Rethinking retail with Google Cloud Retail Search
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Cloud Retail Search, part of Discovery Solutions For Retail portfolio, helps retailers significantly improve the shopping experience on their digital platform with ‘Google-quality’ search. Cloud Retail Search offers advanced search capabilities such as better understanding user intent and self-learning ranking models that help retailers unlock the full potential of their online experience.
Google Cloud’s Discovery Solutions For Retail are a set of services that can help retailers improve their digital engagement and are offered as part of our industry solutions.
Executive Summary
Retailers are always working on trying to keep up with the ever changing consumer expectations and trying to forecast the next trend that can impact sales and revenue.
The pandemic brought its own (and largely new) set of challenges which further complicated the issue over the last two years. The retailers were forced to adapt to the new consumer (low physical touch) behavior in which the browsing and product research was largely digital (endless aisle) and accelerated other trends such as buy online and pick up in stores (BOPIS), curbside pick up and pick up lockers. According to a McKinsey Global Survey from early last year, the pandemic has accelerated the pace of digital transformation by several years.
The National Retail Federation (NRF) estimates that retail sales are expected to grow between 6% and 8% in 2022 (slower growth rate than in 2021), as consumers spend more on services instead of goods, deal with inflation and higher food & gas prices due to geopolitical disruptions in the world.
And the competition continues to be fierce as ever. Amazon continues its dominance in the U.S. retail world and new PYMNTS data shows that Amazon’s share of US Ecommerce sales hit an all-time high of 56.7% in 2021.
Customers now have more choices than ever on how they want to engage with the retailers, where they want to spend the money and make their purchase. They also have increased expectations from the retailers around providing a high quality product discovery experience, which is forcing the retailers to invest heavily on improving customer engagement on their digital platforms to boost conversion rate and overall customer loyalty.
This is where Retail Search can help by providing an enhanced search experience that uses Google-quality search models to understand the customer intent and takes into account the retailer’s first party data (such as promotions, available inventory and price) for ranking results.
How is Google Cloud Retail Search Different
The Ecommerce platform on-site search use case is not new and retailers have been trying to solve it effectively for the last two decades. Most retailers recognize that search is a critical service on the platform and have spent countless resources to improve and fine tune it over the years. Yet the challenge remains. According to a Baymard Institute study in late as 2019, 61% of sites still required their users to search by the exact product type jargon the site uses.
However, users now expect the same robust and intuitive search features as is offered by Google.com and other popular web platforms, who seem to have the uncanny ability to intelligently interpret and yield relevant results to complex search queries.
Google’s decades of experience and research in search technology benefits Cloud Retail Search solution and that is what differentiates it from the competition.
- Advanced Query Understanding: Retail Search can provide more relevant results for the same query due to better query understanding features and knowing when to broaden or narrow the query results. While most search engines still rely largely on keyword based or matching tokens results, Retail Search has the advantage of being able to leverage Google search algorithms to return highly relevant results for product listings and category pages.
- Semantic Search: Intent recognition is a key requirement for semantic search and identifying what the customers mean when they enter the query is a key strength of Retail Search. This is critical for retailers since this has a direct impact on Clickthrough rate, Conversion rate and the Bounce Rate.
- Personalized Search Results: Another key differentiator for Retail Search is its ability to leverage user interaction data and ranking models to provide hyper personalized search results. Retailers are able to optimize search performance to deliver desired outcomes: better engagement, revenue, or conversions.
- Self-Learning and Self-Managed Solution: Retail Search models get better over time because of the self-learning capabilities built into the solution. In addition, the service is fully managed, which saves precious resources needed to keep it running and managing its set up.
- Strong Security Controls: The service runs on Google Cloud and follows security best practices to keep our customers’ data secure. Google never shares model weights or customer data across customers using the Retail API or other Discovery Solution products. For more details about this data use, see a description of Retail API data use.
High Level Conceptual View
Here is a simplified high-level view of Retail Search API. Retailers can call the API for the given search query and get back the results which can then be displayed on their digital properties.
The returned results contains two types of information:
- Search results: Query search results including product listings and category pages based on advanced query understanding and semantic search.
- Dynamic faceted search attributes: Faceted Search is a feature that allows further refinement of the search by providing ways to apply additional filters while returning results.
Retail Search needs the following datasets as input to train its machine learning models for search:
- Product Catalog: Information about the available products including product categories, product description, in-stock availability, and pricing.
- User Events: This is the clickstream data that contains user interaction information such as clicks and purchases.
- Inventory / Pricing Updates: Incremental updates to in-stock availability and pricing as that information is updated.
(Keeping the product catalog up to date and recording user events successfully is crucial for getting high-quality results. Set up Cloud Monitoring alerts to take prompt action in case any issues arise).
Retailers also have the ability to set up business/config rules to customize their search results and optimize for business revenue goals such as Clickthrough rate, Conversion rate, Average size order etc.
How to get started
Retail Search is generally available now and anyone with a Google cloud account can access it. If you don’t already have an account, you can start with a trial account for free here.
Establish a Success Criteria: It’s important to establish a success criteria for measuring the effectiveness of Retail search. Get a consensus on which factor(s) you want to include in scope for measuring the effectiveness of Retail Search. This could include one or two from the following: Search Conversion Rate, Search Average Order Value, Search Revenue Per Visit and Null Search Rate (No Results Found).
- Initial Set Up: Create a Google Cloud Project and set up the Retail API. When you set up the Retail API for a new project, the Google Cloud Console displays the following three panels to help you configure your Retail API project:
- Catalog: displays product catalog and a link to import catalog.
- Event: displays user events and a link to import historical user events.
- Serving configs: contains details on serving configuration and a link to create a new serving configuration.
- Measuring Performance: Retail dashboards provide metrics to help you determine how incorporating the Retail API is affecting the results. You can view summary metrics for your project on the Analytics tab of the Monitoring & Analytics page in Cloud Console.
- Set up A/B Experiments: To measure the performance of Retail Search with another search solution, you can set up A/B tests using a third-party experiment platform such as Google Optimize.
Summary:
As retailers try to navigate through the post-pandemic world where supply chain failures and digital transformation acceleration are major focus areas, they now also have to keep a close eye on the recent geopolitical challenges resulting in rising inflation and costs.
While we can all agree that in-store shopping will continue to be a major source of revenue, it is also important for retailers to tweak the in-store experience for the digital world. Trends such as buy online and pick up in stores (BOPIS), curbside pick up and pick up lockers are here to stay.
Given all the above, consumer engagement and digital experience is more important now than ever before. The cost of search abandonment is way too high and has both short and longer term impact. Retail Search is a great solution to help reduce churn, improve conversion and retention. It provides Google-quality search models to help understand customer intent and the retailers have the ability to set up business/config rules to optimize search results for business revenue goals such as Clickthrough rate, Conversion rate and Average size order.
NVIDIA CloudXR Streaming from Cloud to Transform Gaming and Enterprise AR/VR Experience
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The Opportunity for Streamed AR/VR Content
What if you could get a high quality AR/VR experience without a dedicated physical computer—or even without a physical tether?
In the past, interacting with VR required a dedicated, high-end workstation and, depending on the headset, wall-mounted sensors and a dedicated physical space. Complex tasks in VR can push the limits of sensor reach, cable-length, and spatial boundaries, entangling the artist and restricting their movement. This solution was not scalable beyond a handful of advanced use cases.
Recently, tetherless VR headsets from manufacturers such as HTC and Oculus have emerged that free the user from these odious restrictions, enabling a new freedom to experience VR and AR from just about anywhere. The enhanced portability and reduced cost has led to substantially increased adoption among consumers and opened up many new exploratory use cases in enterprise.
However, while these headsets are more accessible and portable, a tradeoff in compute power was required in order to achieve these goals. The limited on-device compute power of this new generation of Head Mounted Displays (HMDs) is acceptable for many consumer applications such as casual gaming. However, advanced enterprise workloads with heavy graphics, compute, or memory requirements can be difficult or even impossible to run on these lightweight devices.
By combining NVIDIA CloudXR with their powerful GPUs running NVIDIA RTX Virtual Workstations (vWS) in Google Cloud data centers, you can experience high-fidelity VR and AR applications from just about anywhere with a good internet connection. The heavy computations are performed in the cloud on a GPU-attached VM and the content streams to any CloudXR compatible headset.
The combination of Google Cloud’s private fiber optic network — the same network we built for global delivery of YouTube content — and CloudXR’s QoS technologies provides the user with the highest possible quality of service. In fact, the streaming experience is comparable to that of a headset tethered to a powerful physical workstation, but without the friction of hardware and cables.
This combination of power and portability sets the stage to unlock the potential of high-quality gaming and enterprise AR/VR experiences anywhere on Earth.
Case Study: Creating a Masterpiece
Digital character creation is a core skill for many 3D artists today. One of the preferred methods of 3D character creation is digital sculpting, which lets artists create both hard-surface and organic shapes with high levels of accuracy and control.
Sculpting is one of the many tasks in the character designer’s skillset. Artists must also master the texturing, rigging, and posing of characters as part of the digital character creation pipeline.
Mastering all these tasks can be challenging, and often, the technology gets in the way; working in multiple applications requires switching contexts and workflows, breaking the artist’s creative flow. The traditional user experience can also be unintuitive, forcing the creator to translate what they want to do with their hands and head into mouse movement and keyboard presses.
Masterpiece Studio Pro revolutionizes this character creation workflow by giving artists the first fully immersive 3D creation pipeline. Artists work in VR, giving them a far more intuitive and seamless way to work which combines the best of the digital and physical worlds.
In Masterpiece Studio Pro, the artist can work on the character or object at any scale, using familiar tools and hand gestures to sculpt a model, much as they would a real clay figure. Performing other tasks such as skeleton creation is simple, allowing the artist to work directly with the limbs of a character to place and adjust the joints.
Bringing It All Together
NVIDIA CloudXR streaming from the cloud provides tremendous opportunities for new creative use cases within gaming and across the enterprise. This solution joins Virtual Studio for Gaming as the latest in our series to help developers build better games.
The Masterpiece Studio use case is a powerful demonstration of new modalities for content creation and collaboration. To try CloudXR with NVIDIA RTX vWS on Google Cloud for yourself, see this tutorial. Masterpiece Studio Pro also offers extensive learning materials and a free trial.
Speed Up Data-driven Innovation in Life Sciences with Google Cloud
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The last few years have underscored the importance of speed in bringing new drugs and medical devices to market, while ensuring safety and efficacy. Over this time, healthcare and life sciences organizations have transformed the way they research, develop, and deliver patient care by embracing agility and innovation.
Now, the industry is set to reap the benefits of cloud technology and overcome the existing barriers to innovation.
What’s holding back innovation?
Costly clinical trials: The process of trialing and developing new drugs and devices is still long and costly, with more than 1 in 5 clinical trials failing due to a lack of funding.1 The high failure rate comes as no surprise when you consider the average clinical trial costs $19 million and takes 10-15 years (through all 3 phases) to be approved.2
Stringent security requirements: Pre-clinical R&D and clinical trials use large volumes of highly sensitive patient data – making the life sciences industry one of the top sectors targeted by hackers.3 On top of this, the FDA and other regulatory bodies have strict requirements for medical device cybersecurity.
Unpredictable supply chains: Global supply chains are becoming increasingly complex and unpredictable. This can be brought on by anything from supply shortages, to geo-political events, and even bad weather. Making things worse is the lack of visibility into medical shipment disruptions – so when disaster strikes you’re often caught off guard.
Google Cloud for life sciences
At Alphabet, we’ve made significant investments in healthcare and life sciences, helping to tackle the world’s biggest healthcare problems, from chronic disease management, to precision medicine, to protein folding.
Together with Google, you can transform your life sciences organization and deliver secure, data-driven innovation across the value chain.
- Accelerate clinical trials to deliver life-saving treatments faster and at less cost. Clinical trials require relevant and equitable patient cohorts that can produce clinically valid data. Solutions like DocAI can enable optimal patient matching for clinical trials, helping organizations optimize clinical trial selection and increase time to value. How that patient data is collected is also important. Collection in a physician’s office captures a snapshot of the participant’s data at one point in time and doesn’t necessarily account for daily lifestyle variables. Fitbit, used in more than 1,500 published studies–more than any other wearable device–can enrich clinical trial endpoints with new insights from longitudinal lifestyle data, which can help improve patient retention and compliance with study protocols. We have introduced Device Connect for Fitbit, which empowers healthcare and life sciences enterprises with accelerated analytics and insights to help people live healthier lives. We are able to empower organizations to improve clinical trials in key ways:
- Enable clinical trial managers to quickly create and launch mobile and web RWE collection mechanism for patient reported outcomes
- Enable privacy controls with Cloud Healthcare Consent API and, as needed, remove PHI using Cloud Healthcare De-identification API
- Ingest RWE and data into BigQuery for analysis
- Leverage Looker to enable quick visualization and powerful analysis of a study’s progress and results
- Ensure security and privacy for a safe, coordinated, and compliant approach to digital transformation. Google Cloud offers customers a comprehensive set of services including pioneering capabilities such as BeyondCorp Enterprise for Zero Trust and VirusTotal for malicious content and software vulnerabilities; Chronicle’s security analytics and automation coupled with services such as Security Command Center to help organizations detect and protect themselves from cyber threats; as well as expertise from Google Cloud’s Cybersecurity Action Team. Google Cloud also recently acquired Mandiant, a leader in dynamic cyber defense, threat intelligence and incident response services.
- Optimize supply chains and enhance your data to prepare for the unpredictable. With a digital supply chain platform, we can empower supply chain professionals to solve problems in real time including visibility and advanced analytics, alert-based event management, collaboration between teams and partners, and AI-driven optimization and simulation.
Ready to learn more? We’ll be taking a deep dive into each of the challenges outlined above in our life sciences video series. Stay tuned.
- National Library of Medicine
- How much does a clinical trial cost?
- Life Sciences Industry Becomes Latest Arena in Hackers’ Digital Warfare
LearningMate & Google Cloud Partnership to Aid Equitable Educational Opportunities
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A “one size fits all” approach to education no longer works in today’s classrooms. Using cloud-based technologies, schools and educators can take a more personalized approach to education–one that suits each student’s unique learning style, abilities, and needs.
Taking the lead toward more equitable educational opportunities worldwide, education technology pioneer, LearningMate, is partnering with Google Cloud to offer intelligent, personalized learning via Google Cloud’s Student Success Services.
In a student survey by EDUCAUSE, a nonprofit association whose mission is to advance higher education through the use of information technology, nearly all respondents asked for more digital learning and study options. Given a list of educational material types, such as study guides and recorded lessons, 93 percent said they would like to have online access to at least two options and more than half (56 percent) chose seven or more.
The trend towards student choice challenges educators to reconsider how they teach and support learners. Students expect the same qualities in their lessons as they encounter in their other, non-school related digital experiences: personalization; user-friendliness; and engagement. Educators who are used to a more top-down education model can struggle to meet these new expectations.
Google Cloud created Student Success Services to help education institutions meet learners where they are—in the digital age. This suite of tools and services uses Google’s advanced artificial intelligence (AI) and analytic tools to:
- Engage with students via an AI-powered learning platform and interactive tutor
- Help educators and learners collaborate more effectively
- Provide current, actionable data on student progress
To bring our Student Success Services to more schools and organizations worldwide, we’re partnering with LearningMate — a global leader in digital learning infrastructure. LearningMate is a key go-to-market partner, helping schools design, launch, and maintain their own learning infrastructure. To start, LearningMate is adding Google’s AI-powered learning platform to its Frost platform, a popular content management for education.
As the education model continues to change and digital learning becomes the norm, disadvantaged students risk getting left behind. For these learners, the “digital divide” is very real, and stands to hinder them further–not only in school, but in society and the workplace in later life.
“The gap will only widen between those with digital advantages and those who struggle to gain access to devices and network necessities,” EDUCAUSE states. To meet all these challenges, schools need a diverse mix of tools, methods, and partnerships.
To help close the digital divide among students, digital tools need to be able to scale up or down so institutions and districts of any size and budget can use them. Google Cloud designed Student Success Services with this ability in mind. By offering these services, LearningMate aims to ensure that even schools with smaller teams and fewer resources can offer individualized learning experiences to their students.
With LearningMate and Google’s nearly 40 years of combined experience in education, this partnership aims to help educators better understand their students’ engagement, performance, and preferences. To learn more about Student Success Services and our collaboration with LearningMate, watch this session from our Government and Education Summit.
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While innovation remains a top priority across all industries, many companies are not achieving the results they want from their innovation efforts. As companies migrate their SAP enterprise resource planning (ERP) systems to the cloud, technology leaders see this as an opportunity to reimagine business processes and propel their innovation strategies.
This paper will explore the benefits that companies have reaped from their SAP cloud migration, such as using IT resources more effectively, gaining deeper insights from data, and improving innovation. It will also examine the approach organizations are taking to gain buy-in from other stakeholders in their operations, positioning the SAP migration for a successful outcome.
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IDC recently examined the benefits of implementing BigQuery for SAP data. The findings reveal massive improvements to the SAP customers’ overall business results due to faster access to data insights, lower data warehouse operation cost, and increased productivity among the data warehouse and development teams. Download the report now!
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