The retail and CPG industries are rapidly changing. For brands and retailers, the same old approaches no longer cut it. Reinvention isn’t only necessary to keep up—it’s the only way to thrive. Learn how an AI-enabled Cloud Data Platform can help you capture, integrate, and monetize data, while accelerating transformation and enhancing sustainability.
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Enter Fashion/Apparel
Enter CPG
Exclusive report for RETAIL and CPG brands, featuring case studies with:
And more...
AI delivers marked business value to the table.
Getting it Right
Advanced ML and AI allow retailers to base offers, product recommendations, and services on predictive and prescriptive analytics, so they’re highly relevant as well as delivered at the right time and to the right consumers across web, mobile, digital, and other touchpoints.
Flexible cloud-based platforms and tools support an omnichannel shopping experience by consolidating retailers’ customer and marketing data in a single, modern data repository.
A New Home for Data
Directing the Journey
Real-time insights from AI help orchestrate the journey through all channels and dictate adjustments that should be made along the way based on customer behavior, such as changing product selections.
Shopping journeys powered by Google Cloud can start in one channel and conclude in-store—or vice versa. Retailers can also offer multiple delivery options, like buy online, pick up in store (BOPIS) and curbside pickup, with complete customer access to information about local product availability.
Multiple shopping, delivery, and return options
Joining the conversation
Chatbots enabled by AI and ML remove friction throughout the customer journey. They can provide personalized assistance in locating and selecting products, make product recommendations based on customer data, and handle shopper queries.
Success Spotlight: L.L. Bean
+
Success Spotlight: Maison Cartier
+
Success Spotlight: L.L. Bean
APPROACH:
Catalog and bricks-and-mortar retailer engaged Google Cloud to modernize its IT system and leverage a cloud platform to improve omnichannel experience for in-store, web, and mobile customers.
X
RESULTS:
Google Cloud supports the integration of data from multiple sources and systems, yielding enhanced visibility into actionable data. Retailer can also handle peak website tools more efficiently and cost effectively, innovate and deliver new online features to customers faster, and improve online and mobile customer experiences.
Success Spotlight: Maison Cartier
APPROACH:
Partnered with Google Cloud to build data model boutique teams can use to identify specific watch from photograph of desired model. Custom-designed code combines classifiers that run in parallel, first recognizing watch's colors and materials and then pinpointing collection to which it belongs. Users get “top three” list of possible identities and can click to get more information online.
X
RESULTS:
96.5% accuracy within three seconds; sales associates can answer shoppers' questions in seconds, rather than minutes, decreasing shopping friction
Changing consumer behaviors and emerging trends make a strong case for reimagining the retail experience.
A reliable, flexible, AI-driven, cloud-based platform like Google Cloud sparks retail reimagination and omnichannel growth.
of U.S. consumers and 69% of global consumers are less loyal to a brand when they have trouble locating an item on its website
[Google/Harris Poll]
%
of consumers now use more than one shopping channel when making purchases
[Harvard Business Review]
%
[Google/Harris Poll]
of consumers say an unsuccessful online search results in a lost sale for a retail website, with 52% typically abandoning their entire cart if they can’t find least one item
%
Retailers are losing $300 billion annually from “bad” web searches
[Google/Harris Poll]
$
billion
A scalable, reliable, secure technology infrastructure that supports the omnichannel model
Solutions that eliminate friction at every step of the customer journey
Advanced demand forecasting and inventory management processes to promptly fulfill customer requests
Technology that enables retailers to better understand customers and their needs
Efficient, productive operations are a cornerstone of retail growth and reinvention. But so is digital transformation, with a seamless, connected customer shopping journey at its core. Savvy retailers reimagine that journey from start to finish, with:
Reimaging the retail experience
AI-powered solutions let retailers understand their customers and personalize the shopping journey by collecting information, analyzing it, and determining what the next actions should be—like which items or offers to promote, what product best suits a customer given shopper data that’s already been gathered (e.g., size and color preferences and buying history) or what a customer may purchase next. AI-powered solutions also enable personalization at scale, permitting retailers to target groups of customers based on analytics.
Up close and personal
An AI-enabled, cloud-centric platform gives retailers access to multiple types of data insights—from sales activity to store traffic levels and inventory availability—in real time. This leads to more informed decision-making.
Leveraging data differently paves the way for meeting customers’ expectations, boosting the bottom line.
True insights, better decisions
%
[McKinsey & Company]
Companies that personalize the customer experience across physical and digital channels can increase revenues by 5% to 15% across the full customer base
%
[Walker]
of customers prioritize the customer experience over price and will pay more for it
%
[Google/Harris Poll]
of U.S. consumers consider a “good” search function “very important” or “absolutely essential” to a positive online shopping experience—more so than any other element of a website
of customers expect a personalized experience when shopping in stores and/or online
%
[Researchscape International/Evergage]
of U.S. consumers and 69% of global consumers are less loyal to a brand when they have trouble locating an item on its website
%
[Google/Harris Poll]
%
[Google/Harris Poll]
of U.S. consumers and 69% of global consumers are less loyal to a brand when they have trouble locating an item on its website
%
[Researchscape International/Evergage]
For fashion and other specialty retailers, personalization at scale often delivers a lift in total sales that exceeds 2%
%
[McKinsey & Company]
A positive customer experience yields 20% higher customer satisfaction rates and a 10% to 15% boost in sales conversion rates
%
[Google/Harris Poll]
A good search function makes 99% of consumers “somewhat likely” to return to a retail website and spurs frequent additional purchases by 69% of shoppers
Achieve 1:1 personalization at scale, supporting personal interactions with all or a large segment of customers
Get a 360-degree view of each customer, with the ability to predict future behaviors and trends
Make informed decisions based on actionable data hoppers
[Google/Harris Poll]
Reinventing retail goes beyond transforming operational efficiencies and reimagining the shopping experience. It also means using data differently, harnessing its power to:
PAVING A NEW PATH FOR DATA USAGE
Success Spotlight: YES
+
Success Spotlight: Zulily
+
Success Spotlight: Sephora
+
Success Spotlight: Sephora
X
APPROACH:
Using Google Cloud Recommendations AI, multinational omni-channel beauty and personal care retailer provides enhanced personalized service to online customers through custom-tailored product recommendations—mirroring approach taken in its stores.
RESULTS:
50% increase in click-through rates on product pages; nearly 2% boost in overall conversion rate on homepage
Success Spotlight: zulily
X
APPROACH:
Online retailer launches more than 100 sales events and thousands of new product styles daily. Implemented Google Cloud platform to revamp data infrastructure, gain data analytics capabilities needed to support merchant decision-making, and continue differentiating via highly personalized, next-generation customer experience (including real-time customer notifications and targeted offers/campaigns).
RESULTS:
Ability to operationalize live customer data in conjunction with big data at rest and apply machine learning to drive personalized, contextual experiences. Capabilities provided by platform inform business processes and support efficient planning and fulfillment of customer orders, even with 9,000 new products offered and millions of customers engaging with online store daily. Significant lift in key business performance and efficiency metrics.
Success Spotlight: YES
X
APPROACH:
Online shopping platform harnessed Google Cloud tools (Pub/Sub, Spanner, and Kubernetes Engine) to rebuild ecommerce technology stack and embed AI at its foundation to curate customized catalog for individual customers. One-to-one model integrates with brands via Cloud Vision API and adapts results and recommendations as each consumer shops. Also uses Google Cloud BigQuery and Looker tools to integrate and understand data and trends in real time and formulate appropriate decisions.
RESULTS:
Models developed, trained, and refined in short period versus three to four years. Doubled sales during holiday season; continued sales increases. Now maintains one of the most extensive search and recommendation engines in fashion.
APPROACH:
Uses environmental platform developed under partnership between Google Cloud and WWF. Big data analysis/machine learning and other capabilities allow at-scale gathering and assessment of how different raw materials used in textile production impact the environment.
RESULTS:
More responsible sourcing decisions.
X
SUCCESS SPOTLIGHT: STELLA McCARTNEY
SUCCESS SPOTLIGHT: STELLA McCARTNEY
+
RESULTS:
Streamlined retail functions across networks. Accurately and efficiently receives, sorts, tickets, picks, packs, and ships merchandise from distribution centers to stores, including during peak retail seasons (back-to-school and holidays).
APPROACH:
Department store, specialty store, and ecommerce retailer moved infrastructure to cloud and leverages scalability of Google Cloud data warehousing and analytics solutions.
X
Success Spotlight: Macy's
Success Spotlight: Macy's
+
Cloud-centric technology helps retailers analyze the risk and environmental impact of sourcing decisions and/or using specific materials in the production process.
Delivering on the sustainability promise
Click to see Spotlights
Shopper flow and crowding analytics…and other signals that pack the potential to increase store operations efficiencies while enhancing the customer experience.
Recent consumer behavior
Workers’ available shift times
Retailers can only satisfy consumers’ increasing cries for stellar customer service—and run their stores with minimal headaches—when stores are adequately staffed. With AI and ML, retailers can allocate staff based on:
Working smarter, not harder
Identifying inventory sources, making it easier to handle demand for merchandise
Dictating actions to minimize or eliminate merchandise availability issues head-on—for example, proactively arranging for merchandise to be routed to stores in time to meet demand and conducting “what-if” analyses related to logistics.
Anticipating customer purchase behavior and needs
Managing product inventories in the back room and in warehouses
In the retail supply chain, AI and analytics play a pivotal role in:
Streamlining supply chain efficiencies
Meeting ever-changing customer expectations—in turn boosting productivity and efficiencies to foster short- and long-term growth—calls for:
Streamlining supply chain operations
Improving labor planning/workforce management
Answering the call for sustainability
Digital innovation and cloud-centric, AI-powered solutions foster operational transformation.
of consumers are actively focus on sustainability and use it as a criterion in deciding which brands to patronize.
[Future Commerce]
%
[Qualtrix XM Institute]
A “good” customer experience makes consumers 64% more likely to patronize a company that is new to them, but only 30% of consumers forgive a bad customer experience—even the first time around.
%
of consumers will trust a company that provides “good” customer service, but just 40% trust one that doesn’t
[Qualtrix XM Institute]
%
Today’s fashion customers expect more from brands than ever before. They won’t tolerate poor service, lack of merchandise availability in-store or online, or delivery delays. Increasingly, they favor brands whose practices align with their values of sustainability.
Taking Operations to the Next Level
How AI-Enabled
Power Fashion Retail Transfromation
When international beauty retailer Sephora moved its ecommerce operations to an AI-driven cloud platform, the company saw a 50% increase in product pageviews within the first year and a 2% increase in homepage conversions. Talk about fashion-forward.
Like Sephora, today’s leading fashion retailers—including Macy’s, Stella McCartney, and L..L. Bean—are taking advantage of innovative, cloud-based AI applications to reinvent their businesses from the runway to the register, powering new levels of supply chain efficiency and a more personalized and connected customer journey across every touchpoint.
How AI-Enabled Cloud Platforms Power Fashion Retail Transfromation
Bringing big business benefits
x
faster execution.**
**”MIT in conjunction with Google Cloud
x
more data-driven decisions
x
faster decision making
driving success
Leveraging AI and machine learning (ML) will spark success by allowing retailers to formulate
of companies queried for McKinsey & Company’s 2020 Global Survey on AI said it had boosted their sales and marketing revenues over the past year
%
cited increased revenues stemming from AI-supported product and service developments.
%
Learn more
Click here to learn more
Ready to capture digital and omnichannel growth and become customer-centric and data driven while achieving enterprise-wide operational excellence?
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Pre-built solutions that solve for specific retail use cases, such as Recommendations AI for delivering highly personalized recommendations at scale.
Cloud AI Building Blocks that let developers infuse AI into existing applications or build entirely new intelligent applications across a wide range of use cases, with or without ML expertise.
A robust AI platform retailers can use to build their own applications to meet unique business needs.
Google Cloud powers retail transformation with purpose-built offerings that make AI and ML accessible and applicable throughout the enterprise.
A CLEARER PATH TO TRANSFORMATION
AI delivers marked business value to the table.
Getting it Right
Advanced ML and AI allow retailers to base offers, product recommendations, and services on predictive and prescriptive analytics, so they’re highly relevant as well as delivered at the right time and to the right consumers across web, mobile, digital, and other touchpoints.
Flexible cloud-based platforms and tools support an omnichannel shopping experience by consolidating retailers’ customer and marketing data in a single, modern data repository.
A New Home for Data
Directing the Journey
Real-time insights from AI help orchestrate the journey through all channels and dictate adjustments that should be made along the way based on customer behavior, such as changing product selections.
Shopping journeys powered by Google Cloud can start in one channel and conclude in-store—or vice versa. Retailers can also offer multiple delivery options, like buy online, pick up in store (BOPIS) and curbside pickup, with complete customer access to information about local product availability.
Multiple shopping, delivery, and return options
Joining the conversation
Chatbots enabled by AI and ML remove friction throughout the customer journey. They can provide personalized assistance in locating and selecting products, make product recommendations based on customer data, and handle shopper queries.
Success Spotlight: L.L. Bean
+
Success Spotlight: Maison Cartier
+
Success Spotlight: L.L. Bean
APPROACH:
Catalog and bricks-and-mortar retailer engaged Google Cloud to modernize its IT system and leverage a cloud platform to improve omnichannel experience for in-store, web, and mobile customers.
X
RESULTS:
Google Cloud supports the integration of data from multiple sources and systems, yielding enhanced visibility into actionable data. Retailer can also handle peak website tools more efficiently and cost effectively, innovate and deliver new online features to customers faster, and improve online and mobile customer experiences.
Success Spotlight: Maison Cartier
APPROACH:
Partnered with Google Cloud to build data model boutique teams can use to identify specific watch from photograph of desired model. Custom-designed code combines classifiers that run in parallel, first recognizing watch's colors and materials and then pinpointing collection to which it belongs. Users get “top three” list of possible identities and can click to get more information online.
X
RESULTS:
96.5% accuracy within three seconds; sales associates can answer shoppers' questions in seconds, rather than minutes, decreasing shopping friction
Changing consumer behaviors and emerging trends make a strong case for reimagining the retail experience.
A reliable, flexible, AI-driven, cloud-based platform like Google Cloud sparks retail reimagination and omnichannel growth.
of U.S. consumers and 69% of global consumers are less loyal to a brand when they have trouble locating an item on its website
[Google/Harris Poll]
%
of consumers now use more than one shopping channel when making purchases
[Harvard Business Review]
%
[Google/Harris Poll]
of consumers say an unsuccessful online search results in a lost sale for a retail website, with 52% typically abandoning their entire cart if they can’t find least one item
%
Retailers are losing $300 billion annually from “bad” web searches
[Google/Harris Poll]
$
billion
A scalable, reliable, secure technology infrastructure that supports the omnichannel model
Solutions that eliminate friction at every step of the customer journey
Advanced demand forecasting and inventory management processes to promptly fulfill customer requests
Technology that enables retailers to better understand customers and their needs
Efficient, productive operations are a cornerstone of retail growth and reinvention. But so is digital transformation, with a seamless, connected customer shopping journey at its core. Savvy retailers reimagine that journey from start to finish, with:
Reimaging the retail experience
AI-powered solutions let retailers understand their customers and personalize the shopping journey by collecting information, analyzing it, and determining what the next actions should be—like which items or offers to promote, what product best suits a customer given shopper data that’s already been gathered (e.g., size and color preferences and buying history) or what a customer may purchase next. AI-powered solutions also enable personalization at scale, permitting retailers to target groups of customers based on analytics.
Up close and personal
An AI-enabled, cloud-centric platform gives retailers access to multiple types of data insights—from sales activity to store traffic levels and inventory availability—in real time. This leads to more informed decision-making.
Leveraging data differently paves the way for meeting customers’ expectations, boosting the bottom line.
True insights, better decisions
%
[McKinsey & Company]
Companies that personalize the customer experience across physical and digital channels can increase revenues by 5% to 15% across the full customer base
%
[Walker]
of customers prioritize the customer experience over price and will pay more for it
%
[Google/Harris Poll]
of U.S. consumers consider a “good” search function “very important” or “absolutely essential” to a positive online shopping experience—more so than any other element of a website
of customers expect a personalized experience when shopping in stores and/or online
%
[Researchscape International/Evergage]
of U.S. consumers and 69% of global consumers are less loyal to a brand when they have trouble locating an item on its website
%
[Google/Harris Poll]
%
[Google/Harris Poll]
of U.S. consumers and 69% of global consumers are less loyal to a brand when they have trouble locating an item on its website
%
[Researchscape International/Evergage]
For fashion and other specialty retailers, personalization at scale often delivers a lift in total sales that exceeds 2%
%
[McKinsey & Company]
A positive customer experience yields 20% higher customer satisfaction rates and a 10% to 15% boost in sales conversion rates
%
[Google/Harris Poll]
A good search function makes 99% of consumers “somewhat likely” to return to a retail website and spurs frequent additional purchases by 69% of shoppers
Achieve 1:1 personalization at scale, supporting personal interactions with all or a large segment of customers
Get a 360-degree view of each customer, with the ability to predict future behaviors and trends
Make informed decisions based on actionable data hoppers
[Google/Harris Poll]
Reinventing retail goes beyond transforming operational efficiencies and reimagining the shopping experience. It also means using data differently, harnessing its power to:
PAVING A NEW PATH FOR DATA USAGE
Success Spotlight: YES
+
Success Spotlight: Zulily
+
Success Spotlight: Sephora
+
Success Spotlight: Sephora
X
APPROACH:
Using Google Cloud Recommendations AI, multinational omni-channel beauty and personal care retailer provides enhanced personalized service to online customers through custom-tailored product recommendations—mirroring approach taken in its stores.
RESULTS:
50% increase in click-through rates on product pages; nearly 2% boost in overall conversion rate on homepage
Success Spotlight: zulily
X
APPROACH:
Online retailer launches more than 100 sales events and thousands of new product styles daily. Implemented Google Cloud platform to revamp data infrastructure, gain data analytics capabilities needed to support merchant decision-making, and continue differentiating via highly personalized, next-generation customer experience (including real-time customer notifications and targeted offers/campaigns).
RESULTS:
Ability to operationalize live customer data in conjunction with big data at rest and apply machine learning to drive personalized, contextual experiences. Capabilities provided by platform inform business processes and support efficient planning and fulfillment of customer orders, even with 9,000 new products offered and millions of customers engaging with online store daily. Significant lift in key business performance and efficiency metrics.
Success Spotlight: YES
X
APPROACH:
Online shopping platform harnessed Google Cloud tools (Pub/Sub, Spanner, and Kubernetes Engine) to rebuild ecommerce technology stack and embed AI at its foundation to curate customized catalog for individual customers. One-to-one model integrates with brands via Cloud Vision API and adapts results and recommendations as each consumer shops. Also uses Google Cloud BigQuery and Looker tools to integrate and understand data and trends in real time and formulate appropriate decisions.
RESULTS:
Models developed, trained, and refined in short period versus three to four years. Doubled sales during holiday season; continued sales increases. Now maintains one of the most extensive search and recommendation engines in fashion.
APPROACH:
Uses environmental platform developed under partnership between Google Cloud and WWF. Big data analysis/machine learning and other capabilities allow at-scale gathering and assessment of how different raw materials used in textile production impact the environment.
RESULTS:
More responsible sourcing decisions.
X
SUCCESS SPOTLIGHT: STELLA McCARTNEY
SUCCESS SPOTLIGHT: STELLA McCARTNEY
+
RESULTS:
Streamlined retail functions across networks. Accurately and efficiently receives, sorts, tickets, picks, packs, and ships merchandise from distribution centers to stores, including during peak retail seasons (back-to-school and holidays).
APPROACH:
Department store, specialty store, and ecommerce retailer moved infrastructure to cloud and leverages scalability of Google Cloud data warehousing and analytics solutions.
X
Success Spotlight: Macy's
Success Spotlight: Macy's
+
Cloud-centric technology helps retailers analyze the risk and environmental impact of sourcing decisions and/or using specific materials in the production process.
Delivering on the sustainability promise
Click to see Spotlights
Shopper flow and crowding analytics…and other signals that pack the potential to increase store operations efficiencies while enhancing the customer experience.
Recent consumer behavior
Workers’ available shift times
Retailers can only satisfy consumers’ increasing cries for stellar customer service—and run their stores with minimal headaches—when stores are adequately staffed. With AI and ML, retailers can allocate staff based on:
Working smarter, not harder
Identifying inventory sources, making it easier to handle demand for merchandise
Dictating actions to minimize or eliminate merchandise availability issues head-on—for example, proactively arranging for merchandise to be routed to stores in time to meet demand and conducting “what-if” analyses related to logistics.
Anticipating customer purchase behavior and needs
Managing product inventories in the back room and in warehouses
In the retail supply chain, AI and analytics play a pivotal role in:
Streamlining supply chain efficiencies
Meeting ever-changing customer expectations—in turn boosting productivity and efficiencies to foster short- and long-term growth—calls for:
Streamlining supply chain operations
Improving labor planning/workforce management
Answering the call for sustainability
Digital innovation and cloud-centric, AI-powered solutions foster operational transformation.
of consumers are actively focus on sustainability and use it as a criterion in deciding which brands to patronize.
[Future Commerce]
%
[Qualtrix XM Institute]
A “good” customer experience makes consumers 64% more likely to patronize a company that is new to them, but only 30% of consumers forgive a bad customer experience—even the first time around.
%
of consumers will trust a company that provides “good” customer service, but just 40% trust one that doesn’t
[Qualtrix XM Institute]
%
Today’s fashion customers expect more from brands than ever before. They won’t tolerate poor service, lack of merchandise availability in-store or online, or delivery delays. Increasingly, they favor brands whose practices align with their values of sustainability.
Taking Operations to the Next Level
How AI-Enabled
Power Fashion Retail Transfromation
When international beauty retailer Sephora moved its ecommerce operations to an AI-driven cloud platform, the company saw a 50% increase in product pageviews within the first year and a 2% increase in homepage conversions. Talk about fashion-forward.
Like Sephora, today’s leading fashion retailers—including Macy’s, Stella McCartney, and L..L. Bean—are taking advantage of innovative, cloud-based AI applications to reinvent their businesses from the runway to the register, powering new levels of supply chain efficiency and a more personalized and connected customer journey across every touchpoint.
How AI-Enabled Cloud Platforms Power Fashion Retail Transfromation
Bringing big business benefits
x
faster execution.**
**”MIT in conjunction with Google Cloud
x
more data-driven decisions
x
faster decision making
driving success
Leveraging AI and machine learning (ML) will spark success by allowing retailers to formulate
of companies queried for McKinsey & Company’s 2020 Global Survey on AI said it had boosted their sales and marketing revenues over the past year
%
cited increased revenues stemming from AI-supported product and service developments.
%
Learn more
• Macy's
• LVMH
• L.L. Bean
• Remy Cointreau
• Mondelez International
• Unilever
