Archive for the ‘Mobile’ Category

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

As Ray Poynter notes, mobile has finally arrived in market research!

 “people have been saying mobile is the next big thing for over 15 years, even in the days when that meant SMS, or WAP, or writing 100s of apps for different types of phones. At conferences and client sessions I keep being asked “So, when will mobile be the big thing?” The answer is that it is now a big thing, and it has been for probably 18 months or more.

What’s notable though is that industry discussion is still oriented around the ‘grand dames’ of the market research toolkit: surveys (now moving from online to mobile, albeit sometimes “accidental mobile”) and CATI (telephone interviewing). Here at FACE we’re wondering, what about qual?

Well, let’s start talking about mobile qual! We’re excited to have research director Sharmila Subramanian writing a series of articles for us sharing her vast experience of mobile research methods, something she’s built up over many years of research with Nokia in particular.

Mobile research

First, when do you need to use mobile research methods? Sharmila shares three case studies:

Why mobile is useful: 

Here at FACE, we are committed to trying to root consumer understanding and resultant insights within context as much as possible.  This requires us to be able to understand consumer moments and interactions when they happen – not just in the home, not just in the research environment. Out of any tool for capturing thoughts and behaviour, mobile presents the best means of doing so.

Beyond this, mobile provides a simple and intuitive interface for capturing consumer attitudes and behaviours for a number of obvious, but important reasons:

1.  It’s people’s primary communication device

2. It’s an extension of people’s bodies and selves: always with them, always on. This makes it invaluable in gathering in-situ understanding

3. It’s the most personal device that people own, so it’s a fantastic platform for capturing more  private or personal thoughts and behaviours

4.  People are used to engaging through apps, making a mobile research app a logical research interface

This is not to say that mobile should be utilised for any & every research activity. It is a one-way method of research, with little scope for researcher-participant interaction. As a result, it is not for briefs or lines of enquiry that require a great deal of laddering and researcher probing in real time.

Moreover, its very nature does not lend itself to long form, highly considered response. When was the last time you tried to write something akin to an essay on your mobile?  I bet it was pretty painful.  Don’t expect any different for a research participant!

Three use cases for qualitative mobile research

From our own experience on a range of projects, mobile research comes into its own on three types of briefs:

Mobile research FACE App

1. Understanding response to concepts:

Whilst we would not advocate a mobile-only methodology for concept testing and development, mobile can prove an invaluable supplement to F2F methodologies where we wish research participants to “live” with concepts beyond the confines of the focus group facility. Initial reads on concepts often give us an understanding of their initial impact and wow factor. However, getting participants to then live with the proposition, and document when they see roles for certain ideas and concepts via mobile, can go much further in identifying their potential usefulness, and ability to fulfil needs within the real world.

On a recent project using FACE’s mobile research app, this approach proved invaluable in deepening understanding around a concept for a new service.  Whilst an online community and groups gave understanding of the initial comprehension and appeal of that concept, subsequent mobile research gave us a richer picture of where participants actually saw a role for the proposition – in terms of where, when, how they would utilise it and why.  We would not have been able to get that level of understanding by utilising other methods that rely on hindsight or recall.

2. Product trialing:

Mobile can come into its own in terms of understanding product usage and response – ultimately, it gives us the ability to understand those moments in-situ, as they happen.  And it makes it easier for the user to document those moments – no paper diary completion, no need for recalling of hazy memories on an online community or in a group.  Everything from first impressions of a new product, to first and repeat usage, to understanding how response to a product can change over time can be readily captured within mobile research. Moreover, it gives us the ability to understand all of those things across a variety of contexts, times of day, as well as the social dimension that may be at play.  As a result, we get closer to a more holistic understanding of product usage.

A recent example of the power of mobile for product trial can be seen in a project FACE conducted looking to understand response to a new product format.  FACE’s mobile app was used by a range of participants over a week to understand their first impressions of the product, how they used it, the triggers and barriers to use, and how their response changed over time.  This helped us to define the key benefits and use cases for the product prior to launch, as well as helping to provide starter thoughts for which elements of the product experience future communications should leverage.

However, the approach also proved powerful in providing a wealth of rich multimedia material that could be utilised by the client to provide more compelling evidence of the value of the product.

Mobile research FACE App

3. Shopper interaction:

The very mobile nature of the, well, mobile, clearly lends itself to helping to better understand the shopper experience. Whether in terms of gaining learnings on retail environment, in-store communications, or product placement, the discrete form, and bite-sized mode of interaction of the mobile makes it ideal for consumers to gather quick thoughts, images, and documentation of journeys within store.

FACE employed a mobile approach for understanding response to a new store layout format for a well known food and drink brand. This was invaluable in gaining firsthand accounts of what was a new concept in-store – accounts that were not influenced by researcher presence. The unmediated nature of this capture was essential in identifying exactly what the key hooks, and turn-offs of the new format were, and helped provide a compelling story for the client, through the use of raw, consumer generated content, to help our client sell the concept to retailers.

*

So, that’s an initial overview of three times mobile research is one of the best methods we’ve got in our market research toolkit. Next up: getting the most out of a mobile approach – the do’s, the don’ts, and  best practice for making a mobile methodology a success.

If you’d like to discuss this further with Sharmila, contact her at Sharmila@FaceGroup.com, on LinkedIn or Twitter @SharmilaSub. To stay in touch with more of our qual thinking and methodology knowledge-sharing, join our mailing list.

Face CEO Andrew Needham and US Office Head, Philip McNaughton, were at the Insight Innovation Exchange conference in Philadelphia earlier this week. I could not attend, and I was rather disappointed. While I know I have work to do, I still wanted to see Andrew and Philip present on Socially Intelligent Research and catch up on the latest industry buzz.

So I hopped on Pulsar TRAC and started a simple search looking for mentions of the conference and its hashtag (#iiex), similar to how we tracked Le Web two weeks ago. This way I could gather the digital buzz, and that’s the next best thing to being there.

Using Pulsar TRAC I was able to gather all the mentions o the conference. Granted, total volumes were only around 1,500, but that’s not the point. The point is that using Pulsar TRAC’s ability to parse the data, I was able to see what ideas presented got people excited, what articles were shared, and who I should be following on Twitter.

Day 1

People enjoyed the morning’s action-orientated presentations. Charles Trevail’s talk, “Inspiring the Future” was all about how to find breakthroughs in the face of adversity. When Jeffrey Henning summarized it on GreenBookBlog.org, the message continued to travel around the conference the rest of the day.

Day 1 Volume

Trevail was followed by Robert Moran, who kept the energy up with an emphasis on how the industry will look in the future. Apparently we’ll either be futurists, identifying trends, or doing “fast fashion” data analysis, looking at data in real time to facilitate improvements.

Ryan Smith went up next to talk about “Cheaper Faster, Better: How Technology Delivers ROI to Insight Organizations.” His focus on the importance of the researchers who make sense of the data and the continuing development of technology was well-received online.

Following Smith, Jasmeet Sethi from Ericsson spoke about being frugal, both by necessity and choice, in order to help spur innovation. This was perhaps one of the most buzzed about talks, driving mentions at the time and afterword with the sharing of the summary of it on GreenBookBlog.org.

The afternoon’s online chatter continued where Smith left off. Two different speakers, Seth Grimes and Zachary Nippert, had a very similar message: big data is only as good as it is useful, and we need tools that will help us make it useful.

Day 2

Day 2’s online buzz was focused more around behavioral economics with two keynote speakers, Mark Earls of “I’ll Have What She’s Having” fame and John Kearon of BrainJuicer driving most of the online chatter.

Day 2 Volume

The ideas that resonated were, again, that we need to focus on the people, not the technology. According to Earls, rather than focusing on the new technologies themselves, we should be focusing on how this new technology can enable researchers to identify how people are connected to each other, what goes on between them, and finally how things spread from person to person.

Kearon, in turn, discussed the role of emotion in decision making. He focused on the need to understand emotions and habits in order to understand how we make decisions. This resonated with the audience, probably at least in part because of such lovely quotes as the one below:

Kirk vs Spock

Using Pulsar TRAC’s bundle visualization, you can see that “people” – though not the most frequent keyword – ran through most of the other topics discussed online the rest of the day.

People in Conversation

Day 3

The first spike at 9 am focused quite a bit on Simon Chadwick’s talk on investment in market research. People retweeted the stats in his presentation, focusing on such things as a 141% increase in VC funding for MR, particularly in big data, mobile, and social media but not in traditional research at all.

Day 3 Volume

But perhaps the biggest driver of mentions on the last day was sharing links. During the entire conference, only 12.6% of mentions included a link, but on the last day, 22.7% of messages included links.

Links Visualization

The top shared links of the day were all summaries of presentations:

But who would I have met?

That’s all well and good, but beyond going to a conference to hear about what’s hot in the industry, I go to them to meet people. How could PulsarTRAC let me do that?

I used Pulsar’s ability to find influencers based on not just volume, but also engagement to reveal who I should be following online. After all, I don’t just want to follow people who are vocal – I want to follow the people other folk turn to.

From this list, the top 5 influencers I should be following out of the Insight Innovation Exchange are:

  1. @melcourtright, Melanie Courtright, VP of Research Services at Research Now, presented “Research Now and Experien: Bridging the Digital Gap” at the conference
  2. @Pspear. Peter Spear of Spear Strategy, “brand listener”
  3. @SpychResearch, Ben Smithee, CEO of SpychResearch
  4. @lennyism, Leonard Murphy, Editor-in-Chief of the GreenBook Blog and key conference organizer
  5. @AndrewNeedham, Andrew Needham, CEO of Face… I do believe I know this influencer

Influencers

But what was it all about?

The conference was an interesting combination of technology and research methods. At first I was worried that we’d get side-tracked by sexy displays of technology, but it remained focused on how we can use technology to assist and augment our research and analysis. But while the first day was marked by excitement, the next two days saw lower online volumes as people got into the routine of going to panels. The panels themselves were very quick, mostly only 20 minutes long, so there was less to Tweet about for each speaker.

I wish I had been there in person – but seeing as I had work to do in New York, this Pulsar TRAC search was the next best thing.

*

Want to learn more about how you can use online buzz to follow content and conversations? Register now for our Viral Video Webinar: Gangnam Style vs Harlem Shake on 10 July!

Here at FACE, we live for the moment – and we especially like to do it in the name of research. Researching live experiences used to be a matter of showing up, doing interviews at various points, and taking down notes throughout, maybe a survey here or there. But that’s not our style and things have changed (we love change!). Now, people can experience everything the world has to offer in real time while simultaneously contributing and sharing experiences with others through mobile and social media. It’s been great news for us, because we get even more opportunities to delve into understanding what is happening and why.

We’ve been doing more and more research in this area and are fascinated by it. So in the spirit of experiencing and sharing, here are some tips that have helped make our live research live up to the definition on Urban Dictionary: “jumping, full of people, exciting!”

World Cup Stadium
Image by Flickr user Shine 2010 – 2010 World Cup good news

1. Focus

When going into any kind of live event (whether physical or digital, or both) having a clear objective and a plan are incredibly important. Whether we are looking at engagement with a message, understanding behavior in context, or identifying opportunities for improvement, having a focal question helps to narrow in on exactly what kind of information the research should prioritize over all of the other (distracting!) aspects that make live events so fascinating.

2. Technology

Even a few years ago, asking people to do things while they were doing something else was fraught with difficulty (think paper diaries, and intercept interviews). But now, online behaviors have really shifted in our favor in regards to collecting data during live events. Liveblogging, livestreaming, updating, checking in, – all of these methods act as shortcuts that help participants get their thoughts directly to us without getting in the way of the experience itself.

And the best part is that people are already engaging in these behaviors in their personal lives. We’re just extending an already existing behavior into a research situation. Just be sure to choose your technology medium carefully. Make sure that it fits within the situation you’re looking at. For instance, check-ins are useful if you’re studying gym-workout behavior. But they’re not really that useful if you’re looking at the experience of a live concert.

3. Real-time integration

This should go without saying, but I am going to say it anyway. In order to capture what happens ‘live’, the research simply has to be happening at the same time. The information you get from people experiencing something in the moment (even if it doesn’t seem relevant at the time) is extremely powerful and should not be left out of the picture. When people look back on experiences in retrospect, it is often lacking a lot of the rich contextual information that is key to understanding what is really going on in the moment.

4. Thinking about dimensions

Live experiences are akin to animated objects – constantly changing in look, feeling, and experience. There isn’t always a clear beginning, middle, or end, and things can take dramatic turns. There is a lot of reading between the lines.

Where traditional research might normally have limited perspectives across a few points in time, a live research approach gives us the opportunity to explore multiple vantage points over the entire duration of an experience. The added dimension of change over time means that we can better understand the subtleties of live experiences in ways that people might not be aware of in the moment or even after the fact.

Ultimately studying live experiences can be a whale of a proposition but it is always worth it. We are looking forward to the next opportunity to lose ourselves in the moment.

Flashing lights

Social media made online social behaviour measurable.

Now smartphones are doing the same with face-to-face interaction – thanks to ‘machine sensing’. Machine sensing is basically data collection through sensor-equipped machines, where a sensor is a converter that measures a physical quantity and converts it into a signal which can be read by an observer or by an instrument.

Traditionally mobile market research has mimicked what can be done on the web, with poorer interfaces and engagement. But with smartphones enabling mobile sensing, the opportunity got much bigger and much more interesting.

Mobile sensing is the passive recording of a person’s online and offline daily life in a quantitative way. Sensors in the mobile handset can be used to capture communication, proximity, location, and activity data alongside the more established prompted inputs: a 360-degree approach becoming known as Reality Mining.

Longitudinal collection of this data produces a depth of information on behaviours, interactions and states that can reveal patterns and insights that would be impossible to spot on an exclusively qualitative basis.

Back in July 2012 I ran a pilot project on a sample of one (me) to assess the potential of mobile sensing within the industry. How could market research use ‘reality mining’ to develop a better understanding of consumer behaviors and attitudes? And how useful would it be?

The presentation below gives an overview of the Reality Mining project. A more in-depth paper will be published over the next few weeks discussing the details of the set up, the research methodology and the outputs of the project.