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Friday, January 12, 2018

What voice tech means for brands


An overview of the issues around voice technology and top line considerations for brand owners.
Sony’s LF-S50G speaker with Google Assistant. Image via Sony.

Summary

Voice based technology is going to have a huge impact on many sectors, with 50% of all search forecast to be voice-based within just two years. The rate of uptake is likely to vary based on age, geography and literacy — but some markets and platforms already have high penetration, while globally 10% of search is already voice based.
There will be new winners and losers in this space, and incumbent brands will need to look at the impact of losing control of the consumer conversation during the purchase process, making it harder to stand out against their competition.
However, voice interfaces give an unprecedented opportunity for brands to interact with consumers in an extremely powerful new way, and few brands have taken advantage of this yet. Current widely-available functionality is limited in scope and very utility-focused; there are opportunities to develop innovative content and experiences as well as whole new services.
The brands that rise to the occasion are in a good position to increase their market share. Additionally, there are many tools available allowing easy experimentation with voice for minimal investment.
Our recommendation is to start a low investment program of service design and Tone of Voice experimentation as soon as possible — possibly tied in to campaign activity — in order to prepare your brand to take advantage of opportunities that this technology reveals.

Introduction

What do we mean by ‘Voice’?

In the context of this article, we mean ‘talking out loud to automated services’. This covers everything from interactive fiction to utilities, available on bespoke hardware devices, within apps on phones and in the cloud, either accessed via a branded product or one of the major players’ virtual assistants.
A lot of the hype around voice revolves around the uptake of smart speakers (75% of US households are projected to own one by 2020), and the ‘voice assistants’ that come with them. Several of these assistants now allow direct third party integration, a bit like apps on a smartphone.
In addition, it’s important to note that these and other voice assistants are available on other hardware — often phones and tablets, via apps and deep OS integrations, but also bespoke hardware devices and even websites.
In many respects the technologies underlying voice and bots are the same — but the ecosystems and impact are different enough to have made voice very much its own area.

Is voice just hype?

No. It’s true that there is a lot of hype about voice, and that it looks similar to 3D printing and other ‘technologies that will change the way we live’, but interacting with computers via voice interfaces is here to stay.
Apart from anything else there are a range of convincing statistics; for example over 20% of mobile search is already voice based and forecast to rise to 50% of all search by 2020.
Perhaps more interestingly, there are some reasons behind those statistics that might be telling.
It’s often said in technology circles that the majority of next billion people due to get online for the first time will be poorly educated and likely illiterate, as ‘underdeveloped’ nations start to get internet access. For this demographic video and voice will be paramount — and voice may be the only two-way medium available to them.
Additionally, the iPad effect revealed how even very young children could interact with a touchscreen while struggling with a mouse; voice interaction is even faster and more intuitive (once someone can talk) and will undoubtedly be the primary interaction method for some functions within a few years.
It’s also worth considering the stakes involved, especially for Google and Amazon, the biggest players in ad revenue and organic product discovery respectively. Amazon’s aggressive move into voice will already be having a noticeable effect on Google’s bottom line by moving search away from the web and Google ads’ reach— which explains why the latter is working so hard to make a success of its own Assistant.
To their advantage Google can leverage their existing 2.5Bn Android devices in the wild. With numbers that big and uptake gaining traction you can understand the predicted total of 7.5Bn installed voice assistants in operation by 2021.
Concerns about privacy and security do slow adoption in some respects, which we explore later in this article.
A common argument against voice is the social oddness or ‘embarrassment factor’ of talking out loud to a device, especially in a public place (and especially by older people — by which we mean anyone over 20 really). BBH’s view on this is that these norms are fast to change; for example a decade ago it was unthinkable to put a phone on a dinner table in most situations; these days it can be a sign of giving undivided attention (depending on nuance), or it can even be acceptable to answer a call or write a text during a meal in some circumstances.

Overview

Voice is quickly carving a space in the overall mix of technological touchpoints for products and services.
In many ways, this is not surprising; using our voices to communicate is three times faster, and significantly easier than typing. It’s so natural that it takes only 30 minutes for users to relax with this entirely new interface, despite it bringing a freight of new social norms.
There are also contexts in which voice simply beats non-voice input methods; with wet or full hands (cooking, showering), with eyes being used for something else (driving) or almost anything for those of us whose use of hands or eyes may be limited.
Cooking is an obvious example of when it’s preferable to be hands free. Image via saga.co.uk
While voice is unlikely to completely replace text in the foreseeable future, it will undoubtedly have a big impact in many technology-related fields, notably including e-commerce and search.

A brief history of voice

Automated voice-based interfaces have been around for decades now although their most influential exposure has been on customer service phone lines. Most of the systems involved have suffered from a variety of problems, from poor voice recognition to complex ecosystems.
Five years ago industry leading voice recognition was only at around 75% accuracy; recent advances in machine learning techniques, systems and hardware have increased the rate of the best systems to around 95–97%.
Approaching and crossing this cognitive threshold has been the single biggest factor in the current boom. Humans recognise spoken words with around 95% accuracy, and use context to error correct. Any automated system with a lower recognition accuracy feels frustrating to most users and isn’t therefore commercially viable.
Related developments in machine learning approaches to intent derivation (explained later in this article) are also a huge contributing factor. Commercial systems for this functionality crossed a similar threshold a couple of years ago and were responsible for the boom in bots; voice is really just bots without text.
Bots themselves have also been around for decades, but the ability to process natural language rather than simply recognising keywords has led to dialogue-based interactions, which in turn powered the recent explosion in platforms and services.

Assistants

Pre-eminent in the current voice technology landscape is the rise of virtual automated assistants. Although Siri (and other less well known alternatives) have been available for years, the rise of Alexa and Google Assistant in particular heralds a wider platform approach.
The new assistants promote whole ecosystems and function across a range of devices; Alexa can control your lights, tell you what your meetings are for the day, and help you cook a recipe. These provide opportunities for brands and new entrants alike to participate in the voice experience.

Effect on markets

A new, widely used mechanism for online commerce is always going to be hugely disruptive, and it’s currently too early to know in detail what all the effects of voice will be for brands.
Three of the biggest factors to take into account are firstly that many interactions will take place entirely on platform, reducing or removing the opportunity for search marketing. Secondly the fact that dialogue-based interactions don’t support lists of items well means that assistants will generally try to recommend a single item rather than present options to the user, and lastly that the entire purchase process will, in many cases, take place with no visual stimulus whatever.
All of these factors are currently receiving a lot of attention but it’s safe to say that the effect on (especially FMCG) brands is going to be enormous, especially when combined with other factors like Amazon’s current online dominance as both marketplace and own-brand provider.
Two strategies that are currently being discussed as possible ways to approach these new challenges are either to market to the platforms (as in, try to ensure that Amazon, Google etc. recommend your product to users), and/or to try to drastically increase brand recognition so that users ask for your product by name rather than the product category. Examples would be the way the British use ‘Hoover’ interchangeably with ‘vacuum cleaner’ or Americans using ‘Xerox’ meaning ‘to photocopy’.

Role vs other touchpoints

Over the next few years many brands will create a presence on voice platforms. This could take any form, from services providing utilities or reducing the burden on customer services, to communications and campaign entertainment.
Due to the conversational nature of voice interfaces, the lack of a guaranteed visual aspect and the role of context in sensitive communications, few or no brands will rely on voice alone; it won’t replace social, TV, print and online but rather complement these platforms.
It’s also worth noting that a small but significant part of any brand’s audience won’t be able to speak or hear; for them voice only interfaces are not accessible (although platforms such as Google Assistant also have visual interfaces).

Branding and voice

In theory voice technology gives brands an unprecedented opportunity to connect with consumers in a personal, even intimate way; of all the potential brand touchpoints, none have the potential for deep personal connection at scale that voice does.
At the same time, the existing assistant platforms all pose serious questions for brands looking to achieve an emotional connection to some extent. Google Assistant provides the richest platform opportunity for brands, but is still at one remove from ‘native’ functionality, while Alexa imposes extra limitations on brands.
Having said that, voice technology does represent an entirely new channel with some compelling brand characteristics, and despite the drawbacks may represent an important opportunity to increase brand recognition.
We’re all hardwired to see faces around us—and to make emotional connections when we talk. Image via adme.ru

Human-like characteristics

It is well established that people assign human characteristics to all their interactions, but this phenomenon is especially powerful with spoken conversations. People develop feelings for voice agents; over a third of regular users wish their assistant were human and 1 in 4 have fantasised about their assistant.
Voice-based services, for the first time, allow brands to entirely construct the characteristics of the entity that represents them. The process is both similar to and more in depth than choosing a brand spokesperson; it’s important to think about all the various aspects of the voice that represents the brand or service.
Examples of factors worth considering when designing a voice interface include the gender, ethnicity and age of the (virtual) speaker, as well as their accent. It may be possible to have multiple different voices, but that raises the question of how to choose which to use — perhaps by service offered or (if known) by customer origin or some other data points.
Another interesting factor is the virtual persona’s relationship to both the user and the brand; is the agent like a host? An advisor? Perhaps a family member? Does it represent the brand itself? Or does it talk about the brand in the third person? Does it say things like “I’ll just check that for you”, implying access to the brand’s core services that’s distinct from the agent itself?
There are of course technical considerations to take into account; depending on the service you create and the platform it lives on it may not be possible to create a bespoke voice at all, or there may be limits on the customisation possible. This is explored in more detail below.
In some cases, it may even be possible to explore factors that are richer still; such as the timbre of the voice and ‘soft’ aspects like the warmth that the speech is delivered with.
Lastly, it’s worth noting that voice bots have two way conversations with individual users that are entirely brand mediated; there is no human in the conversation who may be having a bad day or be feeling tired.

Tone of Voice in bot conversations

Tone of Voice documents and editorial guides are generally written to support broadcast media; even as they have become more detailed to inform social media posting, guides often focus on crafted headline messages.
Conversational interfaces push the bounds of those documents further than ever before, for a few reasons.
Firstly, voice agents will typically play a role that is closer to the pure brand world than either sales or support; entertainment and other marketing activities make the role of an agent often closer to a social media presence than a real human, but with a human-like conversational touchpoint.
Secondly, both bots and voice agents have two way conversations with customers. In a sense this is no different than sales or customer service (human) agents, but psychologically speaking those conversations are with a human first and a brand representative second.
In a conversation with a customer services representative, for example, any perceptions the consumer has about the brand are to some extent separate from the perceptions about the human they are interacting with.
Lastly, it’s critical to note that users will feel empowered to test the boundaries of an automated agent’s conversation more than they would a human, and will naturally test and experiment.
Expect users to ask searching questions about the brand’s competitors or the latest less-than-ideal press coverage. If users are comfortable with the agent, expect them to ask questions unrelated to your service, or even to talk about their feelings and wishes. Even in the normal course of events, voice interactions will yield some unusual and new situations for brands. For example, this commenter on a New York Times article was interrupted mid sentence, causing a brief stir and a lot of amusement.
How voice agents deal with the wide range of new input comes down not only to the information the agent can respond to, but more importantly the way in which it responds. To some extent this is the realm of UX writing, but hugely important in this is the brand voice.
As an example, if you ask Google Assitant what it thinks of Siri (many users’ first question), it might reply “You know Siri too?! What a small world — hope they’re doing well”.

Service design for voice

Whether based in utility, entertainment, or something else, some core considerations come into play when building a voice-based service. It’s not uncommon for these factors to lead to entirely new services being built for brands.
Obviously it’s important to consider the impact that not having a screen will have on the experience. As an example, lists of results are notoriously bad over a voice interface; as an experiment read the first page of a Google search results out loud. This means that experiences tend to be more “guided” and rely less on the user to select an option — although there are also lots of other implications.
With that in mind, it’s also good to note that increasingly voice platform users may have screens that both they and the assistant can access; either built into the device (like with Echo Show) or via smartphone or ecosystem-wide screens such as with the Google Assistant. While these screens can’t be counted upon, they can be used to enrich experiences where available.
Another important factor is the conversational nature of the interface; this has a huge impact on the detail of the service design but can also mean selecting services with a high ratio of content to choices, or at least where a linear journey through the decision matrix would make sense. Interfaces of this sort are often hugely advantageous for complex processes where screen-based interfaces tend to get cluttered and confusing.
Finally, as with social, context is massively important to the way users access a voice service. If they are using a phone they may be in public or at home, they may be rushed or relaxed, and all these affect the service. If the user is accessing the service via a smart speaker they are likely at home but there may be other people present; again affecting the detail of the service.
In general, services well suited to voice will often be limited in scope and be able to reward users with very little interaction; more complex existing services will often need AI tools to further simplify their access before being suitable to voice.

The voice landscape

In the last two to three years the landscape of voice technology has shifted dramatically as underlying technologies have reached important thresholds. From Google and Amazon to IBM and Samsung, many large technology companies seem to have an offering in the voice area, but the services each offers differ wildly.

Devices and Contexts

It’s important to note that many devices do have capabilities beyond voice alone. Smart speakers generally are only voice, but also have lights that indicate to users when they are listening and responding, and so help to direct the conversation.
Newer Alexa devices like the Echo Show and Echo Spot are now shipping with screens and cameras built in, while Google Assistant is most commonly used on smartphones where a screen mirrors the conversation using text, by default. On smartphones and some other devices users have the option to have the entire dialogue via text instead of voice, which can make a difference to the type of input they receive as well as the nuances available in the output.
Screen based conversational interfaces are developing rapidly to also include interactive modules such as lists, slideshows, buttons and payment interfaces. Soon voice controlled assistants will also be able to use nearby connected TVs to supplement conversational interfaces, although what’s appropriate to show here will differ from smartphone interfaces.
As should be clear, as well as a wide range of available capabilities, the other major factor affecting voice interactions is context; users may be on an individual personal device or in a shared communal space like a kitchen or office; this affects how they will be comfortable interacting.

Platforms and ecosystems

Amazon Echo speakers feature Alexa

Amazon Alexa

Perhaps the most prominent UK/US based voice service is Amazon’s Alexa: initially accessible via Echo devices but increasingly available in hardware both from Amazon and third parties.
Amazon has a considerable first mover advantage in the market (72% smart speaker market share), and it’s arguably the commercial success of the range of Echo devices that has kick-started the recent surge in offerings from other companies.
Alexa is a consumer facing platform that allows brands to create ‘skills’ that consumers can install. End users configure Alexa via a companion app; among other things this allows them to install third party ‘skills’ from an app store. An installed skill allows the end user to ask Alexa specific extra questions that expose the skill’s service offering; e.g. “Alexa, what’s my bank balance?”
There are now approximately 20,000 Alexa skills across all markets, up from 6,000 at the end of 2016. Although many have extremely low usage rates at present, Amazon has recently introduced funding models to continue to motivate third party developers to join its ecosystem.
With an estimated 32M Alexa-powered devices sold by the end of 2017 (of which around 20M in Q4) there’s no doubt that the platform has a lot of reach, but Alexa’s skills model and Amazon’s overall marketplace strategy combine to place brands very much in Amazon’s control.
Google Home features the Assistant. Image via google.com

Google Assistant

Google launched the Home device, powered by the Google Assistant in May 2016, over a year after Amazon launched the Echo. Google has been aggressively marketing the Assistant (and Home hardware devices) both to consumers and to partners and brands. Google already commands a market share (of smart speakers) of 15%, double that of the previous year; their market share of smartphone voice assistants is 46%, projected to rise to 60% by 2022.
Google’s Assistant is also being updated with new features at an incredible rate, and arguably has now taken the lead in terms of functionality provided to users and third party developers.
Perhaps most interestingly, Assistant takes an interesting and different approach to brand integration compared to other offerings, with the Actions on Google platform. Using this platform, brands are able to develop not only the service offering but the entire conversational interface, including the voice output of their service.
Users don’t need to install third party apps but can simply ask to speak to them; much the way someone might ask a switchboard or receptionist to speak to a particular person. Once speaking to a particular app, users can authenticate, allow notifications, switch devices and pay, all through the Assistant’s conversation based voice interface.
By integrating Assistant tightly with Android, the potential reach of the platform is enormous; there are currently 2.5Bn Android devices in operation. The software is also available to third party hardware manufacturers, further increasing the potential of the ecosystem.
Cortana doesn’t have a dedicated device but is available on Windows and Xbox devices. Image via Wallpaperden

Microsoft Cortana

Microsoft’s Cortana is installed on every Windows 10 device and has an impressive 145M monthly active users (probably mostly via XBox), but is currently less heavily promoted and updated than the offerings from Google and Amazon.
Cortana provides a similar ‘skill’ interface to Alexa, but has started developing this relatively late and is playing catch-up both in terms of core functionality and the number of available integrations.
Microsoft’s huge overall user base and its dominance in both work-related software and gaming ecosystems do give Cortana a powerful (and growing) presence in the market, despite its share of dedicated smart speaker devices being small.
Baidu’s Raven speakers are the company’s first foray into dedicated hardware for its well-known voice services. Image via Slate

Baidu

Baidu (often called the ‘Chinese Google’) arguably started the recent trend for voice interfaces with a combination of groundbreaking technology and a huge installed user base with various cultural and socioeconomic predispositions to favouring voice over text.
Baidu recently released DuerOS, a platform for third party hardware developers to build their own voice powered devices, and via the ‘Baidu Brain’ offers a suite of AI platforms for various purposes (many involving voice).
Most consumers currently interact with Baidu’s voice technologies via their Chinese language dedicated services (i.e. without any third party integrations).

Siri, Bixby and Watson

Apple’s Siri and Samsung’s Bixby are both voice assistants that currently only work on a given device or perhaps in the manufacturer’s ecosystem; neither could be called a platform as they don’t offer third parties access to create services.
Both have reasonable market share due to the number of phones they appear on, but their gated offerings and lower accuracy voice recognition now make them seem limited by comparison with other assistants.
IBM’s Watson is perhaps most usefully seen as a suite of tools that brands can use to create bespoke services.

Content and services

There are a lot of considerations when designing services for voice based conversational interfaces; these are touched on above but affect the range of functionality that is available.

— Utility

The vast majority of voice services currently available are utilities, giving access to a simple piece of functionality already available via other methods. These range from the more mundane (playing a specific radio station or listening to news) to the more futuristic (adjusting the lights or playing a specific film on the TV), via provider-specific functions like ordering a pizza or a taxi.
Lots of brands are beginning to offer services in this area, from home automation or similar niche organisations like WeMo and Plex or Philips Hue, to more widely used services like Uber and Dominos, but interestingly also including big brands offering innovative services. Both Mercedes and Hyundai, for example, allow users to start their cars and prewarm them from various voice assistant platforms.

— Entertainment

Various games, jokes and sound libraries are available on all the major platforms from a variety of providers, often either the platform provider themselves (i.e. Google or Amazon) or small companies or individual developers.
A few brands are starting to experiment more with the possibilities of the platform however; for example Netflix and Google released a companion experience for Season 2 of Stranger Things, and the BBC recently created a piece of interactive fiction for the Alexa.
The potential for entertainment pieces in this area is largely untapped; it is only just beginning to be explored.

Tools

Many sets of tools exist for building voice services, as well as related (usually AI based) functionality. By and large the cloud based services on offer are free or cheap, and easy to use. Serious projects may require bespoke solutions developed in house but that is unnecessary for the majority of requirements.
A full rundown of all the tools available is outside the scope of this article, but notable sets are IBM’s Watson Services, Google’s Speech API and DialogFlow, and Microsoft’s Cognitive Services.
All these mean that prototyping and experimentation can be done quickly and cheaply and production-ready applications can be costed on a usage model, which is very cost effective at small scale.

— Speech Generation

Of particular note to brands are the options around speech generation, as these are literally the part of the brand that end users interact with.
If the service being offered has a static, finite set out possible responses to all user input, it is possible to use recorded speech. This approach can be extended in some cases with a record-and-stitch-together approach such as used by TfL.
For services with a wide range of outputs, generated voices are the only practical way to go, but even here there are multiple options. There are multiple free, more-or-less “computer”-sounding voices easily available, but we would recommend exploring approaches using voice actors to create satnav-like TTS system.
The rapidly advancing field of Machine Learning powered generated speech that can sound very real and even like specific people is worth keeping an eye on; this is not yet generally available but Google is already using Wavenet for Assistant in the US while Adobe was working on a similar project.

The technology behind voice

What people refer to as voice is really a set of different technologies all working together.
Notably, Speech To Text is the ‘voice recognition’ component that processes some audio and outputs written text. This field has improved in leaps and bounds in recent years, to the point where some systems are now better at this than humans, across a range of conditions.
In June, Google’s system was reported to have 95% accuracy (the same as humans, and an improvement of 20% over 4 years), while Baidu is usually rated as having the most accurate system of all with over 97%.
The core of each specific service lies in Intent Derivation, the set of technologies based on working out what a piece of text implies the underlying user intent is — this matches user requests with responses the service is able to provide.
The recent rise in the number (and hype) of bots and bot platforms is related to this technology, and as almost all voice systems are really just bots with voice recognition added in, this technology is crucial. There are many platforms that provide this functionality (notably IBM Watson, and the free DialogFlow, among many others).
The other important set of voice-related technologies revolve around Speech Generation. There are many ways to achieve this and the options are very closely related to the functionality of the specific voice service.
The tools and options relating to this are explored earlier in this article, but they range widely in cost and quality, based on the scope of the service and the type of output that can be given to users.

Considerations

Creating a voice-first service involves additional considerations as compared to other digital services.
First and foremost, user privacy is getting increased attention as audio recordings of users are sent to the platform and/or brand and often stored there. Depending on the manner in which the service is available to users this may be an issue just for the platform involved, or may be something the brand needs to address directly.
Recently the C4 show ‘Celebrity Hunted’ caused a bit of a backlash against Alexa as users saw first hand the power of the stored recordings being available in the future. There are also worries about the ‘always on’ potential of the recording, despite major platforms repeatedly trying to assure users that only phrases starting with the keyword get recorded and sent to the cloud.
As with most things however, a reasonable value exchange is the safest way to proceed. Essentially, ensure that the offering is useful or entertaining.
A phone on a dinner table is a lot more socially acceptable than it was a few years ago. Talking out loud to devices will go the same way. Image via musely.com
Another consideration, as touched upon earlier in this article, is that the right service for a voice-first interface may not be something your brand already offers — or at the least that the service may need adaptation to be completely right for the format. We’ve found during workshops that the most interesting use cases for branded voice services often require branching out into whole new areas.
Perhaps most interestingly, this area allows for a whole new interesting set of data to be collected about users of the service — actual audio recordings aside, novel services being used in new contexts (at home without a device in hand, multiuser, etc) should lead to interesting new insights.

Recommendations for brands

We believe that long term, many brands will benefit from having some or all of their core digital services available over voice interfaces, and that the recent proliferation of the technology has created opportunities in the short and medium terms as well.
A good starting point is to start to include voice platforms in the mix for any long term planning involving digital services.
Ideally brands should start to work on an overall voice (or agent, including bots) strategy for the long term. This would encompass which services might best be offered in these different media, and how they may interact with customer services, CRM, social and advertising functions as well as a roadmap to measure progress against.
In the short term, we believe brands ought to experiment using off-the-shelf tools to rapidly prototype and even to create short-lived productions, perhaps related to campaigns.
The key area to focus on for these experiments should be how the overall brand style, tone of voice, and customer service scripts convert into a voice persona, and how users respond to variations in this persona.
This experimentation can be combined with lightweight voice-first service design in service of campaigns, but used to build an overall set of guides and learnings that can be used for future core brand services.

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Top 10 online courses to help your learn mobile app development plus some advice from the experts on why app prototyping makes all the difference!

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Here are our top 10 online courses to help you learn mobile app development:

1 — Android Development Tips Weekly series on Lynda

Teach yourself app development with this series of Android development tips by David Gassner.
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2 — Mobile App Development for Beginners on Udemy

Dee Aliyu Odumosu’s mobile app development course is ideal if you’re looking to break into iOS.
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3 — iOS App Development with Swift Specialization on Coursera

This is the ultimate Swift for iOS development course, brought to you by Parham Aarabi and the University of Toronto.
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Note that this course requires you to own and already be familiar with Mac.
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4 — Introduction to Mobile Application Development using Android on edX

Learn mobile app development and the basics of Android Studio in Jogesh K Muppala’s introduction to the Android platform.
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5 — Full Stack Web and Multiplatform Mobile App Development Specialization on Coursera

If you’re learning mobile application development for Android and found the above course useful, try this course out next.
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6 — iOS 9 and Swift 2: From Beginner to Paid Professional on Skillshare

Mark Price’s online course for iOS Swift is everything you need to know about iOS 9 development.
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7 — The iOS Development Course That Gets You Hired on Career Foundry

Jeffrey Camealy presents the iOS Development course to get your hired.
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8 — Get Started With React Native on TutsPlus

Markus Mühlberger’s course for React Native is perfect for anyone who wants to code for multiple mobile platforms.
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  • Commitment: 1.2 hours
  • Price-point: $29 a month

9 — Build a Simple Android App with Java on Treehouse

Ben Deitch’s course will help you build simple mobile apps for Android with Java, without any prior knowledge.
Best-suited to budding Android developers, this course will explore programming in Android and some very basic concepts of the Android SDK. By the end of the course, you’ll have a working knowledge of how a basic app works.
  • Level: Beginner
  • Commitment: 1.5 hours
  • Price-point: from $25 a month

10 — Try iOS on Code School

Gregg Pollack’s tutorials on iOS app development from the ground up and requires only basic coding experience.
Write your first iPhone app code and learn about different UI elements, such as buttons, labels, tabs and images. Upon completion, you’ll be able to connect to the internet to fetch data, build out table views and navigate between different areas of your app.
  • Level: Beginner
  • Commitment: 6–8 hours
  • Price-point: $29 a month
It’s an exciting time for mobile app developers. And as you can see, there are plenty of resources out there to help get your career off the ground. But don’t forget to look at the big picture.
Prototyping is an integral part of the mobile app life cycle. Download Justinmind now and explore a prototyping tool that’s made with the entire product team in mind.

Thursday, January 11, 2018

How we designed our bank account: NuConta — Part I


In October, Nubank announced our boldest product release since our revolutionary credit card: NuConta, a single account that allows people to save, invest and transfer money in real-time. NuConta is a complete redefinition of how banking accounts should work, and here’s how our design team arrived at this new concept.
NuConta — Main Screen and Account Screen

Start with why

Nubank’s core mission is to remove complexity and empower people. The credit card, our first product, has achieved viral growth among our customers by doing exactly this, but it’s a product accessible only to a select population due to credit analysis requirements. In fact, we have received over 13 million requests to get a Nubank card, but had to say no to a considerable percentage of those people. Our customer base, which is nearing 3 million accounts, is already representative — we’re currently Brazil’s no.5 credit card issuer — but still limited when compared to a market of 120 million Brazilians who are unbanked or have to deal with expensive and abusive banking services that dominate the market.
An example of the list of fees from traditional Brazilian banks
The next logical step in bringing our mission and user experience to a broader population, regardless of their income, credit scores or other barriers, was to build a product anyone could have access to: our version of a banking account, NuConta.

The team

Designing, building and launching NuConta in 12 months was only possible because of how the team was structured and governed. The squad, as we call teams here, was composed from the very beginning of product, financial, engineering and design talent, none of whom had built something like this before. It was a group of unbelievably bright, but most of all humble people, who were completely open to learning and having their opinions challenged.
This was, of course, a fascinating and unique project to be working on, so people couldn’t avoid coming in with their premature views and expectations for what the final product should be. The role of design was as much about facilitating alignment between these expectations, bringing clarity to compromises and decisions, and replacing our biased opinions with real people’s pains and needs, as it was about designing UI flows, copy, or making prototypes.

Design in an Agile Team

As much as we designers like to structure and visualize our process, what happens in our reality is more complex and asynchronous than the diagrams we’ve grown accustomed to.
Doing solid foundational research before starting anything else can surely de-risk product placement, but inevitably delays engineering and thus time-to-MVP.
What we did then, was to work in parallel threads:
  • The Design team working to figure out how to shape the product to answer the customers’ needs.
  • The Engineering team working at full-speed to put the banking infrastructure together.
  • The Intel and Legal team powering through the sea of legislation, third-party interactions and contracts.
How was our process to get to the MVP
Each of these threads constantly fed each other with their learnings and advancements, and we adjusted the product accordingly up to the last moment before shipping.
“Go do the best research you can, come back to tell us what you’ve learned, and we’ll adjust as we go. We’re not afraid of throwing our code away.” — The best thing a UX person could hear from their dev team.

Foundational Research

We were committed to challenging our most basic assumptions about how people understand and use banking services, so our initial conversations were purposefully broad and naive. We started with a simple list of questions, but we adjusted frequently along the way.
  • How do people currently manage their money?
  • What do they think about the different account types? Do they even understand them?
  • Do people save money? Why? Where?
  • Are people aware of product options in the market?
  • How do they feel about the products on the market? What attracts them? What scares them?
  • How complicated is the current landscape for a person with no financial background?
  • If people want to start saving money now, what would be their first step?
The fastest way for us to start asking (and testing) these questions was to sneak them into studies already being conducted by other product teams (namely, credit card and Nubank Rewards). We learned a lot very quickly by “stealing” a few minutes of our colleagues’ interviewing time, but their target audience could be skewed to non-target segments.
To balance that out, we got out of the building to do intercept interviews in places like public universities and spaces, where we could reach a wider variety of people who were not already Nubank customers.
Intercept interviews at the University of São Paulo and Av. Paulista
Designing for financial services is about getting the words right as much as it is about getting screens right
These in-depth early interviews took 40–90 minutes each. We sat down and very informally let people talk about their financial lives, how they felt about saving, investing, transferring, and spending their money. We also experimented with some visual aids such as card-sorting and very cheap prototypes, but honestly our best feedback tools were our competitor's websites and products. We learned an incredible amount just by having people experiment with things other companies have already built.
Analysis of interview transcripts and sense-making phase

Personas

By combining the data from these interviews with others conducted in our lab, and also talking to a lot of our own employees about their finances, we were able to come up with eight personas that represent a gradient of behavior and demographic patterns.
Personas can yield mix results, but we’re confident they were essential in this case. Here’s some of the value personas brought to our process:
  • The team learned that people represent a gradient of experience and behaviors.
  • What we thought would add the most value, was often biased as it was based on our financially savvy perspective.
  • The team learned that it would be impossible to design a product for every type of person, and that we had to choose some group to focus on.
  • Our discussions evolved from being biased by personal opinions to being based on our chosen target’s jobs-to-be-done, pains and needs.
  • Everyone in the team now remembers who Diego (one of our personas) is, what he struggles with, and that our efforts should be focused on making his financial life less complicated and more empowered, instead of our own.
Our eight generated personas

Problem definition

With well-defined personas, we now had a lens through which we could look at the problem. Our initial mission, which was very broad, could now be better expressed in sentences that the whole team could agree on:

What NuConta is / does

NuConta is an evolution of your current and savings accounts, designed for people looking for a more accessible and easy-to-use bank account. It’s free of complexity, doesn’t charge abusive fees, and makes your money grow at a fair interest rate. Differently from big banks and other fintech pre-paid products, NuConta has zero bureaucracy, less friction to adopt and a superior user experience.
Likewise, defining what NuConta was not supposed to do, at least for launch, was equally helpful in creating vision alignment and prioritization:

What NuConta is not / doesn't

NuConta doesn’t serve people looking for advanced investments, home brokerage, paid wealth management advice. It tries to be accessible and self-explanatory, but without becoming an educational product. At its early stage, it also will not support goals or any other kind of gaming mechanics.
We learned from this process that defining a problem is sometimes harder than sitting down to solve it. After dozens of long work days, heated meetings, lots of head-scratching, word-smithing, and sense-making about the material collected during research, the team was finally committed to a unified vision of the product that reflected our customer’s pains and needs instead of our own. We were now ready to deep dive into exploring solutions that would eventually become NuConta.

Part II of this post will tell how the next steps played out: product ideation, UI explorations, concept & usability testing, onboarding design, copywriting, and implementation.
Hit Subscribe to be notified when Part II comes out!


Does your app need a night mode?




With the introduction of OLED screens to the iPhone X, more and more people are requesting night themes in their favourite apps to take advatage of the true blacks on OLED screens, to save battery, and to make it easier on the eyes in some cases. But should you add this option to your app?
Don’t confuse choice with convenience.
If you ask any user if they’d want the option of night mode in your app, they would say yes. As consumers we think we need more choices. It sounds very logical. The more choices I have, the more likely I am to choose something that suits me and makes me happy. But does more choice actually make users happier? In the TED Talk, The Art of Choosing, Sheena Iyengar explains how that might not actually be true.
Just because users are asking for options, doesn’t mean they’re going to start using them or that it’s the right choice for them. Depending on the type of content that you provide to your users, a night mode might actually hurt their engagement.
You have to ask yourself why you’re thinking about a night mode. If you’re doing it solely to give your users options, then please, do yourself and your users a favour and stop. There are many downsides to having a night mode that you have to consider and be OK with before adding it to your app.
A night mode creates inconsistency within your app. It’s already hard enough to keep your apps consistent with iOS and Android, and if you have a website having that be consistent with everything too. Why would you go out of your way to make it even more difficult for yourself?
A night mode might reduce your users’ engagement with your app. Your users are the reason that you have created your app. They have been using your app and are used to it. If you have good information architecture and user experience, they might be even using your app with muscle memory. These users are your friends. They have already memorized your app’s hierarchy and are using affordances and clues in your app to navigate it fluently. Introducing a dark mode would change all of that. Now they have to re-learn your app. Even though everything is in the same place, they have to re-learn the affordances and clues and repeat the process of getting used to it all over again, and this risks alienating your users. They might see the dark mode and think that’s a good choice for them and turn it on, but the next time they open your app they won’t know how to navigate it and it will feel strange. Remember when Instagram switched their UI design to the new flat one with the new logo and everyone was running around setting things on fire and protesting on the streets? Ok no one protested on the streets but some users were pissed. Do you want your users to be pissed? Looking back the re-design of Instagram was a success because it simplified the interface to make room for new features like stories and bookmarking photos and such. But a night mode is not a re-design. Instead of moving your design forward, you would give it a split personality.
Designing a night mode for an app is no easy task either. You might think that it’s just as easy as flipping the background and text colours, but there’s actually a lot to consider. If there are photos in your app, are they going to look their best in dark mode? On each given page, is the right content being highlighted when the colours are switched? Do users’ attention still flow the same way they did in the regular mode? How does the setting page look? Should the setting page also be switched to dark mode? It would look very weird, wouldn’t it? what about all the sub-pages of the settings page? how about the keyboard? Do we change it to the dark keyboard in iOS when in night mode? If you have a black tab-bar, should it now suddenly be white? because if it stays black then there would be no contrast, but if you turn it white, there’s a big bright object at the bottom getting all the attention from the rest of the screen, and that’s not really what you want.
What if my users have sensitive eyes and can’t handle bright lights? Or it’s very hard for them to read balck on white due to dyslexia? Both iOS and Android have very thorough accessibility features to accomodate the whole experience for them. Having those settings on an app-by-app basis would be confusing and inconsistent. There are options to reduce white points, invert colours without inverting the photos, greyscale, adding a tint, and options for different kinds of colour blindness built into the system. So these don’t become an excuse for you to add a night mode to your app.
OK. So there are many reasons why someone shouldn’t add a night mode to their app. But is there a good time to add a night mode? Yes.
It all depends on the context — the type of content or service you are providing your users and the context in which the users use your app. The main complaint around the lack of night mode is prolonged reading at night in a dark environment, mostly in bed or while in a car.
If your app is a game, then don’t bother.
If it’s a productivity app, it’s still a very hard no as changing the colour of the tools and the layout in an app that users depend heavily on might confuse them. Unless you know for a fact that your users are for some reason only using your app in bed with the lights off, then for their sake do not add a night mode.
If your app is related to messaging, then it’s be best to optimize for the Smart Invert feature and let the user control the dark mode from the accessibility section in settings if they wish.
If your app focuses on reading, *cough* Medium *cough*, then it’s a good idea to provide options for your users to adjust the reading environment to their comfort. A great example of this is the Reader mode in Safari.
Reader mode in Safari allows you to change a few settings to find the most comfortable one for you.
If your app is related to driving, like Google Maps or Podcasts, and might stay open while a user is behind the wheel, it’s a good idea to add automatic night mode so that it won’t distract the users while they’re behind the wheel (can’t wait for self-driving cars).

I’ve seen a lot of confusion and frustration from users and designers surrounding night mode and if it should be a system-wide feature or not. I hope this article made it a bit clearer if you should or shouldn’t add a night mode to your app. Happy designing! ❤️

How to Lead High-Impact, Cross-Functional Projects


Even When You’re Not the Boss

This past summer I managed the largest acquisition campaign in my company’s history. I work at HubSpot, a marketing software company that popularized lead-gen campaigns and the whole idea of “inbound marketing,” so this is no small feat (we’ve run massive campaigns over the years).
The campaign, Four Days of Facebook, drove 10x the number of average leads of a typical acquisition campaign and 6x the lifetime value of projected customers.
But I didn’t do it alone. This campaign involved 11 teams and 33 people who directly contributed to the work.
Cross-functional campaigns like this can be big, complicated, and challenging which is why they so often take a boss or recognized leader to make them happen. So I wanted to share my experience as a “non-boss.” I hope it encourages other individual contributors out there to get their co-workers in other departments excited about working on high-impact, cross-functional projects.

Pre-planning: create alignment

You won’t have all the answers on day one, but make sure every conversation you’re having at this stage focuses on one thing: impact. You’ll be asking a lot of people to work hard on something outside of their normal day-to-day, make it clear that your asks will translate into business results.
  • Meet with senior leaders of each team before you ask for their employees commitment on helping. Again, make it clear that you won’t be wasting anyone’s time, you’re out to generate big results.
  • Have a kickoff meeting with the team who will be responsible for delivering the work. At a high-level, you want to let everyone know that you have senior leadership buy-in and the project will be worth their time. On a more tactical level, you’ll also want to get people up-to-speed on the tools you’ll be using to manage the project.
  • Go the extra mile to develop a team culture for your team. You know how developers name their projects crazy-sounding names? It’s surprisingly effective! Give your temporary team a name that makes people feel like they’re a part of something, set up an email alias, and create a Slack channel. Get people excited!
Throughout the pre-planning stage, keep your vision front and center. For Four Days of Facebook we were partnering with Facebook, a fact I repeated constantly.
If people are excited and engaged with your vision, they’ll put up with the inevitable bumps as you achieve lift-off.

During: maintain momentum

The Progress Principle is the idea that humans love the satisfaction of wins, even if they’re small. It’s your best friend as you seek to keep multiple teams and dozens of people aligned and moving in the right direction–constantly show (and celebrate) forward progress.
  • Display it: I put together a registration goal waterfall chart that was updated everyday to show progress. It’s motivating to close-in on and cross that goal line.
  • Never shut up about it: I linked to information about this campaign in my email signature, Slack rooms, wherever I had the attention of my co-workers. And that information was short, sweet, and up-to-date.
  • Be a good partner: You’re not technically the manager of the people on a cross-functional team, but you should implement some management best practices: give people autonomy, figure out how they like to work and what kind of support they need from you.
  • Ask for feedback: I asked questions constantly– Is this system or process working for you? Can I set up these reports in an easier way? At one point during this campaign I asked the senior manager of a few folks working on the project if she had thoughts on how I could run it better, she told me she would love to see weekly updates sent to her and other senior managers. I was avoiding this as I didn’t want to clutter inboxes, but it ended up being one of my best tools for building internal momentum around the campaign.
Don’t overlook the fundamentals of good project management. A framework like DARCI makes roles & responsibilities super easy so you the project lead can just say, “This meeting is for people who are Responsible and Accountable only, we’ll be covering deadlines for next week”, or “This meeting is for people that need to be Informed, it’ll be a milestone check-in.”
Find a project management framework, and stick to it.

Wrapping up: close-the-loop

I run 4–5 acquisition campaigns at HubSpot every quarter and running a campaign of this size and impact was a complete rush and I can’t wait to do it again. But before jumping into the next big project, it’s important to do a clean wrap-up, I want people to be excited to work with me and my team again in the future.
  • Say thank you: Do it publicly via a company announcement or email, and privately. I wrote handwritten notes to every person who contributed to this campaign.
  • Share results soon: Share the quantitative results, but don’t miss Twitter comments from attendees, feedback from partners, or the accolades of your co-workers. This is your chance to make it clear that you promised impact and delivered it.
  • Look for improvement opportunities: Because no matter how successful your campaign was, there are opportunities to do better — Were any deadlines missed? Why? Did any team members not work well together? Can this be addressed?
It’s easy to get stuck in a rut of executing one marketing campaign after the next, and it’s scary to think about leading a big cross-functional project that could potentially fail publicly.
But so often the answer to higher impact is better collaboration. Learning how to lead across teams 10x’ed the impact I was having at my company, I hope it does the same for you.

HTTPS explained with carrier pigeons


Cryptography can be a hard subject to understand. It’s full of mathematical proofs. But unless you are actually developing cryptographic systems, much of that complexity is not necessary to understand what is going on at a high level.
If you opened this article hoping to create the next HTTPS protocol, I’m sorry to say that pigeons won’t be enough. Otherwise, brew some coffee and enjoy the article.

Alice, Bob and … pigeons?

Any activity you do on the Internet (reading this article, buying stuff on Amazon, uploading cat pictures) comes down to sending and receiving messages to and from a server.
This can be a bit abstract so let’s imagine that those messages were delivered by carrier pigeons. I know that this may seem very arbitrary, but trust me HTTPS works the same way, albeit a lot faster.
Also instead of talking about servers, clients and hackers, we will talk about Alice, Bob and Mallory. If this isn’t your first time trying to understand cryptographic concepts you will recognize those names, because they are widely used in technical literature.

A first naive communication

If Alice wants to send a message to Bob, she attaches the message on the carrier pigeon’s leg and sends it to Bob. Bob receives the message, reads it and it’s all is good.
But what if Mallory intercepted Alice’s pigeon in flight and changed the message? Bob would have no way of knowing that the message that was sent by Alice was modified in transit.
This is how HTTP works. Pretty scary right? I wouldn’t send my bank credentials over HTTP and neither should you.

A secret code

Now what if Alice and Bob are very crafty. They agree that they will write their messages using a secret code. They will shift each letter by 3 positions in the alphabet. For example D → A, E → B, F → C. The plain text message “secret message” would be “pbzobq jbppxdb”.
Now if Mallory intercepts the pigeon he won’t be able to change the message into something meaningful nor understand what it says, because he doesn’t know the code. But Bob can simply apply the code in reverse and decrypt the message where A → D, B → E, C → F. The cipher text “pbzobq jbppxdb” would be decrypted back to “secret message”.
Success!
This is called symmetric key cryptography, because if you know how to encrypt a message you also know how to decrypt it.
The code I described above is commonly known as the Caesar cipher. In real life, we use fancier and more complex codes, but the main idea is the same.

How do we decide the key?

Symmetric key cryptography is very secure if no one apart from the sender and receiver know what key was used. In the Caesar cipher, the key is an offset of how many letters we shift each letter by. In our example we used an offset of 3, but could have also used 4 or 12.
The issue is that if Alice and Bob don’t meet before starting to send messages with the pigeon, they would have no way to establish a key securely. If they send the key in the message itself, Mallory would intercept the message and discover the key. This would allow Mallory to then read or change the message as he wishes before and after Alice and Bob start to encrypt their messages.
This is the typical example of a Man in the Middle Attack and the only way to avoid it is to change the encryption system all together.

Pigeons carrying boxes

So Alice and Bob come up with an even better system. When Alice wants to send Bob a message she will follow the procedure below:
  • Alice sends a pigeon to Bob without any message.
  • Bob sends the pigeon back carrying a box with an open locket, but keeping the key.
  • Alice puts the message in the box, closes the locks and sends the box to Bob.
  • Bob receives the box, opens it with the key and reads the message.
This way Mallory can’t change the message by intercepting the pigeon, because he doesn’t have the key. The same process is followed when Bob wants to send Alice a message.
Alice and Bob just used what is commonly known as asymmetric key cryptography. It’s called asymmetric, because even if you can encrypt a message (lock the box) you can’t decrypt it (open a closed box).
In technical speech the box is known as the public key and the key to open it is known as the private key.

How do I trust the box?

If you paid attention you may have noticed that we still have a problem. When Bob receives that open box how can he be sure that it came from Alice and that Mallory didn’t intercept the pigeon and changed the box with one he has the key to?
Alice decides that she will sign the box, this way when Bob receives the box he checks the signature and knows that it was Alice who sent the box.
Some of you may be thinking, how would Bob identify Alice’s signature in the first place? Good question. Alice and Bob had this problem too, so they decided that, instead of Alice signing the box, Ted will sign the box.
Who is Ted? Ted is a very famous, well known and trustworthy guy. Ted gave his signature to everyone and everybody trusts that he will only sign boxes for legitimate people.
Ted will only sign an Alice box if he’s sure that the one asking for the signature is Alice. So Mallory cannot get an Alice box signed by Ted on behalf of her as Bob will know that the box is a fraud because Ted only signs boxes for people after verifying their identity.
Ted in technical terms is commonly referred to as a Certification Authority and the browser you are reading this article with comes packaged with the signatures of various Certification Authorities.
So when you connect to a website for the first time you trust its box because you trust Ted and Ted tells you that the box is legitimate.

Boxes are heavy

Alice and Bob now have a reliable system to communicate, but they realize that pigeons carrying boxes are slower than the ones carrying only the message.
They decide that they will use the box method (asymmetric cryptography) only to choose a key to encrypt the message using symmetric cryptography with (remember the Caesar cipher?).
This way they get the best of both worlds. The reliability of asymmetric cryptography and the efficiency of symmetric cryptography.
In the real world there aren’t slow pigeons, but nonetheless encrypting messages using asymmetric cryptography is slower than using symmetric cryptography, so we only use it to exchange the encryption keys.
Now you know how HTTPS works and your coffee should also be ready. Go drink it you deserved it 😉

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