple on most of these points–and, importantly, that they hard data to back up these consumer preferences.

When working with Networked Insights, a big part of Samsung’s strategy was to vacuum up any information on the iPhone 5 that was posted to social media. This meant using the dashboard they licensed to obtain every iPhone-related post on Tumblr, Twitter, Disqus (a popular commenting platform), WordPress, and YouTube, as well as new hits on Google. This information was then classified, as Neely put it, “15,000 different ways.” A big part of the problem for Samsung and others, Neely said, was the difference in extracting relevant information when they needed it versus finding erroneous information on other aspects of individual customers that were irrelevant to the task at hand. That meant a lot of data processing and fine-tuned analytics.

Importantly, Samsung used the dashboard to find what people were posting online about the iPhone–rather than just looking for posts about Samsung’s own products. They then identified specific complaints about the iPhone where their own products outperformed Apple’s products, and tweaked marketing campaigns to emphasize these Samsung strong points.

So: social media research isn’t just about tracking your own brand activity.

It’s incredibly powerful when you search for unmet needs and pain points – what are the gaps where consumer desires aren’t being fulfilled? Do this across a category (e.g. smartphones) or a competitive set (Apple, Samsung, HTC, Sony Xperia, Nexus, Motorola) to identify the “whitespace” opportunities that  aren’t currently being met.

As such, social media has just as much of a forward-looking role to play in innovation and NPD as it does “looking back” at campaign performance and the past quarter’s KPIs. Use it to shape campaigns and communications, not just to measure their impact.

2. Apple thought it was “nuts” to pay for social media monitoring tools. Their loss

Business Insider’s Jay Yarrow spotted something else interesting in the court documents:

Jay Yarow quote

Apple famously don’t do research, you say? No, Apple do do research – but they don’t necessarily do it well, as Tom Ewing recently illustrated.

You’d see the occasional interesting message if you just look at mentions of “iPhone 5″ through Twitter search… But also an awful lot of noise, at a million mentions per day kind of scale. It’d only be through luck that you might stumble across a message that’d spark any strategic consideration.

You want to understand the relative dissatisfaction with battery life, screen size, and poor signal reception? You need a social data research platform. Social media monitoring tools make this data analysable as a whole  in a way that free online tools simply can’t. For example our platform Pulsar (pulsarplatform.com) collects over 1MB metadata around each tweet, making big datasets like this powerfully segmentable by sentiment, channel, hour, influence level, profile bio and other demographics – allowing for a really fine-grained analysis of not just what people are saying, but who and why.

Technology and data augmentations enable the unmet needs to be identified, quantified and ranked. Use a tree graph to visualise the most common words and phrases that follow “I love…” and “I hate…”. Use semantic analysis to aggregate topics, and compare the top topics across the range of positive, negative and neutral sentiment scores. Start coding tweets into clusters, and use machine learning to extend this across the whole dataset.

Through structured analysis, the depth of insight that can be gained from social data is vast – Samsung realised this, Apple didn’t.

3. What we’ve done

This story was met by us at FACE with a nod of recognition – we have been using social data beyond reputation management for many years now.

Here’s a couple of examples of previous work:

i) Mapping the 4G mobile launch

EE Launch Event..Mandatory Credit Tom Oldham/Tom Dymond

Like Network Insights with Samsung, we also dug into what people were saying around 4G to identify complaints and pain points. What topics were driving discussion – signal, pricing, contracts/tariffs, or the iPhone? For each we identified the specific customer pain points our client needed to address in both comms and their product offer.

“WHAT EVEN IS 4G THOUGH I DON’T UNDERSTAND” – tweet, Sept 2013

But it turned out the biggest unmet need was understanding – a high share of discussion came from people expressing their total bewilderment at the new, high-speed mobile spectrum band.  We used social data to identify and categorise people’s questions, helping our client (a mobile operator) recognise and simplify the messages they needed to communicate to help people understand the new proposition.

ii) “Designing Relevance” for Nokia

Here at FACE we’ve been using social data for strategic insight for years. Back in 2010, Francesco D’Orazio and Esther Garland presented at ESOMAR alongside Nokia’s Tom Crawford on how social media research can be used alongside co-creation to produce a better innovation process:

Innovation should not be so much about ‘creation’, but more about ‘emergence’. Defining the boundaries of possible futures means creating the conditions for fostering the emergence of ideas that are already taking shape in the social space, but have not filtered up to the top or are not formed enough to bubble up yet. In a connected real-time ecosystem where the consumer can be as creative as the designer, the new model of innovation should be listening, reducing complexity, decoding the signal from the noise, collaborating with consumers and only then defining the boundaries of possible futures.

The project started with a “download” from social media to gather the widest possible range of themes and scenarios for this project:

The project kicked off with a two week Social Media Monitoring and Trends Analysis programme using netnography, semantic and network analysis across forums, social networks, blogs, news sites, microblogs, video and photo sharing sites from the United States. Using Face’s social media analysis platform Pulsar we tracked more than 100, 000 ‘sources’ (where Twitter counts as one source) and harvested almost 1.5 million items of content. These were analysed to gather insight into how key consumer segments in North America talk about smart-phones and which key themes, topics and angles were most resonant with them. 

Analysing conversations amongst users talking to each other rather than responding to researchers yielded a huge amount of richness. Furthermore, this helped develop clear learnings on language, tone of voice and attitudes to the brand and the category. It allowed for a different kind of research landscape, one which subverts the traditional question and answer format and replaces it with something far more natural and intuitive. By working in a more natural communication mode we also ended up expanding our research agenda to challenges we didn’t even know existed or that we wanted to investigate.

For the full story, read the full whitepaper up on Slideshare here, or check out the presentation:

Or get in touch if you’d like to talk forward-looking social research – I’m at Jessica@Facegroup.com