Contact Center AI: The State of the Union - Build What's Next

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Trend Analysis

Contact Center AI: The State of the Union

Did you know 31% of CIOs say that they have already deployed conversational AI platforms? And that this represents a 50% year on year growth?

Much of this is driven by customer preferences. By 2023, customers will prefer speech interfaces to initiate self-service activities. Additionally, by 2023, 40 percent of contact center interactions will be  fully automated by AI.

Here are the facts: The latest advances in voice AI are opening the door to a massive transformation of customer experiences. The revolution driven by Contact Center AI (CCAI) is here today and you can benefit from it quickly.

Hear about the state of the Google CCAI offering through real-life customer stories.

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Webinar

Google Cloud’s 2021 Data Analytics Launches

Google Cloud announced closed to 15 services and programs spanning database, analytics, business intelligence and AI to help businesses gain value out of their data. Here’s a rundown of announcements throughout 2021 on analytics solutions and services such as Dataplex, an intelligent data fabric solution, Datastream, a serverless change data capture and replication service and Google Cloud analytics hub. Watch the video to get started with Google Cloud’s Data Analytics offerings.

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Webinar

An Overview of Google’s Data Cloud

Data access, management and privacy has been at the center of priorities for enterprises that are aiming to be more agile, reliable and data-driven. Google Cloud’s technology innovations spanning products like BigQuery, Spanner, Looker and VertexAI help organizations navigate the complexities related to siloed data in large volumes sprawled across databases, data lakes, data warehouses, and data marts in multiple clouds and on-premises. Watch the video to learn how companies are building data on Google Cloud for better analysis, security and management to achieve bottomline!

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Case Study

How Real Companies Are Innovating with AI Today—and the Benefits They’re Seeing

What do you get when you mix Target, women’s swim wear, and AI? “Joy!” says Mike McNamara, CIO and CDO, Target.

McNamara is just one of the many stories of real businesses conquering old challenges, and new disruptive industry challenges, with artificial intelligence.

McNamara, Nick Rockwell, CTO, The New York Times, Larry Colagiovanni, VP New Product Development, eBay, and Dirk John, CIO, LATAM Airlines, demonstrate how AI solutions allow businesses to find opportunity in chaos, innovation under tough conditions, and revenue in the most unlikely of places.

AI at Target

McNamara shows how AI is being applied to solve some of the most basic, yet critical, challenges that retailers like Target–and any business with large inventories—face. (start at 4:04)

AI at The New York Times

Nick Rockwell, CTO, The New York Times, shares how AI and big data tools are being used to leverage old assets and drive business ideas from them. (start at 12:18)

AI at eBay

Larry Colagiovanni, VP New Product Development, eBay, talks about how AI is helping eBay drive conversational commerce, help buyers sift through 1.1 billion items, and personalize the shopping experience.(start at 28:07)

AI at LATAM Airlines

Dirk John, CIO, LATAM Airlines, discusses how LATAM Airlines adopted advanced analytics tools in just a few weeks to accelerate the company’s understanding of their customers’ needs.(start at 35:58)

Trend Analysis

How Google Cloud Solutions Help Retail Firms to ABP(Always Be Pivoting)

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Data analytics and AI-based demand forecasting, product discovery that drive conversion and tools for modern store experiences--are the innovation trio to help retail firms to keep pivoting. Read Google Cloud's role in ushering them towards ABP.

For years, retailers have been told that they must embrace a litany of new technologies, trends, and imperatives like online shopping, mobile apps, omnichannel, and digital transformation. In search of growth and stability, retailers adopted many of these, only to realize that for every box they ticked, there was another one waiting.

And then the pandemic hit, along with rising social movements and increasingly harsh weather. Some retailers were more prepared to take on these disruptions than others, which crystallized a new universal truth across the industry: the ability to adapt on the fly became the most important trait to survive and thrive.

Today’s retail landscape has surfaced both existing and new challenges for specialty and department store retailers. Approximately 88% of purchases previously occurred within a store environment. Now, it’s closer to 59%, with the remainder done online or through other omni methods. 

With such constant change and upheaval, it can feel like the mantra now is ABP: always be pivoting. 

The big question isn’t just how to maintain constant momentum and agility—it’s how to do it without sapping your workforce, your inventory, or your profits in the process. The pivot is now a given. What matters is how you do it.

Adapting requires a flexible base of technology that allows retailers to shift and scale seamlessly with the needs of the moment. 

They need to be able to leverage real-time insights and enhance customer experiences rapidly, online and in the real world (not to mention the growing hybridization that’s AR and VR). They need to modernize their stores to power engaging consumer and associate experiences. They need to enhance operations for rapid scaling between full operations and digital-only offerings.

To help retailers achieve these goals and more, Google Cloud is honing a trio of essential innovations: demand forecasting that harnesses the power of data analytics and artificial intelligence; enhanced product discovery to improve conversion across channels; and the tools to help create the modern store experience.

In other words, here’s some of the biggest ways we’re ready to help you pivot.

Pivot point 1: Harnessing data and AI for demand forecasting with Vertex AI

One of the greatest challenges for retailers when building organizational flexibility is managing inventory and the supply chain. 

We are in the midst of one of the worst global supply chain crises, stemming from soaring demand and logistics issues brought on by the pandemic. This crisis has only heightened the challenge retailers face when assessing demand and product availability. Even in normal times, mismanagement of inventory can add up to a trillion-dollar problem, according to IHL Group (costing $634 billion in lost sales worldwide each year, while overstocks result in $472 billion in lost revenues due to markdowns). 

On the flipside, optimizing your supply chain can lead to greater profits. For instance, McKinsey predicts that a 10% to 20% improvement in retail supply chain forecasting accuracy is likely to produce a 5% reduction in inventory costs and a 2% to 3% increase in revenues.

Some of the challenges related to demand forecasting include:

  • Low accuracy leads to excess inventory, missed sales, and pressure on fragile supply chains.
  • Real drivers of product demand are not included, because large datasets are hard to model using traditional methods.
  • Poor accuracy for new product launches and products that have sparse or intermittent demand.
  • Complex models are hard to understand, leading to poor product allocation and low return on investment on promotions.
  • Different departments use different methods, leading to miscommunication and costly reconciliation errors.

AI-based demand forecasting techniques can help. Vertex AI Forecast supports retailers in maintaining greater inventory flexibility by infusing machine learning into their existing systems. Machine learning and AI-based forecasting models like Vertex AI are able to digest large sets of disparate data, drive analytics and automatically adjust when provided with new information. 

With these machine learning models, retailers can not only incorporate historical sales data, but also use close to real-time data such as marketing campaigns, web actions like a customer clicking the “add to cart” button on a website, local weather forecasts, and much more. 

Pivot point 2: Enhanced product discovery through AI-powered search and recommendations

If customers can’t easily find what they are looking for, whether online or at the store, they will turn to someone else. That’s a simple statement, but one with profound impacts.

In research conducted by The Harris Poll and Google Cloud, we found that over a six month period, 95% of consumers received search results that were not relevant to what they were searching for on a retail website. And roughly 85% of consumers view a brand differently after an unsuccessful search, while 74% say they avoid websites where they’ve experienced search difficulties in the past.

Each year, retailers lose more than $300 billion dollars from search abandonment, or when a consumer searches for a product on a retailer’s website but does not find what they are looking for. Our product discovery solutions help you surface the right products, to the right customers, at the right time. These solutions include: 

  • Vision Product Search, which is like bringing the augmented reality of Google Lens to a retailer’s own branded mobile app experience. Both shoppers and retail store associates can search for products using an image they’ve photographed or found online and receive a ranked list of similar items.
  • Recommendations AI, which enables retailers to deliver highly personalized recommendations at scale across channels.
  • Retail Search, which provides Google-quality search results on a retailer’s own website and mobile applications.

All three are powered by Google Cloud, leveraging Google’s advanced understanding of user context and intent, utilizing technology to deliver a seamless experience to every shopper. With these combined capabilities, retailers are able to reduce search abandonment and improve conversions across their digital properties. 

Pivot point 3: Building the modern store

Stores are no longer places for just browsing and buying. They must be flexible operation centers, ready to pivot to address changing circumstances. The modern store must be multiple things at once: a mini-fulfillment and return center, a recommendation engine, a shopping destination, a fun place to work, and more. 

Just as retail companies had to embrace omnichannel, stores are now becoming omnichannel centers on their own, mixing the digital and physical into a single location. Retailers can use physical stores as a vehicle to deliver superior customer experiences. This will demand heightened levels of collaboration and cooperation between stores, digital, and tech infrastructure teams, building on the agile ways they have worked together.

In many ways, it’s about allowing our physical spaces to function more like digital ones. Google Cloud can help by bringing the scalability, security, and reliability of the cloud to the store, allowing physical locations to upgrade infrastructure and modernize their internal and customer-facing applications. 

Think of it as when a new OS gets released for your phone. It’s the same small, hard box, but the experience can feel radically different. Now, extend that same idea to a digitally enabled store. With the right displays, interfaces, and tools at a given retail location, the team only needs to send an over-the-air update to create radically fresh experiences, ranging from sales displays to fulfillment or employee engagement.

Such an approach can enable streamlined experiences for both customers and store associates. For instance, when it comes to the modern store’s evolving role as a fulfillment or return center, cloud solutions can help drive efficiency in stores through automation of ordering, replenishment, and fulfillment of omnichannel order selection.  

Similar tools for personalized product discovery online can be applied to customers in the store, helping them to browse and explore, or even create a tailored shopping experience. 

The impact of store associates can be maximized by equipping them with technology to provide expertise that drives value-added customer service, as well as increasing productivity in stores by streamlining operations, thus lowering overhead cost. At the register, customers should be able to enjoy frictionless checkout while ensuring reliable, accurate, secure transactions.

Google Cloud can help retailers transform

The ability to adapt and pivot to meet today’s changing consumer needs requires that retailers rely on modern tools to obtain operational flexibility. We believe that every company can be a tech company. That every decision is data driven. That every store is physical and digital all at once. That every worker is a tech worker. 

Google Cloud works with retailers to help them solve their most challenging problems. We have the unique ability to handle massive amounts of unstructured data, in addition to advanced capabilities in AI and ML. Our products and solutions help retailers focus on what’s most important—from improving operations to capturing digital and omnichannel revenue.

Case Study

Largest Beauty Retailer in the US Powers Digital Transformation with Google Cloud Smart Analytics

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Leaders at Ulta Beauty, a chain with over 1196 stores in all 50 US states, knew they had an opportunity to leverage data analytics and machine learning to reach customers in new ways, enhance the guest experience, and continue to grow their active loyalty member base. They partnered with Google Cloud.

Digital technology offers increasing flexibility and choice to consumers. As a result, the retail industry is dramatically shifting toward more tailored and personalized experiences for shoppers, and businesses are rethinking how they deliver value to customers.

This couldn’t be more true for the beauty retailing industry where leading companies are turning to digital technology to create customized shopping experiences.

At Google Cloud, we’re particularly excited about our work with Ulta Beauty, the largest beauty retailer in the United States with more than 1196 stores in all 50 states, and how the company is using Google Cloud technology solutions to power personalization and redefine beauty retailing.

Established in 1990, Ulta Beauty has had incredible success as a company, and as customers become more discerning and curious about their purchases, the company is finding new ways to meet their changing needs.

Recently, leaders at Ulta Beauty recognized a huge opportunity to complement and enhance the shopping experience by helping beauty enthusiasts navigate through more than 500 brands and 25,000 products carried in their stores and online channel.

They decided to leverage the data from Ulta Beauty’s successful Ultamate Rewards loyalty program to create and offer more unique and personalized user experiences.

With more than 30 million members generating data through sales, transactions, product reviews, and social media engagement, Ulta Beauty’s Loyalty Program creates a comprehensive data set, and the company sought the right technology partner to help organize, analyze and transform that data into valuable insights for its customers.

Ulta Beauty’s leaders knew they had an opportunity to leverage data analytics and machine learning to reach customers in new ways, enhance the guest experience, and continue to grow their active loyalty member base. After considering a number of cloud providers, they chose to expand their existing partnership with Google Cloud.

“Google Cloud listened to our needs and worked in tandem with our engineering team to address our challenges,” said Michelle Pacynski, vice president of digital innovation at Ulta Beauty. “The ease of working with the Google Cloud team and their breadth of experience made the decision a no-brainer, laying the foundation for a great partnership.”  

In 2019, Ulta Beauty announced it was working with Google Cloud Platform to unify and organize its data, using:

  • BigQuery to perform data analysis and generate dynamic content, personalized product recommendations, and event-based messages for customers.
  • Cloud Storage to provide highly available, secure, resilient and cost-effective access to data across the entire enterprise.
  • Compute Engine for the high-performance scalability needed to grow with customer demand while painlessly migrating existing applications to the cloud.
  • Anthos to build a hybrid cloud foundation that allows their applications to take advantage of all this data, combining the power and flexibility of GKE with the ability to leverage their existing investment in secure infrastructure on-premises.

Our partnership with Ulta Beauty has enabled increased engagement with customers in store and online, and the creation of new tools and capabilities, including a new Virtual Beauty Advisor tool to deliver tailored recommendations and help shoppers choose the right products, and a Customer Conversation Platform that’s enabling deeper connections with guests, ultimately driving customer loyalty.

“It’s been a really efficient process so far due in part to the ease of working with the Google team,” said Michelle Pacynski, vice president of digital innovation at Ulta Beauty. “They’re experienced, approachable, and their can-do style makes for a great partnership. They listened to our needs and worked in tandem with our engineering team, figuring things out, and getting it done.”

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