Expectations for both consumer and commercial products have changed. Consumers want products that evolve with their needs, adapt to their preferences, and stay up-to-date over time. Manufacturers, in turn, need to create products that provide engaging customer experiences not only to better compete in the marketplace, but also to provide new monetization opportunities. 

However, embedding intelligence into new and existing products is challenging. Updating hardware is costly, and existing connected products do not have the capability to add new features. Furthermore, manufacturers do not have sufficient customer insights due to product telemetry and customer data silos, and may lack the AI expertise to quickly develop and deploy these features. 

That’s why today we’re launching Intelligent Products Essentials, a solution that allows manufacturers to rapidly deliver products that adapt to their owners, update features over-the-air using AI at the edge, and provide customer insights using analytics in the cloud. The solution is designed to assist manufacturers in their product development journeys—whether developing a new product or enhancing existing ones. 

With Intelligent Products Essentials, manufacturers can:

• Personalize customer experiences: Provide a compelling ownership experience that evolves over the lifetime of the product. For example, a chatbot that contextualizes responses based on product status and customer profile.
• Manage and update products over-the-air: Deploy updates to products in the field,  gather performance insights and evolve capabilities over time with monetization opportunities.
• Predict parts and service issues: Detect operating thresholds, anomalies and predict failures to proactively recommend service using AI, reducing warranty claims, decreasing parts shortages and increasing customer satisfaction.

In order to help manufacturers quickly deploy these use cases and many more, Intelligent Products Essentials provides the following:

• Edge connections: Connect and ingest raw or time-series product telemetry from various device platforms utilizing IoT Core or Pub/Sub and enable deployment and management of firmware over-the-air and machine learning models with Vertex AI at the edge.
• Ownership App Template: Easily build connected product companion apps that work on smartphones, tablets, and computers. Use a pre-built API and accompanying sample app that can incorporate product or device registration, identity management, and provide application behavior analytics using Firebase.
• Product fleet management: Manage, update and analyze fleets of connected products via APIs, Google Kubernetes Engine, and Looker.
• AI services: Create new features or capabilities for your products using AI and machine learning products such as DialogFlow, Vision AI, AutoML, all from Vertex AI.

Enterprise data integration: Integrate data sources such as Enterprise Asset Management (EAM), Enterprise Resource Planning (ERP), Customer Relationship Management (CRM) systems and others using Dataflow and BigQuery.

Intelligent Products Essentials helps manufacturers build new features across consumer, industrial, enterprise, and transportation products. Manufacturers can implement the solution in-house, or work with one of our certified solution integration partners like Quantifi and Softserve. 

“The focus on intelligent products that Google Cloud is deploying provides a digital option for manufacturers and users. At its heart, systems like Intelligent Product Essentials are all about decision making. IDC sees faster and more effective decision-making as the fundamental reason for the drive to digitize products and processes. It’s how you can make faster and more effective decisions to meet heightened customer expectations, generate faster cash flow, and better revenue realization,” said Kevin Prouty, Group Vice President at IDC. “Digital offerings like Google’s Intelligent Product Essentials potentially go the last mile with the ability to connect the digital thread all the way through to the final user.”

Customers adopting Intelligent Products Essentials

GE Appliances, a Haier company, are enhancing their appliances using new AI-powered intelligent features to enable:

• Intelligent cooking: Help cook the perfect meal to personal preferences, regardless of your expertise and abilities in the kitchen.
• Frictionless service: Build smart appliances that know when they need maintenance and make it simple to take action or schedule services.
• Integrated digital lifestyle: Make appliances useful at every step of the way by integrating them with digital lifestyle services – for example, automating appliance behaviors according to customer calendars, such as oven preheating or scheduling the dishwasher to run in the late evening.

“Intelligent Products Essentials enhances our smart appliances ecosystem, offering richer consumer habit insights. This enables us to develop and offer new features and experiences to integrate with their digital lifestyle.“ —Shawn Stover, Vice-president Smart Home Solutions at GE Appliances.https://www.youtube.com/embed/zaWAJN8aKOw?enablejsapi=1&

Serial 1, Powered by Harley-Davidson, is using Intelligent Product Essentials to manage and update its next generation eBicycles, and personalize its customers’ digital ownership experiences. 

“At Serial 1, we are dedicated to creating the easiest and most intuitive way to experience the fun, freedom, and adventure of riding a pedal-assist electric bicycle. Connectivity is a key component of delivering that mission, and working together to integrate Intelligent Product Essentials into our eBicycles will ensure that our customers enjoy the best possible user experience.”— Jason Huntsman, President, Serial 1. 

Magic Leap, an augmented reality pioneer with industry-leading hardware and software, is building field service solutions with Intelligent Products Essentials with the goal of connecting manufacturers, dealers, and customers to more proactive and intelligent service.

“We look forward to using Intelligent Products Essentials to enable us to rapidly integrate manufacturers’ product data with dealer service partners into our field service solution. We’re excited to partner with Google Cloud as we continue to push the boundaries of physical interaction with the digital world.” — Walter Delph, Chief Business Officer, Magic Leap

Intelligent Product Essentials is available today. To learn more, visit our website.

Demand for spoken audio content such as podcasts remains robust despite the proliferation of video services and other entertainment options for consumers. Shibin Li, Co-founder of Castbox, credits growth of the global podcast platform to the following: speed and availability, market-leading features, the proliferation of smart devices to deliver audio content, and activities — such as driving and working around the house — that make consuming video difficult.

Founded in 2016 and headquartered in Beijing, China, Castbox enables users to locate, access, and create spoken audio content. Available on iOS and Android, Castbox supports 50 million podcasts, on-demand radio programs, and audiobooks in 70 languages from 175 countries. The platform hosts about 2 million users per day and is the largest podcast platform on Android.

Castbox includes a range of features that build on its core service to provide a high-quality user experience. These features include curated podcast recommendations and in-audio search.

A combination of services

At its inception, Castbox relied on a combination of a multinational cloud services, as well as Google Cloud Platform (GCP) services, including the Google BigQuery analytics data warehouse and Cloud APIs to provide programmatic interfaces with Google Cloud services, and a range of services from the Google mobile development platform Firebase.

However, as Castbox matured and its user base expanded, the business increased its reliance on Google Cloud Platform and Firebase.

“We needed to access stable cloud services as we could not tolerate long periods of downtime that would compromise the user experience,” says Li. “Furthermore, we had to support up to 50,000 concurrent connections, and potentially more in future, without disruption.”

“Based on our analysis of the data in Google BigQuery, we can determine what type of content users are listening to, how long they like to listen to it, and when they like to listen to it. This allows us to recommend similar podcasts to each user based on the preferences he or she expressed, encouraging activity on and return visits to our platform.”

—Shibin Li, Co-Founder, Castbox

Competitive differentiation

Castbox also found machine learning-powered Google Cloud Platform APIs could help deliver features, such as in-audio search, that differentiate the podcast platform from its competitors. In addition, Firebase SDKs and Firebase A/B Testing would enable Castbox to create and analyze new applications, as well as make adjustments based on user feedback. Firebase Realtime Database would allow the business to support tens of thousands of concurrent user connections.

The diligence of the Google Cloud team in advising Li and her team about forthcoming products and services also swayed Castbox towards Google technologies. The business gained the opportunity with Google to join several programs that offered early access to Google innovations.

Signature in-audio search service

Castbox now uses Google Cloud Platform services in the Tokyo, Japan, and U.S. East regions. Cloud Speech-to-Text API plays a key role in delivering Castbox’s signature in-audio search service. This service enables users to search transcriptions of audio content on the platform for words or phrases. The search results incorporate the title of the podcast and the search term in context (for example, within the sentence or sentence excerpt in which it appears). Each use of the word or phrase is time-stamped so it can easily be found. The API enables Castbox developers to apply neural network algorithms to achieve audio-to-text conversion accuracy rates of greater than 96%, while search queries typically experience latency of just 50 milliseconds.

In addition, the latency of comparison data, converting audio to text, is only about 250 milliseconds, contributing to the processing of about 12 minutes worth of audio to text in just 10 minutes. “We can process about 20 hours of audio files in one day,” Li says. “This enables us to transcribe and index all the new episodes of a podcast in that period.”

50,000 concurrent connections

With Firebase Realtime Database, Castbox now supports up to 50,000 concurrent connections to its platform with an average latency per connection of just 10 milliseconds. “Firebase Realtime Database also allows us to continue operating in offline mode, which is extremely helpful if we experience any network disruptions,” Li explains. “When we come back online again, any data is simply synchronized with the database.”

Google BigQuery and the analytics capabilities of Firebase SDKs also enable Castbox to monitor and analyze user behaviors. “Based on our analysis of the data in Google BigQuery, we can determine what type of content users are listening to, how long they like to listen to it, and when they like to listen to it,” Li explains. “This allows us to recommend similar podcasts to each user based on the preferences he or she expressed, encouraging activity on and return visits to our platform.”

“Given our queries may span up to 40 days of data, we may be analyzing up to 1,200 GB at one time. We have no problem doing this with Google BigQuery.”

—Shibin Li, Co-Founder, Castbox

Castbox also uses its analyses of Google BigQuery data to amend banners and summaries on its platform to encourage users to listen to additional content. Furthermore, the service is prepared to make surprise recommendations of content to users based on the preferences and reactions of users with similar tastes.

“We analyze a pool of data growing at up to 30 GB per day,” Li explains. “Given our queries may span up to 40 days of data, we may be analyzing up to 1,200 GB at one time. We have no problem doing this with Google BigQuery.” These analyses also support Castbox’s decision to start creating original content, such as finance and economic news, for its platform.

Checking weekly changes

Castbox does not rely only on analyzing user data to deliver a high-quality experience. The business aggregates user feedback from emails and Google Play reviews to make weekly changes to its platform. It then uses Firebase A/B Testing to check whether these changes are met with a positive user response.

“We are extremely pleased with Google Cloud Platform and Firebase. We have been able to differentiate ourselves from our competitors and provide an attractive option for users at a time when content and entertainment options are exploding. We have a great opportunity with Google to continue to improve the value of our offering to users and build engagement and loyalty.”

—Shibin Li, Co-Founder, Castbox

Castbox’s positive experiences with Google Cloud Platform are encouraging the business to grow its use of the product. “We are trying to move some more services to Google Cloud Platform because it is very stable and scalable,” Li says. The business is keen to explore the capabilities of Cloud Pub/Sub to provide low latency messaging between applications, Cloud Spanner to deliver a distributed relational database service, and Cloud Dataflow to transform and enrich data in stream and batch modes.

“We are extremely pleased with Google Cloud Platform and Firebase,” Li concludes. “We have been able to differentiate ourselves from our competitors and provide an attractive option for users at a time when content and entertainment options are exploding. We have a great opportunity with Google to continue to improve the value of our offering to users and build engagement and loyalty.”

The music industry is rapidly changing. Only 20 years ago, the availability of music and the infrastructure that was required to make an album a sales success were incredibly complex and expensive. With the decline of physical sales and a fundamental shift to digital, music streaming now accounts for more than half of all sales globally.

At the same time, technology has democratized music-making; in many ways, it has made the musical landscape more diverse. Artists can upload their music with the click of a button. But while it’s easier for creators to share their songs with audiences, getting paid has become more fragmented.

Although music is booming, people no longer buy it outright. Instead, listeners download music digitally or subscribe to streaming services to have their libraries with them at all times. To monetize digital content effectively, artists need to know when, where, and how often their songs are played on each service. To help them navigate this complicated royalties landscape and maximize their profits, Berlin-based international music company BMG provides customized, transparent, and fair services to songwriters and artists.

With publishing and recording divisions under one roof, the subsidiary of international media giant Bertelsmann works with both emerging artists and established stars, including John Legend, Kylie Minogue, Mick Jagger, and Keith Richards. With the MyBMG web and mobile application, clients can view and analyze their royalty details in real time and collect payment. When a new record is released, BMG uses data to maximize its impact and revenue for its creators.

“We make sure that everyone who uses our clients’ music knows who needs to be paid the associated royalties, then we collect these royalties and share them out quickly and transparently,” explains Sebastian Hentzschel, Chief Information Officer at BMG. “When our artists release new music, we make sure that it’s marketed and promoted effectively around the world.”

“We needed a scalable solution for our royalty workloads that was intuitive for our developers. We also wanted a partner, not a client-vendor relationship. With autoscaling via BigQuery, excellent customer support, and a clean and simple user interface, Google Cloud ticks every box for us.”

—Gaurav Mittal, Vice President Group Technology, BMG

Getting up to speed with a new way of paying artists

In this digital world, artists aren’t just paid every time a fan buys an album—they’re paid a small amount, or royalty, for each song downloaded or streamed by a listener. So, when the industry shifted to digital, the volume of data that BMG needed to handle grew exponentially. “One CD sale is equivalent to about 1,500 streamed songs or plays,” says Gaurav Mittal, Vice President Group Technology at BMG. “That means IT departments have to process 1,500 times the amount of data to calculate payments for artists, and this makes scalable micropayment processing very important.”

Until 2019, BMG’s infrastructure was entirely hosted on-premises. Hardware limitations made it challenging to scale on-demand, making it harder to handle the data peaks that royalty processing can bring. “With our on-premises infrastructure, we were going to hit a ceiling in a few years,” says Gaurav. “We still managed to process royalty payments for our clients, but it was increasingly time consuming and expensive. To keep focusing on our clients, rather than our infrastructure, we decided to migrate to Google Cloud.”

From the outset, Gaurav and his team had a clear vision for the partnership: “Most importantly, we needed a scalable solution for our royalty workloads that was intuitive for our developers. We also wanted a partner, not a client-vendor relationship,” he says. “With autoscaling via BigQuery, excellent customer support, and a clean and simple user interface, Google Cloud ticks every box for us.”

Keeping artists happy with business-as-usual payouts during migration

To move applications to the cloud while keeping payment cycles on track for its artists, BMG teamed up with Google Cloud partner Rackspace Technology. “We selected Rackspace Technology because it combines strong technical muscle and a global footprint, with the customer service of a local boutique firm,“ shares Gaurav.

BMG’s own technology team put together the outline for the Google Cloud architecture, which they passed on to Rackspace Technology for optimizations and the ultimate stamp of approval. Whenever Gaurav and his developers needed support, Rackspace Technology was ready to go. “So far, we’ve migrated 17 applications successfully, and Rackspace Technology has been 100% spot-on with each suggestion,” says Gaurav. “I can’t recall a single flaw in a Rackspace Technology-approved architecture, and that really says something.”

When BMG began its migration in August 2019, the team developed an ambitious two-year plan. Only 14 months later, however, the project is more than 75% complete. Among the solutions that BMG is using today are Cloud Storage to securely store 130 TB of data, and Cloud SQL as its standard database technology. The web applications run on Compute Engine, App Engine, and Google Kubernetes Engine.

“After successfully moving a few applications, it was clear that with the strong teamwork of BMG and Rackspace Technology, together with the ease of use of Google Cloud, we could speed up the project without sacrificing quality,” says Gaurav. “We’re set to complete our migration six months before schedule, helping us to quickly move out of our hybrid environment.”

“Our income-tracking teams are very savvy on the data, and the simplicity of Google Cloud empowers them to self-serve analytics, rather than wait for IT. Our teams are much more productive.”

—Gaurav Mittal, Vice President Group Technology at BMG

Royalty reporting and processing with BigQuery and Dataproc

So far, all of BMG’s critical workloads are up and running on Google Cloud. Royalty calculations, for example, which require incredible processing power and the collection of many micropayments to ensure full and timely payout, run entirely on Dataproc with output stored on BigQuery for downstream integration and reporting.

Enabling more harmonious workflows through self-serve analytics

As the new beating heart of BMG’s royalty reporting, BigQuery changed the rhythm of collaboration company-wide. In the past, income tracking teams had to contact IT departments if they needed deeper data insights for their work. By integrating Data Catalog with BigQuery, BMG has made the data more accessible to all teams. This helps them detect missing income and new revenue streams independently, maximizing profits for artists.

“Our income-tracking teams are very savvy on the data, and the simplicity of Google Cloud empowers them to self-serve analytics, rather than wait for IT,” says Gaurav. “Our teams are much more productive.”

“Google Cloud enables us to be more client focused and deliver better features faster. We believe it’s just the beginning. We offer rights and royalty services for music publishing, recorded music, neighboring rights, and books. Without scalability limitations, it’s absolutely conceivable to offer our platform as a service to other companies or industries, such as gaming. Google Cloud has opened a world of possibilities.”

—Sebastian Hentzschel, Chief Information Officer, BMG

With a leaner IT environment, BMG can focus its effort on the needs of its clients. Beyond improvements in royalty processing, it can concentrate on app development, releasing new features and enhancements more frequently. By hosting applications on Google Kubernetes Engine, App Engine, and Compute Engine, BMG has built a CI/CD pipeline with automated deployments and testing to significantly speed up workflows.

“In our old system, it could take several weeks to set up an environment,” says Gaurav. “With Google Kubernetes Engine, any of our developers can complete the process in a few clicks. Having that autonomy makes our developers more motivated and self-driven.”

“Google Cloud enables us to be more client focused and deliver better features faster,” adds Sebastian. “We believe it’s just the beginning. We offer rights and royalty services for music publishing, recorded music, neighboring rights, and books. Without scalability limitations, it’s absolutely conceivable to offer our platform as a service to other companies or industries, such as gaming. Google Cloud has opened a world of possibilities.”

With the migration almost complete, BMG is looking forward to its next technology project. It plans to leverage AutoML to further scale and automate royalty tracking with machine learning. On the marketing side, advanced analytics will help BMG determine the effectiveness of promotional campaigns around the world, further increasing profits for artists. By connecting Google Data Studio to BigQuery, BMG will increase the quality of its analyses, helping musicians better understand the reach of their music around the world.

In the end, Gaurav shares, helping musicians is what it all comes down to. “We’re a new kind of music company because we build our services around our artist, songwriter, and publisher clients, not the other way around,” he says. “Google Cloud is helping us maintain strong relationships with our clients, and that’s music to our ears.”