An excellent case study demonstrating the value of social media research has emerged from an unlikely source: the Apple vs. Samsung patent dispute.
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 recognized the power of social data for “thinking forward”, for understanding customer needs strategically to feed into product innovation and early-stage communications planning. At Face, we think this is an incredibly valuable and under-utilized use-case.
Here’s how it works: Samsung used social data strategically, to attack Apple.
From Neal Ungerleider in Fast Company, 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.
Meanwhile, 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:
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 would 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 analyzable as a whole in a way that free online tools simply can’t. For example our platform Pulsar 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 visualize 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 realized this, Apple didn’t.
Jess Owens (@hautepop) is a social media researcher at Face, the socially intelligent research consultancy. As one of the earliest members of Face’s Global Social Insight team, she has pioneered new research methods with social data, from audience mapping, channel effectiveness studies and studying social media virality and content diffusion.