Face MD Job Muscroft started a series of posts about the emerging roles changing the face of market research earlier this month. Now, we’re going to take a closer look at each of these roles in turn, starting with Face social media researcher Jess Owens.

How would you describe your role?

As a social media researcher you’re a customer barometer for your clients – you see far more of what customers are thinking than probably anyone in their business. And, unlike almost all other information sources, it’s all real-time.

In social media monitoring projects, you’re feeding that back to the business – often hundreds of people, including the board – weekly or fortnightly to help the different client teams understand the impact of what they’re doing, what’s working, and what’s not. In insight briefs, the scope is a lot wider – often there’s a big element of explaining trends, “internet culture”, emerging technologies and so on.

How did you become a social media researcher? What’s your background?

I got a job at Face in part through having a Twitter account (@hautepop) which demonstrated that (a) I understood social media and (b) I think analytically about it. I’d been talking to Fran (our Director of Innnovation and head of Face Labs, @abc3d) on Twitter for a while, so when I sent in a speculative CV it got read. As a friend of mine put it the other day, “Our social graph is our passport” now.

But it’s also pretty crucial to be at home with both qualitative and quantitative thinking. I’m a bit of an extreme example here (BA in social anthropology; A-levels in maths, further maths & physics), but being able to handle both analysing datasets and explaining “what it means” is central to the job.

Beyond this, though, I’ve been active in online communities since 1995 and I’m fascinated by online culture. At heart, perhaps every social media researcher is an ethnographer or a “native informant” mediating between online and client worlds.

Any tips for how to stand out from the competition when you’re trying to get a job in social media research?

It’s amazing how many people don’t even have an active Twitter account… It’s a new field, we don’t expect 10 years of experience in “social media research” per se – but demonstrating specific interest and experience in both fields is pretty essential. Don’t be a generic marketer.

Ideally I’d love to see someone who’s big on Tumblr, or makes influential comedy or beauty videos on YouTube – something that really demonstrates that not only do they “get” how a particular channel works, they’re passionate about online sociality in general. Participant-observers can reach deeper insights than voyeurs.

What are the top three rules you have to follow as a social media researcher?

(1) Don’t lose sight of the wood for the trees. When doing analysis, it’s incredibly easy to be distracted by interesting discussions and follow these off, losing sight of the research question you’re trying to answer.
(2) An anecdote is not data. If you’re seeing 2000 mentions/day, one interesting tweet or forum thread is not in itself meaningful. First you need to establish whether or not it’s part of a wider pool of comment or complaints.
(3) Social media research is not PR – if customers are pissed off, your job is to explain that objectively, not play it down or try to cast them as in the wrong.

What’s the biggest mistake you most often see in social media research? What’s so bad about it?

People breaking rule #2 above (mistaking anecdote for data) – a singular “cute story” doesn’t necessarily mean anything and may in fact be misleading. It risks making social media analysis look like PR fluff rather than one of the central sources of business intelligence for the next decade and beyond.

Where do you see your role going in the next five years? What’s the future for social media research?

Big! Social media – and its intersection with mobile – is a really booming field, and moving incredibly quickly. In five years, social media research won’t be a distinct field – in fact it’s not one now, it never has been. Instead it’ll be an umbrella-category for a wide range of research methods done by all sorts of people, from brand and customer analysis to data journalism, economic & financial forecasters, policing & security services, academics and digital humanities researchers. The raw material of analysis certainly won’t just be social media content but integrating social and network data of all kinds.

Obviously market research only owns a minute part of it. The social media analytics field is dominated by tech firms, from IBM to Radian 6, Sysomos etc. Some follow more of a strategy consulting business model, but most are essentially selling product licences and require companies to either accept only pretty basic top-line insights or have an in-house analytics team. Analytics platforms from the social networks hosting the content may also emerge (e.g. Google+ Analytics, Twitter Analytics).

The qualitative and strategic side – the “what it means” – will be a much smaller part of the whole, but doubtless still offering huge opportunities.

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Sounds like you too? If you’re interested in joining Face and helping shape the future of market research as a social media analyst, please submit a CV and cover letter to job@facegroup.com.

Technology is changing faster than consumers. Consumers are changing faster than organizations. Therefore, organizations need to change faster if they are to keep up. Many are finding this difficult to achieve.

A recent IBM Global CEO Study that covers 1,130 CEOs across 45 countries and 32 industries showed that organizations not only felt bombarded by change but many are struggling to deal with it. 8 out of 10 CEOs saw significant change ahead and yet the gap between the expected level of change and the ability to manage it had almost tripled since the previous study in 2006.

There are many different manifestations of this change (too many to cover here) from faster product life cycles and globalization (the shift of budgets to emerging markets), to changing demographics and the challenge of ageing populations on Western economies. But one of the biggest is the impact of the social web on everything we do. EMarketer predicts that the tipping point will happen in 2012 when 60% of all marketing budgets will become social. Linked to this is the arrival of Big Data. In 2010 the human race created 800 exabytes of information. To put this into context between the dawn of civilisation and 2003 we only created 5 exabytes; now we’re creating that amount every two days. By 2020 that figure is predicted to sit at 53 zettabytes (53 trillion gigabytes) – an increase of 50 times. As Hal Varian, Google’s Chief Economist said “We used to be data poor, now the problem is data obesity”.

This presents us with a number of new challenges that I have set out below as hardening client needs. I have concentrated on just a few with some suggestions on what research companies need to do to make sure they’re in a position to meet them.

1. Moving from Big Data to Big Insight

Making sense of all the data out there and simplifying it so that we can derive valuable meaning and insight will be one of 2012′s client mantras. Social listening will give way to social media insight. Having researchers in your team that are also technologists e.g. digital anthropologists that can help to analyse real time social data will become a required skill. Being able to augment different data sets from the virtual and real worlds so that we can help to create one closer view of our customer will depend on our ability to mix different on-line and offline methodologies in a coherent and credible way.

2. Quality without speed is not enough

One of the greatest demands from clients is how to deliver fresh, robust and relevant insight more quickly and cost effectively than we have ever done (or needed to do) before. Qualitative research companies need to lead in the use of technology so that we can become quicker, faster and more responsive in the ways in which we gather insight about our clients’ consumers. We also need to develop research and planning tools that are less generic and more focused on the CMI client needs of today and tomorrow.  This does not mean replacing human analysis – to the contrary the role of the researcher has become even more important than before because of the need to find real quality from the huge quantities of data that is out there. It must also mean we can do better than relying on tools such as the TGI Index.

3. Logic needs to give way to more magic

We are going to see more emphasis on qualitative research as a robust exploratory tool to understand better consumers’ emotional drivers as well as to help improve the quality and shaping of social ideas and social content before things go too far and way before the quantitative testing stage. Too much blind reliance on testing things to death has seen some of the “magic” and “creativity” in marketing lose out to the “logic”. Creating magic today means creating social brand stories that are contagious and can be propagated effortlessly by key consumer cohorts. Co-creating with these consumers, involving them much earlier in the marketing process, leveraging their content and creativity as part of the marketing process will have an increasingly important role to play here. If what goes in is rubbish then testing what comes out will be rubbish. The Coca-Cola Company is leading the way and I am sure other FMCG clients will follow.

4. Creating content excellence

There is a new marketing ecosystem where content is more important than channel, where audience passions/interests are becoming more important than demographics and where the media model has changed – placing more emphasis on created and earned media as opposed to bought and owned. Understanding which “big ideas” have enough social currency  (it’s not what consumers are doing with your brand but what they are doing with each other that counts) and can work effectively across all platforms will attract much more focus. Understanding the different consumer cohorts within a brand audience and their influence will also be key to understanding what content areas will have the most impact when it comes to propagating ideas. Researchers need to come up with a new model here: one based on rational, emotional and social metrics that is continuous and adaptive.

5. New measurement models

With the increasing socialisation of brands and the importance “connected” brands are placing on new metrics such as social brand value and influence (see below), helping clients to understand, validate and measure what ideas work best in the earned and created media space as well as why it works will be increasingly important. Finding ways of proving that the more customers of a brand are interconnected the more they are willing to pay for the product and the more loyal they will be is vital. Working out a more real time model for measuring which big ideas have the best potential for success; are the most likely to be propagated and can work across all media is another area that needs close attention.

The idea is simple: powering traditional qualitative and quantitative research with real-time data.

When we were invited to speak at Warc’s Datacentric Conference, we thought it would be interesting to discuss one of the latest research pilots we have been running in the area of augmented research.

The objective of the O2 Brand Graph pilot was to mine social media data in a way that would allow us to connect it to audience studies.

What follows is an initial exploration of how we can you use social media to augment a segmentation model with real-time data.

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Many companies are learning to listen to conversations related to their brands and competitors.

However, there’s more to social media intelligence than tracking conversations by keywords.

Current social media research focuses on opinion mining and declares itself unable to map audiences. But I think we are giving up too soon.

This inability appears to be born from an assumption in the research industry that you can’t use social media to map audiences because you don’t have access to demographics.

Far from being reality, this assumption is mostly due to three reasons:

1. The architects of social media mining platforms are often not led by a research agenda, but by a tech agenda – this leads to a tendency to productise and mass sell platforms, which can run in counterpoint to an openness to experimentation;
2. Researchers are often not makers or technologists – therefore, they are often lazily happy with what they are given in terms of tools;
3. Researchers do not always know what can be done with existing social media data streams, such as basic machine learning to figure out gender and age groups.

However, mapping audiences through social media IS possible. It’s just not in the way we used to research audiences before.

It’s all in the way you screen your audience and sample it, and in social media sampling via demographics doesn’t work. But there are many other ways of defining and screening an audience. In this study we explored one way.

Instead of tracking contents by keywords (“horizontal” tracking – any content mentioning specific keywords and keyphrases), we looked into mining social media contents and behaviours by audiences (“vertical” tracking – any content generated from a set of sources, regardless of the features of the content).

Whilst tracking social media by keywords allows us to get an understanding of how a specific topic is discussed online, tracking social media by users allows us to build a map of an audience, its hubs, its behaviours and its interests.

We called it the Brand Graph: the conjunction of the Social Graph (defined here as the network of people who are within 2 degrees of separation from the brand through social media channels) and the Interest Graph (the network of interests, topics, activities and behaviours associated with the nodes of the social graph).

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What can you do with it?

• Dynamically understand who your audience is and how is it changing, in real-time;
• Dynamically understand what your audience is about, what makes an interesting topic and how broader cultural conversations affect it;
• Segment your audience in clusters based on topics of interest, passions, life stages, professions, online behaviours etc.;
• Plan and fine tune the content of your social media strategy;
• Engage with your audience in the right way (channels, mechanics, times of the day, tone of voice etc.);
• Assess the impact of your strategies in real-time.

Going forward, we see the brand graph becoming one of the key tools to build a seamless connection between your brand and its audience, networking it with its passions and synching it with its behaviours to maximize relevance and impact.

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So, how did we go about building the O2 Brand Graph?

First of all we had to identify a specific pool of social media users and then analyse their public activity.

For the purpose of this pilot we limited the online audience to one channel – Twitter. We focussed on Twitter because of the granularity of the data publicly available around contents and behaviours.

Sample: We defined our sample as the entire audience of O2 on Twitter, i.e. 58.339+ Twitter users who were following @O2 (as of November 2011).

Methodologies: Statistical analysis, Semantic analysis, Network analysis, Netnography and Content analysis.

By looking at the profiles and the activity of this audience we were able to map the O2 Brand Graph on Twitter.

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We grouped the findings in three areas:

Mapping the Social Graph

We wanted to identify sub-communities within the O2 audience on Twitter.

Because Twitter is an interest graph, we assumed that following someone implied sharing the interest of the followed user.

Therefore, a subcommunity would be identified by a high concentration of horizontal connections within the graph.

To get this information we had to map:

1. 58,339 users following @O2;
2. Who was following each of the 58.339 users;
3. Who else in the graph any of the users was following other than O2 or the primary O2 follower.

For the sake of this exercise we looked at a sample of 1000 users. We then selected the top users with less than 2000 followers. We then mapped their connection to O2. And finally mapped who was following them.

Finally we mapped how the primary and secondary followers were connected to each other user in the graph.

We ended up plotting a graph of 1 million nodes, 1 million primary connections and 574,278 horizontal connections within the graph.

The blue links represent how primary and secondary followers are connected to each other within the graph.

By looking at the density of the connections we could identify hubs within the audience and points of high concentration of similar interests.

Once we knew where the hubs were we than isolated then and looked into the clusters.

We spotted 10 clusters and profiled them, identifying sub communities around topics such as fashion, music, rugby, technology and marketing.

Mining the interest graph / profiles and behaviours

We then analysed the static data of 58,339 profiles on Twitter gathering insights around 10 key dimensions:

-       Who are they (life stage, profession, passions that define them etc.)?

-       When did they join Twitter?

-       Where are they based?

-       Where do they tweet from?

-       How often do they Tweet?

-       When do they Tweet during the day?

-       How many people are following them?

-       How many people are they following?

-       How often are they engaging in conversation with fellow users?

-       How influential are they?

Mining the interest graph / interests and passions.

Finally, we analysed 3,120,371 public tweets, 122,220 tweets/day (avg), generated by the @O2 followers over one month (November 2011).

Based on this corpus we were able to gather real-time insights around a series of questions such as:

-       What does the audience talk about?

-       How and why do the topics change over time?

-       Which contents are the most engaging (i.e. generate the highest number of reactions)?

-       Which contents get shared the most?

-       Which social media channels are the most popular amongst the audience?

-       Which news sites are referred to more often?

-       Which brands and products do they talk about?

-       Which adverts do they mention?

-       What movies are they into?

-       Where does the brand fit in this landscape?

-       How do they talk about the brand’s main competitors?

All this information is constantly updated to the second and can be sliced according to any timeframe, audience segment, audience location and basically any dimension of the audience profile or of the audience social graph.

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The deck above outlines some of the initial data gathered and the insights uncovered. But as you can imagine this is only a glimpse of what we could learn with this kind of study. An example? Slice the topics of conversation of your audience by time of the day and you will know who would you be talking to and what you should be talking about at what time of the day.

As the last image in the deck – “The Measurers” – alludes to, with social media data we are at the very beginning of a new era of audience understanding powered by a new science of measurement.

Pilots like the Brand Graph are initial attempts at defining the boundaries of what can be measured, what could and SHOULD be measured and what we can learn from it to do a better job.

Feedback and questions welcome, belligerent challenges even more so.

An underrated skill in social media research is simply knowing what to search for.

Really? You’re interested in a particular brand, so surely you search for that word or phrase, right?

For brands such as Three, Apple, or the AA? Go ahead, give it a go!  Just don’t be surprised when you get back a lot of content about “Three ways to boost your Twitter profile”, apple crumble recipes, and AA rated sovereign debt.

Searching the internet

We often describe setting up a social media research search for a brand as like doing a Google search.  This is loosely accurate – like Google, a social media research tool ‘crawls’ news, blogs and forums for instances of your keywords. The research tool will also filter social media APIs (e.g. Twitter, Facebook) for instances of these words or phrases.

The problem is that the internet contains a lot more content than you think it does. Normally you never see it, and much of it isn’t even designed for human readers.  Here are a few forms this takes:

Challenge 1: SEO spam

Being at the top of Google’s search results is a very valuable place to be if you want to get visitors to your website or online shop. This has made gaming Google results an industry in itself, called SEO: search engine optimisation.

SEO aims to guess Google’s search algorithms to manipulate clients‘ websites to the top of search listings. Google basically rates sites more highly the more in-bound links they have – i.e. the more popular they appear to be. So gaming Google results entails generating a lot of false links and content, with methods including:

• Fake news sites reprinting press releases and “content farms”, e.g. Demand Media or Articlesbase
• Promo blogs with high numbers of links to the client’s site, with random or copy-pasted text to make Google believe they are legitimate blogs rather than spam
• Legions of Twitter bots (automated accounts with an algorithm rather than a person generating their content) posting links to websites
• Using bots or real people (incentivized by micropayments) to post high volumes of blog comments with links to the client’s site

This gives rise to a lot of misleading digital data, all of it only designed to be “read” by Google’s algorithm rather than human eyes. To a reader – or anyone tracking a brand – it is useless.  The problem is that it’s got your brand name in it, so any generic brand-name social media search will bring back this “noise” too.

Challenge 2: unexpected content

Do a Google search these days and the internet seems an ordered and relevant place. Even when you search for an ambiguous word with several meanings – let’s say “Orange”, the results are sensible – Orange the mobile company and the Wikipedia page on the fruit.

This is because Google have spent years refining their algorithms to ensure it brings back the most relevant content possible.  This doesn’t just mean putting the most popular links at the top of results. Instead Google uses everything it knows about you – your previous searches, your Google profile and Gmail, your stored cookies and more – to deliver personally tailored results.

Social media research tools don’t however work this way. The APIs and scrapers collecting content return all keyword mentions, relevant or not. In searches we’ve run, some of the most unexpected things we’ve found have been:

1. Searching for banks will bring back posts on “carder forums” – the sites where credit card fraudsters sell the card details they have stolen from databases.

2. Almost everything is a word in Indonesian. You thought you were searching a specific and unambiguous acronym? No, it also means something in Indonesian – and volumes can be enormous because Indonesians are one of the most active populations in the world on Twitter.

3. Pharmaceutical searches are near-impossible. Dubious medication sellers will include hundreds or thousands of drugs as keywords on their pages, whether or not they’re selling those products.

Challenge 3: not all relevant content is indexed

So far we’ve described some ways that irrelevant content or “noise” can get into your social media search. There’s also the opposite problem, however – not being able to ‘see’ certain types of social media content, particularly forums:

Message boards are part of the Internet known as the ‘Invisible Web’ and pose many problems to traditional search engine spiders. The dynamic content is usually very deep and hard to search. In addition, many of these sites change their locations, servers, or URLs almost daily presenting special searching challenges [Boardreader]

This makes it essential to use a social media research tool that allows you to check which forums are tracked, and customize the panel of sources as needed.

Impact on social media research

What this means for social media research is that if you’re using an off-the-shelf monitoring package, you’re probably getting a lot of junk in your results. Brands are often keen on easy usability – type your brand name into the search, and get a volume figure and sentiment stats out. But without tailormade search syntax, those figures are almost certainly meaningless.

So how do you make your social media research search relevant?

1. Specific is better

Using broad search terms and then excluding keywords you’re not interested in doesn’t usually work very well. You’ll never be able to filter out all irrelevant content – language is too varied and dynamic. E.g. if you’re after the mobile brand, search for Orange AND mobile, not just “Orange”.

2. But you can filter irrelevant websites

Not that many big content farms exist – so we exclude everything from them by URL.

3. Also filter particularly spammy keywords

e.g. “Viagra” for anything medical.

4. Boolean search syntax

This is the logic that enables you to search for content including A and B, A or B, or including A but not B.  It’s essential not only for designing your social media search strings, but for also searching within the dataset.

5. Test your search terms on Twitter

Enter your search phrases into Twitter Search to see whether you’ve got them right, or if they’re bring back unexpected or irrelevant content instead. Twitter search also helps you understand the volumes of content that’ll come back (is it multiple posts a second, or a couple per day?)

6. Get personal

If you’re specifically interested in what consumers are saying, searching  with personal pronouns – e.g.“my iPhone” – will bring back a much more relevant dataset than “iPhone” on its own.

Which is to say, designing a relevant and accurate social media search can involve a surprising amount of time, thinking and ongoing refinement. Few brands have the time or expertise to do this in-house using an off-the-shelf monitoring tool.  This is why our clients have come to us instead for our expertise in locating what matters in social media – the signal amongst the noise.

When did you get your first computer? I think I got mine when I was in middle school, and that was considered early. Most of my friends started getting one in their rooms in high school. They were not laptops, either, but old-fashioned desktops with towers. Compare that with the current trends. Computers are getting purchased for younger and younger children. According to this MSNBC article proclaiming mobile tech is in for kids going back to school, you may need to get your elementary school grader a new Droid Sonic!

In honor of the back-to-school season, we set up a Pulsar search for mentions of technologybrands looking for how people talk about tech in terms of kids and school. We wanted to see how this trend of youngsters with cool tech is perceived. Turns out there are two answers to this question: the physical technology that people think is weird in the hands of kids and the applications and program technology that can help us raise and teach our children better. And these two answers are dominated by two different brands: Apple and Android.

Children with Technology Is Ridiculous!

One of the first things we found was that people like to joke about children and technology, usually at the parents’ expense. Below you can see a graph of Retweets over time. The two spikes were caused by the jokes in quotes above them. These comments were passed along 50 times each, a pretty good shelf-life for a joke. People find the idea of children and this technology, particularly Apple technology, humorous.

Part of this may be the assumption that children with technology are rich. Several comments referred to how expensive these products are. There was even a small viral protest on Facebook about how spoilt modern children are. The protest called for people to repost varieties of this message to their own Facebook walls if they agreed with it: “When I was a kid, I didn’t have a laptop, iPod, Blackberry, PS3 or iPad. I played outside with friends, bruised my knees, made up adventurous fantasies and played hide and seek. I ate what my mom made and Jollibee was a treat. I would think twice before I said “no” to my parents. Life wasn’t hard, it was great and I survived. Kids these days are spoiled. Kids these days lost something – Appreciation. Re-post this if you appreciate the way you were raised. I think we were happier kids ”

Society just thinks that these high tech gizmos should not be juxtaposed with children. When people view a child with an Apple iPad, for example, the tendency is to either make a joke about it or deride it. It’s just that ridiculous.

But Applications Where It’s At

Phones were only mentioned a little over 5,000 times in this search and laptops and tablets were only mentioned a little over 8,000 times. Meanwhile, applications were mentioned over 9,000 times.

Applications sure have got people talking.

And they are talking in a good way. Many of the applications mentioned in the context of this search either factored in to children’s education or security. Examples include applications to help parents track their children or that allow children to mimic their parents’ driving. Of course school-focused applications are also available in abundance for the tech-savy student. I like this interactive periodic table for the iPad.

The difference between the discussion about applications and the general discussion covered in this study is where the discussion is occurring: news. Blogs and news were the leading channels in our general search, but only for applications did news surpass blogs.

And these mentions were on tech news sites, more so than in the general search which was dominated by local news. Technology news sites cover the up and coming, which includes apps. A quick search on Mashable.com showed 12,900 hits for “phones” while there were 17,700 hits for “applications.” Most people don’t go to their local news station for the latest technology happenings. They do turn to Mashable. Could the market be moving away from the technology itself and more towards what we can accomplish with it?

Apple Dances Center Stage with Android in the Wings

I’ve already hinted at this in this blog post, but yes, Apple reigns supreme. Apple has been involved with the education industry for a long time now. I will date myself by remembering when my school got the large and colorful iMac computers for our computer lab. This link with education has remained.

Or could it possibly be that Apple products are really cool and everyone seems to want one? Apple and Apple products were mentioned over 16,000 times in the search results, indicating how strong the brand image is. But we knew that.

What’s more interesting is that not only are Apple products fun to talk about, they are also considered necessary. Almost 400 mentions, out of a total of 600, of “necessary” and “must” and purchasing words mentioned Apple products. It is apparent that Apple products are more than just fun. They carry more weight than that. No other brand in our search had such a high level of need associated with it. Even generic items, such as “laptops” and “phones” only received around half the mentions of the Apple brand products.

And yet, when it comes to applications, Android is more prevalent, particularly in news discussions. Android was the only other brand besides Apple mentioned in any considerable volume, though considerably less than Apple with only around 2,500 mentions. Android was mentioned most frequently in the news, unlike Apple for which blogs were the leading channel. Considering that applications are apparently the current direction everything is going towards, Android seems to be well positioned.

Could attention be shifting from Apple products to Android applications? We’ll have to wait and see. Meanwhile, it is clear that Apple is benefiting from the back-to-school season.

Do Your Children Have iPhones?

What do you think? Do children need technology in order to benefit from their educations, or is it just something for rich parents to buy for their kids? Is it useful or hazardous? General opinion seems to lean towards it being unnecessary, though news and bloggers tend to think it useful. People certainly like talking about it.

The launch of the iPhone 4S was big news last night, trending around the world and, at its peak, generating almost 17 tweets per second. These tweets were fed into our social media mining platform Pulsar and visualised. The results are now being featured on the Guardian data blog right here.

Keep an eye out for tomorrow’s blog post, when we’ll be posting some new visualisations using more of the data.

One of the most interesting meetings we had in New York a couple of weeks ago when we launched our office there was with someone about social media analytics. She described her role as “all about change and things are constantly changing” so social media research or “qualitative research on steroids” as she described it, is attracting a lot of her attention. Having spoken to a wide range of companies and potential suppliers she divided social intelligence into three broad areas: social listening, social media insights and social media measurement. Interestingly she placed Radian6 and Sysomos in the pure listening camp, while putting us in the social media insights arena – exactly where we want to be. The reason for this is our proposition unites proprietary social intelligence tools together with a team of anthropologists and social media analysts. It is this combination of a passion for and understanding of technology together with a passion for research and analysis that differentiates our social media research offering from just social listening platforms and is helping us to win an increasing number of blue chip clients alongside O2. We’ve learnt that our approach provides a number of unique benefits across four broad areas:

How we collect the data

We believe that it is vital for clients to customize their panel of sources so the search terms are refined to their specific category, competitive set and consumer target. Without doing this the data is too U.S focused and important niche sources specific to key topic areas and core influencers will be missed.

How we process the data

Because social media is made up of many different types of applications, influence spreads in different ways depending on the platform you are in. This is why we have developed specific algorithms for each different channel we track. This helps us to measure what we call the “visibility” of the data alongside the volume. Mapping visibility and key influence is calculated using different indicators depending on the channel we are looking at but it always takes into consideration three key parameters that we have identified as part of this process. Alongside these two key indicators is the way we combine human coding with software analysis so that we can increase the accuracy of our outputs. We crowd source the sentiment analysis with a global panel of “analysts” who are rewarded with micro payments in return for micro tasks.

How we interpret the data

Good, accurate interpretation and analysis comes down to the brilliant team of Face researchers and social intelligence analysts. Our team is growing fast to meet the demand brands are placing on the importance of social media insights. Social media listening as provided by Radian6 and Sysomos was just the beginning – as the market becomes more sophisticated clients will be looking for best in class solutions.

How we present the data

Real time research and planning means you have to craft and shape the insights in a different way. Making data beautiful through well designed visualisations and info-graphics so it’s easy to digest is a key part of this. But we are also learning there are many other important ways to deliver insight through this process.

Finally, many were interested in the next stage of our development: to combine real-time research with other F2F methodologies and on-line qualitative techniques to produce different layers of data some thing we are calling Augmented Research but more on this, another time.

The Royal Society of Arts was a grand venue for what felt like an eye-opening Co-creation Hub event on something that, really, we all should know. In fact, throughout the talk, I began to feel slightly unnerved by the accuracy of a theory that I’d known so well through growing up – although back then it had no fancy name. I wanted Adidas popper trousers and Kickers shoes because they were what the cool kids wore. They would make me popular.

As Mark Earls, co-author of forthcoming book “I’ll have what she is having“, broke the news that our decisions aren’t based on what we, ourselves, believe in or agree with, but by that of influencers – like our friends or other respected sources – it got me thinking about some decisions I’ve made recently and how they may have been based on my social circle. Did I break up with my boyfriend because my friends were all becoming single? Did I move to a rough area because my friends were nearby? Am I thinking about my next holiday destination based on the stories I’ve been told? Probably, yes. Definitely, I’m sure Mark would say.

And it doesn’t stop there. The story of Colin was a clear example of how we are influenced by the people around us, not the other way around. Let me set the scene. You’re at a festival. There’s music. There’s sunshine. Everyone’s relaxing on the grass, apart from one crazy guy dancing on his own. This guy is Colin. At first, you look at Colin and think he’s a bit mental, but he’s relentless and carries on despite the whispers. Soon, another nutter joins him and the onlookers whisper a bit more. When the third dancer joins the spontaneous rave, a seed of doubt starts to grow. Maybe they’re not mental and they’re just having fun? It is at exactly this moment that a small group of revellers more than double the party and your doubt is confirmed. Before you have time to put on your flip-flops, twenty more people have arrived and you’ve become outnumbered. It’s time to join in. Now who’s the crazy one?

In practice, Face’s Director of Research, Francesco D’Orazio explained perfectly how brands should harness this information and use it to engage with customers through social media. His main argument was that people really don’t care about the brands themselves, they care about their personal relationships. So if a brand can communicate in the space between people, it will be much more successful than if it speaks to individuals directly.

O2 have taken this on board and created the RTO2, which, as Jake Steadman, their Brand and Social Media Insights Manager explained, crawls the web to pick up every conversation about the brand. It is fundamental for a number of reasons, from defining their lead influencers to reacting to customers in real time. Ultimately, it gives them access to the whole truth by tapping into a space where people are comfortable and open to opinions on a wider level. After all, getting a positive reputation in that space is arguably the most important of all. Brands become cool through word of mouth and when people don’t think they’re being advertised to, they’ll become much more susceptible.

Upon leaving the seminar, I became increasingly aware of this theory of influence as I unwittingly decided to take the tube from Charing Cross rather than the quicker, more direct route from Holborn. That could have been because it was cold and the walking distance was shorter but I’ve never been one to trade time for comfort. On reflection, I’m pretty sure the decision wasn’t wholly mine. I blindly followed my friends, who in hindsight probably would have followed me, had there been more people travelling in my direction.

Only four days to go until you can catch us at CIPR Social Media Conference 2011.

Advances in communications technology and new channels allow us to engage with the public in a way that has never before been possible. With more bloggers, citizen journalists and online consumer groups, everyone is in on the act and the balance of power is shifting.

We’ll be joining experts from Nokia, Sainsburys, Edelman, Bristol City Council and many more at the CIPR Social Media Conference, on 11 April to ensure that your skills shine through, that you can deliver the most effective, integrated strategy and that your research, planning and evaluation are second to none.

For more info, check out the CIPR website