Microsoft Business Applications Launch Event | April 2021
-We can help our clients turn their own data into more valuable insights. -In recent years, we've become much more of a data-driven company for our decisions. -This will form a very important part of the next generation of education of surgeons.
-Having the tools and resources and technology to do your job more efficiently and effectively definitely makes employees happy. -Rockwell's swift digital transformation has enabled us to empower our customers. -Hi everyone. It's James Phillips,
President of what is now the Digital Transformation Platform Group at Microsoft. And, you know, it's my honor. This is my favorite time of year actually, where I get to come out on stage and represent the great work that's being done by the team building and operating Dynamics 365 and the Power Platform. Boy, do we have a bunch of good stuff to show you today. Super excited.
We're going to look at a lot of demos, a lot of customer cases, and talk in depth about the new capabilities you can expect coming in this first wave of 2021 between April and October. But I'm going to spend a little bit of time before we get into the demos talking a bit about sort of the frame that we're operating in. You can't ignore the fact that for the last year, and certainly for the last period since we've been working on this, this first wave of release, we've been in a really tough situation.
I think isolation is the word that comes to mind, social distancing, please stand here, stay separated from others. Hard to be with your customers, hard to be with your employees, hard to be with your team, and it's created a lot of stress, quite frankly. It's also created a real need for innovation, for thinking differently about how we can go engage our customers, how we can bring our teams together. And that's the work that we've been doing, you know, notwithstanding that we've been mostly, at least at Microsoft, working from home. We've continued this train of innovation. You know, we've been coming to you month after month after month, and semiannually with these major release waves, and we've continued that.
Today, we'll talk specifically about what we're doing in wave one, again, both Dynamics 365 and the Power Platform. So, let's talk about some of the customers that we've been fortunate to engage and partner with over the last six months, new to the family, if you will, Bank of New York Mellon, HSBC, ICICI, Visa, Coca-Cola, iconic brands spanning the globe. Today, we're very proud to say that over half a million companies, 97 percent of the Fortune 500, are leveraging Dynamics 365 and the Power Platform to transform their businesses.
Now, I want to talk a bit about the context that we're living in and really the fundamental change that's occurring in business applications and in business process. This is you. This is your customer, in fact. Let's say that you're a manufacturer. You've got a customer that you've sold a piece of equipment to.
You can see it right there in the middle, it's that thing hanging behind the person. Your customer is an auto manufacturer. They're using this equipment to make cars.
Now, one day, there's a problem. A piece of equipment goes down. It's an emergency. The production line is stopped. Now someone picks up the phone.
They call your service center. Answer the phone. Now an app is opened and that application is used to react, to react to a problem that now exists. But that's what applications have really been all about for the last 40, 50, 60 years in our industry. Someone opens that app, they start typing into a forum, a little bit of data starts trickling down into a relational database, and now you can go serve your customer. It's a very reactive process that has really been unchanged for all time.
But something is fundamentally changing, and really for the first time in the history of our industry or in any industry where technology is playing a part in automating business processes. See, we're all connected. We're connected to our customers, to our suppliers. Our products and services are connected back to us as our customers use them. If you look behind the scenes, what you find is data is beginning to come out of everything, and it's coming first, not because someone typed it into a form and stored it off in a relational database, but because every car, every thermostat, every social media update, everything is increasingly a source of insight.
Those organizations that are able to harness that information, that data, and turn it into value are the organizations that can predict the future, that can anticipate customer needs, that can know that that piece of equipment is on its way to failure before it actually fails. What we build at Microsoft, in the Microsoft Cloud, is a platform system to do precisely that. It starts with this planet-scale cloud.
You don't go store terabytes, petabytes, go into yottabytes of data in relational databases sitting in decades-old, rinky-dink data centers. You need a planet-scale footprint, and that's what we've built. Your data, whether it's big data, little data, streaming, relational, unstructured, we have a place to put it.
We've got an AI platform inside of Azure that can take all that data and turn it into predictions. We're the first company on planet Earth that achieved human parity in understanding natural language. Those insights, those predictions move up where the Power Platform can turn them into applications, into automations. And on top of that, with Microsoft 365 and Dynamics 365, we embody that entire ethos into our applications and create systems that predict the future.
This cloud, the Microsoft Cloud, is the vehicle for moving into the future, and it is as different from the past as it could possibly be. Now, if you look at these applications that are sort of constructed sandwich-like through this cloud infrastructure, we put in the hands of any customer through these layers of technology and with our ISV partners the applications and automations that allow them to better engage customers, better operate, to create a resilient supply chain, and to do a myriad of other things that we'll look at today as we go through this. Now, if we go back to the scenario we had before, now an application in the modern world looks very, very different. The machine is continuously sending information from your customer back to you.
An anomaly detection model can predict that that machine is on its way to a problem before it actually has a problem. That allows you now, through that application, to reach out effectively, whether physically or digitally, to repair the situation before it actually creates a problem, before it takes down the auto manufacturer's production line. That is a game changer. But that's just one business process in one industry. The reality is that every business process, from your suppliers to your assets, employees, customers, products, services, everything is changing.
There's an opportunity to reimagine every single business process in every industry. If you look at what we've built with the Microsoft Cloud, we have a collection of products and services that align to allow you to go on the journey of reimagining each one of these business processes. The entire cloud comes together in one holistic unified digital transformation platform with consistent security, identity, compliance boundaries. To take it one step further, over the last six months we've introduced five industry clouds that allow us to take those horizontal business process domains and tailor them for specific industries. We're going to show you that today with our new Retail Cloud that we announced earlier this year.
So, we're going to focus today primarily on the customer experience part of this business process spectrum. It's where a lot of the change is happening right now, and I think the most exciting change. We're moving from a world where you open up applications and create some drip marketing campaign or take a case from your customer and type it into a form to a world where you deeply understand your customer, where you predict their needs, where you communicate the right message at the right time, on the right channel, in furtherance of the right business outcome, so that your sales people, your marketing campaigns, the offers that you make in your commerce system all align and are all fueled by this intelligence that the Microsoft Cloud provides.
So, now let's get to the good stuff. We're going to go through some customer scenarios and really show all these new capabilities in their full glory. We're going to look at Bank of New York Mellon on the customer experience side, Patagonia for our Retail Cloud, Rockwell Automation with Power BI, and then the broader Power Platform with Coca-Cola. So, let's get started with our first scenario, Bank of New York Mellon.
And I'm going to pass it over to my friend, Lori Lamkin. -Hey, thank you, James. And thank you all for joining us at our launch event this year.
I'm Lori Lamkin and I lead our Marketing Application within Dynamics 365. I'm excited to show you today how our business applications lead with insights and data to elevate the customer experience. In the past, humans help the apps. Humans put data into the apps, maybe ran some scenarios, told the apps what to do, and looked backwards to figure out how to best react.
But now the apps collect data on their own and bring a lot more data as well. We're in a world where apps help humans. Apps can alert us with relevant proactive insights and recommendations that have already been analyzed to deliver the best possible set of customer outcomes. All of this enables a company to deliver the best possible customer experience. When we talk about this customer experience obsession, this isn't just for marketing teams and it's not just isolated to the front office.
Any part of the company that interacts with the customer, from front to back office, needs unified data and insights. And teams from Marketing to Sales, to Customer Service and Customer Experience all need to interact with customers through any channel, both human and digital. Today, we're going to show you how we're enabling organizations to elevate the end-to-end, modern customer experience with some of our new products and features. Let's show this through the lens of one of our customers, Bank of New York Mellon.
Here now is Akash Shah. -BNY Mellon is the oldest bank in the United States and a global provider of market infrastructure. Our ambition is to lead our clients through the next generation of change that's happening in financial services.
So, we think that comes from being, one, visionary in our ambitions for our clients; two, strategic and bold in how we work with them; and three, having a sense of urgency in how we execute. We're really focused on being the most trusted institution that you're working with, and it starts with protecting your data. So, we're obsessed with not just the security but the values you use when you're thinking about how to provide clients their data in a way that they can use it best. Our way of approaching our clients is really based on bringing the best of this entire institution, its global reach, to every client we touch, every single day. And it requires us to bring our expertise, our technology, and our perspective in every interaction. The data and analytics solutions business for us is one of our primary growth areas, and Microsoft's at the cornerstone of that growth.
But there are going to be a number of different areas where Microsoft's technical prowess, our expertise in financial services just make us natural allies in a very dynamic financial services industry. -Akash said it very well, delivering great customer engagement is a key differentiator for all organizations today. Customers expect organizations to know them and to act like they know them, through personalized engagement in tangible, everyday ways. The last great interaction with one company is the standard for the next one. With key investments launching during the April wave, Microsoft has the only comprehensive data-first, AI-powered customer experience platform.
A single platform to connect data, to enrich it, to make sense of it, and to activate it, all while maintaining trust and privacy. This platform enables a comprehensive personal touch, breaking down silos in your organization, unifying data, and unifying orchestration to engage customers through their actions. This is permeating every business.
Let's talk here now about how financial institutions are shifting from a reactive state of waiting on a client to delivering a single, consistent, personalized and proactive experience anywhere and anytime. A good example of this is sustainability in finance. How do you know which clients have interest, when they have interest, and what specifically they're interested in? A modern experience ties data and signals together to engage proactively. Let's look at a demo that shows how Microsoft can deliver meaningful client experiences in moments that matter. We'll see this through a combination of scenarios that Bank of New York Mellon is using, as well as newer scenarios becoming available to customers. So, here is Lisa as an example.
Lisa works for a large organization that is a client of the bank. Using audience insights, the bank pulled together demographic, behavioral, and transactional data across previously siloed data systems. The result is a rich, multidimensional view of Lisa's financial objectives and trends. And the more we know about Lisa, the more tailored the experience we can give to her. So, let's layer in data from external sources on top of this profile.
New enrichment capabilities in audience insights include direct third-party connections to some of the leading data services, such as Leadspace, Experian, and HERE Technologies. In addition to those direct connectors, audience insights now supports custom enrichment from any source, allowing organizations to add enrichment on any type of data. So, here we are showing the bank leverage third-party data to include job roles and decision-maker status in our understanding of Lisa. With that enrichment we just applied, I can now use that data to create more targeted segments.
I'm narrowing down the criteria to create a segment of senior decision-makers. This is specific and this is actionable. But we can do even more. We can imply intelligence to generate KPIs and recommendations for you. The April wave brings several out-of-the-box models to audience insights, including customer lifetime value, subscription churn, transaction churn, and product recommendations. In the past, it would take data scientists weeks or even months to build a model to match the accuracy of what audience insights can offer right out of the box.
Business analysts with no coding experiences can train these models from the first day to be extremely shaped and customized just to that organization's needs. This allows the model to help the bank predict other products that a client may be interested in. Because it's so easy to use, multiple models can be crated on the fly to experiment with different inputs for predictions. With the April wave, we have connections to new services, such as Facebook ads, Manager, Google ads, and Azure Synapse Analytics.
That means you can make use of data and insights from across familiar solutions with no cliffs, even into developer tools. So, let's go back to Lisa. She's browsing some articles the bank published around sustainable investing services. With her consent, the bank can use engagement insights to get a picture of the browsing behavior, such as the pages she's visited, the device and the geography she's located in.
Her visits specifically to those sustainable investing pages signal something to the bank that they can be proactive about through targeted customer journeys. Signals like these can be captured both individually as well as holistically, providing the bank with a rich picture of how customers are engaging with their digital assets. There are a variety of out-of-the-box reports, such as real-time usage, to help the bank understand their audience by device, geography, and other criteria. We also have web and mobile funnels to help show how customers are progressing through a sequence of assets. But even better, let's pull in information from the segments we created earlier on senior job titles and combine that with the behavioral data of website browsing. This can immediately show differences in behaviors between segments.
Do people with senior job titles browse differently than people with junior job titles? Does owning certain products or services impact how they engage the website? These can be valuable signals in understanding digital behaviors. So, you just saw how you can build a detailed picture of your customers across what was data silos within and outside your company. Now let's turn that into business results. We do that with customer journey orchestration, part of Dynamics 365 marketing.
This is totally new and it's going to change the way that you interact with your customers in a one-to-one, very personalized way. Let's take a look at how easy it is to build a customer-led journey that sends webinar invitations around sustainable investing but only based on client behaviors. So, in the case of Lisa, digital signals were captured from various sources around her browsing of multiple sustainable investment pages in a short time. This is a real-time trigger, activating a journey while she's still on those webpages.
The authoring experience is easy to use. We'll add in an entrance criteria in this case, drawing from the segment information that Customer Insights provided. We have the option to use natural language which can dramatically ease the process.
Customer consent is automatically taken into account so that every engagement respects their preferences. This journey will now start real time when an individual is on the webpage, browsing sustainability articles, and who are also part of the targeted segment created by Customer Insights. The next step is to consider how best to interact with the customer, and that means picking a channel. But each customer is an individual with their own preferences and behaviors. Instead of sending every customer through a one-size-fits-all model, we want to pick the very best channel for Lisa. This is as easy as selecting a tile from our toolbox.
Customer journey orchestration allows us to insert a step that intelligently selects the most appropriate channel based on that individual's past behavior and characteristics. This will dramatically increase the effectiveness of our communications. With the channel options in place, let's create the content right from within the tool. This isn't just easy-to-use authoring, it's a brand-new email editor assisted by AI as you author, making it easy to create beautiful and effective content.
In this case, you can see context-based suggestions for images, and real-time previews make it easy to picture what Lisa will see. Let's check out the advanced personalization capabilities. We've rebuilt personalization to be more powerful and easier to use with the new UI. You can now use the data from Customer Insights profile, including all that enriched affinity information, things like what your customers are likely to be interested in.
You can use that data that was passed into the event trigger and, more importantly, will be supporting all of the data in Dataverse. This level of integration between content authoring and the Customer Insights Customer Data Platform is unparalleled. And this isn't just for email. For other channels, like SMS, the bank can create engaging, personalized content very quickly.
As we finish with the content, we can consider downstream actions. A customer-led journey means responding and reacting to customer behaviors and events. With the authoring experience, we can link to any number of events. For example, we can add a step that looks at webinar attendance. If Lisa is going through this journey and she ends up attending a webinar, the journey can respond to initiate action from the sales team.
From digital interactions to human interactions across your business department's orchestration and, therefore, a cohesive customer experience is truly crossing organization silos. But how can you tell if the journey is successful? Each journey is tied to one or more business goals, allowing us to gauge effectiveness well outside traditional means. In this journey, we'll set a goal that measures the percent of clients who ultimately became paying customers of the bank's sustainability investing services. We can tell how many customers went through this journey and achieved the bank's goal, but we can also tell how other journey experiences accrue to that same goal.
That is truly being able to measure impact. From a client experience standpoint, Lisa gets personalized invitations to attend an environment sustainability governance webinar delivered in real time based on her website interest and on her preferred channel. She couldn't be happier about how the bank treats her like the individual that she is.
Lisa then attends the webinar and customer journey orchestration connects her with the sustained investment sales team to have further discussions. For the bank, managing this type of personalization at scale across every business line is critical. As Lisa and other customers of the bank engage with the content delivered to them, it builds a feedback loop. Key insights show how journeys are performing and how many customers are going through the funnels. The bank can continue to adjust for the most optimal journey, and customer journey orchestration will use analytics and AI to help recommend, experiment, and optimize. At a macro level, analytics help give a bird's eye view of the entire set of journeys.
Customer journey orchestration becomes a foundational part of delivering great personalized engagements, and doing so in an easy, seamless manner. What we just saw was an unparalleled level of integration between customer journey orchestration with Customer Insights in Dynamics 365 marketing. It shows how you can orchestrate real-time, customer-led journeys triggered at the right moment with one-to-one personalization and breaking down data and customer experience silos.
Now I'd like to invite Tom to talk about how additional teams in Bank of New York Mellon can also use our platform to deliver unparalleled customer experiences. Tom. -Thank you, Lori. Let's look at how this foundation of data insights and journey orchestration is changing the landscape of client engagement, especially in sales and customer service. Let's come back to Lisa who previously attended the ESG webinar.
She hasn't been responsive to direct calls from the ESG team, so customer journey orchestration is teeing up other options for her. In this case, it will send her an invitation to schedule a remote consultation, and it will deliver this through her preferred channel, email. Leveraging the new self-scheduling capabilities, Lisa can quickly go through the process. Self-scheduling is able to offer times with individuals at the bank who can speak to the specific interests she has.
It can be used at scale, managing millions of combinations of resources, locations, time slots, and more. As Lisa receives the confirmation, the bank can also activate any pre-appointment tasks that are needed. For example, the bank can use customer voice to help collect any necessary information, such as specific ESG investments or other funds that Lisa is interested in. Customer voice can be leveraged as a data collection and information enrichment tool across any use case, including kicking off different journeys. Now it's time for the virtual consult with Lisa. And Robin has been assigned from the bank side.
Robin is an ESG specialist and spends his day to day working with clients. He can leverage sales with new embedded teams calling to conduct the call. This means that Robin can stay within the same experience he uses regularly and still carry on the interactions he needs to. Let's take a look. -Hello, this is Lisa. -Hi, Lisa.
This is Robin Klein from the bank. How are you? -I'm good. How are you doing? -I'm good. Thanks. I'm giving you a call based on the time you selected and hoping to chat with you about ESG analytics options. Is now still a good time? -As the call continues, throughout the interaction, live transcription turns a traditionally analog channel into a digital and intelligent one. Robin can focus on Lisa and the conversation instead of simply trying to keep up with typing notes.
The power is in using the tools you are familiar with today, such as Microsoft Teams and Dynamics 365, and enabling leading AI within those experiences seamlessly. Business insights processing during the call flags key action items that Robin may want to follow up on, as well as competitors and other information. This is tangible AI, something that can help cut down immediately on missed action items, overlooked requests, and more.
We saw how Robin is able to engage on an individual conversation. That is also true at the macro level. Sellers often work with many clients, and visibility into their book of accounts becomes critical. With the new Deal Manager capability, sellers have the visibility they need in a single screen. Here, we can see a hybrid view of opportunities, including key information such as the AI-driven opportunity score.
Robin can interact with the opportunities in line without leaving context of its overall view. He can see key information about the opportunity and act on it immediately. Robin also needs to collaborate with others.
A new Native Teams Collaboration within Dynamics 365 allows this to happen seamlessly. Here we see Robin can collaborate individually or with entire virtual teams at once. In this case, Robin needs help with a request, and a colleague, Katie, responds right away. For Robin, their conversation shows up right in line. If we take a look at Katie's experience, she prefers working in Teams but can engage with Robin and others all the same. In Teams, Katie has the ability to easily interact with records from Dynamics 365, such as looking for opportunities, choosing to edit them, and making updates right from her team's experience.
From the client's perspective, Lisa benefits greatly as the right individuals from the bank can quickly collaborate together across functions, geographies, and other traditional constraints, all to give her the best outcome. Throughout Lisa's recent engagement with Robin and others from the bank, customer journey orchestration has continued to watch for opportunities to positively impact Lisa and her organization, drawing from signals everywhere. Based on past experience, another journey is triggered.
This one to collect some necessary documentation for this process. This time, the recipient of that communication is someone else from Lisa's organization, Eddie. Eddie prefers to talk and decides to call in when he has a free moment.
Let's hear this experience. -Hi, Eddie. Thanks for calling. I'm a virtual agent and you can chat with a live agent anytime by asking. I see that we've recently sent you a notification about documentation needed in regards to ESG services.
Is that the reason you're calling? -Yes, it is. -Great. I'm happy to connect you directly to the appropriate agent. Before I do, are there any other topics that you'd like to discuss today? -Yes, I actually need to talk to someone about our tax withholding and foreign subsidiaries. -I see. Thank you for letting me know. We'll find the best agent available who can handle both topics.
Are you ready to be connected now? -I am. -I will transfer you now and let the team know what we spoke about. Thank you. -What we just heard is a part of the Native First-Party Voice Capabilities.
A conversational AI was able to pull information about Eddie and recent events to immediately deliver personalized service. This AI is Power Virtual Agents extended seamlessly to the voice channel, and using the same powerful authoring experience as digital channels. With Eddie's intents identified, now we find the right agent, in this case, someone who can handle both the documentation and tax topics.
New, powerful, unified routing capabilities brings intelligent routing to records and interactions across channels, allowing the service team themselves to manage even extremely detailed and complex roles. This helps match the right people to the right questions, and dramatically increases successful resolutions. The first key aspect is identifying the necessary skills for incoming interactions.
With AI, the bank can ingest examples of customer inquiries, which is used to train the model on the skills needed to resolve them. This allows unified routing to becoming extremely shaped to the bank's exact taxonomies, terminology, and even the way in which their clients ask questions. The second key aspect of unified routing is the ability to use any of the rich client data we've been talking about to inform routing rules. As an example, we know that Eddie is responding to the bank's notification around documents needed. We can build a rule that looks at the last action the bank orchestrated for Eddie. If it's around documentation and Eddie confirms, then we direct him down this path.
This gives the bank the ability to have no limits when it comes to routing. For Eddie, this gives him a consistently positive experience where his inquiries are resolved the first time, quickly and efficiently. Across service, other new capabilities such as federated search, voice intelligence, and embedded analytics work together to deliver compelling experiences for both customers and agents. Today, we've seen a customer journey through the lens of several teams, using tools and experiences designed for their roles. But what if we need to go beyond that? With out-of-the-box capabilities, we can also create any look and feel. Let's say the bank needs to brief senior employees before meeting with clients, such as Lisa.
We can express all of this rich data in unique ways for the user and convey exactly the right information, such as pulling specific points of data from across the life cycle into a single simple screen. Across every team and interaction at the bank, data is being used to constantly shape the customer's journey, to reduce friction, to preempt issues, and to give them a better experience. Thank you very much. And Lori, back to you. -Thanks, Tom. You just saw what we're doing across business applications to transform the end-to-end customer experience, but this is just a small piece of what we're delivering with the April wave.
We have hundreds of new features coming across dynamics 365 apps, beyond what you just saw here. But each business has its unique needs. We know we can provide industry best practices in the form of tailored solutions, and that's why we're investing in Microsoft Cloud for Industry. Satish Thomas is here to tell us more about our industry solutions. -Thanks, Lori. I'm super excited to build on top of what James talked about in the context of our Microsoft Industry Clouds.
In October last year, we launched our first, the Microsoft Cloud for Healthcare. Today, I'd like to share what's coming next. Over the past year, the global pandemic has proven to be a catalyst for digital transformation. Organizations across industries were compelled to fit years of change into just months, and use technology to compete and grow. This means investing in people and the capacity to create new solutions to meet the challenges of a rapidly-changing economy. Our deep commitment to industry is not new, but it's taken on a new sense of urgency, and we're committed to helping every organization to use technology to improve time to value, increase agility, and reduce cost.
These new industry clouds bring together the breadth of our offerings as only Microsoft can deliver, across Azure, Power Platform, Microsoft 365 and Dynamics 365, all underpinned by the Microsoft Common Data Model. At top, we've added new capabilities: AI, connectors, and standards unique to each industry. Finally, our offerings can be extended by an unmatched global ecosystem of thousands of trusted partners.
We work with leading ISVs and systems integrators so our customers have complete solutions they need to address their unique business challenges. Now, we recognize every industry is unique. Our aim is to deliver solutions tailored to their specific needs.
Today, the Microsoft Cloud for Healthcare is generally available. The Microsoft Cloud for Retail and Financial Services are now in preview. And soon we plan to preview two more industry clouds, the Microsoft Cloud for Nonprofit and the Microsoft Cloud for Manufacturing. Now, let's look at one of these industry clouds in more detail, the Microsoft Cloud for Retail.
In the following demo, you'll see how we're bringing all the technology together in an end-to-end vision to help retailers with their digital transformation. The beauty of the Microsoft Cloud for Retail is that we can meet you where you're at. We can start with your greatest pain points and identify how best to overcome these first.
Then you can continue the journey with us to identify other areas to transform your customer engagement and optimize your operations. We're doing just that with Patagonia, who, today, is implementing and using many of our retail scenarios and evaluating even more. Over the course of the next few minutes, you'll see a combination of the specific scenarios Patagonia is using and newer scenarios that are now available to customers. Before we get into the demo, let's hear from Patagonia themselves. -Working at Patagonia is so much more than just a job. The products that we make, we have some very technical products and we have sportswear products and we have base layers and outerwear.
And people who appreciate our brand understand our mission. We are focused on whatever we can do to save our home planet. -I've never worked for a place where I felt like it was for a higher purpose. Our customers' experience with any interaction with Patagonia is very important to us. It is a big part of our brand, both from a knowledge of the product standpoint, from a customer service "We'll take care of you" standpoint. So, to really make all that happen, obviously you need technology tools to allow you to do that.
-We have had a very longstanding, strong partnership with Microsoft, and we're always pushing on Microsoft within retail to be new and innovative and different. And when we were looking at needing to upgrade, moving to D365 made sense for a lot of reasons. -Literally on the cusp of go live is when, you know, things went crazy last year, in March, and actually completely shut down our business, shut down our warehouse, shut down all call centers, shut down all of our retail stores practically overnight. -Everything was closed. We closed all of our offices.
Everybody went to working remote. We learned how to use Teams overnight. So, we did our entire D365 go live for our direct business remotely, and that was not planned. -Normally, you have an army of consultants and IT folks go on site to make all this happen.
We came up with a plan to execute remotely and, thanks to Microsoft Teams, we actually pulled that off. -And using Distributed Order Management, even though the stores were not open to customers, we were able to turn our stores into mini warehouses to keep our retail employees working. So, we were doing buy online and ship from store. And then eventually we started adding curbside pickup. And all of this was enabled by D365.
-We absolutely want the customer experience to be as efficient as possible and as comforting as possible, and safe and secure as possible. So, you want to be able to tie the customer journey together as they go back and forth between your channels, but in a non-intrusive way, and using Microsoft tools D365 is part of what's allowing us to do that. -That was great to see.
Today, there are three key areas retailers are investing in to develop a compelling consumer experience. First, a deep understanding of their customer to ensure interactions have relevance. Secondly, determine the best way to engage with the customers and meet them where they're at. Lastly, optimizing their operations to enable desired customer experience while striving towards maximizing profitability. Now I'm going to hand it off to Lydia for the first part of the demo.
-In this digital age, customers are inundated with retailers competing for their attention. It's more crucial than ever that we deeply understand them, so that we can personalize every stage of their experience to keep them excited to buy from us. Let's see how we develop an in-depth picture of our customers.
Cameron is our customer for today. Observational and transactional data from his interactions on our website, social media, customer service and more are used to generated real actionable insights about Cameron, like what products we should recommend and which channels we should interact via. Next, this information is used to design our approach to engaging with him. The way marketing journeys are planned has changed.
We no longer design static flows that can't flex and change as we learn more about Cameron. Now, instead, our journey is led by Cameron's actions. Anytime Cameron interacts with the brand, online, in store, through the call center and more, his journey is triggered in real time and he receives a personalized communication.
How does that work? Right now, Cameron is browsing online at some products. He has looked at three different jackets. AI has identified his preferred channel and he receives a real-time email about the items he's been browsing.
Within the effective email editor, AI suggests images that are more relevant and engaging for him, increasing the likelihood that he will purchase these items. These interactions are not just limited to marketing. He receives them across his retail journey, whether he's interacting with the content center or a sales representative, helping to strengthen his faith and enthusiasm about the brand. Of course, he's going to continue to receive hyper-personalized content, even when he's not interacting with them, ensuring they're top of mind. Let's go back to Satish to learn more about how we now engage our customers.
-Thanks for showing us the first part of the journey, Lydia. Now that we deeply understand Cameron, let's meet him where he's at. Within the Microsoft Cloud for Retail, we have a commerce anywhere approach. We have the modern solutions required to run end to end online, brick and mortar, and call center retail channels, and we're able to provide our team with the full picture about Cameron so that they can deliver consistent experience.
One of the reasons that we're able to deliver this consistent experience is our headless commerce engine. At the core of all of our retail capabilities is a universal architecture that we've been building for over a decade. It's this piece that is truly, truly differentiating for us. Using one central headless commerce engine means our retailers can be agile.
When a new trend comes along, like social engagement or livestreaming, they can quickly meet the customer where they're at, with full visibility about them. Lydia, why don't you please show us what that looks like. -Let's jump into a journey using Patagonia as our example retailer. Today, Patagonia has seen a transformation in the way they engage with customers. Before purchasing, customers often want tailored advice on which items will work best for them. They contact them by chat or over the phone.
And today, over eight percent of their orders are captured by the call center team. How might that experience play out for Cameron? It's Friday night and he's browsing Patagonia jackets. He has more questions, so he picks up his phone and starts to chat with a virtual agent.
He's looking for a puffy jacket that can work both as an insulation layer for skiing and also be used for spring hikes. During the conversation, the virtual agent transfers him to an educator who can give Cameron personalized guidance. Here, the educator can continue the conversation. On the right-hand side, his full order history can be accessed, meaning the agent can give him personalized guidance on the best products to meet his specific needs. He then offers to process his order, ensuring a sale. In Cameron's case, he's choosing two items, the jacket he received guidance about and a second hoodie.
He asks for home delivery for one item and curbside pickup for the other, and the agent can easily complete this request in one simple order. Let's talk about what happens when a customer walks into a brick-and-mortar store. Point of sale equips in-store staff with a complete understanding about their customers. When Cameron visits the store, staff have full visibility into his insights profile and can understand things like his next best steps and churn scores, and can then click further to see his full purchase history, wish lists, and product recommendations.
This visibility helps him to have conversations about products they know he's interested in and can easily upsell. What's more, thanks to his personalized journey, when he walks through the door and connects to the Wi-Fi, he receives an automatic text message welcoming him and offering directions to the section of the store that has the items that are still in his online cart. This kind of interaction is guiding him directly to the products he's excited about and making it easier for him to make a purchase.
Using Microsoft Cloud for Retail, the combination of receiving AI-assisted content and true visibility across all channels for customer-facing teams is taking Cameron's brick-and-mortar experience to new heights. If we're going to transform our in-store operations to match the service we deliver online, we need to understand how customers interact with our store on a larger scale. Microsoft Cloud for Retail does just that. AI helps retailers to understand how many people visited the store and how long they were waiting in a queue before being served.
Using this information, they can then plan staffing more accurately to make sure long queues are not a barrier to purchases. They can also receive notifications when the store is reaching capacity so it doesn't violate local COVID regulations. Furthermore, retailers can access real-time insights about how their endcap displays perform.
They can understand how long customers spent interacting with them, and these insights tell them how best to present their products to maximize sales. The ability to unlock these observational insights for the first time puts retailers at a significant advantage compared to their competitors and enables them to take the brick-and-mortar experience for their customers to the retail edge. Let's pause for a second here.
We've heard from our customers that the environment of the last 12 months has shone a spotlight in an area that hasn't been solved well historically, the B2B space. This is a key component for retailers like Patagonia for whom B2B is a critical element of their business. Retailers want to replace disconnected experiences based in spreadsheets with the same rich consumer-like experiences that they deliver today in the B2C space.
Using Microsoft Cloud for Retail, we're transforming that by leveraging the existing B2C ecommerce capability and extending it to meet the needs of the B2B space. Now retailers can use one solution to deliver a fantastic experience for both their B2C and B2B customers. B2B customers have access to full product catalogues along with rich insights about product popularity with B2C customers, meaning they can make informed decisions when choosing products.
They can easily group products together, making it far easier to complete bulk orders. In a world where customers are historically reliant on spreadsheets and emails to coordinate these purchases, templates make bulk order completion incredibly efficient. When it comes to checking out, the option to use account credit instead of always needing a credit card once again means orders can be completed faster and are far easier to reconcile. What's more, they have access to a host of online self-service capabilities, like quick order entry, account management, and the ability to track and pay invoices. Accessing all of these capabilities within the same solution as rich product records means they have a one-stop shop for their retail relationship and find it easier to engage.
Retailers like Patagonia build fantastic, eye-catching ecommerce websites. Some of the questions our customers often struggle to answer are, is it hard to navigate, can our consumers easily find the products they were searching for, and how can we unblock them to make it easier to reach their goal of purchasing a product? Using Microsoft Cloud for Retail, retailers can use session replays to see how customers actually interact with the ecommerce website and where they get stuck, helping them to clearly identify how to improve the website and make it easier to complete a sale. Furthermore, heat maps highlight the most popular areas that deserve front and center attention on the website.
Ultimately, both of these capabilities help customers find the right product and check out consistently. With that, we'll hand back to Satish to land in our final section, how we can transform our operations. -Finally, let's understand how within one cohesive solution we can not only deliver incredible engagement experiences but also ensure we deliver on the customer promise. Lydia's now going to show how we're helping to transform operations and prioritizing profitability, efficiency, and customer visibility.
-For what continues to be a massive issue for retailers across all channels, whether it's in store or online, fraudsters rarely place a single order and walk away. Instead, they continue to exploit gaps they find until they're stopped. This adds up to a massive financial loss for retailers. Traditional fraud protection apps often present retailers with solutions that, in an effort to prevent all fraud, result in high numbers of rejections for genuine transactions.
With our solution we're approaching things differently. We place great focus on finding the balance between stopping fraud and reducing customer friction, including the number of good customer transactions that are inadvertently stopped. We call this finding profit efficiency. Our solution also enables retailers to prevent customer accounts from being overtaken by fraudsters and can help find anomalous returns and discounts associated with in-store transactions.
This helps retailers protect themselves against fraud, reduce chargebacks, maximize profit, and deliver great experiences across their customer's engagement journey. Once an order is placed in either the B2B or B2C setting, it's time to deliver on the promise. Orders are seamlessly consumed into order management. Here, every stage of the order journey is automatically coordinated to meet customer delivery expectations while maximizing profitability and prioritizing efficiency. Here we can see that Cameron's order is ready for processing.
If we click in, we can see the full order details. We have full visibility in the timeline about what has been achieved so far as part of his order. And if we go to Order Details, we can understand where his individual items are going.
In this case, one to curbside pickup and one for home delivery. The full orchestration flow shows us the steps each order goes through to identify the most efficient and profitable way to get the product from a store or warehouse directly into the hands of the customer. Behind each of these layers, we can see the logic used to ensure the order is a success. Not only does the team have full visibility but Cameron is also sent an update at every stage, ensuring he has no doubt that his order will arrive on time and can feel confidence in his decision to buy from Patagonia.
Let's close off Cameron's journey by taking a look at what happens with the curbside pickup portion of his order. Cameron's jacket arrives at his closest store, having been shipped by priority overnight from a nearby warehouse. The frontline workers at the store can easily track handing over the order.
In this case, he's already paid when the order was placed, so they simply want to capture that the pickup is complete. Once that's completed, the status is immediately available to everyone throughout the retail journey, whether that's in the call center, fulfillment center, or Cameron's own team. The team can also use walkie-talkie capability to communicate as he arrives to make sure he has a smooth collection process. Hi, Ryan. Cameron Cook is here to collect his order. -I am on my way.
-Once he has received his package, he gets an automatic message. He's asked to complete a survey about his experience. And when he responds, he is sent a digital gift card to spend on an item they know he's excited about, in this case, a new pair of gloves. He heads home delighted with his new items and excited to engage for many more successful purchases. As we saw throughout our demo, rich insights were being generated at every stage, from customer engagement through to order completion.
We know that intelligence isn't just about dashboards, it's about those insights being put to work automatically so that retail journeys are continually improving. Whether it was personalized customer engagement events being automatically generated anytime Cameron engaged with the brand or auto processes being intelligently updated to drive efficiency, retailers can, for the first time, use one intelligent platform to understand their customers, engage more effectively, and transform their operations across their entire B2B and B2C offering. This is truly retail on the edge. This was all made possible by using the latest capabilities from the Microsoft Cloud for Retail. Back to you, Satish.
-Thanks, Lydia. In addition to our end-to-end connective first-party capability, we have a set of amazing partners who have invested in our solutions to bring specific capabilities, helping our customers to excel in their retail segment. Two great examples of where this is happening today are Amicis for end-to-end restaurant point of sale and management solutions, and Adyen for out-of-the-box, omni-channel payments. And to bring this all home, I'm so excited to see what we do together to enable every organization across industries to reach their full potential.
With that, I'll hand over to Arun to talk about Power BI. -Thanks, Satish. Hello everyone. James talked to you about how the Microsoft Cloud helps you drive a digital transformation. In this section, my colleague Charles Lamanna and I will focus on the Power Platform. The Power Platform provides a single integrated local stack that helps you empower business and build entirely new applications in hours or days instead of weeks or months.
In a world in which things are constantly changing, the Power Platform helps you understand and act with intelligence. The Power Platform consists of four major services, Power BI to help you gain insights from data, Power Apps to help you build web or mobile applications, Power Automate to help you build UI or API-based automations, and Power Virtual Agents which helps you build intelligent bots all with no code. I will cover Power BI, and I will transition to my colleague Charles who will cover the rest of this stack. James talked about how in today's world data comes first.
And the ability to tap into these massive volumes of data available today and enable intelligent action is key to our customer's competitive advantage. With Power BI, our vision has been to help our customers drive a data culture where every employee in the organization can make every decision based on data at any scale. One of the customers we work with very closely is Rockwell Automation. As the world's largest company dedicated to industrial automation, Rockwell has massive amounts of data at their disposal.
Rockwell is an industry leader in taking advantage of all of this data to help improve their customer's experience. Let's hear directly from them. -Rockwell Automation is manufacturing for manufacturing. We build things to enable production lines, everything from the smallest component all the way up to all of those components put together. -We have 1,400 Power BI content creators who are helping their team deliver analytics to optimize the work that they're doing.
-What we're trying to do is make the easy stuff easy, let my engineers be engineers. Our group is building ways to generate revenue for the company. With Microsoft Azure IoT Hub, we have the ability to look at a circuit board, collect the IoT data, and then we feed a model to accurately predict will that circuit board fail based on a machine learning model. -So, we don't suddenly get to the point where we have to shut down. As a lean organization, we take shutdowns exceedingly serious.
That is how we maintain our price point. ML and Power BI really helped us drive that to a new level. -We can feed that back into Synapse, the data warehouse, and then Power BI can have reports that sit on top where now we're able to alert people in real time. -That cuts out tons of our waste and inefficiencies, and increases our quality of our products that we're putting out. The lowering of waste lowers our cost, right, so that we're able to give our customers the least expensive stuff out there.
-As we ingest that data, we can make it available back to the customer, making our customers' lives easier, making them understand where their factories are, when they're about to run into problems. You know, everybody in manufacturing is striving to this. How can I not ship defective things; right, and then the cost to reclaim that and make it right. -Being able to integrate Synapse, Power BI premium Gen Two, and Teams allowed all of our engineers to understand the status of our projects faster and more reliable than before.
And to clearly communicate back and forth, this has been really key in keeping this project up, running, and at the pace that we need it to in order to hit our enterprise goals. -It was great hearing from Rockwell. Now I will show you how Rockwell leverages some of these capabilities that we ship to the release wave to help them drive a data culture.
I will start by showing you how easy it is for Rockwell Automation to build a stunning Power BI report that can immediately help their users find insights in their data. Building this report so far has been very intuitive. As I have my familiar offers driven here on top and the same gestures that I would use in PowerPoint, for example, grouping, being able to resize items together, and even these red snap finds that you see that make it easy for me to position my visuals correctly. As someone who uses Office every day, I feel right at home.
To help users consume all of the important information in this report, I'm going to add the new Smart Narratives visual to this page. This is an AI visualization that will immediately analyze everything that's going on in my report, and it communicates the most important insights through natural language. For example, we can quickly see that there's been a 17-percent increase in units sold in the last few months. The Smart Narrative is fully customizable.
I can change the way it looks. I can make parts of my text bold. I can even add my own dynamic values that will get recalculated as my data updates. In a couple of clicks, I can make this a beautiful part of my report so it fits right in, just like you can see over here. Now, when I look at the text generated by my Smart Narrative, I see that it noticed something interesting.
It noticed that one of our business units, CompactLogix, has a high number of units sold, but it also has a very high return rate. So, perhaps we should investigate this a little further. Selecting CompactLogix cost filters all of my data and it also reruns my narrative. Now something else has caught my attention. Firstly, units sold is growing at a faster rate, with an increase of 82 percent.
And it looks like a narrative identified that there are a couple of anomalies found in the last few months. In fact, it looks like there was an anomaly as recently as February 10th. Now, to explore these anomalies even further, it is very easy for me to enrich my data and visualize these anomalies directly over the time series itself by just clicking on this button here on top. Now we can visibly see these anomalies and we can even customize the way that they're represented, tweaking things like the sensitivity of the algorithm, the colors, and the size. So, the next question is, what's actually causing these spikes in units sold so I can take some action? It is as simple as clicking on the anomaly so I can investigate it further. In this case, we can uncover that the latest spike took place in North America and it had to do with our micro and nano product categories.
This new capability with anomaly detection and Smart Narratives, allows me to explore all of the anomalies in any of my business units, and I can simply select other datapoints and have the machine learning model rerun. With all of my AI enrichments added to this report, my business users will now be able to explore the data and find their own insights. Power BI is the only BI platform with comprehensive AI capabilities focused on business users and business outcomes.
Today, we have over 80,000 customers using the AI capabilities in Power BI. For the second part of my demo, I'm going to show you the new Power BI app for Microsoft Teams that enables Rockwell Automation to create a datahub for all of their users. This app brings all of Power BI into Teams. Users can quickly find reports, dashboards, and the Power BI apps that they use frequently.
Rockwell can feature and certify content so users can find authoritative data which can be used to make important business decisions. The app also helps users getting started, open recent items, and discover recommended reports. Rockwell pinned the Power BI app to the team's left rail.
Now everyone at Rockwell can use Power BI along with all of their core team's capabilities, making it very easy for them to collaborate with data. Let's see how Allen, an analyst at Rockwell, can find, investigate, and collaborate without ever leaving Teams. Allen opens the Financial apps in Power BI. As we discussed before, he noticed that CompactLogix has a high return rate.
Now Allen can use the AI Power Decomposition Tree to quickly explore what contributes most to return rates. He discovers that there's an infrastructure issue in the Asia Pacific region related to the process product category. The decomp tree is incredibly flexible.
Clicking on any node or slicing on any other visual on the page updates the decomp tree automatically, helping Allen dig into the data faster. Once he's found an insight, Allen can use the chat in Teams feature to let his colleagues know what insight he has found, enabling them to start resolving the issue. The Power BI app for Teams is not just where you find your reports; it's also where you find your Power BI datasets that you can use for analysis.
Allen can find all the datasets he has access to, and he finds recommendations on certified and promoted datasets as well. So, he knows which are the most authoritative and up-to-date that he can use for analysis. When Allen takes a specific dataset, he sees all of the details for it, including who endorsed it, the workspace it's in, and when it was last refreshed. Allen can see all of the related reports as well, including those that are most popular. The lineage view helps Allen see what source system the data comes from and the reports that consume that data. This improves Allen's confidence in the datasets he's using and it also helps him understand the impact of any potential changes.
The Power BI Datahub enables Allen to create new reports or make new Excel Workbooks that are connected to the live Power BI dataset with just a couple of clicks. Allen now has an Excel Workbook with the pivot table that's live connected to the Power BI dataset. He can add measures like revenue and gross margin.
He can format his data with rich Excel conditional formatting. These connected workbooks can be added to Power BI and authors can now create Power BI applications that bring together Power BI reports and Excel Workbooks blended together seamlessly, just like you see here. Power BI users at Rockwell can analyze the data in Excel Workbook using all of the power and familiarity of Excel, and the data is continuously updated from the underlying Power BI dataset. So, users are always making decisions with the most recent data.
We know that Excel is the world's most popular tool for working with data. This deep integration of Excel into Power BI helps users save time from manual export-based workflows and ensures that they're using the most accurate data to make business decisions. No other BI product in the industry provides such a rich, seamless experience with Excel. We saw how Rockwell Automation is using Power BI and Microsoft Teams and Excel to bring data into decision-making, and enable the whole organization to drive a data culture. For the last part of my demo, I'm going to show you how Rockwell Automation uses Power BI with Azure Synapse Analytics to analyze massive volumes of data and get incredible performance with no manual tuning required.
When I refresh the data in this report, given the large volume of data analyzed, we can see that this report is taking more than 12 seconds to load, which is clearly not a great end-user experience. To alleviate this issue, we recommend the use of the Power BI Performance Accelerator for Azure Synapse. This accelerator monitors all of the incoming queries for Synapse from Power BI and uses the machine-learning model to automatically optimize Synapse and deliver massive performance improvements. To show how this works, let's look at the query plan coming from one of the queries coming from Power BI. As you can see, the query gathers data from multiple tables and scans over eight billion rows of data, which is why this report is taking more than 12 seconds to load. The performance accelerator for Azure Synapse can be abled from the Synapse Studio with just a few clicks, and can be done on a per-database level.
You can see how simple it is to do right here in this user experience. Now that I have turned on the Performance Accelerator for Synapse, to determine the effect of it, let us once again look at the Power BI query to see the pertinent query plan. Now, the same query retrieves data from automatically creating materialized views. The performance accelerator's machine-learning model determines the optimal set of materialized views to optimize the query coming from power BI.
As a result, the number of rows can drop from 8 billion down to only 4. 6 milli