Category Archives: Augmented Research

Research methods that combine data sources

Social Intelligence: Not Just for Social Strategy

At FACE, we’re a hybrid group of “qualies” and data analysts who keep an open mind about what it means to be a researcher in 2014 – how research should happen and where the most valuable information comes from. We’re increasingly incorporating social media intelligence in our work, used either as a primary methodology or a layer of context in qualitative studies. However, we’re aware that some of our colleagues and clients are hesitant to consider social research methodologies.

I’ll get this out of the way upfront: social analysis is not the right fit for every research objective. Yet social is often dismissed simply because clients assume that anything social is not in their jurisdiction. That’s what I want to argue against in this blog post – instead, let’s start thinking of how social media can inform every dimension of brand planning.

Here are some familiar examples of the reasoning behind why social gets cut from budgets or even passed over in favor in of much more expensive approaches:

  • “This data may be interesting, but our brand doesn’t tweet, so social media stuff is not for us”
  • “Looks like you have strong social capabilities, but that’s not really relevant to my team; maybe I’ll put you in touch with our PR department.”
  • “We’ve got a dedicated team working on social marketing. They’re not set up for research, exactly, but I can have them pull any reports I need”

It seems there is a not uncommon perception that social data is exclusively for social strategy: analyze social conversation and sharing to become a better social conversationalist and sharer.

I disagree. In fact, the value of social understanding is far more expansive than that. Incorporating social insight is an exercise in lateral thinking that can make research more potent across the spectrum of strategic planning.

Stanley Pollitt's book 'Pollitt on Planning'

Stanley Pollitt, co-credited with starting the ad agency practice of account planning, had an important take on this theme long before digital social networks were in play:

“The account planner is that member of the agency’s team who is the expert, through background, training, experience, and attitudes, at working with information and getting it used – not just marketing research but all the information available to help solve a client’s advertising problems.”

This perspective is relevant beyond advertising problems. Research must be focused, but focus shouldn’t mean “same old” or one-dimensional, whether that’s traditional focus groups or brand trackers. If your strategic goals are ambitious, your research goals – and methodology – should be too. “…all the information available to help solve a client’s problems.

We’re now living in a world where the subjective emotion we share and the measurable data trail we leave behind are both signs of our humanity. So as a researcher you’ve got to love talking face-to-face with a consumer as well as studying how that person comes to life in a spreadsheet.

Social is a unique stream of information and is there, as Pollitt would suggest, “to get used.” Social data is exciting in that it’s vast, readily available, and relatively cost effective to access. Moreover, social conversation is generally unprompted – a chance to throw away the discussion guide and purely listen. What you’ll hear will inform far more than how to write your next tweet.

Beyond social marketing strategy, here are several thought-starters for how to get smart from social insight and use it across your brand or business, not just for social media strategy.

1. Audience Profiling

  • Segment social users talking about a brand  or topic to learn more about existing customers – or discover potential new target audiences
  • Improve recruitment for subsequent research, e.g. build a smarter screener based on fresh insight into demographic and lifestyle parameters

2. Advertising effectiveness measurement

  • Optimize media spend by detecting regions of brand interest before messaging is in-market
  • Track impact of online or offline advertising by region, based on social reaction (either organic reactions or in response to a call to action, such as a promoted hashtag)
  • Gauge performance of local activations, e.g. in-store events or franchise promotions
  • Assess PR activity such as news editorial coverage and native advertising
Pulsar location map - US by state

Pulsar location maps can show where people are talking about your brand, stores or advertising

3. Understand your online sales funnel

  • Measure links shared to Ecommerce properties to understand where consumers are talking about buying your products or competitors and the category at large
Pulsar most shared Media visualisation  by domain

Pulsar’s Media visualisations analyse the links being shared within a topic of discussion

4. Design Inspiration for products & services

  • Identify consumer-generated content and use it as stimulus for brainstorming for new product development, creative production, packaging design and more
  • Gather unmoderated feedback on a purchase journey or product experience to inform future UX design

Social media allows real-time customer journey feedback

These four options are just a start: there are many other ways to get more creative and more analytical with social data. Studying social conversation provides a window in to consumer mindset and behavior, not just a view of popular chatter. It’s helpful to think about social media by breaking it down to its basics: networks of people sharing opinions, speculating about the future, and reviewing experiences. In that lies true insight for business problems, so there’s no use in being anti-social!

For more ideas for leveraging social data, see Fran D’Orazio’s Future of Social Media research blog post.

Marc Geffen is based in our US office. If you want to discuss how he can help your business in the New Year then send him an email:


How Stuff Spreads | How Video Goes Viral pt. 2: the role of audience networks

In the first part of this blog series (How Stuff Spreads | How Videos Go Viral part 1: Models of Virality) we identified 7  dimensions that describe and quantify virality. Although none of the variables alone proved able to define a viral phenomenon on their own, they correlated into two models of viral diffusion. One model we called “spike” – the sudden ‘explosion’ of sharing activity – and the other we called “growth”, where popularity is a slower and steadier grower.

Spikers vs Growers

In this blog post, our Chief Innovation Officer and  VP Product Francesco D’Orazio using social network analysis looks at how the audience composition and structure influence the way video spreads.

What makes a viral video spread in one or other of these ways? Most studies on the subject  focus on virality as a feature of the content. But what if virality is (also) a feature of the audience? Can the demographics and the structure of the audience for a video explain how it goes viral?

To recap, we were studying 4 videos:

In this blog post we will show how we analysed the demographics and the social network properties of each video’s audience to understand better how they spread.  Read on for some of our best network graphs yet and some fascinating findings…

Metric #1: Amplification and influence

The first thing we looked at is Amplification. Amplification is a measure of the average “visibility” of the tweets carrying the meme. Tweets with higher visibility imply a more influential status of the author who posted them. Can the influence level of the audience of a meme explain its slower or faster diffusion?


Amplificiation is similar across all audiences. It’s fractionally lower for the Turkish protest video and for Ryan Gosling, the first primarily shared in Turkey, the second appealing to a slightly newer (though still very active) Twitter audience. And it’s slightly higher for Dove Real Beauty Sketches and Commander Hadfield. In both cases the variation doesn’t correlate with the virality model of the meme.

Metric #2: How international were the audience?

So the next hypothesis to explain the velocity of the memes was the geographic distribution of the audience. We quantified this as Globality: the percentage of meme shares coming from countries other than the main country. So does the “internationalness” of a video affect its virality? Does a more global or a more local meme spread faster?


The answer is again, no. The Turkish protest video was “local” but so was Ryan Gosling – and one spread instantly but the other peaked on day 18. Since both Amplification and Globality seemed not to correlate with one or the other model of virality, we then looked at the demographics engaged with each video.

Metric #3: Demographics.

Does the demographics of the audience affect the way content goes viral? Do young, techie male students from global cities push a meme faster than, say, middle aged housewives from rural Germany?

We used Bayesian statistical inference to analyse the demographics of the audience. This method uses the available information on Twitter and matches it to a sample audience interviewed in real life to get known demographics, across the various countries involved in the study. Below is a summary of the most prominent demographics traits of the four audiences:





Although students and global cities feature heavily in all audiences, there doesn’t seem to be any direct correlation between virality models and demographic traits. Instead the demographics are completely different for each meme. Not to mention that students represent 33% of the Ryan Gosling audience, the slowest meme of all – so it seems that youth demographic probably isn’t necessarily a critical cause for a video to go viral quick.

And now some Social Network Analysis…

The audience gets more interesting when you start to look at its social structure. As we couldn’t find any correlation between demographic traits and virality models, we turned to the structure of the audience by mapping the social graph of the people who shared the video.

Your ‘social graph’ is the network of the people you know, and how they’re connected to each other. Because we were studying Twitter sharing of videos, we had easy access to this data through two variables: who each video sharer was following on Twitter,  and who they’re followed by. In technical terms, this gives us a ‘directional’ network with two possible ways for nodes to be connected.  Analysing these connections highlighted some really interesting differences.

Metric #4: Degree, or ‘social connectedness’

First of all we looked at the Average Degree of each audience network. Each person in a network can be assigned a ‘degree’ value: that’s a count of the number of connections they have to other people in the network. We were studying how videos spread in Twitter, so those connections are easy to identify: it’s who they’re following and who they’re followed by.

Interestingly enough, the audiences of the Spiker memes (Commander Hadfield and Turkish protests) are showing the highest levels of interconnectedness – while the audiences of the Grower memes (Dove Real Beauty and Ryan Gosling) show the lowest.


Metric #5: Modularity, or “fragmentedness”

The memes that spread faster could do so because the audiences that engaged with them were highly interconnected. But how are this connections organised? To do this we used another social network analysis metric called Modularity. This describes how fragmented the network is and how many sub-communities can be detected based on the density of mutual social connections within clusters of users.


The lower the modularity, the less fragmented the audience is into sub-communities, the more cohesive it is and the easier to reach it is. Not surprisingly, the audiences of the Spiker memes are the most cohesive ones, while the audiences of the Grower memes are the most fragmented ones. Cohesiveness and fragmentation becomes much easier to understand when looking at the total number of communities identified within each audience.

Metric #6: the number of Communities

Social network analysis tools allow you to measure the number of ‘communities’ in a social network. Tools such as Gephi provide access to algorithms, such as the Modularity one, that can quantify how people’ s connections tend to gather together into definable ‘clusters’ of closely-connected groups.





Whereas the audience of Commander Hadfield is split into 130 communities and the audience of the Turkish protests is split into 51, the audience of Ryan Gosling is split into 382 communities and the audience of Dove Real Beauty Sketches into 1356.

This has a strong impact on the ability of memes to spread through the audience network. Whereas reaching out to just 2 communities is enough to reach 50% of the audience of the Turkish protest, spreading the news to 50% of the audience of Dove Real Beauty Sketches requires reaching out to 8 communities. It follows, then, that where a meme has to travel through more communities to reach people, it moves a little slower – in a ‘grower’ model. By contrast, memes ‘spike’ where they take off in a small number of communities very quickly.


So what have we learnt so far?

Yes, the audience’s social structure – the way that people are connected within in – shapes the way something goes viral.

Audiences with a low Average Degree, low connectedness or low density, are more fragmented. The more an audience is fragmented into sub-communities (high modularity of the audience network), the slower a video or piece of content spreads through it . But what causes a higher or lower fragmentation within a specific audience?

Understanding the communities within an audience

To answer this question we tried to measure the demographic diversity of the audiences. The assumption being that an audience showing a higher demographic diversity will also be more fragmented and therefore slower to transmit viral videos.

So we ran the demographics analysis again on the four audiences: this time running it separately on each of the top 5 community clusters identified within each audience. You can see below the results for the top 2 clusters of each audience:


The audiences of Ryan Gosling and Dove Real Beauty Sketches show higher demographic diversity, while the audiences of Commander Hadfield and Turkish protests show lower demographic diversity. So high demographic diversity correlates with high modularity and slower meme velocity after all. How is this useful?

How the audience affects How Stuff Spreads

To start with, this means that a meme which is appealing to a broad demographic is probably going to spread slower than a meme that is appealing to a narrow demographic.

This also means that a meme with a broad demographic appeal is going to be more expensive to make go viral. Expensive because it will require more intense paid for seeding/advertising in order to reach out to a higher number of disconnected communities (Dove Real Beauty Sketches is a good example). It may also need persistent replication of the meme to break through the attention of multiple audiences who might not take notice the first time (Ryan Gosling won’t eat his cereal is a good example).

Finally, the organisation of the audience in sub-communities means that influencers lists by subject are pretty useless when trying to reach out to an audience. For example, your top 100 influencers for beauty might well all be part of the same two communities out of the 1356 total communities that make the Dove audience. So identifying gatekeepers and influencers is useful only once the audience you want to reach has been mapped and its communities identified.

The social dynamics of virality

In our previous post we identified and defined two models of virality: Spike vs. Growth.

From this audience and community analysis, we can now augment that with a 3-part model of how content is seeded through groups of people:

1) TRIGGER: A higher than average emotional response to the content triggers an impulse to share

2) VALIDATION: The impulse to share gets then validated against the community the user is part of. This validation happens both in terms of topicality (is this of interest to my audience?) and timing (has anyone else already shared this within my circles?). See this paper for more research on this aspect

3) ESCALATION: The gatekeepers (e.g. media channels, celebrities etc) share the meme helping it reach the tipping point within a specific community. The tipping point is when every member of the community is likely to receive the meme from another member of the community.

Once everyone’s seen the meme and starts to share it on themselves… That’s when you’ve got virality on your hands!

 So what does this mean for you?

Content that generates an emotional reaction is more likely to go viral. People share to say something about themselves. Emotional content helps them figure out easily what it is they are saying about themselves by sharing it.

Picture the audience your content is going to be appealing to, and find them in social media. Learn who they are and what makes them tick.

Your online audience is not a monolith. Online audiences are organised in sub-communities and congregate around key demographics variables such as age, profession, passions and interests.

Map your audience and identify the key communities that are going to help you reach out to at least 50% of your audience.

Once the communities are mapped,  identify the key gatekeepers by community and the connectors between key communities. This will help you reduce the outreach effort.

If your content is going to appeal to a broad demographic expect a longer run and make sure you have the right resources in place for seeding and advertising to a fragmented and  harder to reach audience.

Good luck.


Previous posts in this series:

Found this interesting? Got viral content of your own that you want to understand? Check out the tool we used for this study, Pulsar ( and contact us to arrange a demo – send an email to and we’ll be in touch in no time.

Or get in touch with the study authors, Francesco D’Orazio (@abc3d /LinkedIn) and  Jess Owens (@hautepop / LinkedIn).

The future of social media research [presentation]

In an article recently published in Research World Magazine and on his Tumblr blog Abc3d, our Chief Innovation Officer, Francesco D’Orazio outlines the challenges facing the social media monitoring industry – and 10 ways to tackle them.

Following the article Francesco has been invited to present at the MRS Social Media Research Summit  in London and at the Researching Social Media Conference in Sheffield, you can find the full presentation here:

Fixing Abercrombie & Fitch: how socially intelligent research can reconnect them with their customers

Our last blog post talked about ‘social intelligence’ as “a new life skill for brands”, and focused on Abercrombie & Fitch as retailer desperately in need of some.

But over on Twitter, @AlexPearmain had a question for us: “What would you have them DO?” A very good question! And, being a bit of a fashion brand nerd, I couldn’t resist working out the answer.

That is, if Abercrombie was closer to their customers they’d have seen this coming. Here’s how research could help them get back together.

Defining the problem

So Abercrombie have faced global negative press – headlines like, ‘Thin and beautiful’ customers ONLY: How Abercrombie & Fitch doesn’t want ‘larger people’ shopping in its stores.

But this discussion is led by adults, people outside A&F’s target demographic. Maybe their customers think differently?  Marketer Nicola Carter argued in the Guardian:

“A&F’s target audience are the cool kids at school, primarily teenagers. If Mean Girls is to be believed, members of this cool clique are thin, attractive, and prepared to protect their position – even if that means picking on the fat kids. It sounds like A&F’s positioning as a cliquey brand that likes to exclude others (especially the bigger boned) will be just great for that group’s filters.”


Some adults’ opinions certainly do matter to Abercrombie & Fitch: those of investment analysts, the people influencing their share price. That share price is well below 2011 levels, and below the heights reached in 2005-2008. Finance sites report their stock as a sell recommendation, and rising up the ranks of the most-shorted. Analysts’ comments continually talk about Abercrombie ‘losing its cool’ and failing to keep up with trends. So A&F need to do some serious repositioning work to fix that problem.

But worse, the evidence is strong that Abercrombie’s target customers are indeed being put off. Sales fell 13% last quarter. And Abercrombie are having continuing problems with inventory, which strongly suggests they don’t know what customers want, when, in which stores and in what quantities. Consumer tracker surveys back this up: sentiment about the brand is down.

Meanwhile, Florida 18-year-old Benjamin O’Keefe has set up a petition with 78,000 signatures calling for an end to their size discrimination. And their Facebook profile is a mess:

Abercrombie & Fitch criticism on Facebook

Our brief

Put Abercrombie & Fitch back in touch with its customers.

Recognise a grain of truth in the offensive things its CEO has said in the past - “Candidly, we go after the cool kids… A lot of people don’t belong [in our clothes], and they can’t belong. Are we exclusionary? Absolutely.”

So Abercrombie seeks to be an aspirational brand. We can work with that.

Thing is, it’s out of touch with what’s aspirational among its core audience.

It also needs to learn about how aspirations have changed. What’s aspirational in a difficult economic climate? Is ‘aspiration’ even as relevant to Millennials, or are other values in the ascendant? And how does Abercrombie evolve its white preppy aspiration model in an America that’s rapidly becoming majority-minority?


[Source: The Black Ivy, project by Joshua Kissi and Travis Gumb of The Street Ettiquette fashion blog]

Our research approach

So we’ve been talking about “socially intelligent research” a lot recently at FACE – now here’s a chance to outline what this might look like in practice.

1. Participation is continuous with teens’ existing digital lives

Why this is socially intelligent: An immersive research experience gives deeper, more accurate insights. We can also use passive data collection from social media to gain insights at scale to validate – and extend – our thinking.

What this looks like:

  • Research tasks take place on Pinterest and Tumblr – sites they’re already using. We don’t want essays about what teens find aspirational – we want them to show us visually
  • Chats and video hang-outs through Skype and Google Hangouts
  • All already mobile-optimised – completely essential for this age-group

Doing research that fits with teens’ digital lives also means integrating the data created by their social media activity. We’d do this in two ways:

1. Social media brand tracking to capture what tens of thousands of people think about the brand, not just our direct participants. These insights can be fed into the research community as questions or tasks – or resources we invite them to reflect on. This way we triangulate our insights and build much more robust conclusions.

2. Integrate teens’ digital activity into our community as a data resource. With their permission, mine their Facebook activity, Twitter, Instagram, Spotify, YouTube and other media use.  We get more accurate data – what they actually say & do, not their recollections of their behaviour. And the participants are of course incentivised for this data sharing and get to focus on the more fun and creative tasks.


2. Teen participants as co-creators, not research subjects

Video has to be central to this research – we’re talking to a generation making YouTube videos, Instagram video, Vine and Snapchat. It’s also a great way to deliver stories and on-the-ground narratives in a digital way – cutting down our research time and costs.

So we’d propose to use video in many of our tasks:

  • “Auto-ethnography” and narrating their experiences
  • Interviewing friends
  • Involve a couple of particularly video-literate participants in editing and producing final videos, aggregating the group’s submissions

Key to an ethnographic model is inviting self-reflection – that is, never disrespect your research participants by assuming they’re not capable of analysing their own behaviour. Teens can be some of the most self-aware people out there in terms of thinking through social & group norms and how they modify their behaviour to fit. Given that we’re talking about what’s aspirational, it’s crucial to bring this social reflexivity in.

We’re doing that with the video ethnography methods – but we’d also involve our participants in the research analysis process and test our insights with them. They are co-creators and the ultimate judges of our brand positioning outputs – if it can’t pass our teen test panel, it’s not yet a solution for Abercrombie.


[Source: How To Be An Explorer Of The World by Keri Smith]

3.  Immersive experience for brand stakeholders

Why this is socially intelligent: Research needs to work as thoughtfully with the needs & cultures of our clients as we do with our participants. Abercrombie’s a fashion company: 100-slide Powerpoint decks won’t help them change.

What this looks like:

  • Video outputs strong emotive communication of the overall message. We’re trying to reposition a brand – it’s got to work at gut-level if it’s going to succeed.
  • Video is also more shareable around the company than a PPT
  • Moodboards on Pinterest and Tumblr provide a lasting and visual resource, helping designers and stylists keep in touch with their
  • Final delivery involves face-to-face interactions with our participants – e.g. in-store walkthroughs and workshops. This brings the message home to Abercrombie execs in an immersive and unforgettable way


So that’s an outline of how we’d help Abercrombie get back in touch with its customers and return to being a brand teens want to wear – and buy – again.

Most of the project’s run digitally, meaning it’s faster, cheaper, and able to cover more of Abercrombie’s customers and markets. It combines the scale of social media research with the deep ethnographic insights of qual – because here at FACE we don’t believe these things are exclusive. And it produces rich visual, video and immersive outputs – no Powerpoint required.

Socially intelligent research, using social data, to turn brands into ‘social businesses’ able to tap into all the ideas, creativity and resources beyond their walls. That’s our vision.


Liked this thinking? Follow Jess on Twitter (@hautepop), get in touch ( or hear her talk about how Gangnam Style went viral in our webinar next week.

Building social businesses: the role of research

Following CEO Andrew Needham’s blog post introducing the idea of “socially intelligent research”, we – that’s MD Job Muscroft and social media researcher Jess Owens – wanted to talk more about this concept in its wider context.

What is ‘social business’ and how did this idea develop? What kind of tools and working practices does it involve?  And what kind of research might socially intelligent businesses need?

What is social business?

The term ‘social business’ is closely associated with Prof. Muhammad Yunus, the Nobel prize-winning Bangladeshi economist who developed the Grameen microfinance bank. His 2008 book, ‘Creating a World without Poverty: Social Business and the Future of Capitalism’ popularised the notion. It’s worth noting, however, that the Yunus Foundation  defines a social business as “a company created for social benefit rather than private profit”. In the UK, we’d tend to call this a ‘social enterprise’ – in the US, a ‘non-profit’ – and its focus would be explicitly charitable.

The definition of social business that we’re using is slightly bigger (Cello shareholders will be glad to hear private profit is allowed!) but it shares a core belief in building a business whose impact and relationships extend beyond its own four walls.

It’s a tech-informed model that takes from the rise of social media in the 2000s. Social media changed media because it made the relationships between people as important – and as visible – as their top-down relationships with ‘authorities’. It turned the general public from a passive audience into active creators. People’s opinions (and disagreements) about a topic no longer had to remain private, but could be presented on the same channels as the news article itself.

The world did not become ‘flat’ overnight – hierarchies remain, and indeed new ones have been formed. But the shift in social, cultural and political power has been profound.

Social business tools

Social business takes these principles and applies them to business organisation. And it recognises that tools inspired by social media – such as forums, wiki discussion boards, chat and social networks – should become a core part of business communications too.

So companies use tools like Yammer which provides a social network like Facebook and Twitter, allowing employees to build relationships across teams and collaborate (and innovate) more effectively. As consumer social media has made visible, relationships among peers are just as valuable – or more so – than the formal structures of teams and organisational hierarchy.

Yammer enterprise social network dashboard

Or back in 2007, telecoms company BT created ‘BTpedia’, a Wikipedia-style resource about how their business operated. As their intranet manager Richard Dennison explained,

“The idea is that, by simplifying and democratising the publication process, we will unlock a wealth of informal information that is currently excluded from the highly structured and more formal content hosted in our web content management system. Each article also has a discussion tab associated with it which flushes out like-minded people and facilitates connections between them and ultimately communities.”

So social businesses are companies that are thinking hard about their human and intellectual resources, and how best they can really work. And it’s not just about employees – recognising the value that sits outside the business is just as important. This may be relationships with suppliers, or trusted advisors – or even finding opportunities to collaborate rather than compete with other companies in your industry or region.

But the other big pillar of social business is the customer and the ideas and creativity they can share with businesses willing to listen. The customer is absolutely central to the success of your business, after all (if they don’t buy, you don’t have a business…) so the more involved they can be, the better your products can meet their needs.

How social businesses connect with their customers

The mobile network operator GiffGaff uses both ‘social sales’ (customers are financially incentivised to encourage their friends to join the network), and social customer support, provided peer-to-peer in the GiffGaff forums rather than by phone. This saves them a huge amount of money in staffing, allowing them to offer an extremely competitive tariffs and build market share – and a loyal customer base.

Or ‘crowdsourcing’ – even though the term was only created in 2006, its uptake among businesses has been rapid. Unilever have crowdsourced consumer contributions for everything from a Peparami advert to their sustainability initiatives. Ben & Jerry’s also frequently uses crowdsourcing for ice-cream flavours, names and ingredients, gaining both press coverage and customer engagement.

Ben & Jerry's crowdsourcing ice cream flavours

Crowdfunding through Kickstarter is also becoming an increasing channel for new businesses to get off the ground – the Pebble smart watch recently raisedover $10m, proving the model can scale and is likely to be a serious new retail channel to watch.

All these examples  should show that social business is not just about social media, as some may think. Instead, social business is a guiding principle of openness to influences outside the company’s four walls – new and fresh ideas may well come from outside. Then, social business also involves a reorganisation of internal processes so that these ideas from new sources can successfully turn into real products and real changes. It’s business as hub and coordinator – a move away from old “command and control” models to something radically more collaborative, flexible and adaptive.

Nonetheless, social media has to be mentioned as a way businesses can listen to their customers and tap into the wisdom of the crowd. Social dashboards can help spread this insight throughout the company, bringing the business closer to its customers and helping these “outside” ideas inform decisions within the business, in real-time. Take a look at this article covering three great examples where listening did – or should have – helped brands manage difficult decisions.

What is the role of research in a social business?

Research has long been what connects the business with the customer – who they are, what they want, how they’ll use your product and the context of their lives that it has to fit into. So research has to be a crucial part of the social business toolkit as companies seek competitive advantage by more fully using the ideas and creativity their customers have.

Since about 2007 we’ve been seeing a substitution of old research methods such as surveys and focus groups for ones with more of a ‘social business’ slant. These methods include online communities, co-creation, social media research, and crowdsourcing innovation projects. The benefits are substantial:

  • Using technology for greater efficiency, both for the participant and for clients engaging in the research process day-to-day
  • Faster projects, allowing companies to use customer opinion in more decision-making
  • More collaborative, allowing many different ideas to feed into the final solution
  • More social, helping brands see their customers in the context of their wider social interactions and lives

The research industry has to a considerable extent embraced these methods, but what we have been less clear about is the new model of knowledge creation and business benefit.

Altimeter have produced several important research papers developing social business models as a whole, but it’s not especially market research-focused.

Meanwhile the research industry is in danger of presenting tools like online communities as a mere cost-effectiveness improvements, without advocating strongly enough for how deeply they can advance the relationships brands have with their customers.

So this is what we are seeking to do at FACE with our “Socially Intelligent Research” model. We want to combine social business technologies and models with social intelligence: “the capacity to effectively navigate and negotiate complex social relationships and environments.”

Socially Intelligent Research Framework

Social business + social intelligence = socially intelligent research

That’s the toolkit our clients need to help them adapt to the hyper-connected digital lives of their customers and the challenging global economy that, five years into a slump, shows few signs of improving. New, more efficient and creative ways to deliver customer services and create new products are essential in this environment.

And it’s the toolkit we ourselves need as a research consultancy too. Social business provides a model for how we can work most efficiently and collaboratively with clients, freelancers and our international offices. And social intelligence is the capacity we need to show in how we understand the context of consumers’ lives, and design research projects to work productively with this.

Tech is certainly an important part of this, from understanding the technology and media use shaping consumers’ lives, to the technologies and data sources we may use as research methods. (Not to mention the ways we communicate with clients, whether by teleconference or video workshop outputs). But it’s not the end goal.

The end goal is a holistic view of the customer, creating insights situated within the social context of customers’ lives at a level earlier research methods couldn’t do.

The end goal is helping brands put the customer and their needs at the heart of their business, building better customer experiences and stronger, more profitable relationships. Ultimately businesses fail when they don’t meet customers’ needs and solve people’s problems. The role of socially intelligent research is to help companies keep these needs central to everything they do.

Stay tuned for more updates on how we’re doing this and the results we’re able to achieve…