What has a pandemic to do with marketing?

What is a pandemic?

Many of us learned the word Pandemic for the first time thanks to coronavirus and COVID-19. Pandemic is an outbreak of disease prevalent over the whole world. The H1N1 flu virus in 2009 is a good example of that. By contrast, the famous SARS (Severe Acute Respiratory Syndrome) outbreak in 2003 was an epidemic spread in Hong Kong and surrounding Cantonese regions. Similarly, the Ebola outbreak in West Africa was considered an epidemic. The difference between a pandemic and epidemic is the size of its impact. Despite that, both words refer to an illness of similar nature and derived from a common source, in excess of what would be normally expected in a community or region.

A map of the coronavirus outbreak as of March 2020

How does "virality" look like?

Coronavirus is shutting the whole world down because it spreads more easily than other diseases. Because of that, we see the exponential growth in confirmed cases on COVID-19 when not enough measure was in place to stop the spread.

To us marketers, viral growth is a more familiar term. Virality typically refers to the tendency of an image, video, or a piece of content to be circulated rapidly and widely from one internet or mobile user to another. Viral marketing is one of the most promising channels to grow product adoption and product usage organically. 

Hockey stick growth of COVID-19

TikTok is a great example of viral-content-enabled hockey stick growth. SensorTower reported over 700 million global downloads of TikTok, beating Facebook & Instagram in 2019.

The same hockey-stick growth seen on TikTok

How to measure virality?

There is a way to calculate the virus’s basic reproduction number, or R0 — the number of people on average one infected person will pass the virus to.  Coronavirus suggests a range of 2–2.5 in R0,  exceeding seasonal flu in the range of 1-2. 

R0 (Basic reproduction number) comparison on Coronavirus

There is a similar metric to R0 in viral marketing called K-factor. The K-factor can be used to describe the growth rate of websites, apps, or a customer base. The formula is roughly as follows:

 (e.g. if each new customer invites five friends, i = 5)
 (e.g. if one in five invitees convert to new users, c = .2)

In the example above your K-factor is 1. The higher the K-factor, the higher the virality and the faster the product will grow in downloads or installs. Notice here I didn't say userbase instead - the reason being that active user base also highly depends on the effectiveness of user onboarding and retention, which we can cover in a different post.

2019 Q4 global downloads of the top social apps

Why is viral marketing so desirable?

First of all, viral marketing is powerful because it is implemented through content and enabled via technology in today's products. This makes it scalable.

Secondly, viral marketing success isn't limited to the size of your marketing budget as its outcome doesn't necessarily correlate to the amount of acquisition dollar put behind your campaigns and the spread of the content could be completely free or just slightly incentivized. Therefore it is more affordable.  

Using TikTok as an example, they focused on short-form mobile videos. By providing users with tools to make impactful visual and sound effects, TikTok enables its users to easily create viral content. TikTok further makes it easy to share their videos on other social platforms with TikTok signature look and feel - Douyin, TikTok's Chinese version also includes a sound signature in each video. When users share TikTok content, they are building mindshare in their community about the TikTok brand. With more and more social influencers getting onto the platform, their fans follower their footsteps to adopt the app.  What a powerful way to grow a product!

Final words

Now that you've learned that every person who contracted COVID-19, with or even without symptoms, may pass the virus on to two or more people,  are you finding yourself better at keeping social distance, washing hands often and not touching your face?

Are you interested in learning more about viral marketing? Is viral marketing for everyone? How to construct a successful viral marketing strategy? How to measure k-factor if your budget doesn't allow you to pay for those expensive attribution tools? Let me know if you're interested in learning more and I will follow up with more posts on this topic!

Read my related growth hacking articles:

Try Out Beets, Because It Will Make You Red Pee

Test Improved Conversion over Control by 20%. Deploy? Think Twice.

Why You Should Ignore Everything You Have Been Told About Growth Tactics

i18n & l10n - Boost Your Addressable Market by 10X+

What is i18n & l10n?

i18n & l10n stand for internationalization and localization, meaning I-eighteen-letters-n and L-ten-letters-n. They refer to adapting apps to different languages, regional differences as well as technical and business requirements of a target locale. Internationalization is mostly in the product development phase where an app is designed and developed in a way that removes barrier for localization and allows same great UX for users outside of the original country. While localization is the actual adaptation of the app into various language, culture and preferences of the foreign markets, it is often executed in both product and marketing.

Ideally, internationalization occurs as a fundamental step in the design and development process, rather than as an afterthought that can often involve awkward and expensive re-engineering. It has potential to significantly affect the ease of the product's localizations.

Translating the Language

English to English translation: If your original app is built in and for US market, do not easily dismiss the opportunity to localize for your fellow English countries such as the UK, Canada and Australia, especially if written and verbal communication is important for your app. Consider adjusting spelling, date/time format, currency, and local slangs.

English to other language translation: It is important to leave extra space for translation to another language when doing user interface design. German, Turkish and sometimes French have longer translations. And wait till you take a look at this paragraph in Greenlandic: 

Sure, on an average weekday, you probably won't build for the Greenland market, but you get my point.

Last but not least, don't forget text that is embedded in the images. In an ideal world, instead of embedded text, you would have text overlay with CSS so that it is a lot more manageable when it comes to localization - not to mention how much your designer would love you for that decision. An example of better internationalization approach right here.

More Than Just the Language

Localization is often thought of only as a synonym for translation of the user interface and documentation. In fact it is often a substantially more complex issue.

Growth Case Study in Japan Market 

I recently worked on driving growth of SoundHound, the best music discovery app, in the Japan market. We set the initial goal of the project to be adoption of a certain product feature. After analyzing data on the local market, I realized there was a bigger gap in user adoption of another interdependent feature. We re-scoped the project and discovered as we dug deeper with a native specialist that there is local regulation in the Japanese market which may deteriorate user experience of the said feature. We researched the extent of the impact and went back to the drawing board for a workaround. The takeaway here is to never overlook the potential implication of local regulation and market development.

Referral is one of the most important sources of organic growth and international markets often require deeper thoughts. Japan is an iOS market and users use Line in lieu of phone call and sms service provided by cellular network, as the unlimited data is typically included in one's cellphone plan. When we promoted social share features in Japan, we put Line icon front and centered to achieve better CTR.

Ultra popular social network app Line in Japan

We also uncovered that Japanese users use SoundHound more for discovering English songs than for Japanese songs when we compared top charts in SoundHound to the local hottest hits. This differs from European markets where top local charts in and out of SoundHound app are highly consistent.

Final words

i18n & l10n is challenging, fun and rewarding, especially when you work with a team of product manager, UX designer and developers that keeps l10n in mind. Feel free to share your thoughts and experience in i18n & l10n with us!

Read my related growth hacking articles:

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Why You Should Ignore Everything You Have Been Told About Growth Tactics

Follow me on twitter (@qindizhang) or add me to your Google+ circle, my friend! Let me know in the comment what other topics you want to read about!

Are We Really Ready for Voice Assistant - Why User Engagement is Challenging for Voice Apps

Five Levels of Consumer Awareness

All the way back in 1966, Eugene Schwartz laid out the 5 phases a consumer goes through before they buy a product:

• Completely Unaware: The consumer doesn’t even know that they have a problem, though they have their own ideas and preferences
• Problem-Aware: The consumer is aware that they have some kind of problem, but they’re not aware there are solutions
• Solution-Aware: The consumer is aware that there are solutions to their problem out there, but they don’t know about yours
• Product-Aware: The consumer knows that you sell a product that matches their problem, but they’re not convinced that it will completely solve it or be right for them
• Most Aware: The consumer knows they have a problem, they know solutions exist, and they know your product is a solution—now, they just need to be “closed.”

Where is Voice Adoption on the Awareness Scale?

The answer is: all over the place!

To some degrees, all of us are somewhat familiar with brand names such as Siri, Alexa, Google Assistant or even Cortana. Does it mean, as long as the shiny little speakers make their way into people's living room, we can all go home? 

At the same time, millions of people are still risking their lives and others everyday - texting, typing and swiping on their phone behind a wheel when they should've relied on their voice as a much safer way to command their phone.

Why is User Engagement so Challenging for Voice Assistant?

Voice use cases are many but far in between. Alexa has 100+ skills, same as Google assistant as actions and Hound as domains, although all is not equal.

Adopting Eugene Schwartz's 5 levels of awareness:

• Completely Unaware: Over the holidays Google and Alexa have been educating users on holiday themed use cases such as Play New Year's Mad Libs. I played it and it was fun for the first time but not a use case that sees a typical users more often than once a year.
• Problem-Aware: During one of the in-house user studies, almost all the users acknowledge it is very dangerous to text and drive. 10-20% admitted they're guilty of charge. Are most users not aware that they can use their voice to check messages, reply and launch apps, or the products in market lack appeal one way or another?
• Solution-Aware: Many users know to use their voice on Google map and Waze to get to destinations. These voice add-on features aren't making or breaking the deals though.
• Product-Aware: Philips hue light bulbs are known for being one of the most popular personal wireless lighting solutions, working alongside google homes. The name brand comes to people's mind when you talk about voice controlled lights.
• Most Aware: Streaming music and control home appliances such as lighting on smart speakers. The most commonly known and adopted voice use cases include setting up alarm and inquire weather forecast. They exist in all the voice assistant products, therefore have become a hygiene factor instead of a differentiator.

Summary

In spite of the fact that Amazon & Google manage to convince a dozen million consumers on the initial investment for the hardware, all voice assistant providers still struggle on getting the usage up in volume as well as frequency.

Voice will eventually take over the current UI of type, tap & swipe, but so far, voice assistant providers continue to see screen-involvement & cross-devices to be the engagement key for voice service - counter intuitive I know. This shows us that it will take another few years to see higher adoption and deeper engagement in voice interface as the technology catches up for better UX and more reliable result or action taken upon command.

Read my related growth articles:

Test Improved Conversion over Control by 20%. Deploy? Think Twice.

i18n & l10n - Boost Your Addressable Market by 10X+ 

Why You Should Ignore Everything You Have Been Told About Growth Tactics

Follow me on twitter (@qindizhang) or add me to your Google+ circle, my friend! Let me know in the comment what other topics you want to read about!

Why You Should Ignore Everything You Have Been Told About Growth Tactics

We have all heard various recommendations on growth tactics: Mandatory registration, rich push notifications, frictionless user onboarding; the list goes on. Some of this advice is very convincing as they come in as learnings from successful growth projects.

Common Mobile Growth Tactics

Andy Carvell shared a case study from SoundCloud where he tested putting emojis into push notification, a heart 💗 at the beginning and the end of the message title. The open rate improved. The team went ahead and tested with two hearts 💗💗 and the open rate yet improved again.

You probably at some point saw one or more growth tactics like the below, most of which come with numbers:

• Emojis can increase push notification open rate by 85%
• Email open rate increase by 4x if a user's name is included 
• In-app behavior based messages increase the open rate by 9x
• Push notifications lift retention rate by 20%

Next time when you encounter an exciting and seemingly convincing growth tactic, ask yourself the questions below to get a better understanding regarding the context of the data provided, and evaluate how applicable they are to your particular problems:

1. When was the data collected? Has the OS significantly changed in related features for these test results to stay relevant today?

2. How large is the sample size? Does the data cover one app, several apps by one company or many apps by many companies?

3. Is the data industry specific? For example, does it relate to e-commerce, game or utility apps?
4. Does the data cover multiple geo and/or language market?

Growth Tactics Don't Always Work, Now What?

Next time when we feel the urge to flood our push notification messages with emojis  😼🤣😘🎉 in the hope of improving that depressing 2% push open rate, let's first take two actions:

1. Discover WHAT

I'm all for testing every sensible growth lever, but first and foremost we need to be crystal clear what we are really testing or other factors play a major role in the test result. 

For example, a rich push was tested on both Android and iOS where users are required to press and slide down the notification in order to see the full content (e.g. an image, gif or CTA buttons) attached to the rich push. This test is highly dependent on users' understanding and adoption of a particular OS feature. If the open rate didn't improve, it may not be your image or CTA, as the users simply need more education on how to use the feature itself.

2. Find Out WHY

After we find out about what works and what doesn't, the next and more important step is to understand what drives the user behavior resulting in the data you see.

An app I've worked on tested emoji and saw absolutely no noticeable lift on the test cohort. User analysis revealed that the app's user base gears towards an older age group, and surfaced that some recipients found emojis overwhelming and made it harder for them to read the text of the actual message. 

Takeaway

The larger goal in testing is beyond individual wins. Rather, it is about getting better understanding of our own UNIQUE user base so that we can apply the learning systematically to future treatments. In the long term, we want to be able to design more meaningful test and treatments to address users' underlying needs.

So test away my friends, with your North Star in mind!

Do we know what we're really looking for?

Read my related growth articles:

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Follow me on twitter (@qindizhang) or add me to your Google+ circle, my friend! Let me know in the comment what other topics you want to read about!

Test Improved Conversion over Control by 20%. Deploy? Think Twice.

The Invisible Traps in AB Testing: A Conversion Optimization Case Study

As a conversion optimization hacker, you pride yourself in making data backed decisions for your business. You follow the AB testing guidelines to a tee. After dozens of tests, you've finally found your diamond in the rough - your new landing page is performing 15% better in converting visitors for registrations. You're so pumped, you're ready to go! 

Don't.

At least not before you've checked all the data. 

Case study

Pinterest once ran a test on the visual design where they increased the size of the related pin to the original image that brought users to their landing page.

It created more equality for the extended image roll and may get users into the mode of scrolling on more instantly. Brilliant idea! Data agreed too. They saw a lot of engagement and the new layout was 25% more effective at convincing a visitor to sign up. 

They didn't ship that page. 

Why? Because the new design broke SEO. Well, kinda. They saw a double digit drop in traffic coming through. The resizing of the images forced search engines to re-crawl tons of pages and the traffic through image search was negatively impacted. This was a highly trafficked landing page so the percentage drop in top of the funnel was considerable. 

Key Takeaway

It is a simple but often overlooked phenomenon in conversion optimization - when you're laser focused on improving one key metric, make sure you've buttoned up on the entire data flow when making your decision. Pride yourself on being the data detective - keep your ears open when your data is screaming a B-side story.

Follow me on twitter (@qindizhang) or add me to your Google+ circle, my friend! Let me know in the comment what other topics you want to read about!

The Rise of Voice and Collective AI

WHAT DO WE WANT?
Natural language processing!
WHEN DO WE WANT IT?
Sorry, when do we want what?

— Benedict Evans (@BenedictEvans) January 22, 2017

Ben Evans is a partner at the renown venture capital firm Andreessen Horowitz (also called a16z). He generously shares his industry insights with the public and has hundreds of thousands of followers on Twitter.

In Ben's recent post Voice and the Uncanny Valley of AI, he started with

Voice is a Big Deal in tech this year. 

The Rise of Voice

Ben attributed the rise of voice to four causes: 

1. The advancement in machine learning reduced the error rate in voice recognition and natural language processing.
2. Better hardware, lower cost.
3. If voice most existed as people's side projects in the past, the resource is abundant today. 
4. The desktop-to-mobile platform evolution has shown, the more engaging UX is, the more control companies have which own these platforms - Apple and Google had more control over the mobile user base than Microsoft ever had with the desktop.

The twitter feed from Ben at the top of the post was mocking at AI not being able to connect dots in a human way. In fact, the ability of today's virtual assistants at handling context in a conversion is continuously increasing. You can ask a series of questions such as:

"What are the 5 star rating restaurants nearby?" 

"How far is the first one?" 

"How much  does it cost for Uber to take me there?"

And product such as Hound handles it like a champion. You don't even need to get out of the app to call for a Uber ride of your choice.

The Era of Sharing Economy, Knowledge & Intelligence

Collective AI came into view as one of the key contributors to the increased AI performance. Collective intelligence is shared or group intelligence that emerges from the collaboration, collective efforts, and competition of many individuals and appears in consensus decision making. What happens when we apply this to building AI?

SoundHound is the leading innovator in voice-enabled AI and conversational intelligence technologies. SoundHound's vision of Collective AI is to provide the tools and platform for developers to build more intelligent solutions easily and rapidly. 

The era of sharing economy, knowledge and intelligence brings a voice-enabled AI platform and its technology to the ISV community - something once only possessed and controlled by name brands such as Google, Apple, Microsoft and Amazon. What a gift!


The closing thought - what's the face of your personal AI? 

For the record, my personal AI definitely has the face of Wall-E. ;o)

Read my related machine learning articles:
Want More Funding? Machine Learning!
How to Build a Recommendation Engine without Machine Learning Experts?

Follow me on twitter (@qindizhang) or add me to your Google+ circle, my friend! Let me know in the comment what other topics you want to read about!

Try Out Beet, Because it'll Make You Red Pee

The Red Pee Proposition

Most parents have had the challenge of convincing their kids to eat vegetables.

"Try some brocolie, honey. It's good for you." 

"Why?'" 

"Because it's healthy. It gives you lots of vitamins and fiber." 

" No, thanks." (Looking away)  

This conversation I had with my kindergartener yesterday wasn't so typical.

"What is this red food?"

" It's called beet and it makes you red pee tomorrow if you eat enough."

"How many is enough?" 

"20 little pieces, I guess." 

"One, two, three... I got twenty!" (Chewing) 

Get Inside of Your Audience's Mind

Much of a Product Manager’s responsibility is to juggle multiple streams of conversation and move them towards closure. As a PM, you're required to influence and sell on a daily basis, to different audiences. During a good portion of your day, you make data-driven decisions (hopefully) with your left brain. Is it good to extend that capacity and sell with evidence or on the technicality side of the story? 

It depends. 

To an engineering audience, it may very well be the best way to go about it.  At the meantime, you'd better be prepared to sharpen up your right brain in order to take on an audience made up of sales, design or anyone new to the technology or concept you introduce on. 

How to Talk Tech to Non-Technical Audience

Live like an adult and think like a child - If you want to convince a child, you first learn how a child thinks.

The focus of the left brain is verbal, processing information in an analytical and sequential way, looking first at the pieces then putting them together to get the whole. The right brain of the brain focuses on the visual, and processes information in an intuitive and simultaneous way, looking first at the whole picture then the details. Left brain thinking is verbal and analytical. The right brain is non-verbal and intuitive, using pictures rather than words. 

Left brained organization such as Amazon invented non-powerpoint presentation and evangelizes the beauty of 6 pagers. If you want to work at Amazon, be sure to brush up on AB testing, market sizing questions and learn how to write hypothetical product's press release and FAQ announcement. Amazon uses this "working backwards" approach because it forces the team to get the most difficult discussions out of the way early. They need to fully understand what the product's value proposition will be and how it will be pitched to customers. If the team can't come up with a compelling press release, the product probably isn't worth making. 

Case Study: Tell a Technical Story in the Language of your Audience

R2D3 is an experiment in expressing statistical thinking with interactive design. Using a data set about homes, they created a machine learning model to distinguish homes in New York from homes in San Francisco. This is the most powerful visual storytelling I've come across recently. How elegant!

SCROLL

Immerse yourself in the data story

This is part 2 of story telling series. Find part 1 there.

Follow me on twitter (@qindizhang) or add me to your Google+ circle, my friend! Let me know in the comment what other topics you want to read about!