In the December quarter, Apple became the largest seller of smart phones in the world for the first time. Here is my tweet from September 4th.
So I can’t say I’m shocked. Yet, with a number of analyst firms reporting or about to report we are getting confirmation Apple did indeed pass Samsung in sales last quarter.
You can expect some mild disagreement with this claim. Counterpoint has come in and given the lead spot to Apple. While Strategy Analytics has called it a “shipment” tie. Granted, the Strategy Analytics headline acknowledges Apple as the top vendor, since Apple sold through their number and Samsung did not. I also expect Gartner and IDC to come in around this range for Samsung shipments. The takeaway is it was close. However, one thing no one at any of the firms will deny is Apple did, in fact, sell more smart phones than Samsung.
I prefer to base my models attempting to track sell through. I have access to live device data which helps me put parts of this puzzle together. From all the sources I have, and trying to get closer to sell through by the vendors, this is where I landed.
For Tech.pinions subscribers next week, I’ll do a deep dive on the December quarter smart phone data and detail the implications pointed out in my global model as well as look at some updated installed base estimates.
While an impressive feat, last quarter’s iPhone numbers are further evidence Apple defies conventional wisdom. Certainly, Samsung will be number one again next quarter. There are also certain questions circulating around Apple sustaining this growth as Bob O’Donnell goes into here for our subscribers. What we have to recognize is the trend lines. Trend lines, followed by sound study of global markets, is what gives us insight into not just current trajectories but future ones as well. Ultimately, that is what matters in this analysis. A good analysis is not just a snapshot in time but sheds insight into where things may go. This is where the focus will lie as we analyze the key story lines for 2015. Luckily, using sound data models, we can develop more educated insights about what lies ahead.