When
the iPhone X launched, a lot of designers were put off about the screen
shape. Those complaints have mostly died down, but I haven’t seen much
design-nerd talk about cool corner treatment details. Fortunately, deep
nerd shit is my specialty.
iPhone X screen shape
What’s Your Angle?
When you’re starting a design like this, the obvious, and comically
cheaper option is to make all corners square. Machines exist and/or are
calibrated to make those screens, so keeping edges squared requires
fewer manufacturing changes and less talent along the pathway to
production.
Everyone
knows how to make a right angle — designers don’t have to do math,
engineers need fewer calculations, the people making the machine are
clear on what to do.
And yet, let’s examine how crappy all-square corners would look:
I’m a pixelated bear cub. Rawr.
Once
Apple knew they wanted to take advantage of new full-screen technology,
that gave them the opportunity to alter screen shape because they would
need to address the manufacturing process anyway. Presumably, the
expense was mostly built in.
Still, there were lots of ugly ways to do this:
Meh.
This is where they landed:
That’s better.
Screen Corners
Here’s
where the nerd part comes in, iPhone X rounded screen corners don’t use
the classic rounding method where you move in a straight line and then
arc using a single quadrant of a circle. Instead, the math is a bit more
complicated. Commonly called a squircle, the slope starts sooner, but
is more gentle.
The difference is real subtle, even in gif-form, but here we go:
Difference between common rounded rectangle maths and Apple maths.
Apple
has been doing this to the corners of laptops and iMacs for years, but
this type of rounding didn’t penetrate iOS until version 7. This shape
has classically been difficult to achieve, because it wasn’t available
in 2D design editors, though that’s starting to change. Read about it
more detail here.
The Notch
Now
let’s talk about the notch itself. The left and right sides have two
rounded corners. Because of the curve falloff, one curve doesn’t
complete before the next one starts — they blend seamlessly into each
other. As a result, no tangent line on this edge actually hits a perfect
vertical.
Ooo. Fancy.
Come Correct
iPhone
X templates I’ve seen out there don’t 100 percent duplicate the
official shape, probably because it was either too hard to make or they
haven’t noticed. This is why it’s good practice to use official assets
from Apple, found in the design resources section of the developer site for creating icons and mockups.
Future
iterations of this design will surely alter these sizes, so it will be
interesting to compare how hardware sensor evolution impacts design
shifts.
Overall,
these decisions seem minor, but from a design viewpoint they’re fairly
opinionated. Even when designers are willing to spend social capital to
push these ideas, most organizations won’t put resources behind them.
Rounding the Bend
One
of the things I love about indie apps is their ability to be
opinionated. It’s nearly impossible to ship strong viewpoints from
larger companies where there are fifty people in a room examining
angles. So it’s cool to see Apple still has the ability to take a strong
stance in this way.
Sweating
thousands of minor details is what separates Apple from other
companies. Their ability to do that is hard-won, but damn it’s pretty to
watch.
To
anyone working in technology (or, really, anyone on the Internet), the
term “AI” is everywhere. Artificial intelligence — technically, machine learning — is finding application in virtually every industry on the planet, from medicine and finance to entertainment and law enforcement.
As the Internet of Things (IoT) continues to expand, and the potential
for blockchain becomes more widely realized, ML growth will occur
through these areas as well.
While
current technical constraints limit these models from reaching “general
intelligence” capability, organizations continue to push the bounds of
ML’s domain-specific applications, such as image recognition and natural
language processing. Modern computing power (GPUs in particular) has contributed greatly to these recent developments — which is why it’s also worth noting that quantum computing will exponentialize this progress over the next several years.
Alongside
enormous growth in this space, however, has been increased criticism;
from conflating AI with machine learning to relying on those very
buzzwords to attract large investments, many “innovators” in this space have drawn criticism from technologists
as to the legitimacy of their contributions. Thankfully, there’s plenty
of room — and, by extension, overlooked profit — for innovation with
ML’s security and privacy challenges.
Reverse-Engineering
Machine learning models, much like any piece of software, are prone to theft and subsequent reverse-engineering. In late 2016, researchers
at Cornell Tech, the Swiss Institute EPFL, and the University of North
Carolina reverse-engineered a sophisticated Amazon AI by analyzing
its responses to only a few thousand queries; their clone replicated the
original model’s output with nearly perfect accuracy. The process is
not difficult to execute, and once completed, hackers will have
effectively “copied” the entire machine learning algorithm — which its
creators presumably spent generously to develop.
The risk this poses will only continue to grow. Inaddition
to the potentially massive financial costs of intellectual property
theft, this vulnerability also poses threats to national
security — especially as governments pour billions of dollars into autonomous weapon research.
Not
only is this attack a threat to the network itself (i.e. consider this
against a self-driving car), but it’s also a threat to companies who
outsource their AI development and risk contractors putting their own
“backdoors” into the system. Jaime Blasco, Chief Scientist at security
company AlienVault, points out that this risk will only increase as the world depends more and more on machine learning. What would happen, for instance, if these flaws persisted in military systems? Law enforcement cameras? Surgical robots?
Training Data Privacy
Protecting the training data put into machine learning models is yet another area that needs innovation. Currently, hackers can reverse-engineer user data out of machine learning models
with relative ease. Since the bulk of a model’s training data is often
personally identifiable information —e.g. with medicine and
finance — this means anyone from an organized crime group to a business
competitor can reap economic reward from such attacks.
Further,
as organizations seek personal data for ML research, their clients
might want to contribute to the work (e.g. improving cancer detection)
without compromising their privacy (e.g. providing an excess of PII that
just sits in a database). These two interests currently seem at
odds — but they also aren’t receiving much
focus, so we shouldn’t see this opposition as inherent. Smart redesign
could easily mitigate these problems.
Conclusion
In
short: it’s time some innovators in the AI space focused on its
security and privacy issues. With the world increasingly dependent on
these algorithms, there’s simply too much at stake — including a lot of
money for those who address these challenges.
When it comes to building mobile apps, app makers tend to overcomplicate their ideas and strategies.
The
app winds up becoming a clunky Swiss Army knife — one that offers too
many features, is difficult to learn and use, and costly to maintain.
But
when we think about successful apps, it’s often the simplest ones that
come to mind — apps like Dropbox and Evernote that address a pressing
pain point, yet are effortlessly easy to use.
As Steve Jobs famously said:
“Simple
can be harder than complex: you have to work hard to get your thinking
clean to make it simple. But it’s worth it in the end because once you
get there, you can move mountains.”
Below, I’ll share about tried-and-tested strategies that I’ve used to help startups and entrepreneurs at Appster come up with simple app ideas effectively.
1. Train yourself to become an idea machine:
How do you get better at coming up with app ideas?
The answer, according to entrepreneur, best-selling author and podcaster James Altucher is to become an idea machine.
In
Altucher’s words, it’s akin to being a superhero, where you’re never at
a loss for ideas — regardless of whichever situation you’re in or
whatever questions you’re thrown at.
If
this sounds unrealistic, it isn’t — but it does require plenty of
practice. Here’s a quick roundup of Altucher’s tips for becoming an idea
machine:
How many ideas should you come up with each time?
10.
Why 10 ideas?
Most
of us wouldn’t have much difficulty with conceiving a handful of ideas,
even if it’s centered around topics that we don’t usually ponder about.
But after the fifth idea is just about when it gets challenging — where we find ourselves at a loss for ideas.
The point of the exercise is to break through this stage in order to build up your idea muscle.
How can you assess your ideas?
You can’t, and evaluating your app ideas isn’t the priority at this point in time. Says Altucher:
“You
have to try multiple ideas and see which ones gets the excitement of
customers, employees, and you can see that people are legitimately using
it and excited by it.”
What are topics you can start brainstorming on?
The key here is to have fun with the ideation process, so don’t limit yourself to business-related ideas.
It
helps to think out of the box, and conceptualize ideas around topics
like “10 ridiculous mobile apps I would want”, “10 ways an app can solve
a problem that I’m facing”, “10 mobile apps that I can reinvent” or “10
mobile apps I would improve”.
How long does it take to become an “idea machine”?
Altucher suggests doing this daily for at least six months.
2. Hone your problem-solving skills
How can app makers go about finding the right idea for their startup?
Daniel Kempe, founder of hand-curated content suggestion platform Quuu elaborates in a Forbes article:
“It’s
not about the search for ideas, it’s identifying problems or gaps with
existing products or services. Ideas are tough to come by, at least good
ones are. But problems, they’re everywhere! Almost every product or
service you use on a daily basis was created to solve a problem.”
Here four strategies you can use to hone your problem-solving abilities:
2.1. Review problems you face on a day-to-day basis
The first place to start is by identifying problems that you encounter on a day-to-day basis.
It
can be difficult to come up with ideas in a brainstorming session, so
start by observing any moments of frustration you have throughout the
day — whether it’s an interruption or delay that occurred at work or a
problem that crops up in your personal life.
At
first glance, these issues may appear to be minute or mundane — but
resolving a personal problem has been the launching point for apps like
Dropbox and Summly.
The
idea for Dropbox arose out of co-founder Drew Houston’s frustration
with the absence of a seamless storage solution for his files, while
Summly was conceived when founder Nick D’Aloisio found it inefficient to
click through Google search results while preparing for his exams.
2.2. Pay attention to everyday conversations
Everyday conversations and seemingly banal complains can become a source of inspiration.
Try
carving out a block of time — say five days to a week — where you pay
close attention to and note down problems that crop up in conversations
all around you. “I wish this could be better”, “I hate this…”, “Why does
this keep happening…” are some phrases you’d want to prick your ears up
for.
2.3. Tap on social media
Social
media platforms are a great way to find out about larger scale problems
encountered by individuals and communities all around the world.
There
are different ways of conducting a search via social media: you may
create hashtags around the problems you’ve picked up on through the
above methods, or come up with a list of hashtags around topics or
problems that you’re concerned about.
2.4. Go to where your potential users are at
Blog
articles, blog comments, forums, discussion boards, Quora — apart from
being a useful source of information, these sites are also a great way
to interact with potential users or target audience.
Take
note of common problems and issues that are being discussed, and don’t
hesitate to post comments or start a new thread around any questions you
might have — this could spark off conversations that will shed light on
problems that you weren’t previously aware of.
3. Keep a close watch on your competitors
A
competitive analysis should be carried out at several stages over the
lifetime of a mobile app: during the ideation process, before
significant changes are made to your app or business strategy, and at
regular intervals to keep up with changes in the competitive landscape.
Below, I’ll be focusing on competitive analysis conducted at the ideation stage.
Pay attention to user feedback and comments
User
feedback and comments are a treasure trove of information. Start poring
through reviews and ratings left by users of your competitors’
apps — from app store reviews to social media comments and forum
posts — to obtain a clearer idea of features and strategies that
resonate with your potential users.
If
you’re in the midst of sounding out your ideas with friends and family
or testing your MVP, keep an eye out for remarks like “I’ve tried out
the ABC app, but didn’t like a particular feature they had” or “This
feature reminds me of XYZ app” — you’ll know that these are competitors
to keep track of.
Dig deep into your competitors’ strategies
By
delving deep into the strategies implemented by your competitors, you
can then break these down into simpler elements, and reverse engineer
the processes to replicate their success.
The
objective here isn’t to imitate what your competitors are doing, but to
combine their strategies with your existing ideas to create concepts
and features that work for your app.
Here’s a checklist of questions to help you get started on your research process:
Which strategies have produced the best results for your competitors?
What were unsuccessful strategies implemented?
How can you improve on strategies your competitors implemented?
How can you adapt these strategies to make it work for your mobile app?
Don’t forget about indirect competitors
While
your indirect competitors may not have launched a mobile app, they are
still targeting a similar set of users — so it helps to pay attention to
how they’re attracting your potential users with their products or
services.
Here are key questions to guide you in your analysis of indirect competitors:
In what areas are their products or services similar to yours?
What are successful strategies and ideas that have helped them target and retain their users?
How can these strategies be improved on?
Can you adapt these ideas or concepts to make it work for your mobile app?
4. Stay on top of the latest trends
The ever-changing mobile landscape is a challenging space to navigate.
App makers are up against the intense competition — a 2017 Statista study
indicated that Android users were able to choose between 2.8 million
apps, while the number of apps on the App Store totaled at 2.2 million.
In addition, the emergence of trends like augmented reality, virtual reality and chatbots are revolutionizing the way users engage with mobile apps.
Strategies
and features that are effective now may easily be rendered irrelevant
in a matter of months. Generating ideas that resonate with today’s users
requires a constant pursuit of keeping up with the trends.
Here are a few tools and websites you can use to stay on top of the latest developments:
App Annie:
App market data and insights company producing consumer and competitive
information on downloads, revenue, ratings, usage, search terms and
more. App Annie’s Insights Blog and webinars are also great resources for app makers.
Priori Data: App Store intelligence company providing market data and competitive benchmarking information on the global app economy.
Forrester Research: Market research firm providing advice on existing and potential impacts of technology.
Trendwatching: Independent trend firm scanning the global market for promising consumer trends and insights.
Springwise:
Provides information on innovation intelligence. Springwise sources for
the latest innovation, startup, and business ideas from around the
world.
Trends and mobile apps outside of your industry
Too
often, startups and businesses fall into the trap of living within the
industry bubble. In adopting a myopic focus on industry trends,
benchmarking and best practices, companies eventually wind up providing
run-of-the-mill experiences that fail to stand out.
This
can be prevented by studying and introducing ideas and concepts from
industries, businesses or mobile apps that differ from your own.
Here are key takeaways you can gain from studying mobile apps across different industries:
Zappos:
Zappos is known for delivering stellar customer experiences, and its
mobile app is no different. App makers can learn about providing
top-notch experiences through studying features like Ask Zappos, a
feature that helps users find any product with just a tap of their
camera, and Handover, which enables users to shop seamlessly between
their Apple devices.
JetBlue:
Pesky push notifications are a bane for smartphone users. Learn from
JetBlue’s timely and thoughtful communication, which includes providing
flight check-in reminders 24 hours before a flight is scheduled to take
off, as well as notifications to let passengers review flight
entertainment options in advance.
Venmo:
App makers can learn from the convenience and efficiency that mobile
payment apps like Venmo provides — from the way user information is
saved for easy access, to how a complex process like sending out money
or making purchases can be completed in a few quick taps.
Sometime
in the mid-2000s, I was a freelance web developer in Philadelphia with
some pretty crappy health insurance. I started having occasional heart
palpitations, like skipped heart beats. My doctor said it was probably
not serious, but she could do tests to rule out very unlikely potential
complications for about $1,000. That seemed pretty expensive to rent a
portable EKG for a single day, so I googled around for some schematics.
Turned out you could build a basic three-lead EKG with about $5 worth of
Radio Shack parts (I no longer have the exact schematic, but something like this).
I didn’t really understand what the circuit did, but I followed the
directions and soldered it together on some protoboard, connected a 9V
battery, and used three pennies as electrodes that I taped to my chest. I
hooked the output of the device to my laptop’s line in and pressed ‘record’.
screenshot of my heartbeat in Audacity
Audacity
displayed the heartbeat signal live as it recorded. Sure enough, I was
having pretty common/harmless Premature Ventricular Contractions.
There’s one on the right side of the screenshot above.
Calling
the 1/8th inch connectors you’d find on pretty much every piece of
consumer electronics until recently “audio jacks” does them a
disservice. It’s like calling your car a “grocery machine”. Headphone
and microphone ports are, at their most basic, tools for reading and
producing voltages precisely and rapidly over time.
My
homemade EKG is a voltage converter. Electrodes attached to points
around my heart measure tiny differences in voltage produced by signals
that keep it beating. Those measured signals are amplified to about plus
or minus 2 volts. That new voltage travels through an audio cable to
the “Line In” on my sound card.
Sound cards happen to carry sound most of the time, but they are perfectly happy measuring any AC
voltage from -2 to +2 volts at 48,000 times per second with 16 bits of
accuracy. Put another way, your microphone jack measures the voltage on a
wire (two wires for stereo) every 0.2 milliseconds, and records it as a
value between 0 and 65,535. Your headphone jack does the opposite, by applying a voltage between -2 and +2 to a wire every 0.2 milliseconds, it creates a sound.
To
any headphone jack, all audio is raw in the sense that it exists as a
series of voltages that ultimately began as measurements by some tool,
like a microphone or an electric guitar pickup or an EKG. There is no
encryption or rights management, no special encoding or secret keys.
It’s just data in the shape of the sound itself, as a record of voltages
over time. When you play back a sound file, you feed that record of
voltages to your headphone jack. It applies those voltages to, say, the
coil in your speaker, which then pushes or pulls against a permanent
magnet to move the air in the same way it originally moved the
microphone whenever the sound was recorded.
Smartphone manufacturers are broadly eliminating headphone jacks
going forward, replacing them with wireless headphones or BlueTooth.
We’re going to all lose touch with something, and to me it feels like
something important.
The
series of voltages a headphone jack creates is immediately
understandable and usable with the most basic tools. If you coil up some
copper, and put a magnet in the middle, and then hook each side of the
coil up to your phone’s headphone jack, it would make sounds.
They would not be pleasant or loud, but they would be tangible and
human-scale and understandable. It’s a part of your phone that can read
and produce electrical vibrations.
Without that port, we will forever be beholden to device drivers
between our sounds and our speakers. We’ll lose reliable access to an
analog voltage we could use to drive any magnetic coil on earth, any
pair of headphones. Instead, we’ll have to pay a toll, either through
dongles or wireless headphones. It will be the end of a common interface
for sound transfer that survived more or less unchanged for a century,
the end of plugging your iPod into any stereo bought since WWII.
Entrepreneurs
and engineers will lose access to a nearly universal, license-free I/O
port. Independent headphone manufacturers will be forced into a
dongle-bound second-class citizenry. Companies like Square — which made
brilliant use of the headphone/microphone jack to produce credit card
readers that are cheap enough to just give away for free — will be hit with extra licensing fees.
Because
a voltage is just a voltage. Beyond an input range, nobody can define
what you do with it. In the case of the Square magstripe reader, it is
powered by the energy generally used to drive speakers (harvesting the
energy of a sine wave being played over the headphones), and it
transmits data to the microphone input.
There’s also the HiJack project,
which makes this whole repurposing process open source and general
purpose. They provide circuits that cost less than $3 to build that can
harvest 7mW of power from a sound playing out of an iPhone’s headphone
jack. Because you have raw access to some hardware that reads and writes
voltages, you can layer an API on top of it to do anything you want,
and it’s not licensable or limited by outside interests, just some
reasonably basic analog electronics.
I don’t know exactly how
losing direct access to our signals will harm us, but doesn’t it feel
like it’s going to somehow? Like we may get so far removed from how our
devices work, by licenses and DRM, dongles and adapters that we no
longer even want to understand them? There’s beauty
in the transformation of sound waves to electricity through a
microphone, and then from electricity back to sound again through a
speaker coil. It is pleasant to understand. Compare that to
understanding, say, the latest BlueTooth API. One’s an arbitrary and
fleeting manmade abstraction, the other a mysterious and dazzlingly convenient property of the natural world.
So,
if you’re like me and you like headphone jacks, what can you do? Well,
you could only buy phones that have them, which I think you’ll be able
to do for a couple years. Vote with your dollar!
You
can also tell companies that are getting rid of headphone jacks that
you don’t like it. That your mother did not raise a fool. That aside
from maybe water-resistance,
there’s not a single good reason you can think of to give up your
headphone jack. Tell them you see what they’re up to, and you don’t like it.
You can say this part slightly deeper, through gritted teeth, if you
get to say it aloud. Or, just italicize it so they know you are serious.
Evil
kills good people with mass shootings, tensions with North Korea
increase daily, and actors abuse actors as sexual playthings.
Yet despite the torture of humanity, thousands of people complain about the iPhone X’s notch.
Not
me. I enjoyed the iPhone tittle tattle. In the run up to the iPhone X’s
release I salivated over articles on the X’s lush colours, OLED screen,
Face ID, super-duper performance, glass construction, wireless
charging, bionic chips. Oh, how I could go on.
I read political stories too but only to feel more adult.
On
October 27th I sat by the iMac and waited until 08:00 am to pre-order
the iPhone X — like millions of other people — I hit refresh repeatedly.
What
is it about the iPhone X that drives me to pre-order, and because I
expected a 10th anniversary phone, join the Apple Upgrade Programme?
Is it madness?
More money than sense?
Am I still 13½ years old?
(Those were rhetorical questions).
The
answer might be clever marketing because after two months with the
iPhone X, I’ve done nothing the one-year-old 7 Plus wasn’t capable of.
Close Encounters of the Apple Kind
My
first encounter with Apple — the iPod Classic — was a difficult
decision. A friend recommended the Creative Zen MP3 player, but it was
near obsolete so I opted for the iPod and the addiction began.
Perhaps if I’d opted for the Zen, I’d be using an Android phone today.
A
few years passed and BBC News featured a new phone called iPhone. But I
gazed at my silver Sony Ericsson and wondered what more you’d want in a
phone?
And
the cost 11 years ago? I would never pay £30 a month for a carrier
contract. However after coffee with friends, who all had an iPhone,
coupled with an illness in the family to emphasise the impermanence of
life, I went iPhone.
One iTunes library, four iPhones, two iPads, one iMac and a MacBook Pro later, I’m beyond redemption.
But brand loyalty can’t be why I ‘rented’ the iPhone X. I could have kept the 7 Plus.
El Notch, Yosemite
Go Figure 8
I tried to resist the X and considered the smaller iPhone 8. The size was perfect, but the camera would be a step down.
The
8 is cheaper on the upgrade programme. £18 less than the X or £12 less
for the Plus. But the iPhone 8 Plus offers little that’s new since it’s
the 7 Plus in glass.
Wireless charging?
There’s no such thing. The charger mat still needs plugged in.
The iPhone 8 is a decoy phone — the iPhone 7s.
But iPhone 8 can’t be why I fell for the X. My 7 Plus was still a premium phone without a scratch.
Drip, Drip, Drip
When I was a child, I got excited about Christmas from around September.
For
Apple’s 10th anniversary iPhone my anticipation began one year before
release. No sooner was the 7 Plus in my hand, the tech press speculated
on the next iPhone.
The whole market place was primed by the media and whipped into a frenzy.
Rumours, from people familiar with the situation, leaked as usual but with one difference.
2017
saw the leaking of price. Customers needed to be acclimatised to the
first £1000 phone so when it became official, the shock factor would be
lost.
You’ve been primed.
In
marketing terms, priming is the preparation of subconscious consumer
behaviour through the subtle use of information. The new X for example,
was secret, but there was just enough sexy news to whet your appetite.
The X was everywhere and nowhere.
But
stories about a non-existent phone cannot be the reason I wanted one.
There are stories about HomePods, cellular watches and iPad Pros and I
want none of those (fingers crossed).
Apple Framed the X as The Future… Today
After a succession of similar iPhones, the X promised reinvention.
The X’s keynote described the product as the future and you can hold it in your hand.
The
message was misleading. Edge to edge displays, wireless charging, OLED
screens and facial recognition, have been available on other phones for
years.
But
know this, the X looks beautiful, when switched on. When off, it looks
like the Blackberry Leap. The build quality is superb though.
It’s
a wonder of marketing. You can feel unique using a product when
millions upon millions of people across the world have the product too.
But
an OLED screen and facial recognition can’t be reasons to spend £56 a
month. The 7 Plus screen is fabulous and fingerprint ID seamless.
If having the future isn’t enough to make you buy, there’s always fear.
Scarcity
Scarcity and fear of missing out (FOMO) come into play.
If one thing puts the fear of God into consumers, it’s the wait to get what they want.
When
I was a small boy, my favourite superhero was Spider-man. I begged Mum
to buy me a Spider-man figure. At the toyshop we discovered it would be
weeks before Spider-man would be back in stock.
So
what did I do? I settled for the Human Torch (one of the Fantastic
Four). I regretted it soon after and my impatience meant I didn’t get
Spider-man, ever.
When impatience strikes, I think Spider-man.
Drip feeding consumers with stories of scarcity and production line problems fan the flames of fear, the fear of missing out.
I
knew the X’s production would be fine and prepared to wait. Supply
problem stories come out before every iPhone launch. In terms of missing
out, of all features, only Face ID and Animojis were absent from the 7
Plus.
So, FOMO can’t be why I wanted an iPhone X.
Prize Value
£1000 is scary for a phone but it’s not £1000 more than we’re used to paying.
Prices
have crept up for years, and be honest, if you can afford £700 or £800
for a phone, you can also afford £1000. Apple know it too.
It may be borderline out of reach but it’s also borderline within reach.
A high price is one tactic marketers use to put the quality of a product in the mind of consumers.
The high price tag of the X may set it apart from competitors but cost definitely isn’t the reason to want the X.
Here and Now and Why
My
late Dad used to say there’s no such thing as a bad car. In the 1970s,
cars looked good in the showroom but once you drove one and it rained,
they rusted and fell apart before you got home. Cars are not like that
anymore.
Like cars today, there’s no such thing as a bad phone. Most brands have caught up.
You’ll not do anything different on the X than you could do on many of the latest smart phones.
The
X may not be the future, just a brilliant phone that perfects what
others have already done, while leaving room for development.
Over
a year I’ll pay £677 to hire Apple’s latest palm-top computer. The
device I use everywhere to read, write, take pictures, research, web
browse, meditate, enjoy music. Oh and make phone calls.
Why do I want one?
It’s not brand loyalty, decoys, scarcity or the features.
In 1923 when asked by a New York Times reporter why he wanted to climb Everest, George Mallory said “Because it is there”.
I want the iPhone X for the same reason you do — because it is there.
Which
trends will shape app monetization in 2018? As the world becomes better
adapted for mobile, developers will benefit from greater revenue than
ever before. However to do this they must balance the needs of the user
with app monetization practices.
We’ll look at five trends that will influence the way that app monetization will work in 2018.
App experience will become more important for developers relying on ads to generate revenue.
In-app ads remain a popular method of app monetization for developers. Despite them having obvious drawbacks when applied poorly.
In
2018 app advertising will be all about the user experience. developers
must strike a balance between the number of ads, where they appear and
how the user interacts with them. This will be pivotal to app
monetization success. App owners will also have to consider how these
changes will affect their users in 2018. Too many ads will negatively
affect the user experience. But that doesn’t mean that it’s impossible
to provide value whilst delivering in-app ads.
Mobile
app advertising is maturing quickly. Make sure you look for a network
that uses safe brands, smart ad targeting, and provides support for
interactive ads.
When
integrating an app advertising strategy you may find a trade-off
between ease of integration and spamminess of ads. In 2018 it might be
worth taking the time to focus on putting user experience first.
Don’t
expect revenue from app ads to jump to new heights anytime soon. If
anything expect app ad revenue to decrease as more apps adopt in-app
advertising. Perhaps 2018 could be the year to supplement your app
revenue with another method.
More apps will adopt a freemium model as more users are becoming used to an app being free at the point of use.
Freemium
is allowing app owners to increase session length and generate engaged
users. This is a great place from which to convert users into healthy
revenue. After a positive app experience app users are more likely to
opt-in for premium features. Having the chance to nurture and educate
your users before this has a positive effect on your app monetization
strategy.
Try
not to appear like you are cheating your users. Make it clear that your
app is a freemium app from the very beginning. They won’t want to
invest a lot of time in a game or app to realise that they have to pay
to use some features.
It
seems that freemium is here to stay. With users finding it standard
practice to not pay for an app at the point of purchase. Because of
this, developers are finding it harder to justify an upfront fee. The
freemium app monetization model is a great opportunity to engage and
nurture audiences for app monetization.
Users will become dissatisfied if they have to commit huge amounts of time or money to unlock all app features.
In-app
purchases as a method of app monetization is still experiencing healthy
growth. This may be slightly overstated due to the inclusion of
‘services’ as purchases (think Uber etc).
One of the main trends well see in 2018 is that app developers will need to focus more on engagement rather than only increasing app monetization.
Once
a user has purchased in-app content then they are more likely come back
and spend more time in the app. This translates to better engagement
and retention and in turn better monetization.
No
category has benefited from in-app purchases more than the gaming
category. Here, developers are benefiting by placing engagement first.
The user now has the option to pay to advance through the game quicker
or access powerups and features.
Developers
need to make sure they are getting this balance right. In-app purchases
are effective because a few users spend a lot. There will always be
users who only want to play your game for free. True these users don’t
generate revenue, but they are still important for your app to exist.
Whilst
not being a mobile app, developers can still learn a lot from the EA
debacle in the new Battlefront game. Users quickly noticed that to
unlock some of the features they would have to play the game for 1000
hours. Alternatively, they could pay to unlock them. This seemed rather
unfair, especially when they had purchased the game upfront.
To keep users happy, developers will need to strike the right balance between monetization and experience.
In
2018 more and more users will become aware of how apps monetize their
users. That’s why app monetization methods must be clear and fair, in
the long term it will benefit you.
A conversation will need to be had with users about monetization of data and opt-out methods.
Users
are more aware than ever of the need for developers to monetize their
app audience. The conversation around app monetization is shifting to
help users understand why apps are free.
In
2018 consumer personalization will be a high priority for brands. They
will achieve this by using consumer data to help provide an improved
user experience.
Mobile app owners are sitting on a lot of behavioural data around their users. This is of value to those who wish to improve personlization for their users.
Data monetization
is secure, private and becoming more popular amongst developers. Users
are more likely to understand that this data will help to generate
improved personlization. By communicating the benefits and education
users about opt-in developers can monetize their app in this way.
A
benefit of app data monetization is that the user experience remains
intact. There are no intrusive adverts or the need for the user to pay
anything upfront. This means that the user will spend more time in the
app and engage with the app’s features. The app monetization strategy
can be adopted alongside other methods of monetization.
Data
monetization allows developers to monetize a much higher percentage of
users. The users don’t need to be engaged for it to work. The revenue
that you generate from each user will also be higher. This means you
don’t have to worry about monetization in relation to platform. It’s the
same regardless of the device.
Expect
revenue from data monetization to increase from a high starting point
with better technology. 2018 will see the consumer become more aware of
the power of big data and better educated on how it affects them.
App subscription models will more closely resemble SAAS subscriptions.
The
subscription model is one that looks to remain popular in 2018. Again,
users are used to trialling an app and its features before parting with
any cash
Subscription
models are becoming more complex than a simple buy or don’t buy. In
fact, many pricing structures now more closely resemble a SAAS model.
It’s common to see several pricing tiers with many different features.
This
allows app developers to persuade users who would previously not part
with any cash to subscribe to a lower tier of membership. This method of
app monetization is still the best fit for service apps.
A
side effect of this is that developers will need to clearly help users
understand the benefits of upgrading. More tiers and features mean a
better explanation is needed.
Closing thoughts for 2018
Developers
will continue to benefit from the app economy with revenue from app
monetization set to grow throughout 2018. Free apps will become the new
normal, compared to previously where single pay purchases were the most
popular. This will allow developers to generate more revenue over a
longer period of time.
Developers
will need to place more emphasis on the monetization experience. This
means that the developers are more likely to miss out on revenue from
app monetization if the app experience is not up to scratch. Due to the
free to download culture, more emphasis on experience and education is
needed. This will help to persuade users to enter into premium models
and subscriptions or to engage with in-app purchases.
More and more developers will need to adopt hybrid monetization strategies. Developers should
not
rely on a single method of app monetization. Instead, spreading
monetization across multiple strategies will provide stability.
Especially in a market that can change quickly. The preference of app
users is volatile. The changing platform rules around app monetization
may also affect developers in 2018. It’s important to stay one step
ahead!
A
prankster who made repeated hoax distress calls to the US Coast Guard
over the course of 2014 probably thought they were untouchable. They
left no fingerprints or DNA evidence behind, and made sure their calls
were too brief to allow investigators to triangulate their location.
Unfortunately
for this hoaxer, however, voice analysis powered by AI is now so
advanced that it can reveal far more about you than a mere fingerprint.
By using powerful technology to analyse recorded speech, scientists
today can make confident predictions about everything from the speaker’s
physical characteristics — their height, weight, facial structure and
age, for example — to their socioeconomic background, level of income
and even the state of their physical and mental health.
One of the leading scientists in this field is Rita Singh of Carnegie Mellon University’s Language Technologies Institute.
When the US Coast Guard sent her recordings of the 2014 hoax calls,
Singh had already been working in voice recognition for 20 years. “They
said, ‘Tell us what you can’,” she told the Women in Tech Show podcast earlier this year. “That’s when I started looking beyond the signal. How much could I tell the Coast Guard about this person?”
Rita Singh is an expert in speech recognition
What your voice says about you
The
techniques developed by Singh and her colleagues at Carnegie Mellon
analyse and compare tiny differences, imperceptible to the human ear, in
how individuals articulate speech. They then break recorded speech down
into tiny snippets of audio, milliseconds in duration, and use AI
techniques to comb through these snippets looking for unique
identifiers.
Your
voice can give away plenty of environmental information, too. For
example, the technology can guess the size of the room in which someone
is speaking, whether it has windows and even what its walls are made of.
Even more impressively, perhaps, the AI can detect signatures left in
the recording by fluctuations in the local electrical grid, and can then
match these to specific databases to give a very good idea of the
caller’s physical location and the exact time of day they picked up the
phone.
This
all applies to a lot more than hoax calls, of course. Federal criminal
cases from harassment to child abuse have been helped by this relatively
recent technology. “Perpetrators in voice-based cases have been found,
have confessed, and their confessions have largely corroborated our
analyses,” says Singh.
Portraits in 3D
And
they’re just getting started: Singh and her fellow researchers are
developing new technologies that can provide the police with a 3D visual
portrait of a suspect, based only on a voice recording. “Audio can us
give a facial sketch of a speaker, as well as their height, weight,
race, age and level of intoxication,” she says.
But
there’s some way to go before voice-based profiling technology of this
kind becomes viable in a court. Singh explains: “In terms of
admissibility, there will be questions. We’re kind of where we were with
DNA in 1987, when the first DNA-based conviction took place in the
United States.”
This
has all proved to be bad news for the Coast Guard’s unsuspecting
hoaxer. Making prank calls to emergency services in the US is regarded
as a federal crime, punishable by hefty fines and several years of jail
time; and usually the calls themselves are the only evidence available.
Singh was able to produce a profile that helped the Coast Guard to
eliminate false leads and identify a suspect, who they hope to bring a
prosecution soon.
Given
the current exponential rate of technological advancement, it’s safe to
say this technology will become much more widely used by law
enforcement in the future. And for any potential hoax callers reading
this: it’s probably best to stick to the old cut-out newsprint and glue
method for now. Just don’t leave any fingerprints.
Hardik Gandhi is Master of Computer science,blogger,developer,SEO provider,Motivator and writes a Gujarati and Programming books and Advicer of career and all type of guidance.
