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Poor Product Discovery Causes Shoppers’ Abandonment, Time to Augment ‘Search Experience’ with Google’s Retail Search!

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How many times has a shopper searched for a product on a store’s website only to get results that aren’t relevant—or worse, provided no search results at all? While most ecommerce sites have search capabilities, few accomplish their ultimate goal: making it easy for customers to discover the products they want.
Some 94% of U.S. consumers abandoned a shopping session because they received irrelevant search results, according to a 2021 survey conducted by The Harris Poll and Google Cloud. It’s a phenomenon known as “search abandonment.” Indeed, poor product discovery experiences can stop a purchase in its tracks and leave shoppers frustrated. Retailers miss out on a staggering $300 billion each year due to search abandonment in the U.S. alone.
With the announcement today of our latest discovery solution, Retail Search, now generally available, retailers worldwide can supercharge their websites and mobile apps with Google-quality search. Built on Google’s technologies that understand user intent and context, the solution helps businesses improve the search and overall shopping experience across all of their digital touchpoints.
Already, early adopters like Lowes, Fnac Darty, and Casas Pernambucanas have been using Google Cloud’s discovery solutions to increase sales conversions, boost basket sizes, and improve customer engagement.
Understanding user intent in search is a hard problem
While we’ve come a long way from the days when search was largely based on keywords and boolean rules, shoppers still struggle to find what they’re looking for. They often have to come up with a perfectly-worded query that a retailer’s site search engine will understand, sometimes rephrasing several times before getting the results they want—if they find anything relevant at all.
Traditional search technologies don’t work in the modern age of online retail, where tens or even hundreds of thousands of items are available on a single ecommerce site.

Today, people expect search engines to understand their intent more deeply, return relevant results faster, and help them discover new products easily with personalized recommendations.
Fortunately, product discovery experiences on retail sites can now offer superior, contextual experiences for consumers, combining marketing and data science insights along with advanced search technologies based on machine learning and artificial intelligence.
Now, through the power of Retail Search, when a shopper searches for a “long black dress with short sleeves and comfortable fit” on an ecommerce site, they should immediately get results for precisely that—rather than refining their search multiple times, or worse, giving up their shopping journey.
Helping retailers solve their search experience woes
Retail Search transforms the shopping experience and makes it easier for shoppers to find relevant products by surfacing results that are intuitive and contextual.
This fully managed service is easily customizable, enabling organizations to craft shopper-focused search experiences. Our site search solution builds upon decades of Google’s experience and innovation in search indexing, retrieval, and ranking. Retailers can make product discovery even easier for shoppers, while optimizing for their business goals with advanced capabilities, including:
- Advanced query understanding that produces better results from even the broadest queries, including non-product searches.
- Semantic search to effectively match product attributes with website content for fast, relevant product discovery.
- Optimized results that leverage user interaction and ranking models to meet specific business goals.
- State-of-the-art security and privacy practices that ensure retailer data is isolated with strong access controls and is only used to deliver relevant search results on their own properties.
Retailers can now shape product discovery into a shopping experience that is timely, relevant, and personalized—all powered by Google Cloud.
Early adopters seeing immediate impact
Several leading retailers around the world have been able to quickly create better online shopping experiences for their customers and capture more digital and omnichannel growth using Google Cloud’s product discovery solutions.
“With limited customer signals and no historical data, descriptive long-tail searches are some of the most challenging queries to understand,” said Neelima Sharma, senior vice president, technology, e-commerce, marketing and merchandising at Lowe’s. “We have been partnering with Google Cloud to give our customers relevant results for long-tail searches and have seen an increase in click-through and search conversion and a drop in our ‘No Results Found’ rate since we launched.”
“Making constant improvements to our website search engines has always been a priority for us as we aim to give our customers a simpler, more customized and enhanced online shopping experience,” said Olivier Theulle, Fnac Darty’s chief ecommerce and digital officer. “As we implement Google Cloud’s site search solution on our Fnac Darty websites and are the first French retailer to do so, we expect the solution to deliver increased conversion rates while also offering greater customer satisfaction.”
“Google Cloud has helped improve the indexing and quality of search results on Pernambucanas’ digital platforms, providing a better experience to our customers and improving sales conversions,” said Fabiano Rustice, chief information officer at Pernambucanas. “On Black Friday in November 2021—the largest retail date in Brazil—we saw a 20% reduction in search refinements per user, for which Retail Search was instrumental. We are proud to be an early adopter and to have Google Cloud as a strategic innovation partner.”
In addition to Google Cloud’s efforts working directly with customers, our ecosystem of key partners, including GroupBy, Lucidworks, GridDynamics, SpringML, and others are also leveraging Google Cloud discovery solutions to provide value added services to their customers.
“In the fast paced and extremely competitive ecommerce environment, we are seeing that forward-looking and innovative retailers are prioritizing product discovery,” said Roland Gossage, CEO of GroupBy. “GroupBy has proudly partnered with Google Cloud to launch its product discovery solutions across several client environments. Already we have seen a more than 10% increase in online revenues, which equates to millions of dollars, and this is just the beginning.”
To learn more, visit Discovery Solutions for Retail or contact your Google Cloud field sales representative.
Empowering AI Startups: Google Cloud’s Game-Changing Benefits

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New AI startup program benefits and Accelerator introduced at the Google Cloud Startup Summit
Google Cloud is committed to supporting the growth and advancement of startups, with particular focus on helping startups looking to build and scale. We’re seeing tremendous innovation from startups choosing Google Cloud to advance their generative AI development, thanks to our fully-managed and serverless data, AI, and infrastructure solutions. That’s why today’s Startup Summit, and announcements, are focused on AI.
Following our March 14th announcement that we were expanding the Google for Startups Cloud Program with exclusive benefits for AI startups, we’re excited to announce that the program is now live. Starting today, eligible seed to series A startups that use AI as their core technology to develop their primary products or solutions can apply here. This gives them access to all the Google for Startups Cloud Program benefits, including:
Up to $350,000 USD over two years in Google Cloud credits
For Google Cloud and Firebase usage covered in:
- Year 1: 100% up to $250,000 USD in Google Cloud credits [1] (includes standard program credits plus an additional $150,000 USD for the AI startup program)
- Year 2: 20% up to an additional $100,000 USD in Google Cloud credits
Technical & collaboration support
We’re providing credits to allow AI startups access to fast, high-quality Customer Care Enhanced Support, access to Google Cloud Startup Customer Engineers, and a dedicated Startup Success Manager to accelerate onboarding with Google Cloud. We’re also offering 12 months of free Google Workspace Business Plus for new sign-ups.
Additional AI benefits, such as access to AI experts, training, and resources include:
Webinars & live Q&A sessions
Exclusive access to join webinars and live Q&As with our Google Cloud AI product managers, engineers, and developers.
Insight into AI innovation
Direct visibility into Google Cloud’s latest AI advances and product roadmap.
Hands-on AI learning labs
Free access to advanced hands-on learning labs focused on AI/ML and the latest Google Cloud technology.
Exclusive AI ISV/Saas startup access to Built with Google Cloud AI
Access to the AI Center of Excellence, tools and training, co-marketing, and amplification on Google Cloud Marketplace. These resources have historically been available only to AI enterprise ISV/SaaS companies, but will now also be offered to ISV/SaaS startups in our program.
Dedicated AI technical guidance, workshops, and best practices
Architectural guidance and best practices to get started and build with Google Cloud AI solutions, including technical deep dives and hands-on workshops.
We’re also excited to announce an inaugural North American Google for Startups Accelerator: Cloud. This 10-week virtual Accelerator is equity-free and best suited for cloud-native startups leveraging AI and ML in their operations. Designed to help prepare for the next phase of the growth journey, participating startups will work with the best of Google’s programs, products, people, and technology. Applications are open now until May 30th and the program kicks off in July. Find out more here.
Our goal is to enable more AI-first startups and give them the technology, community, and resources they need to build and grow their startup faster, smarter, and cheaper. Furthermore, partnering with Google Cloud lets startups seamlessly integrate with other Google solutions and leverage our global infrastructure. Google Cloud’s AI platform, Vertex AI, gives startups the intelligence they need to make smart business decisions and allows them to easily build, deploy, and scale machine learning (ML) models faster. They can also quickly build with Google Cloud’s advanced generative AI technologies or use our best-in-class speech, vision, translation, and language APIs. To learn more about Google Cloud’s recently-announced Generative AI Support in Vertex AI, check out this deep dive, and to keep up with Google Cloud’s latest generative AI news and thought leadership, read The Prompt on Transform with Google Cloud.
Startups around the world are choosing Google Cloud. Join us and let’s build the future, together.
Unified, Flexible and Accessible: How Companies’ Data Help Them Achieve More on Google Cloud

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As the volume of data that people and businesses produce continues to grow exponentially, it goes without saying that data-driven approaches are critical for tech companies and startups across all industries. But our conversations with customers, as well as numerous industry commentaries, reiterate that managing data and extracting value from it remains difficult, especially with scale.
Numerous factors underpin the challenges, including access to and storage of data, inconsistent tools, new and evolving data sources and formats, compliance concerns, and security considerations. To help you identify and solve these challenges, we’ve created a new whitepaper, “The future of data will be unified, flexible, and accessible,” which explores many of the most common reasons our customers tell us they’re choosing Google Cloud to get the most out of their data.
For example, you might need to combine data in legacy systems with new technologies. Does this mean moving all your data to the cloud? Should it be in one cloud or distributed across several? How do you extract real value from all of this data without creating more silos?
You might also be limited to analyzing your data in batch instead of processing it in real-time, adding complexity to your architecture and necessitating expensive maintenance to combat latency. Or you might be struggling with unstructured data, with no scalable way to analyze and manage it. Again, the factors are numerous—but many of them accrue to inadequate access to data, often exacerbated by silos, and insufficient ability to process and understand it.
The modern tech stack should be a streaming stack that scales with your data, provides real-time analytics, incorporates and understands different types of data, and lets you use AI/ML to predictively derive insights and operationalize processes. These requirements mean that to effectively leverage your data assets:
- Data should be unified across your entire company, even across suppliers, partners, and platforms., eliminating organizational and technology silos.
- Unstructured data should be unlocked and leveraged in your analytics strategy.
- The technology stack should be unified and flexible enough to support use cases ranging from analysis of offline data to real-time streaming and application of ML without maintaining multiple bespoke tech stacks.
- The technology stack should be accessible on-demand, with support for different platforms, programming languages, tools, and open standards compatible with your employees’ existing skill sets.
With these requirements met, you’ll be equipped to maximize your data, whether that means discerning and adapting to changing customer expectations or understanding and optimizing how your data engineers and data scientists spend their time. In coming weeks, we’ll explore aspects of the whitepaper in additional blog posts—but if you’re ready to dive in now, and to steer your tech company or startup towards success by making your data better work for you, click here to download your copy, free of charge.
Pindrop and Google Cloud Get Together to Make Way for Next Wave, Voice-first Interfaces!

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If you’ve ever used only your voice to authenticate a payment, place an order, or check an account over the phone, there is a good chance that Pindrop’s technology made it possible.
Founded in Atlanta in 2011, Pindrop provides software and technology that uses machine learning, voice recognition, and behavioral analytics to help detect and prevent fraud in voice channels like AI-powered call centers and solve the long standing identity problem commonly encountered in customer care and contact center experiences. Demand for Pindrop’s technology has grown considerably over the past decade, as more organizations and people adopt voice as an interface for customer service, transactions, entertainment and more. As that demand has grown, safeguarding these voice interactions from fraud or authentication loops continues to be a unique challenge.
Now, with frictionless voice-driven customer experiences at an all-time high, cybersecurity is more critical than ever. In fact, research shows that fraudsters are able to accurately answer knowledge-based authentication questions 92% of the time, as opposed to only 46% for actual customers. To address this, Pindrop is bringing its products and technology to Google Cloud in order to scale and develop new capabilities that will help enable the next wave of voice-first interfaces and call centers.
The new partnership will enable Pindrop’s teams to accelerate their development of new capabilities to address an ever-shifting landscape – like detecting deep fakes and robocalls, helping banks authenticate transactions, providing retailers with AI-powered call center support, and helping IoT makers optimize for security, speed and simplicity.
More specifically, the partnership will help Pindrop scale its own businesses, and meet ever-growing customer needs in several ways.
First, Pindrop is bringing its SaaS platform to Google Cloud, enabling customers to deploy it at global scale, on secure, sustainable, and highly performant cloud infrastructure. Not only does this give Pindrop the ability to deliver secure voice interactions with low-latency, it also aligns with its mission to enable customer choice when selecting and implementing security technology. And for customers already operating on Google Cloud, getting started with Pindrop can be done directly within their cloud environment, now that the company is making its solutions available on Google Cloud Marketplace.
Second, Pindrop plans to offer its voice secure technology with Google Cloud’s Contact Center AI (CCAI) capabilities to develop new solutions that will enhance call center experiences. CCAI capabilities in understanding, augmenting, and ML-processing conversations allows companies to deliver interactions that are helpful and keep costs low. These capabilities alongside Pindrop’s authentication and anti-fraud solutions will enable the company with the tools and technologies needed to create the next evolution of frictionless experiences in a secure way.
Finally, building on top of Google Cloud will equip Pindrop with multicloud capabilities that will offer new channels to increase revenues through. Using technologies like Google Kubernetes Engine, frequently chosen by startups and tech companies, to quickly launch and scale new ML applications up or down will also support Pindrop’s growth as it adds to its suite of technologies.
Supporting innovative startups and digital native businesses like Pindrop is in Google’s DNA, and we’re delighted to support Pindrops’ growth, and the success of their customers, with Google Cloud infrastructure, Contact Center AI, and go to market expertise.
You can learn more about Pindrop on Google Cloud here, and Google Cloud’s Contact Center AI solution here.
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Bra Fit or Brad Pitt? Fun Moments of Using AI for Contact Centers
For many enterprises, the wish to tap into the power of AI is negated only by a lack of know-how: How AI works, what sort and how much data they will need to gather and structure correctly, and how to use the platforms that make AI adoption easier.
Google understands that. Which is why the AI solutions they have built “are basically plug and play, ready to go with our partners, so that you (businesses) can have immediate business value for your specific use case, and for your specific workflow without a deep investment of any kind into machine learning,” says Levent Besik, Group Product Manager, Google Cloud.
Among the more interesting use cases that’s seeing adoption is contact center AI.
“So one thing that we see quite often, especially from our B2C customers, is that they often have this growing pain in their call centers. They face a trade-off between operational efficiency and great customer service. With the advances in language and conversational AI, that doesn’t have to be the case anymore,” says Besik.
That’s exactly the problem in front of Akash Parmar, Enterprise Architect,. “One of the big challenge we had was: how do we effectively manage 14 million calls, which come into our contact center, stores and head office? In the past, these calls were managed by completely different platforms with their own IVRs, with their own routing and reporting solutions. It was expensive, plus the experience across them was very inconsistent.”
Digging deeper, Parmar and team figured that the challenge was in the fact that an IVR couldn’t really capture the hundreds of reasons customers call.
To get around the problem Parmar and team decided to let customer tell them why they were calling. They then used AI to decipher what the customer was saying, extract the customer’s intent from that, and then help them directly, or re-route them to the best department.
Overall, it proved to be a big success, says Parmer. Although there were funny moments.
“In our early days, we were getting some transcriptions from the Speech API, which were not what we expected. It was not word by word and we had to kind of train the model to make sense of it. For example, we started to get calls about Brad Pitt. We were like, we’ve really won the Oscar here. Brad Pitt is calling us. It was not actually call for Brad Pitt. These were calls about bra fit, which it’s a big business for M&S,” remembers Parmer.
Find out how three companies, including Marks and Spencer, are using AI today.
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