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How Google Cloud is Fortifying the Social Safety Net
The COVID-19 crisis is triggering both immediate and longer-term challenges for state and local governments.
In this video, Denise Winkler, Strategic Business Executive, Google Cloud and Jennifer Ricker, Assistant Secretary – Illinois Department of Innovation & Technology (DoIT), discuss a number of challenges and solutions around the pandemic.
First, they outline the programs that constitute the social safety net and the impact that COVID-19 has had on the social safety net and citizens. Then they share the Google Cloud solutions that have been mobilized to assist these agencies.
Ricker will also share how Google Cloud Contact Center AI supported the Illinois Department of Employment Security.
Finally, they talk about how Google Analytics can help communities open and recover.
Learn how Google Cloud is enabling public officials to gear up to meet unprecedented demand for unemployment and social services programs, launch expanded digital services, and more.
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8:00 Minutes
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AutoML Vision: Among the Fastest and Easiest Way to Adopt AI for Your Enterprise
What’s among the largest impediment to the adoption of AI within enterprises? Not enough access to skills. According to 80 percent of business respondents to an EY survey, the top challenge to an enterprise AI program is the lack of requisite talent.
What companies need today is a way to facilitate—and therefore accelerate—the adoption of AI. There are a few challenges that need to be overcome. Two of the most critical challenges include the data science skills required to create customized models, and the right IT skills to power the underlying infrastructure.
Both of these skills are hard and expensive to come by.
There are ways around this problem. Google Cloud’s recently launched AutoML Vision is one such solution. It significantly lowers the amount of IT and data science heavy lifting required to start customized machine learning applications around computer vision.
That’s possibly one of the reasons why Google is the most popular cloud provider for data scientists, according to the State of Data Science.
In this short and simple-to-understand video, Yufeng Guo, Developer and Machine Learning Advocate at Google Cloud, walks you through a real use case of AutoML Vision.

Le Figaro Uses Google Firebase to Personalize Experiences and Generates 3X Revenue Results
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1:45 Minutes
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Le Figaro, established in 1826, is France’s oldest and largest daily morning newspaper. The company’s mission is to provide timely, digestible and engaging news to their readers. As one of the first in the industry to offer digital content, Le Figaro engages their subscribers across 11 Android, iOS and web apps that cover news, sports, lifestyle and games. Le Figaro has about 22M monthly active users on their mobile and web apps and 120K paid digital subscribers.
The Challenge
In a saturated news app market, Le Figaro was looking to increase paying customers and to retain existing paid subscribers. To do this, Le Figaro’s development team needed to engage readers with personalized content at the right price point, but how could they pull it off with limited time and resources?
The Solution
Le Figaro used a number of Firebase products to retain existing users and increase paid subscriptions. They sent targeted notifications through Firebase Cloud Messaging reminding customers to follow topics and journalists they found interesting. This helped reduce churn by keeping subscribers engaged in content they valued. They also tested different subscription amounts using Firebase A/B testing, which helped Le Figaro identify the price points that led to the highest number of conversions among both Android and iOS users.
“Using Firebase has completely transformed Le Figaro’s digital business by making it easy to rapidly innovate and personalize content for our readers. With Firebase we have seen continuous increases in retention, downloads and screen time in our apps!”
Valentin Paquot, Mobile CTO, Le Figaro
Le Figaro found their biggest increase in paid subscriptions came from embedding real time interactive infographics into their mobile and web app articles. When a user added information into the infographic, it triggered a Cloud Function that accessed data stored in Cloud Firestore and returned a personalized infographic to the user in real time.
For example, in the article “Are you rich?” readers could input their income into the infographic and compare it against different income groups in Paris instantaneously. The infographics was behind a paywall and users had to subscribe to gain access.
According to Le Figaro, this infographic saw 3X the rate of paid subscription sign-ups compared to their other infographics. The team built this interactive infographic system in 3 days instead of their average time of 2-3 weeks using a traditional backend service. Using Cloud Functions and Cloud Firestore, they estimate they were able to reduce development time by 86%.
The Power of Personalization: Ocado Retail’s Strategy to Boost Revenue and Lower Churn

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Retailers are becoming more skilled at making individual customers feel heard and valued. This is a necessity given the fact that 66% of respondents to a McKinsey survey stated that they expect email marketing messages to be tailored to their needs. While marketing personalization expertise is growing, it’s still difficult to manage, especially at scale.
Ocado Retail, one of the world’s largest dedicated online grocery retailers, delivering to over 645,000 customers in the U.K., has made personalization integral to its success.
Let’s look at how Ocado retail worked with Google Cloud and partner Cognizant to develop a new data platform to power its personalization efforts from the ground up.
Unifying data for more holistic, powerful personalization
To achieve its goals of personalization at scale, Ocado Retail needed a central data warehouse that could turn all forms of merchandising, advertising, business, and customer intelligence data into actionable insights. It wanted a means to accelerate customer segment identification, as well as the ideation and launch of relevant campaigns.
“We standardized on Google Cloud, including BigQuery, as the foundation for our data platform because we knew it was the right solution for now and the future,” says Kieren Johnson, Head of IT at Ocado Retail. “We have an incredibly lean team and we needed a partner with exceptional expertise to help build an ambitious enterprise data warehouse to provide powerful insights. Cognizant was also the clear choice to help us get there.”
Cognizant worked closely with Ocado Retail to make sure its expertise in Google Cloud and other technologies aligned with Ocado Retail’s vision to drive more advanced personalization at higher scales using machine learning. The partner helped build the foundation on BigQuery, and then incorporated other Google Cloud tools such as Cloud Run, Vertex AI, and Vertex AI Natural Language to provide no-ops, all-code warehousing, and analytics capabilities.
Cognizant also took advantage of the Google Cloud Partner Success Services (PSS) program to ensure best practices were being followed throughout the project. PSS provided advisory services that guided Cognizant through the highly complex process of building the new data warehouse for Ocado Retail on Google Cloud.
Building the enterprise data platform in this way allows Ocado Retail to leverage the full power of cloud-based analytics while maintaining a lean team. It also allows the company to greatly scale up its personalization efforts.
Making customers feel valued at every touch
The work Ocado Retail has done with Google Cloud and Cognizant has positioned it to make its growing customer base feel valued, understood, and supported in every interaction. Before launching the project with Cognizant and Google Cloud, Ocado Retail was only able to run a couple of campaigns per week and knew it lacked optimal insight into each campaign’s efficacy.
“We now run 10 times the number of campaigns we used to with the help of the data platform Cognizant built on Google Cloud,” says Kieren. “We run multiple campaigns every day for different customer segments, and all of that increased activity is entirely driven by data insights. The positive impacts on our marketing and customer service performance have been clear. We’re now working to expand what we do.”
Ocado Retail has enjoyed solid growth since the new data platform went live, including a 13% rise in active customers during fiscal year 2022, and has also seen a reduction in churn. It attributed these improvements to being better able to tailor products and communications to specific customer preferences.
Throughout the project, Cognizant supported data clean up while maximizing the scalable, flexible, and future-proofed data analytics infrastructure offered by Google Cloud.
Increasing data-driven actions
Ocado Retail plans to provide more data-driven insights to its commercial suppliers through a product called Beet Insights. So far, Beet Insights offers suppliers with intelligence about how their products are performing on the shelves. The result has been improving the role data plays throughout the supply chain, from production to purchase and beyond.
“By putting real-time insights about costs, marketing spend, and supply-funded activities into the hands of our commercial team and buyers, we are better positioned to improve our profits,” says Kieren. “At the same time, building data analytics into every part of our business will allow us to build on our personalization efforts.”
From the project’s inception, Ocado Retail ensured that the platform would be scalable and dynamic. Now, it is working to feed more data sources and streams into the warehouse to accelerate time to insights. Ocado Retail believes this next step in the evolution of the platform will unlock even more opportunities to initiate high-impact programs that transform personalization and every customer interaction.
Learn more about what Google Cloud and partners like Cognizant can do for your customer intelligence and personalization.
Personalization with Recommendation AI Improves Reader Experience on Newsweek Platform

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Newsweek provides the latest news, in-depth analysis, and ideas about international issues, technology, business, culture, and politics to its readers around the world. While editors pick the best articles to display on the home page and topic pages, it is also critical for Newsweek to offer a personalized experience by delivering fresh and relevant article recommendations tailored to the unique interests of each reader. This need became even more important during the pandemic as readers wanted to be kept informed about the latest news and understand its impact on their own lives and businesses.
Personalization with Recommendations AI
Google has spent years delivering recommended content across flagship properties such as Google Ads, Google Search, and YouTube. Recommendations AI takes advantage of Google’s expertise in recommendations and is powered by state-of-the-art machine learning models. It is also a fully managed service with automated model training and recommendation serving infrastructure that have helped to meet Newsweek’s planet-scale needs.
Newsweek had been concerned that a sizable fraction of their users left the website after reading only one article and as a result was evaluating deploying ML-based recommendations on their article detail page to increase user engagement. Newsweek and Google Cloud expected that highly personalized recommendations from Recommendations AI would help readers find the articles they would be most interested in, thereby significantly increasing the click-through rate (CTR) of recommendations being shown.
Newsweek ran A/B tests on both desktop and mobile to compare their existing solution with content recommendations from Recommendations AI which leverage a user’s reading history along with article metadata such as categories, titles, and article publish time to ensure that recommendations are relevant, fresh, and personalized. The result was a strong improvement in business metrics.
“Google Cloud Recommendations AI has not only improved our CTR by 50%-75% and subscription conversion rate by 10%, but also allowed us to increase total revenue per visit by 10%,” says Michael Lukac, Newsweek’s Chief Technology Officer. “The fully managed service, advanced AI, and real-time personalization have allowed us to make an improvement in our user engagement. It has improved the diversity of content and personalized assets to the individual reader. Newsweek has been able to easily create and edit models from the dashboard while retraining them daily to handle changing catalogs.”
Next Steps
Newsweek has seen tremendous benefit from Recommendations AI’s ability to create a superior reader experience with personalization, and sees opportunities to further improve the reader’s journey by having Google cover more real estate on their site, app, and on other channels such as personalized newsletters. To explore what Google Cloud’s Recommendations AI can do for your business, click here.
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How FLYR and Google Cloud Help Airlines Forecast Demand and Set Prices
FLYR Labs is an international team of industry experts and specialists in revenue management that works to bring in intelligence to the airlines companies. FLYR uses machine learning and AI to help predict demand and optimize price so that every airline is operating its complete capacity. Watch the video from Architecting with Google Cloud to deep-dive into a use case with FLYR involving the use of historic data, competitors data and future information to build model for outputting demand, set prices and optimize revenue. You can can even have a quick view of the FLYR ML platform!
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