Tackling Real-Time Bidding Challenges: Arpeely’s Fresh Approach with Google Cloud
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At Arpeely, we’ve developed some of the world’s most advanced advertising technology. Our machine learning (ML) media acquisition platform and “win-win” business model enables customers to bring highly intentful users to their offerings with precision, peace of mind and minimal overhead.
Real-time bidding is a dynamic and intricate process that involves buying and selling ad impressions in milliseconds. Each time a user opens an app or website, advertisers or ad-tech companies acting on behalf of advertisers have milliseconds to bid on ad spaces in real-time auctions, and the highest bidder wins the opportunity to display their ad. This is where Arpeely comes in, leveraging advanced algorithms, innovative UX and funnels to optimize the bidding process and maximize performance for advertisers.
At Arpeely, we use various signals often not used by traditional competitors to outperform the market and zero-down on high-intent and soon-to-be loyal users. For example, in advertising a mobile app, we predict, based on real-time conditions and user context, the user’s likelihood to make an in-app purchase many weeks into the future.
As for the ads themselves, gone are the days of simple banners; today’s ads are “mini products” that captivate and engage users. We employ a wide range of ad formats that go beyond industry standards. Our ads can be immersive videos, compelling messages, interactive experiences like mini-games or mini-apps, or even a multi-step mixture of all of the above. By integrating logic and interactivity, Arpeely enables users to engage with the ad content seamlessly and gauge user intent without leaving their main activity.
Our business model dictates that we don’t get paid if our advertiser doesn’t get paid. We like to say that our algorithms, like water, can trickle into hidden market opportunities missed by the rest of the industry that uses less granular tools. These and other capabilities make Arpeely a strategic partner in the challenging space of media and user acquisition.
Innovation at the edges of data science and engineering
Today, we handle millions of impressions per second and over a billion ML predictions daily. We are directly connected to seven of the world’s largest real-time bidding exchanges, including Google AdX. We also work very closely with our clients, ranging from prominent startups to companies in the S&P Top 20.
Daily, we tackle complex engineering and data challenges on multiple fronts. On the engineering side, we ensure that every real-time auction receives a lightning-fast response within a strict 150ms timeframe. On the data side, we fire multiple ML predictions per auction and ingest TBs of data daily. On the user-serving front, we serve A/B-tested assets across a long tail of geos and devices, with even the slightest fluctuations in load speeds affecting business dramatically.
Right from the start, we knew we couldn’t do it alone when it came to building our technology stack. When you look at available platforms, it’s clear Google Cloud has a robust architecture that is easy to manage, use and scale, especially for our use cases. They also have reliability and feature completeness which are critical in our line of business.
Under the hood
Building upon Google Kubernetes Engine (GKE), we run multiple services that handle our main bidding flows. We utilize Golang for services that run at a large scale and Python for when we prioritize development speed, community and readability. All of these can reach an immensely high scale, which is managed and monitored automatically in GKE. Communication between these services and our Redis (our Google Cloud partner) cluster happens in sub-millisecond latency over Google Cloud’s strong network infrastructure and enables us to run complex real-time logic for every impression.
Once we have tackled the actual bidding, we are left with the challenge of streaming our data into BigQuery for analytics and model training. We utilize a mix of Cloud Pub/Sub, Memorystore and Cloud Storage to create a mechanism capable of ingesting many TBs per day in near real-time without compromising on cost. Real-time data is critical for a company like Arpeely to test and reiterate at a fast pace.
BigQuery is our data warehouse for operational analysis and is an essential part of our business. We use it both as a warehouse, for large-scale computations and in an operational capacity that closes the loop between production, data, and ML retraining. A team of two or three people can manage petabytes at scale with minimal maintenance.
On top of these, we’ve built a state-of-the-art in-house model pipeline suited specifically for ad-tech industry purposes. It allows us to effectively deploy complex solutions — on-the-fly calibration, flexible conversion steps, sampling of heavily imbalanced data sets, adjusting weights, and A/B-tested model deployment and more.
Google Cloud also offers us an entry point for several very useful built-in products that have become deeply embedded in our daily stack and routine. Among them are Operations Suite (formerly Stackdriver), Cloud Profiler, Cloud Storage, Cloud CDN, Cloud SQL, Memorystore, Cloud Scheduler, Error Reporting, and more.
In addition to all the technology, there’s also a human touch. Google’s skilled Customer Success team possesses a unique blend of technical expertise and business acumen, acting as strategic advertisers and opening doors we did not know existed.
Opening the door to the future of advertising
Standardizing on Google Cloud enables us to focus our resources on innovation and growth. Instead of having to research business solutions and invest time integrating disparate technologies, we can tap into a wide range of Google Cloud tools as needed. Thus, it is crucial that we set up a good technological foundation and prepare for future growth of the business.
Google Cloud enables us to focus our resources on innovation rather than our infrastructure. This means we can put more effort into finding ways to match clients with high-value customers and grow their revenues. Even though online advertising has been around for over 20 years and pioneered by Google itself, Google Cloud gives us the impetus to disrupt the market and deliver greater levels of value to our customers today and in the future.
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.
Check out the Redis listing on Google Cloud Marketplace. Please give it a try and let us know what you think!
Google’s Intelligent Products Essentials Assist Manufacturers in Product Development Journey
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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.
Google Cloud Featured at TechCrunch Disrupt 2021
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Startups need to move quickly and focus their limited resources on areas where they can differentiate. If infrastructure isn’t your differentiator, don’t put a lot of energy into your infrastructure when someone else can do it for you. What’s more, time-to-market matters to startups more now than ever. Successful early stage companies know this, and leverage existing tools, libraries, frameworks and innovations whenever possible.
Next week Google Cloud will be featured at TechCrunch Disrupt, the iconic annual event where “founders and investors shaping the future of disruptive technology” come together to share stories, network, and learn from each other. Google Cloud will host a session and Google Cloud engineers will be available in a virtual booth to answer startup questions.
The session, “Demo Derby – How startups are disrupting the status quo with innovative data analytics, AI and modern app development” will be a fun, fast-paced set of presentations showing short demos of startups and startup projects built with Google Cloud.
Demo Derby Presenters
- Andrea Le Vot, Chief Data Protection Officer with startup BlueZoo will deliver a demo showing how they are revolutionizing the property insurance industry with AI and Cloud – and doing so while actually protecting people’s privacy.
- Dale Markowitz and Zack Akil, Applied AI Engineers, will show how easy it is to use AI for everything from video search to editing to automated translation.
- Vidya Nagarajan, Group Product Manager from Google Cloud will deliver a fast paced demo that shows how startups can drive developer productivity with serverless innovations.
“Disrupt is iconic for its engagement with founders, investors, and the broad community of early stage companies,” said Andrea Le Vot, Chief Data Protection Officer at BlueZoo. “We are thrilled to share our insights with others in our community, and to show how we have partnered with Google Cloud to innovate faster than most of the larger, well funded insurance companies in our market.”
The series of snippet sized demos will be followed by a roundtable discussion with the demo developers focused on lessons learned, best practices, how to reduce time-to-market, and how to focus on where you can most effectively differentiate.
The session will air on Day One of the event: Tuesday September 21, 2021 at 1pm PT and will be available on demand after the event for all Disrupt attendees.
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Predicting Treasury Settlement Failures with ML
BNY Mellon’s Government Securities Services (GSS) business is the sole provider of treasury settlement services in the United States of America. Given its unique market position, GSS is exploring how to help clients improve their forecasting of $70+ billion in daily settlement fails leveraging Google Cloud.
Sarthak Pattanaik, Chief Information Officer, Clearance and Collateral Technology, The Bank of New York Mellon and Victor O’Laughlen, Digital Business Leader, Clearance and Collateral, The Bank of New York Mellon, share how they utilized Google Cloud AI solutions to predict treasury settlement failures.
They take us through the business process, the steps they took to set up their AI solution, and what they have learnt on their journey—not just from a technical standpoint but from a cultural one as well.
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Chronicle Security Analytics: Key to Address Security Data Overload
Google Cloud’s Chronicle is a security analytics platform built for modern use cases to combat modern threats. In today’s world, enterprises have undergone significant changes in all aspects, and must adapt to their security needs to counter threats and attacks. Watch the video to learn Google Cloud’s initiative to help businesses improve their security by 10x to catch up with the way the world is changing and how Chronicle Security Analytics is poised to help address data security challenges.
Anthos for Manufacturing: Tackle DevOps Complexities and Drive Digital Transformation
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