Thirteen years’ experience in e-commerce has given Teddy Chan, Chief Executive Officer and Chief Technology Officer, AfterShip, a deep understanding of the challenges of shipping and tracking packages to customers worldwide.

“The key problem many merchants face is customers asking ‘where is my order?’ and ‘when I will get the package?’” Chan says. “When I considered this issue, I came up with the idea of AfterShip.” Chan helped found AfterShip in 2011 to enable merchants to keep track of packages sent to customers via a web portal or an API. AfterShip also allows merchants to notify customers of anticipated delivery times.

“Using AfterShip, merchants can provide the same experience to buyers regardless of which couriers they use,” Chan says. “Merchants can also improve their customer engagement by including up-selling or marketing content with their delivery notifications.”

Hong Kong-headquartered AfterShip continues to grow quickly and now has a 40-person team. Thirty members of this team are based on the China special administrative region and 10 are based in India.

“Google Cloud Platform has a network of global datacentres with deep connectivity that enables us to put our infrastructure close to our customers. In addition, the ability to horizontally scale our global database using tools such as Google Cloud Spanner eliminates any limits on our geographic expansion.”

—Teddy Chan, Chief Executive Officer and Chief Technology Officer, AfterShip

By October 2017, the business was tracking about 30 million packages per month and had expanded its services to include label and rate calculation and self-service return. Revenue, package transaction numbers and team size have doubled every year for the past three years, while more than 300,000 merchants and 426 couriers are signed up to the service. Key customers include Wish, Etsy and Groupon.

Close to half AfterShip’s customers are based in the United States, about one third in Europe and the remainder are located in Asia. AfterShip had initially delivered its applications and services from an incumbent public cloud service. However, the company wanted to continue its growth trajectory while automating key infrastructure processes, implementing a continuous deployment model and controlling costs.

The business needed to achieve these objectives while maintaining a global presence and high-quality service. AfterShip started reviewing its options and decided to migrate to Google Cloud Platform (GCP). “Google Cloud Platform has a network of global datacentres with deep connectivity that enables us to place our infrastructure close to our customers,” Chan says.

“In addition, the ability to horizontally scale our global database using tools such as Google Cloud Spanner eliminates any limits to our geographic expansion. Furthermore, the managed services provided through GCP would allow us to focus on building better features for online merchants.” The reliability provided by GCP would also enable AfterShip to meet the stringent service level requirements of large digital marketplaces in the United States, Asia and elsewhere.

“Google Cloud Platform could manage the high volumes and enable us to deliver the service levels that would realise our ambition of becoming the number one tracking API platform in the world,” Chan says. “For example, with Google Cloud Platform, we can provide a 99.95% monthly uptime service level to our customers.” Finally, GCP provided managed solutions, including Google Kubernetes Engine powered by open source container orchestrator Kubernetes, that would enable AfterShip to automate processes such as scaling and enable its team to focus on developing applications.

AfterShip has moved its websites into GCP infrastructure in three datacentres around the world and anticipates completing the migration in Q4 2017. “Google provided a lot of assistance, particularly early in the project when we needed it,” Chan says. “They briefed us on several services we hadn’t known about that could replace the equivalents in the public cloud we were using previously.” The business then completed the migration using its own skilled team members. As well as Google Kubernetes Engine and Google Cloud Spanner, AfterShip is using Google BigQuery to store and analyse transaction information.

“Google Cloud Platform could manage the high volumes and enable us to deliver the service levels that would realise our ambition of becoming the number one tracking API platform in the world.”

—Teddy Chan, Chief Executive Officer and Chief Technology Officer, AfterShip

Deployment times down from one hour to two minutes

With deployment times falling from up to one hour in its previous cloud environment to about two minutes in GCP, AfterShip has been able to adopt a continuous deployment model. “This has improved our service levels,” Chan says. “If there are any issues we can fix them quickly, while we can iterate faster to create new features in response to customer requests or changes in the market. “This enables us to continue to lead our competitors.”

Targeting a 30 percent reduction in costs

AfterShip is now targeting a 30% reduction in costs by optimising its use of Docker containerisation technology on GCP.

“By using Docker with Kubernetes, we have been able to fine-tune our use of compute resources and better control our costs,” Chan says. “We’re extremely pleased with Google Cloud Platform as it really is built for engineers,” he adds. “In addition, its documentation is extremely clear, allowing us to troubleshoot or carry out activities on the platform ourselves. “We look forward to continuing to grow and extend our package tracking and associated services with Google Cloud Platform.”

Editor’s note: Meet Gareth Walkom, an entrepreneur dedicated to helping others with speech disorders.

Turning life experience into innovation

Did you know that 3% of Americans have a speech disorder, while 1% of the world’s population have a stutter? Just getting what they need in everyday interactions can be stressful, which intensifies when the stakes are raised during job interviews, presentations, public speaking, and other activities. As a result, some people with speech disorders may avoid conversations and relationships, and risk being denied jobs because of a difference in how they speak.

As a person who stutters, I know firsthand the ableism that people with a speech disorder can encounter in wanting to use their voice in a judgemental world: the frustration of sometimes not being able to say exactly what you want to say and therefore speaking less in speaking situations. And the educational and career opportunities are lost when doors remain closed to us, especially when employers advertise their jobs as requiring someone who speaks the language ‘fluently’.

While researchers still don’t definitively know what causes stuttering, emerging technologies are giving us new and promising pathways for improving the quality of life of people with speech disorders. 

That’s why after years of researching and testing potential therapeutic uses of virtual reality, and with the support of the Google for Startups Cloud Program, I founded withVR on International Stuttering Awareness Day (October 22) in 2020. The mission of withVR is to prepare people with speech disorders for real-life speaking situations by utilizing the power of virtual reality. 

Working through it

One of the difficulties in adapting to any disability is the opportunity to work through it in a safe and nonjudgmental environment. withVR provides a virtual space for individuals, in collaboration with their speech therapists, to practice real-world speaking scenarios in safe, controlled environments. 

Imagine being able to raise your hand in class and give your opinion without hesitation, ordering the meal you want rather than something that’s easier to say, or sit across the table from an avatar of an employer and explain why you are the right person for your dream job. Then further customize the speaking situation and its surroundings to challenge yourself and be ready for anything. That’s what withVR offers individuals and their speech therapists.

Making VR come to life

To bring the withVR vision to life, we are developing applications using the Unity game engine on Google Cloud with integrated Firebase services including authentication, web hosting, storage, and database. It’s a powerful combination that’s enabled us to build industrial-strength applications that we’ve rapidly deployed on a global basis. Today we are already collaborating with 80+ labs, clinics, and hospitals in more than 20 different countries worldwide.

These organizations help us to test and refine a virtual reality application to support people in achieving their speech goals and build comfort through immersive VR experiences using easily available viewers like Google Cardboard. 

The application works in conjunction with a web app through which speech therapists configure customized VR scenarios for their patients to use. As no real-life speaking situation is ever exactly the same, customization of VR scenarios is vital. They can construct different scenes, create and script avatars, and through the Google Text-to-Speech API can even choose from hundreds of different voices in a variety of languages. This gives them the flexibility to create many unique speaking situations for their clients no matter where they are in the world.

Progress from the practice sessions is presented through a dashboard that provides therapists with a tool to monitor their clients’ progress and provide feedback and encouragement.

No shortage of support

My founder’s journey has been supported by many passionate people. The Google for Startups Cloud Program has been instrumental in helping us come so far in the first year, and we’ve only scratched the surface of what’s possible. There are many capabilities in Firebase and Google Cloud that we have yet to explore, and through the startup program I now have a Google Mentor who can help guide that exploration. 

We also joined the 2Gether-International (2GI) Tech Cohort, which is supported by Google for Startups and is built for and run by entrepreneurs with disabilities. At the end of the 10-week cohort, we finished with a pitch competition, where I was one of six selected founders to pitch in just three minutes. I was very fortunate to win the Best Overall Pitch Award, gaining 10,000 USD in seed funding. This award not only highlights the potential of withVR, but also showcases that anyone can pitch their idea in a short amount of time no matter their difference. 

Working with 2GI also gave me the opportunity to collaborate and learn from other founders who have disabilities. It’s a safe space where I don’t have to explain my everyday challenges and can focus on the all-important task of advancing the vision of withVR, while seeing how others use technology in their domain. 

Building on a strong foundation

I’m amazed to look back and see what we’ve accomplished in just one year and humbled by the thousands of lives we’ve touched. Every day we receive valuable real-life feedback from people in the field—both clinicians and those with speech differences who benefit from VR therapy. That knowledge tells us that we are heading in the right direction and opening our eyes to new possibilities for where to take withVR. And inspiring us to keep moving ahead.

If you’d like to participate in testing or if you are speech therapist or researcher, please feel free to reach out to us. We’d love to show you how you can contribute to a world where anyone with a speech disorder can truly use their voice in any situation. If you’d like to take part, contact us at hello@withvr.app.

If you want to learn more about how Google Cloud can help your startup, visit our page here to get more information about our program, and sign up for our communications to get a look at our community activities, digital events, special offers, and more.

With access to more data than ever before, companies have never been better positioned to adopt precision marketing methods and target the right customers at the right time. Emarsys, a digital marketing platform, enables its clients to collect, analyze, and act on a wide variety of data. From websites to mobile apps to emails, Emarsys’ customers can handle data from all its digital channels on a single, easy-to-use platform. Emarsys also makes sure that customers receive the highest quality data possible, making for smarter decisions and better business practices.

“We were close to the limits of our internal data warehouse, scalability-wise. We didn’t want to get to the point where we’d have to delete data or cancel projects. In Google Cloud we saw a platform that could scale with our ambitions and be optimized for AI and real-time solutions.”

—Levente Otti, Head of Data, Emarsys

Since launching as an email solutions provider in 2000, Emarsys has grown into the world’s largest independent digital marketing platform, with more than 2,500 clients worldwide and reaching more than 1.4 billion people. By 2016, the company felt that its existing data warehouse platform was close to its limits, affecting not just day-to-day operations but also important strategic goals.

“We were close to the limits of our internal data warehouse, scalability-wise. We didn’t want to get to the point where we’d have to delete data or cancel projects,” says Levente Otti, Head of Data at Emarsys. “In Google Cloud, we saw a platform that could scale with our ambitions and be optimized for AI and real-time solutions.”

Minimal maintenance, unlimited scale with Google Cloud

Digital marketing is a highly competitive environment. Emarsys works alongside big players with a huge market share on the one hand and smaller, specialist companies on the other. It has thrived by successfully combining the all-inclusive offerings of the former with the agility of the latter, constantly looking for ways to innovate and improve. In recent years, the company had started to feel that the ability to handle large quantities of data was no longer enough. The next challenge was speed. “We truly believe that in the future, everything will be done in real time, including data processing, analytics, and AI predictive models,” Levente says.

At the start of 2016, Emarsys’ existing data warehouse was a software-as-a-service solution running on-premises, which required hardware and software maintenance in order to keep up with the company’s growing appetite for data-heavy use cases such as prediction and analytics. The existing platform had proven its worth processing large amounts of data in batches, but its real-time capabilities were limited. Moreover, Emarsys had begun to experiment with AI technology, but found that its data warehouse couldn’t scale to accommodate some of the more resource-intensive processes, such as training the predictive models. The company decided that it needed a new, cloud-based data platform.

After evaluating some of the leading cloud providers, Emarsys chose Google Cloud for its mature AI capabilities and its ease of use. “With the other solutions, we still had to rent virtual machines and hardware and be responsible for maintenance. At the time, Google Cloud was the only provider that could take that management overhead away from us, while keeping customers accounted for on every query level,” Levente says.

To implement its new data platform, Emarsys teamed up with Google Cloud Partner Aliz. Over a series of meetings, workshops, and architecture reviews, Aliz helped Emarsys navigate the Google Cloud ecosystem to find the right products for the solution it was looking for. “Aliz really helped us set off in the right direction,” explains Levente.

With Google BigQuery, we can run queries which process terabytes of data, in seconds. We can also develop our own user-defined functions, incorporating Bayesian statistics into our predictive algorithms. That means we can take into account historical data, resulting in much more accurate predictions in a scalable way within seconds.”

—Levente Otti, Head of Data, Emarsys

Emarsys’ new data platform would actually be two: one platform for batch processing data and one for real-time analysis and interactions. Firstly, a proprietary publishing component gathered all the data points from Emarsys’ various channels including the website, mobile, emails, and custom events. With Cloud Pub/Sub and Cloud Dataflow, Emarsys transported and processed the data into BigQuery, which allows for further work and reviews that take into account errors or delayed events. After this, the data was exported to the main batch processing platform, which ran on BigQuery. For the real-time analytics, Emarsys used Cloud Bigtable to access data and Cloud Dataflow to pipeline it into the real-time platform, which could communicate with AI components or interaction components via an API to deliver real-time interactions with customers.

On top of the overall data infrastructure, Emarsys built a new AI platform with Google Cloud components. Training the predictive models had been an issue in the past due to the large number of resources required, so Emarsys chose to use Google Kubernetes Engine clusters, which can scale up and down on demand, without the need for hardware configuration or management. The trained models were held securely in Cloud Storage. From here, they were integrated with BigQuery for power and flexibility, allowing Emarsys to improve not just the speed of its AI predictions but also the quality.

“With Google BigQuery, we can run queries which process terabytes of data, in seconds,” shares Levente. “We can also develop our own user-defined functions incorporating Bayesian statistics into our predictive algorithms. That means we can take into account historical data, resulting in much more accurate predictions in a scalable way within seconds.”

Real-time insight, long-term satisfaction

Google Cloud enabled Emarsys to build a scalable data and AI platform that delivers powerful, actionable insights in real time. According to Levente, the company wanted to spend less time managing overload and more time considering how it should handle data. An immediate result of the new platform has been that data is now available in a scalable way, without hardware additions and management.

“With Google Cloud, we’ve been able to build a truly real-time data platform. The norm used to be daily batch processing of data. Now, if an event happens, marketing actions can be executed within seconds, and customers can react immediately. That makes us very competitive in our market.”

—Levente Otti, Head of Data, Emarsys

The clear and innovative pricing schemes of Google Cloud have also brought a new level of accountability to Emarsys’ costs in a way that wasn’t possible with its on-premises infrastructure. “Now that we only pay for what we use, we can assign costs to specific customers or queries, which has a huge impact on our pricing and product development strategies,” says Levente.

Thanks to the power of BigQuery and the scale at which it can handle data, Emarsys can now apply its analytics and AI tools to their full potential. “It’s very important to enable our clients to create the best possible experience for customers,” says Levente. At the same time, the company has cut its AI platform costs by 70% with Kubernetes while increasing scalability compared to the previous solution. The whole data platform was built to be scalable, and its first big test came during the retail peak of Black Friday, when it comfortably handled 250,000 events per second. “Perhaps the biggest impact on the business came with the real-time nature of the new platform,” says Levente.

“With Google Cloud, we’ve been able to build a truly real-time data platform,” he explains. “The norm used to be daily batch processing of data. Now, if an event happens, marketing actions can be executed within seconds, and customers can react immediately. That makes us very competitive in our market.”

Since implementing the new platform, Emarsys has continued to innovate with it and is about to release a new Real-Time Decision Framework, which will provide customers with even more real-time products and tools. The company continues to work with Aliz and Google Cloud, exploring other products such as Google BigQuery ML and TensorFlow to improve its AI processes. “We had a problem that we wanted to tackle now, and for us, Google Cloud was the best way of doing that,” says Levente. “But it was also about looking ahead. We felt that Google Cloud offered us the best way of future-proofing our platform.”