Thai protests in Bangkok

Despite barricades all around the city, Thai businesses found a way to carry on.

In an interview with BBC News, aCommerce Founder and Group CEO Paul Srivorakul talks about setting up a company in the middle of a political coup and how, despite the turmoil, the tech logistics startup managed to find a silver lining during a tumultuous situation.

paul_bbc

People stayed at home. They were scared to go out and shop, therefore they did more ecommerce.- Paul Srivorakul

The experience showed the American-Thai CEO that businesses should not be reliant in one area, especially in a developing country such as Thailand, where risks are higher. Diversification of services offered, as well as geographical diversity can also enhance business visibility and minimize risk when there is an issue in one market.

Siam Piwat Group, a Thailand based shopping mall and real estate enterprise also has a policy of actively trying to invest and expand in a time of domestic turmoil. Siam Piwat owns and manages Siam Paragon, one of Bangkok’s most iconic luxury shopping center. CEO Chadatip Chutrakul says this decision makes sense, as it is the cheapest time to do so.

All the construction costs go down. When we build, it takes around two to three years to complete. By that time, the economy would catch up, which it did everytime- Chadatip Chutrakul, CEO of Siam Piwat Group

Despite Thailand’s political instability, growth in the country remains relatively robust. Thailand’s GDP grew 3.2% year-on-year in Q1 of this year, up from the previous quarter’s 2.8% growth. During times of turmoil, private companies mostly continued operating as normal, with ongoing instability making companies more efficient. Ho Ren Hua, CEO of Thai Wah Group, a large food products business with operations across Asia, credits Thailand’s private companies as growth enablers.

The role of the private sector is to continue to help deliver economic growth, innovating new jobs and services.- Ho Ren Hua, CEO of Thai Wah Group.

With two government overthrows in the span of six years (2006 and 2014), Thailand has indeed been a politically volatile country, a factor that may scare off short term investors. However, as Thai companies and CEOs continue to successfully find opportunities despite government issues, it continues to makes for a interesting economic landscape.

A version of this appeared in BBC News on June 28. Read the full article here.

 

 

Thailand's cashless ecommerce

Rabbit Pay being used at McDonald’s In Thailand Source: nationmultimedia.com

Thailand’s ecommerce market is booming and shaping up to be one of Asia’s top performers. The imminent start of the government’s national e-payment system aimed at making Thailand a cashless society and expected to see double-digit growth.

The value of the ecommerce market was forecast to be $58.4 billion (2.1 trillion THB) in 2015, a 3.65% increase from 2014. Moody’s Analytics found that the increased use of electronic payments, including credit, debit and prepaid cards, added $3.18 billion (0.19%) to Thailand’s gross domestic product from 2011-2015, the largest weighted average increase in Asia.

The big winner in Thailand’s online marketplace has been its social commerce scene. Thai consumers are rated as being among the most likely in the world to use social media networks to find products and sellers. A March 2016 survey by PwC found that 51% of online Thai shoppers had purchased directly via social media. The rise of mobile commerce has proven to be a boom for e-payments platforms.

The national e-payment system, which will be launched by the government this fall, aims to make Thailand cashless and support the country’s digital economy policy.

Analysts expect the national e-payment program to help propel growth in ecommerce and related fintech.

Earlier this month, Facebook was revealed to be trialing an option in Thailand that would allow users to pay for products listed on Facebook Page, but Facebook is late to the party. Chat app Line, with two million users base has already launched extensive payment options. Alibaba’s third party e-payment platform, Alipay, has also been making inroads in Thailand, along with some of its main Chinese competitors.

As global giants continue to close in, it is this knowledge that could allow the Thailand ecommerce landscape to avoid the fates of South Korea or the United States, where the market was consolidated to the point that only the major players were left standing.

A version of this appeared in Forbes on June 27. Read the full article here.

In 2016, more than 15% of the population will make purchases from abroad worth $85.76 billion and by 2020, more than a quarter of the population will shop digitally for foreign products, according to eMarketer in its first analysis of the consumer trend.

Cross-Border-Ecommerce-In-China-emarketer

The chart above in eMarketer’s brand new study represents buyers age 14 and up who have made at least one purchase from a foreign seller either directly through a foreign-based site or an intermediary at least once during the calendar year. Includes desktop/laptop, mobile and tablet purchases.

Last year’s intense growth is also attributable to Alibaba launching Tmall Global in 2014, and JD launching JD Worldwide in 2015, enabling overseas brands to sell their goods directly to digital shoppers in China. In addition, in some categories, such as infant products, consumers in China perceive overseas goods to be higher-quality and more trustworthy.

Cross-border buyers in China are expected to spend an average of $473.26 each this year on global goods, representing 4.2% of the total retail ecommerce market and will amount to a spend of $85.76 billion this year. 

 

Cross-Border-Ecommerce-In-China-emarketer change over time

The eMarketer forecasting analyst Shelleen Shum predicts shifts in platform use towards official and organized sellers.

“Furthermore, cross-border ecommerce goods sold via the business-to-consumer (B2C) channel are expected to take up a growing share of the total cross-border ecommerce market in 2016 as consumers shift to platforms that are more professional and organized. Since the merchants selling on these B2C platforms have to be authorized, they are considered more trustworthy.”

Rising  global brand.com cross-border ecommerce in China

More ‘professional and organized’ sellers? The article does not cite specifically what those disfavored platforms are (one can take a couple guesses) but with the current negative press around the proliferation of counterfeits on Alibaba, it’s probable that official brand.com webstores and non-marketplace models may see a spike in popularity as cross-border ecommerce in China booms.

Excerpts from eMarketer on June 14. Read full article here. 

By Felicia Moursalien
Wal-Mart Yihaodian Fails in China, B2C bloodbath

(Hint: It’s a red ocean bloodbath), Image source: FactsRider

Its demise was inevitable. Since its 2008 launch, Wal-Mart’s online grocery business Yihaodian struggled to gain traction in China in the red sea of deep pocketed local B2C ecommerce players. Finally, Yihaodian has thrown in the towel and being sold to ecommerce Goliath JD.Com. The recently announced deal means JD will take over Yihaodian online and Wal-Mart will acquire a 5% stake in JD.com.

The Chinese branch of Sam’s Club, an American chain of membership-only retail warehouse clubs owned and operated by Walmart, will open a flagship store on JD.com, and the two companies will link their supply chains, broadening the range of imported goods. Wal-Mart, No. 8 in the China 500, will receive approximately 145 million newly issued Class A shares of JD.com in the transaction. So why and how did Wal-Mart’s seemingly successful Yihaodian fail so quickly in China?

 

Wal-Mart Yihaodian Fails in China Acquired by JD.com

Wal-Mart Yihaodian fails in China because the B2C market in China is a bloodbath. Smaller or global players will be hard-pressed to succeed there.

Wal-Mart’s Yihaodian fails in China, but why?

Walmart’s China strategy sought to establish itself as a source of high-quality food products after a series of safety issues in China, but failed because it could not adapt to local culture and buying patterns. It could also not compete with the economies of scale that giants JD and Alibaba wield. In TechCrunch last year, Sheji Ho and I predicted this when writing Forget China, There’s a Gold Rush in Southeast Asian Ecommerce Sphere

“In the Chinese ecommerce race the market giants have taken too large a lead for too long in China.

“Smaller” players such as Amazon, Rakuten, and Neiman Marcus entering the market struggle to compete because of fewer domestic resources, a lack of understanding of the Chinese market, as well as slower execution. Recent examples include Macys and Neiman Marcus shutting down their China ecommerce initiatives and Amazon throwing in the towel and opening a store on Tmall, China’s largest B2C marketplace.

With Tmall and JD owning close to three quarters of the Chinese B2C ecommerce market, there just isn’t much room for both “smaller” global and local players like Yihaodian, Suning, Amazon and VIPShop to compete. They cannot tap into the economies of scale enjoyed by the market leaders. B2C ecommerce is a winner-takes-all market where the rich get even richer.”

With nearly 6,000 delivery and pickup stations in approximately  2,500 counties and districts across China compared to Yihaodian’s mere 250 hubs, it sadly did not have a strong chance.

Cross-border ecommerce isn’t the answer either

Nonetheless, the company seemed optimistic last year. At a logistics conference in Shanghai, Yihaodian senior manager Yang Shenling said with confidence that ‘cross-border is the last blue ocean for Chinese ecommerce.’

The inbound cross-border market is estimated to be 155 billion RMB ($25 billion) and is expected to grow to a whopping 1 trillion RMB ($164 billion) by the end of 2018 according to The China e-Business Research Center cited by Shenling. But when we asked Yihaodian how big its new cross-border business was in terms of percentage of total company sales it turned out to be only 2% and projected to go up to 10% over the next five years.

Ten percent is still a very small number and getting there would be an uphill battle as the quality and safety of domestic products will no doubt increase over the next few years thanks to increased government pressure and regulation. As quality improves, there will be no need for Chinese consumers to look abroad.

In many ways, cross-border ecommerce in China can be seen as a desperate move to cope with the fact that the domestic market is reaching saturation. And despite all the hype, it is still a very small business compared to the Chinese domestic ecommerce market.

Lucky for them, JD.com has been doubling down on winning the food category. Last August, it bought a 10% stake in Yonghui, a rival that specializes in fresh food. From the Yihaodian acquisition, the company stands to gain credibility of a global brand in its efforts to be seen as a more trusted food retailer in the rightfully suspicious Chinese food ecommerce landscape.

Businesses are realizing that China is a Venus Flytrap – plenty of allure but crushing once inside.

This is just the beginning as global players are increasingly realizing that China is a Venus Flytrap – plenty of allure but crushed once inside. They instead start to look longingly south towards the real blue ocean- Southeast Asia. Expect China’s B2C ecommerce bloodbath to get a lot murkier as global and smaller ecommerce players learn the Amazon and Yihaodian China lesson the hard way.

By Felicia Moursalien

Please share your feedback to @ecomIQ and @LilFel

Why you’re reading this article

Harvard Business Review calls it a “management revolution”. McKinsey released a whopping 156 page report touting it as “the next frontier for innovation, competition, and productivity.” Palantir, a startup that used it to help the US government track down Osama Bin Laden, is now one of the hottest companies in Silicon Valley valued at $20B based on their latest funding round. Forget Google, Facebook, and Twitter, bright college grads have already shifted their sights set on Palantir. Big data has become the new black.

The big data wave isn’t simply creating companies slated for multi-billion dollar IPOs and exits, it has also created new job opportunities. What used to be a boring number crunching chore is now called data science, which Harvard Business Review coined the “sexiest job of the 21st century”. Every cool startup now boasts a data science team led by some chief data scientist. As usual, digital agencies are jumping on the bandwagon with some of them creating new units that supposedly “bring together data sciences, social, new age content, and emerging marketing technology with sound business thinking to create a proposition that’s truly integrated.” Whatever that means.

“There’s gold in the streets, just waiting for someone to scoop it up.” – Walter White in Breaking Bad

Using big data to look at big data, Google shows that search volume for ‘big data’ follows a nice hockey-stick trajectory envied by many startups. It’s pretty clear – big data is big business.

The Real Reason why you’re reading this article

“Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it…” – Dan Ariely

Despite all the media hype about big data, the sad reality is that no one actually truly understands it. What’s causing all this misunderstanding and why are we long overdue for a paradigm shift in big data?

Mythbusters: Debunking Big Data myths

1. Big Data requires an expensive enterprise platform

The biggest lie in big data is that it’s complicated and tech-heavy. It’s also the primary reason why companies fail to adopt big data. We’re talking specifically about fear of technology and/or obsession with technology. The notion that big data requires a tech-savvy professional puts off a lot of people and prevents them from taking initial baby steps towards working with data in their organizations. On the other hand, there are those that focus too much on technology for technology’s sake. Big data platforms are a means to achieve business goals, not an end in itself.

Peter Thiel, the billionaire venture capitalist who founded Paypal and Palantir, argues against over-emphasizing technology. In his bestseller Zero to One: Notes on Startups, or How to Build the Future, Thiel says that “we’ve let ourselves become enchanted by big data only because we exoticize technology. We’re impressed with small feats accomplished by computers alone but we ignore big achievements from complementarity because the human contribution makes them less uncanny.”

Only until people see through this smokescreen of big data complexity created by what we’d like to call the “Big Data-Industrial Complex” – the sum of companies with three-letter acronym names that peddle big data technology products – we’ll be able to move on towards addressing the real challenges of big data.

Doing a simple search on Google for ‘big data’ shows how competitive this space is and how much money is at stake for the Big Data Industrial Complex.

This supplier-side bias is compounded by a consumer-side that’s often clueless about big data. CXOs in Fortune 500 companies insist on purchasing the latest big data platforms and technologies in order to ensure their “competitive advantage”. In reality, most of what these companies are trying to achieve can be done at a fraction of the technology and cost. The reason why people still go for the flashiest platforms is because of fear – “a fancy tool just gives the second-rater one more pillar to hide behind,” says Hugh MacLeod, blogger, cartoonist, and best-selling author.

2. Big Data needs a lot of data (Duh?)

The second myth in big data is that we need to have a lot of data in order to do “big data”.

“Today’s companies have an insatiable appetite for data, mistakenly believing that more data always creates more value. But big data is often dumb data,” says Peter Thiel.

The reality is that most companies don’t need that much data. If your company is not in the business of finding a cure for cancer or tracking down terrorists; there’s no need for mountains of data to properly sell your product.

The reason why people in mostly large companies end up obsessing over endless data is very simple: it’s because they’re afraid. Afraid of making decisions based on less than perfect data. Afraid of having to do actual work. Afraid of taking responsibility because they can hide behind the smokescreen. People fail to realize that the real value lies in the action that comes after analysing the data set, big or small.

“Companies brag about the size of their datasets the way fishermen brag about the size of their fish. They claim access to endless terabytes of information. The advantages seem obvious: the more you know, the better,” says Slater Victoroff in his brilliant TechCrunch article.

Not enough data Just enough data

Like the Lean movement that encourages companies and employees to take an “MVP” approach towards building businesses and products, big data is long overdue for an MVP revolution. You don’t need a lot, you simply need enough.

3. Big Data is the domain for data scientists

There are countless cases where companies invest millions of dollars into big data tech but still fail because they don’t have the right people in place to analyse and execute. As Thiel said, “Computers can find patterns that allude humans, but they don’t know how to compare patterns from different sources or how to interpret complex behaviors. Actionable insights can only come from a human analyst.”

According to McKinsey,

There will be a shortage of talent necessary for organizations to take advantage of big data. By 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.”

Data Scientists are not the solution

Hiring ‘sexy’ data scientists won’t fix the problem. According to Josh Attenberg and Foster Provost who teach the practical data science course at NYU Stern, “one of the complaints about the data scientists trained in computer science departments is that they’re “just technical”, understanding algorithms well, but lacking important skills in problem formulation, evaluation, and analysis generally. On the other hand, those trained in business schools tend to have underdeveloped technical skills.” Getting organizations up to speed on working with big data requires more than just hiring traditional data scientists or MBAs; instead, everyone needs to be able to work with data.

There have been positive changes though, especially in marketing. “The new job title of “growth hacker” is integrating itself into Silicon Valley’s culture, emphasizing that coding and technical chops are now an essential part of being a great marketer. The role of the VP of Marketing, long thought to be a non-technical role, is rapidly fading and in its place, a new breed of marketer/coder hybrids have emerged,” says Andrew Chen who popularized the term growth hacker.

Auren Hoffman, CEO of LiveRamp, shares on Quora: “The role of the chief marketing officer (CMO) is changing dramatically and is becoming “moneyballed” and very data oriented. Today’s Moneyballer CMO plans her marketing initiatives the way Billy Beane built the Oakland A’s. She leverages granular data on customer actions to expand beyond the traditional CMO role, influencing product strategy, customer service, and optimized sales pitches.”

Buzz words aside, a quick look at job postings for marketing positions at Facebook and Uber for example illustrates the transformation we’re going through. Uber’s growth marketers are expected to use tools like Tableau and understand languages like Python and SQL in addition to being able to process and analyze complex data sets. Where to find these folk? Graduates with majors in engineering, computer science, math, economics, or statistics. Meanwhile, traditional digital agencies are still stuck in 2005 and hiring communications majors for “performance marketing” roles (good luck with that).

Ashley Madison leak reveals if bigger is better…

To illustrate our point that a smaller data, people-focused, and lean approach can lead to useful insights, we’ve analyzed the leaked Ashley Madison data dump to answer the following four questions:

  1. Are Sagittarius men more likely to cheat?
  2. What are the most popular sexual kinks?
  3. Do sexual preferences change over time?
  4. What is the churn rate and LTV (lifetime value) of Ashley Madison users?

Tools and technologies used: MySQL, Python, PHP, Excel, Notepad++

Q1: Are Sagittarius men more likely to cheat?

“He’s the main cheater of the zodiac. He may espouse high morals, but these can loosen when he sees a pretty face or nice body. Tie your Saggi to the bedpost,” says one believer.

But is this really true? After running our SQL query, we get the results below. There’s obviously one outlier, Capricorn, caused by the default month and year settings in the (previous) Ashley Madison registration dropdown menu. After removing the Capricorn outlier, we see that contrary to popular belief, Saggies are not the biggest cheaters in the zodiac.

Q2: What are the most popular sexual kinks?

When signing up on Ashley Madison, users indicate their sexual preferences. We used a combination of SQL and Python to parse the preferences and map them out by gender.

Q3: Do sexual preferences change over time?

Yes, apparently they do. By mapping out sexual preferences by birth year, we found that the younger generation is more open to experimenting and one-night flings whereas older people enjoy cuddling and naughty talk.

Q4: What’s the churn rate and LTV (Lifetime Value) of Ashley Madison users?

As marketers, we’re naturally interested in measuring churn rate and LTV because these numbers can make or break a business. According to Andrew Chen, investors usually don’t fund dating startups because of the built-in (and typically high) churn rates as well as high customer acquisition costs (CAC) associated with the industry. Typical annual churn rates can go as high as 93%. Looking at the Ashley Madison data, we’re seeing churn rates of 80%.

Ashley Madison LTVs are roughly $400 USD. Their monthly cohorts show a jump in user quality starting October 2013. This could be due to new product initiatives such as pay for mobile access, business travel, pay to get noticed, and, ironically, pay to get your account fully removed.

A few parting words

Everyone can utilize big data as long as you emphasize people over platforms, processes, and politics and understand that small (data) can be beautiful if you know minimal SQL and/or Python. Don’t be afraid, learn the critical tools, and make big data your friend.