Modelling Sales of iPhone 5 Series
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Transcript of Modelling Sales of iPhone 5 Series
Modelling the sale of iPhone 5 series BUSINESS DYNAMICS
Final Project report
Abhik Tandon Vishal Lunker
Anmol Pandey Akshat Gupta
Table of Contents
Contents
Background _________________________________________________________________ 1
Success Factors _____________________________________________________________ 2
CLD & SFD _________________________________________________________________ 4
Final results ________________________________________________________________ 18
Appendix __________________________________________________________________ 20
Pg. 01
Background
Background iPhone 5 became an instant success when it was launched in 2012. Apple witnessed record
sales and the product series was one of the most important reasons to propel Apple as most
valued company in history. This success was followed by another launch in September 2013
with the introduction of iPhone 5S. The growth of iPhone 5 series has been phenomenal and
has been attributed to various factors ranging from brand loyalty to product superiority. This
growth phenomena has been studied and modelled in this report.
Apple announced the launch of iPhone 5 in September 2012 and simultaneously began taking
pre-orders. It received two million pre-orders within the first 24 hours. The phone was a
considerable upgrade from the 4 series with better hardware and software features. iPhone 5
was reported to be sold out twenty times faster than the 4 and 4S models. However, the model
was discontinued in the subsequent year to give way to the 5S model - keeping in with Apple’s
strategy for previous iPhone generations.
iPhone 5S was launched with its mid-range counterpart iPhone 5C in September 2013. 5C
model has not been considered as part of this model as it was targeted at a different segment
altogether than 5 and 5S models. A comparison of features and specifications of iPhone 5 has
been summarised in Appendix 1.
Pg. 02
Success Factors
Success Factors The success factors of a new product launch has been studied in a publication by Gabriela
Capatina and Florin Draghescu1. The authors have identified the below success factors for a
new product launch
1. Product differentiation through product advantage
2. Strong market orientation through a high level of mkt knowledge
3. Clear and early product definition
4. Synergy between technology , production and business proficiency
5. Orientation on meeting the customer needs
6. The market timing
The authors go on to illustrate the success factors at different levels for iPhone product series.
These factors were included in the model.
Consumer factors
1. Demographics – The word of mouth publicity of iPhone’s target consumers
was a big factor in the success of the product.
2. Preferences – Consumers wish to have a mobile device which could function
as a mini computer was answered with iPhone. This increased attractiveness
of the product coupled with a great app ecosystem helped boost the sales of
the phone.
Company factors
1. Product – The product features as highlighted in Appendix 1 was one of the
most important factors in fuelling the demand for the product
2. Price – Apple provided the phone under a contract with telecom operators.
This helped customers to get the phone with a reasonable price
3. Distribution – The phone was distributed through Apple stores and Apple’s
website. The Apple stores provided a good platform for Apple’s salesforce to
increase iPhone’s consumer base and convert potential sales into final sales.
4. Promotion – Apple launches its product through keynote presentations. The
date of these presentations are announced in advance. The tech media helps
1 Success Factors of New Product Launch: The Case of iPhone Launch
Pg. 03
Success Factors
in creating the sufficient buzz for these events. Speculation is rife and is fuelled
by the media reports with new phone rumors. This helps Apple promote its
products. Apple also used traditional advertising but only in later stage of the
product launch.
Pg. 04
CLD & SFD
CLD & SFD Planned model variables :
Brand/Social influence: Word of Mouth, network effect
Pool of installed base of iPhone users
Rate of users added depends on Marketing, features and compatible products
Product attractiveness of the features
Competing phone and their features (Samsung Galaxy)
Advertising
Influence of complementary goods
Figure 1: Causal loop diagram
Pg. 05
CLD & SFD
The 4 loops shown above form the back bone of our diagram and are explained below along
with the SFD
Stock Variables
Potential Sales: The potential sales is total number of users that fit into the income category,
inclined to buy a smartphone from Apple and would buy once they like the product features.
This pool gets of potential sales, would get more users from geographic expansion indicated by
additional sales force addition and quality.
Sales: Final converted sales of iPhones in the time period, which is taken as quarter due to the
data constraints of analyst reports. Taking time period as quarter also makes sure that the
geopgraphic expansions and launches do not cause a kink and are accounted for inside
quarter from launch
Installed Base: The installed user base consists of current users of iPhone devices across
different generations who have bought the phone in previous 12 months , i.e.iPhone 3G, 4,4S
users.
Complementary Goods: The complementary goods here are referring to the app ecosystem,
where app developers work on the apps which are utilizing the current product features of the
launched phone. Now initially the apps launched would be huge using the current features
Pg. 06
CLD & SFD
which then would increase at a declining rate.
Figure 2: Stock & Flow diagram
The above diagram describes the various stocks and flows. As can be seen from the diagram
the effects of complementary goods and media reports feed into the attractiveness of the
product. While the word of mouth and network effects along with the advertising directly impact
the demand factor.
The variables are documented in Appendix
Pg. 07
CLD & SFD
Network Effects on the sales of iPhone
Figure 3: Network Effects Loop
Network effect is the largest contributor after the attractiveness of the product to the sale of the
iPhone. Easy switch to the newer iPhones from the existing ones and high costs of switching to
other smartphones has ensured the iPhone 5 series was able to build on the existing user base.
Pg. 08
CLD & SFD
The variable ‘attractiveness from network size’ is exponentially dependent on stock variable
‘Installed Base’
.
Figure 4: Dependence of attractiveness from network size on Installed Base
This attractiveness feeds into the demand factor with a weight of 30%. The demand factor is a
multiplicative factor of the conversion rate ranging from 0 to 1.
Figure 5: Attractiveness from Network Size
Pg. 09
CLD & SFD
Competitiveness of the product
Figure 6: Competitiveness of product
As a new phone is launched, it is capable of competing with all the phones in its segment. But
with passing time, it is expected that competitors take appropriate actions and the phone in
itself becomes less attractive and consequently less competitive.
Competitiveness is modeled as having a counteractive effect on the demand factor.
Competitiveness ranges from -1 to zero and has a ramp down effect with passage of time as
can be seen from the plot below. New phone launches propel competitiveness towards 0.
Pg. 10
CLD & SFD
Figure 7: Competitiveness over time
Sales force’s effect on Potential Sales:
Figure 8: Impact of salesforce & outlet addition
Every product attracts two types of customers, existing users of similar products and new
users.
The sales force has been modeled to attract new customers through the quality of the sales
force and the size of the sales force. Potential sales are the stock which is also affected by the
discard rate of existing users.
Pg. 11
CLD & SFD
Impact of complementary goods
The decision by third parties to produce complementary goods for a particular product depends
on the installed base of users and the potential revenue that can be generated.
Figure 9: Impact of complementary goods
We have modelled the attractiveness of the market to third parties as follows –
Pg. 12
CLD & SFD
Figure 10: Attractiveness to third parties
Market power over app developers has been modelled as follows -
Figure 11: Market power over app developers
Thus, as the sales increases the market power over app developers continuously increases.
The variable can take values between zero and 1 but even at the highest sales the value
achieved is approximately 0.8.
The market power over app developers and attractiveness of market to third parties along with
a dampener which varies over time. As time increases, the impact of these variables reduces
as shown below -
Pg. 13
CLD & SFD
Figure 12: Dampener
The attractiveness from availability of complementary products results in product attractiveness
that ultimately feeds into demand factor.
Product differentiation
Another set of positive feedback arises from the ability of the firm to invest in product features.
Apple invests heavily in its products. In the case of iPhone 5 the product was differentiated due
to its new and improved 16:9 form factor (larger screen) and certain other features. Based on
research reports we identified that the following trends justify the investments done by Apple –
Figure 13:Productive value of investment in features
Pg. 14
CLD & SFD
The productive value of the investment is shown in the graph shown above. The productive
investment drops in the 3rd quarter where the iPhone 5 investments are no longer made. After
that, investments for iPhone 5s become productive and these get reflected from 5th quarter.
Favorable Word of Mouth
There are four principal channels: advertising, direct sales effort, word of mouth, and media
attention, where all these channels create positive feedbacks.
Word of mouth loop works by installed base of users who would talk positively about the
product in their social circles, increasing demand and thereby increasing competitiveness.
Figure 14:Favorable Word of Mouth positive feedback loop (indicated by red arrows)
Favorable Word of Mouth Lookup function(range [0,1]) consists of already a loyal iPhone user
base, which makes it start from intermediate value, which first increases rapidly and then with
declining rates as the number of installed user pools starts to cover the smartphone user base
completely.
Pg. 15
CLD & SFD
Figure 15: Favorable Word of Mouth Loop Lookup function
Media Reports Loop
Media reports are taken to be weighted average of growth rate factor(40%), favorable word of
mouth (30%) and new iPhone rumors(30%).
Pg. 16
CLD & SFD
Figure 16: Media reports positive feedback loop (indicated in red arrows)
Growth rate factor which indicates the growth rate of Apple in terms of revenues also helps
attract media reports. Higher growth indicates stronger reception from buyers, and more
analyst, media coverage on brand of Apple itself. We have limited the growth rate for modelling
purposes in a time period to 200%, indicating factor as 1 for the value, and increases
exponentially between 25-50% quarter growth and plateaus after that.
Figure 17: Growth rate factor as function of revenue growth
Figure 18: Media reports factor over time
Pg. 17
CLD & SFD
Favorable Word of Mouth helps in generating mass interest in the product which is then picked
up the media and more articles start coming out of it. The new iPhone rumors are taken only
for quarters before launch, using the ‘pulse’ function to indicate 0.5 from time period 5 till the
launch of iPhone 5s.
Media reports indicate that since launch of iPhone 5, there has steady coverage, which
increases rapidly with the rumors of new iPhone 5s and then remain steady and then die down
as they are replaced by newer iPhone rumors and other products. Media reports feed into the
product attractiveness which then feeds into demand with weight of 50%.
Pg. 18
Final results
Final results
Figure 149: iPhone 5 series model results vs Actual
Based on the model we were able to simulate the key trends of iPhone 5 series sales and
compare that to the actual sales given in the research reports. The results were encouraging
and we were able to achieve a MAPE of 0.32. Due to certain limitations of the model this
MAPE may look high but by introducing some additional but less important variables we can
improve the accuracy of the model. Also, the model improvement can be modelled more
accurately if geographic expansion scenarios (apart from those included via sales force
addition) are included explicitly with proper dates of launch. Also, if data is available on monthly
basis it could help us in predicting trends with better accuracy and would obviously be more
insightful instead of just 4 data points in a year.
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
Dec Mar Jun Sep Dec Mar Jun Sep Dec Mar
Actual Model
‘000 units
‘000 units
Pg. 19
Final results
Figure 20: Complementary goods simulation
0
0.5
1
1.5
2
2.5
Dec Mar Jun Sep Dec Mar Jun Sep Dec Mar
Complementary Goods Actual data
Pg. 20
Appendix
Appendix
Variable explanation
(01) advertising= Min(0.5,Revenue*1e-012) Units: **undefined** (02) Attractiveness from availability of Complementary Products= Complementary Goods*0.1 Units: **undefined** (03) Attractiveness from Network Size = WITH LOOKUP ( Min(Installed Base,3e+008), ([(1,0)-(3e+008,1)],(1.41177e+006,0.0106762),(1.24588e+008,0.177936),(1.52176e+008 ,0.227758),(1.86765e+008,0.316726),(2.19294e+008,0.41637),(2.49765e+008,0.55516 ),(2.70765e+008,0.679715),(2.84353e+008,0.758007),(2.92176e+008,0.822064), (2.97941e+008,0.886121),(2.98765e+008,0.935943) )) Units: **undefined** (04) Attractiveness of Market to third parties = WITH LOOKUP ( Min(Installed Base,200*1e+006), ([(0,0)-(2e+008,1)],(-1.05882e+006,0),(3.88235e+006,0.0106762),(1.09412e+007 ,0.0355872),(2.01176e+007,0.0604982),(2.57647e+007,0.0818505),(3.14118e+007 ,0.128114),(3.88235e+007,0.213523),(4.55294e+007,0.270463),(5.08235e+007,0.341637 ),(5.92941e+007,0.455516),(6.42353e+007,0.505338),(6.88235e+007,0.558719), (7.72941e+007,0.683274),(8.71765e+007,0.822064),(9.50588e+007,0.850534),(1.14706e+008 ,0.918149),(1.33176e+008,0.921708),(1.66588e+008,0.950178),(1.80706e+008,0.960854 ),(2.01412e+008,0.978648) )) Units: **undefined** (05) Competitiveness= RAMP(-1/25, 2 , 4 )+STEP(0.075, 5 )+RAMP(-1/10, 6 , 12 ) Units: **undefined** (06) Complementary Goods= INTEG ( New goods added, 1) Units: **undefined** (07) Conversion rate=
Pg. 21
Appendix
IF THEN ELSE(Time<1,0, Max(Demand factor+Competitiveness,0.01)*Potential Sales ) Units: **undefined** (08) Dampener = WITH LOOKUP ( Time, ([(0,0)-(12,1)],(0,0.4199),(0.2259,0.2064),(1.948,0.09253),(4.744,0.04982 ),(6.042,0.03559),(7.2,0.04626),(7.9,0.03203),(9.09,0.02135),(9.544,0.0143 ),(10.31,0.0143),(11.18,0.01068),(11.49,0.003559),(12,0) )) Units: **undefined** -0.0686x + 1.2063 (09) Demand factor= advertising*0.1 +Attractiveness from Network Size*0.3 +Favorable Word of Mouth*0.1 +Product Attractiveness*0.5 Units: **undefined** (10) Discard rate= (Installed Base-Sales)*Max(0.05*ABS(COS((2*3.14/8) * Time)),0.01) Units: **undefined** (11) Favorable Word of Mouth = WITH LOOKUP ( Min(Installed Base,317*1e+006), ([(1.25e+008,0)-(3e+008,1)],(0,0),(1.09412e+007,0.0725979),(1.8e+007,0.145196 ),(2.71765e+007,0.251957),(3.6e+007,0.341637),(3.6e+007,0.354448),(4.05882e+007 ,0.405694),(4.65882e+007,0.439858),(5.78824e+007,0.469751),(7.34118e+007,0.529537 ),(9.88235e+007,0.602135),(1.24588e+008,0.597865),(1.27471e+008,0.622776), (1.32e+008,0.661922),(1.40235e+008,0.701068),(1.43353e+008,0.72242),(1.50118e+008 ,0.740214),(1.61235e+008,0.772242),(1.78529e+008,0.80427),(3.03294e+008,0.88968 ) )) Units: **undefined** (12) FINAL TIME = 12 Units: Quarter The final time for the simulation. (13) Growth Rate= IF THEN ELSE(New users added/Installed Base*100 >200, 200 , New users added /Installed Base ) Units: **undefined**
Pg. 22
Appendix
(14) Growth rate factor = WITH LOOKUP ( Growth Rate, ([(0,0)-(200,1)],(0,0),(22.0183,0.0336842),(39.1437,0.109737),(53.211,0.306579 ),(69.7248,0.49),(80.1223,0.821053),(100,0.99),(200,1) )) Units: **undefined** (15) INITIAL TIME = 0 Units: Quarter The initial time for the simulation. (16) Installed Base= INTEG ( New users added-Discard rate, 125*1e+006) Units: **undefined** iphone 3gs+4+4s users / last 12 month sale (17) Investment in Product Features= 1e+006+ STEP(-1e+006,3)+STEP(2e+006,5) Units: **undefined** (18) Market Power over App Developers = WITH LOOKUP ( Min(Sales,1.2e+008), ([(0,0)-(1.25e+008,1)],(-294118,0.00355872),(3.82353e+006,0.177936),(7.94118e+006 ,0.252669),(1.88235e+007,0.370107),(2.55882e+007,0.41637),(4.02941e+007,0.548043 ),(4.88235e+007,0.6121),(6.17647e+007,0.683274),(8.26471e+007,0.743772),(9.70588e+007 ,0.811388),(1.14706e+008,0.846975),(1.24706e+008,0.886121) )) Units: **undefined** (19) Media reports= Favorable Word of Mouth*0.3+Growth rate factor*0.4+New phone rumours*0.3 Units: **undefined** (20) New goods added= (Attractiveness of Market to third parties+Market Power over App Developers )*Dampener Units: **undefined** (21) New phone rumours= PULSE(5,5)*0.5 Units: **undefined** (22) New users added= DELAY FIXED(Conversion rate, 0.1 , 0 ) Units: **undefined**
Pg. 23
Appendix
(23) "Pot. add rate"= Sales force addition*quality of salesforce Units: **undefined** (24) Potential Sales= INTEG ( Discard rate+"Pot. add rate"-Conversion rate, 1.25e+008) Units: **undefined** (25) Price= 600 Units: **undefined** (26) Product Attractiveness= Attractiveness from availability of Complementary Products*0.2 +Media reports*0.1 +Product Features*0.7 Units: **undefined** include qlty of wrk 0.1 (27) Product Features = WITH LOOKUP ( Min(Investment in Product Features,1e+008), ([(0,0)-(1e+008,1)],(0,0.3),(1000,0.32),(10000,0.35),(100000,0.4),(1e+006 ,0.5),(1e+007,0.75),(1e+008,0.9),(1e+008,1) )) Units: **undefined** (28) quality of salesforce= 1000 Units: **undefined** (29) Revenue= Price*Sales Units: **undefined** (30) Sales= INTEG ( Conversion rate, 10) Units: **undefined** (31) Sales force addition= 0.01*Revenue/100000 Units: **undefined** say 100,000 investment required per outlet with customer (32) SAVEPER = TIME STEP Units: Quarter [0,?]
Pg. 24
Appendix
The frequency with which output is stored. (33) TIME STEP = 1 Units: Quarter [0,?] The time step for the simulation.
iPhone 5 comparison
Apple Samsung
Galaxy S III Droid RAZR HD Nokia
iPhone 5 Lumia 920
Screen Size 4 inches 4.8 inches 4.7 inches 4.5 inches
Resolution 1,136 x 640 1,280 x 720 1,280 x 720 1,280 x 768
Weight 3.9 oz 4.7 oz 5.1 oz 6.5 oz
CPU Dual-core Apple A6
Dual-core 1.5GHz Snapdragon S4 (in the U.S.)
Dual-core 1.5GHz Snapdragon S4
Dual-core 1.5 GHz Snapdragon S4
Storage 16GB, 32GB or 64GB, no card slot
16GB, 32GB or 64GB +microSD slot
12GB+microSD slot
32GB, no card slot
Connectors Apple Lightning microUSB microUSB microUSB
Operating System
iOS 6 Android 4.0.4 (Ice Cream Sandwich)
Android 4.0.4 (Ice Cream Sandwich)
Microsoft Windows Phone 8
Battery
225 hours standby, 8 hours talk time (3G)
790 hours standby, 11:40 hours talk time (3G)
TBA
300 hours standby, 10 hours talk time (3G)
Camera
8MP, 3264x2448 pixels, autofocus, LED flash
8MP, 3264x2448 pixels, autofocus, LED flash
8MP, 3264x2448 pixels, autofocus, LED flash
8MP, 3264x2448 pixels, optical image stabilization, autofocus, dual-LED flash
Networking Wi-Fi, 2G, 3G, 4G LTE
Wi-Fi, 2G, 3G, 4G LTE
Wi-Fi, 2G, 3G, 4G LTE
Wi-Fi, 2G, 3G, 4G LTE
Pg. 25
Appendix
Price
$199 for 16GB, $299 for 32GB, $399 for 64GB; avail. Sept. 21
$199.99 + $35 carrier fee
$199 (estimated, launch end of 2012)
TBA, launch Q4 2012
iPhone 5 vs 5s
Design
Device type Smart phone Smart phone
OS iOS (7.x, 6.1, 6) iOS (8.x, 7.x)
Dimensions 4.87 x 2.31 x 0.30 inches (123.8 x 58.6 x 7.6 mm)
4.87 x 2.31 x 0.30 inches (123.8 x 58.6 x 7.6 mm)
Weight 3.95 oz (112 g) 3.95 oz (112 g)
the average is 5 oz (143 g) the average is 5 oz (143 g)
Materials Main body: aluminum Main body: aluminum
Display
Physical size 4.0 inches 4.0 inches
Resolution 640 x 1136 pixels 640 x 1136 pixels
Pixel density 326 ppi 326 ppi
Technology IPS LCD IPS LCD
Screen-to-body ratio 60.82% 60.82%
Colors 16 777 216 16 777 216
Touchscreen Multi-touch Multi-touch
Features Light sensor, Proximity sensor, Oleophobic coating
Light sensor, Proximity sensor, Oleophobic coating
Camera
Camera 8 megapixels 8 megapixels
Flash LED Dual LED
Aperture size F2.4 F2.2
Focal length (35mm equivalent)
33 mm 29 mm
Camera sensor size 1/3.2" 1/3"
Pixel size 1.4 μm 1.5 μm
Pg. 26
Appendix
Features
Sapphire crystal lens cover, Face detection, Digital zoom, Self-timer, Digital image stabilization, Back-illuminated sensor (BSI), Autofocus, Touch to focus, Geo tagging
Sapphire crystal lens cover, Face detection, Digital zoom, Self-timer, Digital image stabilization, Back-illuminated sensor (BSI), Autofocus, Touch to focus, Geo tagging
Settings Exposure compensation Exposure compensation
Shooting Modes High Dynamic Range mode (HDR), Panorama
Burst mode, High Dynamic Range mode (HDR), Panorama
Camcorder 1920x1080 (1080p HD) (30 fps)
1920x1080 (1080p HD) (30 fps), 1280x720 (720p HD) (120 fps)
Features Time-lapse video, Digital image stabilization, Video calling
Time-lapse video, Picture-taking during video recording, Digital image stabilization
Front-facing camera 1.2 megapixels 1.2 megapixels
Hardware
System chip Apple A6 Apple A7
Processor Dual core, 1300 MHz, Apple Swift
Dual core, 1300 MHz, Cyclone ARMv8, 64-bit
Graphics processor PowerVR SGX543MP3 PowerVR G6430
System memory 1016 MB RAM 1024 MB RAM
Built-in storage 64 GB 64 GB
Battery
Stand-by time 9.4 days (225 hours) 10.4 days (250 hours)
the average is 19 days (450 h)
the average is 19 days (450 h)
Talk time (3G) 8.00 hours 10.00 hours
the average is 15 h (903 min)
the average is 15 h (903 min)
Music playback 40.00 hours 40.00 hours
Video playback 10.00 hours 10.00 hours
Capacity 1440 mAh 1570 mAh
Not user replaceable Yes Yes
Multimedia
Music player
Filter by Album, Artist, Genre, Playlists
Album, Artist, Genre, Playlists
Features Album art cover, Background playback
Album art cover, Background playback
Speakers Earpiece, Loudspeaker Earpiece, Loudspeaker
YouTube player Yes Yes
Internet browsing
Pg. 27
Appendix
Browser Safari Safari
Built-in online services support
YouTube (upload) YouTube (upload), Twitter
Technology
CDMA 800, 1700/2100, 1900 MHz
GSM 850, 900, 1800, 1900 MHz 850, 900, 1800, 1900 MHz
UMTS 850, 900, 1900, 2100 MHz 850, 900, 1700/2100, 1900, 2100 MHz
FDD LTE
700 (band 13), 850 (band 5), 1800 (band 3), 1900 (band 2), 2100 (band 1) MHz
700 (band 13), 700 (band 17), 800 (band 18), 800 (band 19), 800 (band 20), 850 (band 5), 900 (band 8), 1700/2100 (band 4), 1800 (band 3), 1900 (band 2), 1900 (band 25), 2100 (band 1) MHz
Data
LTE Cat 3 (100/50 Mbit/s), HSDPA+ (4G) 42.2 Mbit/s, UMTS, EDGE, GPRS, EV-DO Rev.A, EV-DO Rev.B
LTE, HSDPA+ (4G) 42.2 Mbit/s, HSUPA 5.76 Mbit/s, UMTS, EDGE, GPRS
nano-SIM Yes Yes
Positioning A-GPS, Glonass, Cell ID, Wi-Fi positioning
GPS, A-GPS, Glonass, Cell ID, Wi-Fi positioning
Navigation Turn-by-turn navigation, Voice navigation
Turn-by-turn navigation, Voice navigation
Connectivity
Bluetooth 4 4
Wi-Fi 802.11 a, b, g, n, n 5GHz 802.11 a, b, g, n, n 5GHz
Mobile hotspot Yes Yes
USB Yes Yes
Connector Proprietary Proprietary
Features USB charging USB charging
Other TV-Out, Tethering, Computer sync, OTA sync, AirDrop
TV-Out, Tethering, Computer sync, OTA sync, AirDrop
Other features
Notifications
Music ringtones (MP3), Polyphonic ringtones, Vibration, Flight mode, Silent mode, Speakerphone
Music ringtones (MP3), Polyphonic ringtones, Vibration, Flight mode, Silent mode, Speakerphone
Additional microphone(s) for Noise cancellation, Video recording
for Noise cancellation, Video recording
Sensors Accelerometer, Gyroscope, Compass
Accelerometer, Gyroscope, Compass, Fingerprint (touch)
Pg. 28
Appendix
Hearing aid compatibility M4, T4 M4, T4
Other Voice dialing, Voice commands, Voice recording
Voice dialing, Voice commands, Voice recording
Availability
Officially announced 12-Sep-12 10-Sep-13
Shopping information
Accessories
Apple EarPods with Remote and Mic, Lightning to USB Cable, USB Power Adapter, Documentation
Apple EarPods with Remote and Mic, Lightning to USB Cable, USB Power Adapter, Documentation