根據 Fast Company 的報導，三星聘請 Networked Insights 分析線上資訊，以了解 iPhone 的缺點
"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."
然後，推出行銷廣告以強調三星的優點
"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."
進一步則是利用機器學習 (machine learning) 做客群分類 (classification)
"Dan Cropsey, a senior vice president at Networked Insights, added that a big part of how this benefited Samsung was affinity classification. Samsung could look at customer sub-segments they viewed as likely iPhone switcher-overs, see which celebrities they most admired, and then make sure Jay-Z and Martha Stewart are turned into Samsung users.
The same affinity classification was used to look at customers’ lifestyle preferences--using machine learning, you can infer with reasonable accuracy whether a customer prefers Whole Foods or Trader Joe’s, for instance. This was then used to bunch Internet posts into clusters which were used to find unexpected complaints about Apple like long lines at Apple stores or dissatisfaction with the headphone jacks on Apple products. This information was then later used to refine Samsung’s anti-Apple marketing efforts."
蘋果公司的反應？
"Apple could have done the analysis, but other documents unearthed in the hearings show that Apple declined to hire Networked Insights. Arthur Rangel, a senior director at Apple, sent an email in January 2013 to Apple senior vice president Phil Schiller referencing a Fortune article on Samsung and Networked Insights and asking why Cupertino didn’t use a social media monitoring service like their Korean rival. Schiller said there was no need for one."
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