# Computing Estimated Sales for iPhones of Fiscal Q1 2015

We are attempting here to estimate the total revenue from iPhone sales for the holiday quarter 2014 (Apple’s fiscal Q1-2015). Obviously, we can only estimate based on certain assumptions. Some of these come from news reports, others are our own.

In order to compute the iPhone revenue for any given period, we need two thing:

1. Number of units sold
2. Average Selling Price (ASP)

Units:

In the Seeking Alpha article, we show that analysts are predicting as high as 72 million iPhones will be sold this quarter. So here we will use figures ranging from 58 million units to 72 million units.

ASP:

The ASP estimates are a lot more difficult to compute than units sold. To do so, we need to know two different distributions:

1. Distribution of memory configurations for each model.
2. Distribution of models sold.

The 5c has only one model.

The 5s has just two models, 16 & 32 GB, and I have assigned 90%/10% respectively.

The 6 & 6 Plus I have assumed will have similar distributions of the memory configurations. We have both conservative and bullish distribution estimates.

In some of the charts, tan rows hold conservative estimations, and turquoise rows will hold more estimations.

To compute the overall ASP for a given model, you take the sum of the price for each configuration times the distribution percentage.

Computing overall ASP

Once we have an ASP for each iPhone model, we can compute an overall ASP by multiplying each model ASP by its percentage, and summing the products.

The results is \$665 for the conservative model, and \$720 for the more bullish estimates. This gives a range of \$55 for overall ASP

Computing Revenue

Revenue is simply the product of the number of units estimated to be sold, times the ASP. The table lists for several sales figures.

The low of 58 million is only a 14% increase over last year’s sales, which should certainly qualify for a conservative estimate.

Note that the bullish estimate is bullish both for distribution of the various models and the distribution of the configurations within each model.

For complete revenue analysis see the companion article

Historical data Q4 & Q1 2014 (fiscal)

Margins

We have also computed Gross Margins for the products, using bill of material (BOM) figures from IHS and teardown.com. Combining these with memory configuration distributions gives average gross margin per product.

For iPhone 5s and 5c I have assumed 10% cost reduction from last year.

BOM figures include manufacturing costs. Currently, for the 6.6+ models there is an extra cost of about \$22 for the 64 GB configuration and \$47 for the 128 GB configuration.

From here we compute the average gross margin per product model.

Finally, we have the tables with the BOM estimates from IHS and Teardown.com.

• …the company is spending only \$47 more on the 128 GB version, if we compare it to the 16 GB model. By contrast, the gross margin on the iPhone 5 and the iPhone 5s was 69%.
• “They seem to be configured and priced to encourage you to buy the models with the higher memory,” said Andrew Rassweiler, the IHS analyst who supervised the teardown. He estimates that Apple is paying a price of about 42 cents per gigabyte on the flash memory, which is supplied by numerous companies, including Micron and SK Hynix.

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