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Driving business transformation in retail using AI

Carrie Tharp
VP Retail & Consumer - Google Cloud at Google
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Google Cloud Next 2020
July 14, 2020, Online, San Francisco, CA, USA
Google Cloud Next 2020
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About speaker

Carrie Tharp
VP Retail & Consumer - Google Cloud at Google

Innovative Chief Digital Officer/Chief Marketing Officer with experience driving growth and business transformation in retail, consumer products and eCommerce based businesses. Creating data driven, customer centric strategies that drive growth through new customer experiences, digital innovation, and business model expansion. Currently focused on evolving retail capabilities for the new digital age - dedicated to building teams and experiences to serve customers in new and compelling ways.

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About the talk

Watch this discussion of how retailers are working with Google Cloud on machine learning and AI to transform their business. Retailers face numerous challenges in their business every day. This session presents an overview of the AI Platforms, products, and solutions Google Cloud is building to address those challenges across digital and omnichannel personalization, merchandising, the supply chain, and optimizing operations. Hear real world examples of how customers are using Google Cloud AI in practice today.

Speaker: Carrie Tharp

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product: Cloud Retail Solutions, Cloud AutoML; fullname: Carrie Tharp;

event: Google Cloud Next 2020; re_ty: Publish;

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Hi. Welcome to reception and driving visit transformation in retail using a guy and I'll eat every tale for Google Cloud. I'm excited to be here today to chat a little bit about the state of AI in retail and how Google Cloud. It's helping Implement and then share some best practices. When you think about what's going on in retail today, the landscape is certainly, changing piece of change is accelerating and covid-19 has certainly changed in many plans. What's more important than ever is the use of data in your business, to help unlock value, whether that's changing customer experiences.

Improving operational performance. What do you think about AI in ml in your business? If it's a crucial component to the future of retail strategies and choices that you may be making today on your platforms and capabilities to be a big part of your performance tomorrow? Very passionate about driving the adoption of AI and ml in retail research shows that they're certainly value to using l. A, i n m l in your business, it can help you make more data-driven decisions, five, times, faster, decision-making, and three times faster to execution However

AI is really still seen in its high cycle. For retail we did some recent research in the specialty and department store space and found that 60% of retailers had twenty or more pilots in progress on that. Only 45% of those Pilots had been transition to full implementation in production and I'm looking at those that have been implemented. Retailer's, only. 40% of them represented. The high-value use cases potential opportunities to still a big opportunity

to go after. We are the biggest value in retail is So, what's holding people back in our discussions, we find that data availability continues to be an issue. This really covers a whole host of problems. Everything from data being siloed and not being able to get at all the different combinations of customer. Transaction product in supply chain, data to having issues with data and data modeling. Stuck in is technical Talent, do you have enough resources on your team from a technology standpoint or the data and analytics team do after a

lot of these more complicated, it take more preparation of the data and a deeper understanding of the business. Last is financial constraints. So we all have kind of scarce resources when we think about the capital and expense were able to deploy their businesses. And so do you have the right amount of resources to go after the opportunities that you see ahead of you as a team? With all the challenges of implementing a high-end retail, it's more than ever to focus. And prioritize we've done research to understand where the value is locked up in retail. And I found that the top 10 to

15 use cases is actually where most of the value lies out of hundreds of Youth cases, you could be thinking about working on, Weather is in Food, Drug in math, or specialty and department store will be on this list. There's a couple of teeth around inventory, customer experience and store operation Google can join you. In these conversations of participation to help you understand what might be the best opportunities for you to go after short-term and in the longer term. How Google can help from an anti perspective is in three key buckets.

First were Building, industry-specific Solutions, that are pre-built and ready-made to help accelerate. The transformation example would be Vision products or customers to take pictures of product catalog. Second is using the building blocks that we've already established. One of the examples here is dialogflow, rather than trying to take on natural language, understanding to create a customer care or voice interaction with your customers. You can use dialogflow as a jumpstart to creating those

experiences. And third is been just using our platform to custom build yourself. There's a variety of use cases that you may feel are very specific. Your business leverage components that already exist. When we think about these pre-built Solutions, we're focused in three key areas. First, it's helping drive digital and omni-channel Grove, think of everything. That's a part of Driving Experience and your e-commerce business. Stuck in its helping. You accommodate eccentric customer-driven retailer. This is all of the data platforms and a, i n m l,

that's needed to help you drive new personalization experiences and understand your product into inventory data. That our third is operational performance Improvement. So this is helping you unlock operational value inside. The p&l weather is store operations or reducing your cost in your infrastructure. First, let's talk a little bit more about driving digital, an omni-channel Revenue grow. One of the cheap seats here is helping a ball product, Discovery when you think about e-commerce, today from site to

using a search text box. I'm customer shopping. Journey, looks very different than that. So we've been focused on providing solutions, that help you evolve that customer interaction. All retailers are dealing with several key trends. So first, is the changing Dynamics in shopping visit. So covid-19 has changed how much retailers have customers? Visiting your store, and how big their back its eyes is when they visit. And so, it's become more important than ever to provide new digital. Discovery experience says, second. Its environment has

experienced a big priority, making sure that your customer has all their expectations met whether or not, they can interact with an Associate has become critical. And then personalization, this has been a theme in retail for years, but it's now very important to make sure you're putting the right product in front of a customer. Wherever there's Journey, may be taking place. Our offerings are focused on reducing friction for Shoppers first is Vision product, search. This is the capability that I mentioned, that allows you to use visual images to start the catalog. So think of a

grocery store customer instead of building their list, by writing it down, or searching for it on your ass, they could simply take pictures and preload their shopping list. Max's recommendations AI this is focused on providing personalized recommendations for your choppers with a broad understanding of their Journey. This is bringing the power of Google Search directly to your e-commerce website. What do you think about recommendations Google call brings best-in-class, recommendation, based on our experience in building recommendations as the

foundation for several of our products that are billions of users worldwide. Recommendations II Works in three key step in a greater catalog and user events date of recommendations that I do many of the tools you're already using like merchant center, Google tag manager, Google analytics, 360 Google cloud storage and big fiery as well as other data sources in most cases without having to write any code. Once your data is in, with a few clicks, you can choose your model type, Define your objective, and begin training, your

model and three to seven days, the initial model training and shooting and you'll see a visual indicator in the dashboard. That the model is ready to query. You can then begin serving recommendation to your customers. You can now, also visually preview the recommendation generated by the models before you serve them in production, to make sure that your setup has been satisfactory. The recommendations are than constantly improving in optimizing. Refreshes. Sephora is a customer that's using our recommendations. Aiud is certainly a

space that recommendations can be very important journey and they've seen an increase in rates as well as their conversion. How can you use data to effectively predict customer and what your demands might look like? Demand forecasting is an example of an area that is critical to retail all the retailers belabor their forecasts, trying to make sure that they don't miss out on Revenue opportunity to make sure that they don't have excess product sitting around. This is a product that we have that's in our Early Access program We took on this face because the demand

forecasting is still a challenge for many retailers today retailers often have trouble integrated new signals and insides into their forecasts are often based on static views of what happened last year and maybe some more advanced statistical modeling, but most retailers versus Rider sitting today is understanding new products and new categories not having enough information to really understand what the demand for that product. Maybe making those decisions based on intuition thoughts or similar

product performance, many forecasting models. Don't really understand local demand impact of things like whether consumer behavior and even now shelter-in-place orders, Google demand forecasting leverages our best-in-class AI in ml and datasets from across Google is designed to integrate with your current systems and does not require a written replace a spot for him that you were merchants and Planters maybe using today, explainable Ai and helps you better post for cats review, where you're getting

for and what's really expecting all Insider forecast for customer acquisition allows retailers to model future planning as well as she has to feed into allocation replenishment and planning system. We are now building out the end-to-end solution and partnering with a handful of retailers. In the Early Access program to take the solution from development to lunch, in addition to the solution, we were also working with retailers who are investing in their own efforts in this base

using r. A, i n m l platform offering. And finally, we also work with an extension to Lloyds and isvs like 09 who can help you get results quickly and realized your data with integrated and out-of-the-box solution. One example of a retailer that were working within this space, is car for one of the largest grocery retailers in Fran. We parted with them across several facets of their business. Exciting area is artificial intelligence. Solutions like optimizing a product assortment, it's very important. As you guys know, to have a deep understanding of what's most relevant,

an individual store location and so, using our recommendations and AI capabilities to understand that assortment level has been a great value to Carrefour. Netflix, talk a little bit about driving operational excellence, providing the best-in-class, customer care and support call centers and Chad has always been important. That has become ever more important in the times of covid-19, as call centers have been overwhelmed with all sorts of questions from. Do you have certain inventory in stock and what are your special shopping

hours? Like all organizations retailers are facing a revolution in customer care of retail, customers will consider switching to a different retailer. If they had a bad experience and estimates show that over the next several years, I will be a, a large component of providing a service to customers in. Call centers important to be thinking about how you artificial intelligence and make impact in your business. Google Cloud contact center, AI solution is built for this new world

based around a conversational cord that understands human interaction and incorporates. The contact is first religion, a I handled incoming calls or messages and engages in natural human-like dialogue to handle common. You cases and clothes, including it having to go off-script when the call can't be handled automatically, it's past a human agent. And the agent, is this day, I stepped in to support with the relevant content in the knowledge base in contacts about the user and their situation. The inside, then surfaces Trends analysis to help

the entire system. Improve for retailer is the fact that is centralized means you can apply consistent intelligence across every application in the customer Journey. The biggest call Stephen can often be found from deflecting voice calls into your contacts Center in the past because conversation can Meander and Ivy are trees may not be able to adapt the inability to flex to human conversation style. His also has a limited ability to agents in real-time contact ability to go off-script. So you can work outside. The

predefined flow answering complex questions, full of unexpected, stopped and stars were implied. Meaning Contact center. A I also has the ability to handle multiple use cases for your customers like taking a payment updating information, like a phone number, giving them information about store hours and allows you to fully automate routine tests. And further, deflect call, you can start with an easy use case and grow your adoption depending on your organization during covid-19. For example, with a deluge of customer inquiries to

the store timing and special hours are team. Offered up a rapid response virtual agent that could be set up in days and take the volume of calls off your busy Cajun. And most importantly, make sure that customers felt supported through the period of heightened anxiety. Spencer is one of the customers we worked within the context Center AI space. They work with our partner developed to leverage, dialogflow to help manage their contact center interactions. Sensor is one of the best belove retail brands in the UK with over thirty million loyal customers and they had

nine million calls a year. You can imagine that's a lot to understand the different things. Bad customers may be calling about to that store, but also brought a question that can be answered more effectively using dialogflow. They were able to reduce that call volume to the stores by 50% and Route more than 7 million called into. The inner know that we talked more about our Solutions, in some of the challenges that retailers have using and ml in their business. I'd like to share a little

bit about some of the best practices. Across all the customers were working with first is understanding your data first strategy. Making sure you're thinking about your data and a holistic platform based approach that really it expands to meet all the needs you have going forward, unlocking, those data silos and bringing together the product transaction customer and supply chain data. Second is Alia truly a team sport. Getting evaluated, out of a, I can often sit at the intersection between several different stakeholders in retail, whether the merchant

the planners, or the marketers, they may have a very different view of where Valley cyst and how your brand should really take on using a dye. Your CEO is Austin, your top Advocate to help bring the adoption of a, i n m l in the business. Bird is thinking about how you can test for scale. So given there so many different use cases you could do. After if it's a best practice to use, proof-of-concept to prove the value to your leadership team and then get kind of resources and more attention to move forward, with more youth kids is going forward. It can give Executives

and you were stakeholders. A firm sense of what type of value they can expect and how they can be interacting with data to drive value. And then left is going mainstream. So, thinking about how you can better exposed in inside, to all of the universe within your organization to help visualize and help people understand what the day. Might be telling them. It will speed rate of change and bring people along the journey much faster. This is kind of taking data out of the rearview mirror and putting it into something that

directs the future. Your organization. Now that we talked about, it Solutions best practices. I'm excited to see what you can do to drive the adoption of AI and ml in your business. We have a variety of resources available. If you're interested in learning more about each of these Solutions, customer reference examples to go a little bit deeper, as well as partners that can help you on your journey. I'm excited for what comes ahead and retell is at the center of All Digital transformation, and there's great things to come.

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