2958 Google Cloud Platform Testimonials

"We run our business entirely on software, so having developer-friendly SDKs and APIs that make technical sense was a big draw for us. Besides, we had no doubts that we’d be able to scale as a business on Google Cloud."

"Combining self-service touch screens with dynamic menu boards, the Commercial Chrome OS technology is already providing a huge return on investment. We're seeing a noticeable increase in brand awareness and a large boost in customer spend."

“With time, our on-premises infrastructure simply became too complex to handle. We also need to meet strict compliance standards, such as GDPR, which became increasingly difficult. We wanted to reduce complexity and simplify development, without compromising on security, which led us to Google Cloud.”

“We were encouraged by the positive responses from employees when we announced we were going Google. Working with Google and SADA Systems, in one weekend in November we took 23,000 users live, and a total of 28,000 users live globally within six months.”

“SADA suggested a phased in, launch and learn method, building on experience through waves of implementation across our global user base. Through this, we fine-tuned our training and change management to make each wave of go-live better each time. In addition to onsite training, we added online reference tools, webcasts, and training material in various languages. It was a positive experience that accelerated our G Suite migration.”

“The Google Cloud Professional Services team was instrumental in driving the success of some key projects for the GO-JEK data science team. Ultimately, thanks to Google Cloud Professional Services, we had a deeper understanding of Google technologies, greater collaboration, smarter designs, and a faster time to market.”

“At 17 Media, we extensively use containerization for fast development and testing. With Google Kubernetes Engine, our development cycle experienced an 80 percent increase in overall speed. Google Kubernetes Engine fits our requirements perfectly. Moreover, Google Cloud data processing products such as BigQuery and Cloud Dataflow enable us to better understand our user base, as well as monitor, analyze, and review the quality of our services.”

“We moved our services to Google Kubernetes Engine as it allows us to deploy containerized applications, monitor and control our environments from a dedicated console, and scale according to user demand.”

“We thought if we could be a member of the community that embraces the innovation captured in Google Cloud Platform products, we could continually improve our ability to seize opportunities and solve problems for our clients.”

“This innovation cycle allows us to run very hard at opportunities and have confidence that what we deliver with Google Cloud Platform will benefit us and our clients.”

“With our previous infrastructure, it took about three weeks to set up our Hadoop cluster, and we spent five hours a week on maintenance. It took only a few minutes to get up and running on Google Cloud Bigtable, and we don’t spend any time maintaining it. It just runs.”

“We create risk profiles of third-party sellers, so our customers know who is representing their products, how their products and IP are being represented, and their customer’s experience. When a customer has a poor experience from a counterfeit branded product, the brand may lose a customer, but the marketplace operator may not.”

“With the feedback classification model we’ve built, and by leveraging Google Compute Engine and Cloud Dataproc, we can perform an analysis of more than 160 million customer reviews of more than 2 million sellers in just under 4 hours, which is phenomenal.”

“The big challenge in our sector at the moment is personalization: tailoring a website to a visitor’s interests, in order to enhance conversion rates and customer satisfaction. To make the modifications as targeted and pertinent as possible, an enormous volume of data is required to develop sophisticated, automated algorithms.”

“Now, at every stage, we can manage and update the pipeline without interrupting the service. Cloud Dataflow does its job perfectly: it handles everything automatically so we can be sure of every cluster and really stand by the quality of our data.”