Apple Bites on Social Media
On Monday, Apple made a sizeable bet on the value of social media by acquiring social media search and analytics company Topsy Labs for upwards of 200 million dollars.
There's a lot of speculation on why Apple made this purchase, but a few things are clear: First, one of the largest and most successful retailers in the world has further validated that there's value in the wealth of data that social media provides. Second, just collecting the data isn't enough. Third, consuming and analyzing the data is of utmost importance.
A purchase of this size isn't just about data. Apple, as a Twitter partner, already had access to the Twitter data firehose. There are other Social Data Aggregators in the marketplace (DataSift and GNIP, for example), too, so Topsy must have something special. That would be Topsy’s user-facing tools, including a topic and trends search engine, which have made it one of the more popular options for people looking to make sense of the stuff people are tweeting about.
Topsy analytic capabilities might have appealed to Apple for a number of reasons, including using social media data to better target advertisements or to feed relevancy algorithms for suggestions in the App Store.
Topsy did an experiment involving one of Apple’s flagship products, the iPhone 4S. In a September interview, Topsy executives described a project for a hedge fund in which they tracked sentiments on Twitter about the October 2012 introduction of the Apple phone. The phone underwhelmed professional critics, sending Apple’s stock down. But Topsy found that Twitter users were more positive, suggesting that the phone would sell well. Sure enough, Apple reported strong sales figures later, sending the stock up.
There's more. Interestingly, social media analytics has shined a light on the value of gathering insights from unstructured textual data. Social media happens to be the most popular source unstructured data, but organizations across all industries have an abundance of unstructured and semi-structured data they have been gathering for years, including call center transcripts, maintenance/repair logs, customer notes in CRM systems, and emails to a help desk. We're working with our customers to drive value out of those sources, as well as social media sources like Twitter and Facebook, by applying text analytic techniques, like word frequency or sentiment analysis, and then exposing those results throughout the organization using InfoApps or search-based applications.
At any rate, it's clear that it’s never enough to just have the data. The job isn't done until you've made something out of it by analyzing the data you have. I don’t know about you, but if I see an apple on a table I may just keep walking -- but if I see an apple pie, I’m going to stop and take a bite.