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An Autodesk Backstage Pass—How We Can Create Exponential Customer Value, Today and Tomorrow

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Top Autodesk thought leaders from all parts of the enterprise share their exclusive insights on our leading edge software development practices, our evolving effort to partner with and learn from our customers, and our initiatives to meet your needs in the next 5-10 years. This will be a unique, fast paced, highly interactive format with 15-minute engaging dialogues in each key area, immediately followed by a networking reception with the panelists.  It is a great opportunity to deepen your connection to Autodesk, and to consider how to position yourself for the future with Autodesk as your partner.

Moderator—Minette Norman, Vice President Engineering Practice

Development Practices—Maria Giudice, Vice President Experience Design and Alicia Wong, Director, Agile Practice

Customer as Partner—Moonhie Chin, Senior Vice President of Global Customer Support and Operations (GCSO) and Leeann Manon, Director, Product and Platform Marketing

The Future—Heather Kerrick, Senior Research Engineer and Lynelle Cameron, Senior Director, Sustainability and Autodesk Foundation

주요 학습

  • Understand the Forge Platform and Autodesk's changing relationship with the developer
  • Understand Autodesk's evolving connection to the customer
  • Understand the changing way in which Autodesk creates its products
  • Network with some of the key executives leading Autodesk into the future

발표자

  • Daniel Guillory
    <p>Autodesk Director, Global Diversity & Inclusion</p>
  • Lynelle Cameron
    Lynelle Cameron is Vice President of Sustainability at Autodesk and President & CEO of the Autodesk Foundation. She founded both to invest in and support people using design to solve today’s most epic challenges. Under her leadership, Autodesk has won numerous awards for sustainability, climate leadership and philanthropy. Prior to Autodesk, Lynelle led sustainability teams at HP and has 10 years of experience at the intersection of conservation and economic development with WWF, TMI, and NOLS.Lynelle serves on numerous for-profit and nonprofit boards including Innovators International, CEH, Luke Hand,UC Berkeley CRB, Biomimicry 3.0, and previously Net Impact. Lynelle was recently recognized as one of the Most Influential Women in Business by the SFBT. She has an MBA from UC Berkeley, MS from U of Michigan, and a BA from Middlebury College.
  • Minette Norman
    Minette Norman serves as Vice President of Engineering Practice at Autodesk and is responsible for a collaborative culture and state-of-the-art engineering practices. Minette spearheaded “radical collaboration” – initiatives that recognize engineers who contribute to one another’s code, designs, and tests. Previously, she gained international attention by transforming Autodesk’s localization team through best-in-class automation and machine translation. Before joining Autodesk, she held a variety of technical communication and management positions at companies including Symantec and Adobe. Named in 2017 as one of the “Most Influential Women in Bay Area Business” by the San Francisco Business Times and in 2018 as one of the YWCA Silicon Valley’s “Tribute to Women” Honorees, Minette is a recognized industry expert with a unique perspective. Minette has a broad approach to community service, working with local, national and international non-profit organizations. She serves on the Board of Directors of D-Rev, a non-profit devoted to developing medical technologies for impoverished and vulnerable populations worldwide. Minette also works with GirlsWhoCode and YesWeCode, national organizations that help under-represented populations succeed in the technology sector. Minette holds degrees in Drama and French from Tufts University and studied at the Sorbonne Nouvelle in Paris.
  • Moonhie Chin 님의 아바타
    Moonhie Chin
    As the Senior Vice President of Digital Platform and Experience (DPE) at Autodesk, I lead the mission of offering our customers a superior digital experience wherever they engage with the company. DPE’s charter is to deliver digital capabilities that enable self-service and automated experiences for customers, service providers, and employees, as well as productivity tools for customer-facing teams. I am passionate about improving the end-to-end experience for customers, and increasing productivity for both Autodesk and our service providers through anytime, anywhere service, support and information. I have held various executive roles since joining Autodesk in 1989.
  • Alicia Wong
    Senior Director, Agile Delivery; Experienced technology and transformation leader with a track record for quality delivery in high-growth fast paced environments. Expertise in Agile systems for scale, lean product manage and driving increased value and execution amidst constant organizational change. Recognized as a strategic thinker with the ability to identify and synthesize large complex problems and translating strategy into results. Successful history of leading large scale enterprise & operational transformations yielding quality delivery structures and deliverables under rigorous timelines. Proven track record in building and fostering strategic cross-organizational relationships spanning all levels.
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Transcript

MINETTE NORMAN: Still wandering, but we are going to get started. Welcome. You've made it, and you got your backstage pass. How many of you are customers? You're not associated as employees of Autodesk? Please raise your hand. Excellent. So this is the first time we've done this. We wanted to offer you some insights behind the scene of what happens at Autodesk. And we want this to be a very interactive session. So what we're going to do today, we have this panel of amazing leaders from broad different areas of Autodesk. They all represent a completely different function. And we're going to cover sort of three main areas as a starting point.

We're going to talk about product design and development as a starting point. And then we're going to talk about customer as our partner. And then we're going to end with a talk of the future. What are we thinking about in the future? And the way I'm going to do this is I'm going to start off with some questions for each of the panelists, and they're going to talk and have a conversation. And then we're going to ask all of you to ask questions, to provide commentary and insights on anything that we discussed or anything that is on your mind as our partners as customers.

And so while the panelists are talking, jot down any questions that you have, because we'll have a good Q&A session at the end when you can ask anything that's on your mind. And then after that Q&A session, you see tables at the back of the room. We're going to have a reception. Please stay and join us for food and drink and conversation. You can talk to any of us. There are a lot of other Autodeskers here. And talk among yourselves as customers.

So I'm just going to introduce myself. My name is Minette Norman. I'm the Vice President of Engineering Practice. And I'm just going to move right in to introduce our first panelists who are going to talk to us about product design and development. So let me introduce my first partner in crime here, Maria Guidice, Vice President of Experience Design and Alicia Wong who's the Director of Agile Practice. And I'm going to kick off their conversation with a question about how people are going to use our products differently in the future, and how does that impact the way our products will be designed and built? So Maria, do you want to start?

MARIA GIUDICE: Yeah. I'd love to. First of all, I just

MINETTE NORMAN: Move the mic a little closer.

MARIA GIUDICE: Hello? OK. I'll just talk like this. I just think it's such an amazing time to be at Autodesk right now. I actually joined Autodesk about a year and a half ago to help with the next generation of product experiences for you all. And I-- everything is changing right now. Everything. And you're going to hear the themes over and over again. You can see it in the keynote.

But for products, product design in particular, I don't know about you, Alicia, but I grew up in a time when we were just grateful when the technology worked. I just remember growing up, and like a young designer, opening up Photoshop 1.0 and rotating an object, and going to have lunch and coming back, and the object is just finished rotating. And it was just like magic. We loved it. We forgave the time it took. We forgave when things crashed, because it enabled us to do things that we weren't able to do before.

But we don't live in that world anymore. There's a whole generation of people who have grown up with technology expectations where they expect things to work. They expect things to work any time, any place, in any context. And so Autodesk is a 34-years-old company. We have over 100 products in our suite. And they were built with that ability to be incredibly powerful, but not necessarily optimal when it comes to experiences.

And so I'm really excited about how we're working together to evolve the next generation of products so that they work better, they're more fluid, they're more inneroperable, and that you can access it on any device in any time. So that's really sort of the product revolution that's happening internally at Autodesk.

MINETTE NORMAN: Alicia, I think I'm going to just ask a starter question for you in this context. So as you see, Alicia's title is Director of Agile Practice. And you may wonder what that is. And so I'm going to let Alicia talk about that. But in terms of agile-- one of the things we are doing is we're moving to the cloud. And as we move to the cloud, we know that we need to deliver products more often, and we need to be able to update them based on customer feedback. So how does agile and agility play into the cloud and the need for continuous delivery?

ALICIA WONG: That's a great question. I'm just curious by a raise of hands, how many of you actually know what agility is? All right. Rock on. So I usually have probably less than half the audience that actually gets what agile is. And oftentimes, I have folks come up and say, hey Alicia, I have this agile process, and I really want you to come check out. And then I sort of bow my head in sadness, because it really is about dynamic interaction, frequent touches with the customers, and bringing those feedback loops continuously and as seamlessly and as quickly to our product development teams and designers so that we can get working software delivered to you all as our customers as rapidly and as quickly as we can.

But it truly is about-- it is-- I started my career in Waterfall as an engineer building. Define it, design it, develop it, test it, and deploy it. The one thing with Waterfall that didn't work is there was never the time or the budget. And scope always bled over and over again. So how do we deliver quickly? It's the bringing that agility too so that we can build cloud as quickly as we can, delivering customer value, but including customer as our partner.

MARIA GIUDICE: The beauty of agile is also enabling constant feedback loops.

ALICIA WONG: Absolutely.

MARIA GIUDICE: Where the old way of thinking is do all the research, understand the customer, and then deliver it after six to nine months. But now, with our ability to continuously iterate and deploy, we can really respond to where people are getting stuck and the things that they actually want to see quicker.

ALICIA WONG: Absolutely. Oftentimes, we find the large enterprise companies that come in and say, we've got changes that have come in from our customer requirements. And if you're building 12 months of a documentation that says this is exactly how we want it, I promise you, three months in, the changes and the requirements have been bubbled up to the top. And then those teams are scrambling. So you're delivering subpar value to the customer. So I can't agree more with Maria.

MINETTE NORMAN: Maria, one of the things you've talked about quite a bit internally, and customers may not have heard this, is you talk about building products that customers love, not that they just like. So maybe you could talk about either in the context of agility or in just engaging more, how are we building products that our customers love?

MARIA GIUDICE: Yeah. I think if any of you have had experience actually building and shipping products, there is a term called the MVP. How many people know about the MVP? So probably the same people who know about agility, because it's connected to the MVP. And we all know that the idea of the MVP is kind of flawed, because it depends-- what does minimum viable mean? It often goes more towards minimum versus viable.

And so we at Autodesk are now saying, well, what is the minimum lovable product? What is the minimal thing that we can give to the customer that has the maximum amount of love? And we define minimum level product really in three different trajectories. Is it immediately valuable to you? Is it well-crafted experience? Is it of high quality? Is it emotionally engaging? Are we speaking like a human being? And then is it-- are we removing all the friction to make it as easy to use as possible? So these are the principles that we are aspiring to in product design to make sure that we are really not-- that we are trying to give you the maximum amount of love in the smallest amount of time.

ALICIA WONG: I couldn't agree with you more. It's really bringing the customer into the center of our practice.

MARIA GIUDICE: How do you-- as an engineer-- how do you interpret minimum level product? Where are those criteria that you've seen?

ALICIA WONG: When we are prioritizing in our backlog the work that's important, that needs to get a feature or a set of features out the door, we really sort of prioritize based on what is it that's going to make the customer delighted? And what is it that's going to provide the most end to end functional composite value so that you're not getting sort of this unconnected sort of value out to our customer.

MINETTE NORMAN: Anything else you want to say about product development, design--

MARIA GIUDICE: We have a lot of work to do. And that's what's really exciting. And as we move from this 100 plus portfolio of products to this one Autodesk experience where you can have consistency, where you can expect the same kind of functionality, things working across space and time, that's sort of my version of nirvana as a product designer. And we're really up for the task. And everybody in the company is really rallying around where Autodesk is going as a platform company less so than a-- more than just a product company. And so it's just a great time, again, to be where we are right now.

ALICIA WONG: And just a last sort of ditty for information for folks is Autodesk is pretty unique in the sense that we are distributed globally-- pretty globally around the world. I've been traveling for about 18 months nonstop, and I still haven't been able to sit with all the teams. So to orchestrate and collaborate across the products to bring those lovable products to our customers truly is a feat that we're trying to evolve over time and iterate as we move along.

MINETTE NORMAN: Right. Thank you. And we're not going to be able to do any of this without partnering with you. And so I want to move into the second section of our panel, which is customer as our partner. And let me introduce our panelists. We are very fortunate to have Moonhie Chin here today. Moonhie is Senior Vice President of Global Customer Support and Operations. She sits on CEO staff. So it's great to have her here today. And we have LeeAnn Manon, Director of Autodesk Education Experiences. So Moonhie, I'm going to start with you.

MOONHIE CHIN: OK.

MINETTE NORMAN: And then we can segway, or you can have a conversation, however you want to do it. So how does Autodesk help our customers unlock the value of our products and solutions?

MOONHIE CHIN: That's a great question. But before I start, I want to actually just note that I became one of those people that I look different than picture. That actually happens. I need to change my picture. I think Autodesk is really lucky to have millions of customers who are using our products passionately. And at the same time, they are really excited to share their expertise to other people. So when you come to AU event like this, you actually see the commitment, dedication, and connection. So to me, AU is all about learning and community.

So while this is great that we're sitting in the same room, and we're going to share a glass of wine later, I think what is actually more important is for us to create an ecosystem online that actually brings the same kind of connection and where people can go and get help and learn our products a little bit more easily. So we introduced AKN, which is Autodesk Knowledge Network. And its an ecosystem that we're hoping people go and get help and learn and connect. And today, we have 16 million sessions on a monthly basis that actually people come to AKN. And you can get to AKN from different places. From in Product Help, or actually from search engine through websites, and also support forums that we actually have.

So to deliver and nurture this kind of ecosystem, it actually was a very different kind of thinking that we took the journey a couple of years ago. So the very first thing we have done is we collected every single learning and support content in Autodesk, and we put it into AKN. We actually used Creative Commons. So what that means is anybody in the world actually getting into AKN can use learning and support content for remixing and changing.

So there are a lot of examples, but one of my favorite examples is actually a customer in Vietnam taking our sustainability workshop and translating into Vietnamese, because the building a sustainable building kind of project is really hard to do in these emerging countries. So that's actually the value of network like this one.

And I think the second one I would actually say is our attitude towards managing community is very different. So how many of you are using Fusion 360? Great. And if you actually go to Fusion 360 Community, you actually see our engagement really from all different parts of organization of Autodesk. But I think we are also making some of the customer expert to be a little bit more real. And we have a program called Autodesk Expert Elite Program where we actually recognize our customers' contribution.

So we have 350 Expert Elites around the world. And frankly, about 60 of them are here this week and kind of enjoying and learning from each other. So I've think having programs like that and making sure that we recognize contribution by other people is actually quite important.

And the last thing I'm going to actually talk about AKN is we syndicate content from different places. So we know there's a lot of great content, for example, in YouTube. We actually syndicate content from YouTube and other third party partner sites. So linda.com is top of the list. Kad Learning and other partners.

But the great example that I can actually come up every day, but I met this customer last night when we were having some event. This customer actually has a blog on Reddit. So he has awesome content on Reddit. How to use Reddit. And before he was connected to AKN, traffic to his blog was 200 visits per month. Within four months, putting his content connected to AKN, he's getting 8,000 visits today.

So I believe that I think if we can put some time in to connect these kind of greater network of expertise, I think we can actually make a big contribution in making learning to be a little bit easier. And by doing that, our customers can actually get the full value of what they actually paid for and use all the powerful features and functionalities.

MINETTE NORMAN: Thanks, Moonhie. So I'm going to do a brief segway to LeeAnn. And I think it may come back to the AKN topic as everything does. But I wanted to ask you-- we talked a lot even in the main stage today about the new generation. We saw one of the new generation Z members up on mainstage today [INAUDIBLE]. And so I want to ask you is what impact this next generation is going to have on the behaviors and norms in the workplace? And perhaps how that might interface with AKN if they're using things in a very different way.

LEEANN MANON: Yeah, absolutely. So Gen Z for folks who may not be aware is loosely defined as people who are born between 1995 and 2010. So they are somewhere between 6 and 20 years old. And they are on track to be the largest cohort to date. So there are about 2.52 billion Gen Zers worldwide. So we're so over millennials. No one cares anymore. Sorry. Sorry. We still love you, but you're too old.

This is a huge group that is-- by 2020-- going to be 40% of the world's consumers. So right now they're 25% of the world's population. So Gen Z is definitely going to have a huge impact. In the education group, we're really looking at how do we need to be working with this generation? How do we need to be helping these students to be successful and to learn the way that they need to learn? And so Moonhie and I were talking earlier about AKN and that peer to peer aspect and all of the content that's out there. And I love the open sourcing, the Creative Commons nature of the content.

And that's right in line with what this generation wants to be doing. These are folks that really came into a world that was defined by upheaval. We've got the global refugee crisis. We've got terrorism happening on a global scale. There's a lot of things that are happening in the world that are causing this generation to be more realists than optimists, whereas the millennials really weren't-- had this degree of optimism. And Gen Z is a little bit more concerned, and they really want to impact and change the world and share those experiences with each other.

And so that's why I was excited to hear-- when Moonhie and I were talking earlier and these folks that are taking content. You can't learn without content. And so as a partner-- and these are customers partnering with each other to take this knowledge forward and really learn these next generation technologies. It's fantastic.

MINETTE NORMAN: And it's a paradigm shift, because we used to always think that Autodesk had to provide all the help for all of our products. That's how we worked for 30 plus years is we have to write the help. And now that's really changing in that our customers are providing help for one another. And as you said, this next generation is really very open source oriented, very much into sharing. Do you think-- either of you, Moonhie or LeeAnn-- do you think that changes anything that we're already doing? Are you thinking about anything differently in terms of our knowledge network or our engagement with the customers?

LEEANN MANON: Yeah, you can go. That's fine.

MOONHIE CHIN: Yeah, I think it's on. I think one of the things that we are actually thinking about-- so this is the backstage part of actually [INAUDIBLE]. We are trying to actually look at some service marketplace where we can be a provider of platform where people go look for actually learning and consulting and training help. And where individuals and companies can actually offer services. So that's actually something that like one phase more than just free sharing. So we are looking into that. So if you have any feedback, we would love to hear it.

LEEANN MANON: And I think another thing that we're looking at doing differently-- so we do do a lot of to students free sharing. We share all of our software for free to students around the world. But one of the things that we've started talking about is-- this is amazing. We have this huge group of students who are using our software and who are passionate. And what they want to do is they want to go out in the world, they want to create things, they want jobs.

And then at the same time, we have all of these customers, and we hear like in the leadership forum yesterday-- I understand this was a topic a conversation-- we have customers who are looking for their next generation of the workforce. They've got roles that they can't fill. And here we sit. Autodesk is in this great position. And to be able to match these folks up, it's a win-win. And so we really see where our customer of tomorrow is also our customer of today's employee of tomorrow and that there's a lot that we should be doing to connect these two things.

MINETTE NORMAN: Thank you. That's a perfect segue into our last section, which is about the future. And let me introduce our speakers here for our panel. We have Lynelle Cameron, and Lynellle is Senior Director of Sustainability, and she's also the CEO of the Autodesk Foundation. And then we have Heather Kerrick who is a Senior Research Engineer in the office of the CTO. Very future looking. And so I want to ask either one of you-- and Lynelle, if you want to kick it off-- we're talking about these Gen Z customers. And so how are we thinking about supporting them in the future? And especially-- many of them are focused on creating impact in the world in a different way from a maybe our traditional customers.

LYNELLE CAMERON: Yeah. That's their truly exciting part. So millennials want to find careers where they can change the world. And they say about 40% of millennials want to change the world. But 60% of Gen Zers want to change the world. And about 70% of Gen Zers actually care about climate change. That's very different than my generation. And so we-- and then here's the thing. The next generation is going to be living in a world that's fundamentally different than the one that we live in today.

So just to paint a quick picture. In about 30 years, there's going to be 10 billion people on the planet, up from seven. Half of those people will be in what's called the global middle class. So expectations of cars and computers and all the luxury goods that we have here today. So twice as many people with consumer products. 75% of those people are going to live in cities. Many of those haven't even been built yet. And of course, we know that that's going to take twice as much energy to power these lifestyles, which needs to be clean and renewable sources of energy.

So this is the design challenge for the next generation. This is what our young people are thinking about, caring about passionately. And so at Autodesk, we are partnering with many of these customers who are using our technology to specifically solve social and environmental challenges. So just like there's free software for any student anywhere in the world, we also offer free software to any nonprofit, any entrepreneur anywhere in the world who's pursuing impact, who's intentionally creating a business or an organization to make the better world.

And why? So why is Autodesk doing this? Certainly we feel great about partnering with people like Christian. You all saw Christian this morning. Amazing. These are the kind of customers that we are working with very closely, and we feel great about that.

But the real value of why Autodesk is investing in these nonpaying customers, if you will, is because we learn from them. We learn about how our software is going to need to evolve to meet the needs of our Rwandan customers or customers in Myanmar or India or you name it. Customers who are solving totally different challenges than our customers today. We met with people yesterday who come up with technologies to transform human waste into charcoal, people who are using our technology to model coral reefs that are affected by climate change. We never expected our technology to be used in the way that we are.

And so that gives us so much more insight that filters all the way down the line to how we as a company need to evolve to meet these emerging needs. And I'll just end with one example, because we just had a team of Autodeskers return last week from Rwanda. So we've started a pro bono program specifically to get Autodeskers-- give them an opportunity on company time to go partner with these customers of the future to learn how our technology may evolve. And certainly, the organizations in Rwanda had a great experience. Human centered design, training, learned our software, all of that.

But the real value is when those 10 Autodeskers come back to headquarters, come back to their job with an entirely different worldview about how our technology can serve the emerging needs of the future. So it's really how much we learn from partnering with these customers, which changes the company that we are and that we become. And Heather, you live in the future in the office of the CTO, and how do you guys think about that?

HEATHER KERRICK: Well, I think we in a lot of ways think about how technology that is just kind of coming up the pipeline is going to smash into all of those sort of geopolitical population environmental things that are coming, as well, where some of those are things that we don't necessarily have control over. Like I'm not sure how much say we have in what the global population is in 20 years. But the interesting part of emerging technology like robotics, artificial intelligence, machine learning, virtual and augmented reality is we're inventing those. Humanity gets to define what those look like and what shape they take and how and why they're used.

And so if-- we can be intentional about how we approach these technologies when we're being thoughtful about how they're going to meet up with the challenges and opportunities of the future. So we kind of look into technologies that are just emerging that are kind of on that bubble of, is this just like a hype thing that two years from now nobody's going to care about, or is this this thing that's going to fundamentally alter the world? I think everyone can think of examples of things like Facebook. People are like, oh, who would have thought that Facebook would have impacted the way we discuss politics? That technology can have unintended consequences. It can have surprising reach.

And so it's sort of our mandate to find that tech. Kind of look ahead and be like, VR. Is that going to-- Oh, yep. Yep. VR looks pretty important. We should probably be shaping some tools that people can use in order to engage better with VR as consumers and as content creators. So it's on us to keep an eye out on those things to engage with them and a hands on way. So you might have seen me with the robots in the exhibit hall. So it's like, OK, we need to make software to control robots better. Should probably buy a robot. Should probably make something with the robot. And then kind of running into all the things that you learn.

So we tried to be our customer of the future as we try to get our robot to do things that nobody would try to get the robot to do, because it's impractical and expensive and slow, because the software doesn't exist to help you do it. So we try to do that now so that we can inform the company about what's important and what isn't and what's difficult and what's easy and what other people are already doing and what no one seems to have done and what people get really excited about. Like we kind of play in that area, and then we can go back to you guys, and then that can turn into a thing that people use and people love. So, yeah. It kind of is this constant feedback loop.

MINETTE NORMAN: That's interesting you mention that, because Jeff Kowalsky this morning mentioned Project Dreamcatcher, which was something that started in the office of the CTO and has been sort of incubating there and is now coming around and will come to us for product development. And so this is sort of a full cycle here that you see on the stage. Heather, is there anything that you're looking at right now in terms of research that you want to share or that you want any customer in the room to be thinking about?

HEATHER KERRICK: Well, I think that as we're kind of reaching this interesting point where a lot of different technology is just starting to emerge between what we're capable of computing and all the-- what we're capable of sensing and just how big and small the world is becoming. A lot of things kind of roll back to machine learning in a really meta way.

So we've got-- coming up with new algorithms and ways to deal with data. The internet of things as the thing that might absorb that data. And then coming up with different hardware and devices like robots, like your Facebook news feed, sort of physical and digital tools that utilize that data and work around you in a way that you stop noticing. Like there's sort of machine learning around us all the time that you stop appreciating.

Things stop being smart the moment it becomes so expected. Like my AutoCorrect. I don't think about AutoCorrect anymore. That's just the thing that-- but that is smart. And that was machine learned. And Google's predictive text, all these things that once they get figured out, nobody worries about it anymore. And pretty soon, our world will be actuated in a way that we can take for granted. And will be sensed in a way that we can take it for granted. And so I think trying to be on top of that curve as far as collect data now, but be smart about it. Get data scientists-- think about things that were never sensed before are going to start becoming smarter. And things that were never never moved before are going to start becoming acctuated.

So some of you people that may not think you work in an industry that is impacted by robots or the internet of things or machine learning, in a few years, you will probably be wrong. And so if you can start thinking about that now-- and I think that can kind of-- like biology gets super interesting as well with the different things that we can digitize. Like coding DNA and the blurry line between growing and building.

I think that's a little farther down the pipe, but I think all of this data introduces some really interesting ethical questions, as well, that it's really easy to lose sight of. But if your data is bad or has some fundamental flaw in assumptions that you made when you collected it, those assumptions are going to get-- you're going to make biased end results. Like you might-- if you take for granted that the weather's going to change, you're going to miss sensing something. If you have an algorithm that's based on data that has some sort of racial bias in it, you're going to have a racist algorithm. That's going to happen.

And if you're not really, really careful-- sort of trash in trash out-- if you're not really, really careful at the first thing that you start with-- like what you're sensing, how you're sensing it, why you're sensing it-- and if there's potential things that you're missing or assumptions that you're making and what you're sensing, you're just going to start building a foundation that other things are going to be built on that other things are going to be built on that inherit all of those flawed assumptions.

And I think just from a social standpoint, and also an engineering standpoint, it's easy to make assumptions that are wrong technologically speaking. I think there's a bit of a minefield waiting for people that aren't careful that they might jump on this machine learning train and drive in a very bad direction.

MINETTE NORMAN: OK. You heard it here first. You've been warned. So I'm going to ask one more question here before we open it up to the room. And I want to come back to Moonhie, because Heather was just talking about machine learning. And I know one of the things that you're working on is some machine learning for customer support using IBM Watson. And I thought you should talk about that, because it's pretty interesting.

MOONHIE CHIN: So machine learning is now actually one of those things that everybody's actually working on. So we started working with IBM about a year ago. And about three months ago, we introduced a digital Asian based on an IBM Watson giving activation code.

And I think over time, what we're going to actually use IBM Watson for are three things. One, if there's a business transaction-- like if you want to cancel the contract, you want to renew the contract, you'll just automatically do it without anybody's help really quickly. And at the same time, if the-- and by the way, if it actually has a great knowledge, then we're going to actually find the right one over time much better. And if none of those things work-- there's no web services or knowledge assets-- then we're going to actually find the best people to help you, whether it's a one on one support from Autodesk or our partners or actually sending them to community. So I think that's how we are using IBM Watson.

I just want to talk about actually the big data that we touched a little bit on. About three months ago, we actually put every single customer interaction in our universe into a database and built the model. So this is every community thread, all the chat sessions, all the phone calls, all the e-mails that we received. And we did a clustering exercise on really understanding the intent of what customers are really asking. So I think these at the beginning of actually machine learning. Thank you.

MINETTE NORMAN: All right. Now this is your time. And we have two mics in the room. So anyone who has a question, a comments, some feedback for us, raise your hand, and you'll get a mic. And I hope there are lots of questions. Please. Here's one. Start us off.

AUDIENCE: Would you talk a little bit about impacts sourcing and diversity sourcing and what the plans are around that for Autodesk?

MINETTE NORMAN: Who wants to take that? Impact sourcing? Diversity sourcing?

LEEANN MANON: Can you clarify that question?

AUDIENCE: That was supposed to be an easy question. So impact sourcing is when Autodesk buys services or products. They look for providers who are not only providing good products, but also making the world a better place. Diversity sourcing is making sure that when we're thinking about sourcing products, we go for-- we give an extra shot at those who are perhaps a woman owned or a veterinarian owned business. So these being sustainable is important, and it's really the core, but we have a lot of power in the marketplace as well that can influence the world to be a better place simply by our buying decisions.

LYNELLE CAMERON: Yeah, I can speak to that briefly. So through all of our sustainability programs, we are looking at our supply chain and thinking about both of those issues. What is their impact in the world? What are their sustainability practices themselves? Whether it's energy or other issues. And then similarly, in terms of diversity and wanting to make sure that we are having vendors that represent the diversity that's out there in the world, as well. So both of those things are things that we look it up in our supply chain, which people don't actually think about very often.

HEATHER KERRICK: I have something I just learned a few days ago. So like grain of salt. It's two degrees of separation away, so I think I'm getting this right. At AU itself, Autodesk actually was able to make some demands of our venues to achieve various sustainability standards. And those demands were able to go up the pipeline in Vegas and actually, to my knowledge, made changes in how the venue that we are currently in dealt with their supply-- dealt with their waste stream and their various sustainability practices. So events like this are a huge way that we are a big customer. Like we rent a venue. And so that's an example that I just learned about that is topical to us all.

LYNELLE CAMERON: It's a beautiful example. I should have thought of it. We did it actually several years ago where we were working with the Venetian and with these huge vendors on energy, on waste, on food. And we actually made a video about all of the ways that Autodesk University influenced this fine city that we're in. And this year, for the second year in a row, AU is carbon neutral. Again, it's kind of old news, but it's exciting news. And we've made it carbon neutral by partnering with our customers on several different projects that then offset the conference. So, thank you for the question and the answer.

MINETTE NORMAN: Great Other questions in the room? There's one up front here.

AUDIENCE: Thank you very much. It was great. My question is more toward--

MINETTE NORMAN: This end.

AUDIENCE: Yes. That side. I'm in the construction and design business, and also I'm educator. If I just want to explain my situation is I'm generation X. I'm between baby boomers. I get the goals and objectives of the company. And I'm going to use Generation Y and Z to create them.

And there is a huge gap between emotional intelligence that baby boomers used to direct me. And I cannot use the same process to connect to my team. That's number one, the big challenge that we have as a customer.

The second one is about stakeholder engagement. When you guys come up with these amazing idea of how to collaborate these application, building information modeling has huge effect on us. And I love it. I'm software engineer too, so it speaks my mind. But when we want to implement it, we'd have all these different generation with different skill set. You can't ask the president that has 40 plus your experience to just leave it to us. And you can't trust Generation Z. Absolutely not. I did it. I almost lost my job.

So what I'm asking how you engage your stakeholders from mud and blood, because what I see here, it's a group of very bright scientists that they are futuristic. But at the moment, we need-- I didn't know that I can't do integrated project delivery, because the insurance company wouldn't cover the architect we engaging in. But if I come here to this venue, it's the only way-- the only way for the future. You guys Ubering our industry. And you need to realize that. Are you doing anything to make it easier for us to implement it? That's my question.

MARIA GIUDICE: That's a really great question. And what's really interesting too is when we look at the products that we deliver, you can look at it two ways. One is we're actually creating functionality. We're creating things that enable people to make things. It's like-- I think of that sort of the nouns of what we do.

But then there's the verbs. It's all of the customer needs, their behaviors. Nothing is done in isolation. Everything is done in a team format. And you also have the complexity of deep people who have very deep expertise. You have multiple complexities. One is, how do you create products that support people who are new to the industry like younger people and who have very different expectations for technology and how it works? And all the way up the chain to people who have been in this industry for 15, 20, 30 years who are used to operating a certain way and use products a certain way. And they're like, really, don't move my button, because I've been trained that that button is right there. You move my button, I'm going to die.

And so it's a really hard problem to solve. How do you design experiences for that scope of people? And you could say that there's a lot of complexity in that, but you could also look at, what are the shared characteristics between the people who are new in the industry to people who are old in the industry? What do they need? What do they want? What do they desire? And then how do you make those tradeoffs so that you can create and deliver experiences to the maximum amount of people in a great way?

So you don't make choices. You don't say, we're going to ignore all the people who've been in the industry for a zillion years. Or we're going to ignore Generation Z, because frankly, they don't pay for our software yet. You have to really look at trends and behaviors and design for sort of the maximum amount of people with an eye towards the future. And what is our responsibility wrapping up sort of where Heather in the end-- how do we tie-in those things that you should be knowing about, that you need to know about? How do we educate or bring you along in a way that is a path forward?

So there's a lot of different trajectories, but we're not ignoring people who've been in the industry for a long time. And we're not ignoring people who are entering the industry. We have to look at that as a system that has to be solved, because that's the world we live in.

ALICIA WONG: Can I add to that?

MARIA GIUDICE: You can.

ALICIA WONG: I love your question, by the way, because there is a spectrum. And one of the things that Autodesk is really doing in our pivot to this new business model is when we write criteria for development-- software development-- we write them in this form of a story-- a user story-- with acceptance criteria that's about, what is it that's going to delight our customer? But really, looking at stakeholder management, as well.

I challenge. And I've got fellow colleagues out there in the audience that know I am a hard nose about-- I don't want just the architect in the room of that partner to come and give me the requirements. I want a cross-section of customers that are going to be those stakeholders who are truly going to give us that spectrum of what really is going to delight our customers and make our product something that's going to enable that incubator that a preemie that's born three or four months ahead of time in Rwanda can live to tell the next day. So really, it's a great question. And it is truly top of mind for us at Autodesk.

MARIA GIUDICE: Can I add one more small thing? Which is one of the things that everybody has in common, that everybody all needs, is that our products have to work a lot more smoother-- more simply. There's a lot of things we can do to remove the friction in the system to make an experience better for everybody. So that's an example of something that we're always looking at, which is removing the complexity in the product so that people could actually ramp up and learn a lot quicker. You're welcome.

AUDIENCE: [INAUDIBLE]

MARIA GIUDICE: I will have a drink with you later.

AUDIENCE: Thank you.

MARIA GIUDICE: You're welcome.

MINETTE NORMAN: Other questions in the room? Is there one back there?

AUDIENCE: Somewhat related. How do you manage releasing changes to workflows and updates to the products? And what some of those challenges would be?

MINETTE NORMAN: We can't hear you, I'm afraid.

AUDIENCE: Sorry. That better? What has some of the challenges been of updating workflows and changes in processes for the product or product suite? It's kind of a complimentless question. I hope some of those challenges will be really interesting to hear about.

ALICIA WONG: Workflow questions? How do we orchestrate?

AUDIENCE: And manage the release of updates to products--

ALICIA WONG: That is a million dollar question, and I would be dishonest if I told you we've completely figured that out. We actually have a few folks sitting back in the audience there that are our partners in crime. And we are constantly at the center of agility inspecting and adapting.

One of the facets of what we're trying from an agility perspective is something called the scaled agile framework, which is safe. And it's the notion of release trains. It's simplify, but really understand what is a thin slice of value we're going to deliver, but orchestrate as simply and as holistically as we can? So we really are sort of-- if you miss one train, we know that-- at least the Shinkansen in Japan-- you miss one train, 15 minutes on the dot, there's going to be another train. So that we're constantly delivering sort of this CICD continuous delivery of value-- constant delivery of value.

So we're moving a little bit to that notion of release trains. And we are orchestrating this, but we're going to try something. And if three months from now, it doesn't work, inspect and adapt, iterate it, and change it, so that we can move that forward. Hope that answered your question.

MINETTE NORMAN: I'm going to add on to that question. Because one of the things that-- so it's the backstage pass. It's the insider's view. One of the things is that we are struggling with this honestly because of our internal complexity. So this is where I'm being very honest. We have all of these product groups around the company. We're trying to deliver a seamless experience to all of you. And we have to figure out how to work together seamlessly internally so it can be really invisible to you, and we're not exposing our seems to you.

So that's something that, in my role, I'm working on very closely with Maria and with Alicia to make sure that we get rid of the friction internally so you don't experience it all. But we are not there yet. We are very much in the throes of it right now. Did that answer the question that you had? Thumbs up. OK, cool. Couple of more questions there.

AUDIENCE: This on? Yes. So this question is more towards the right hand side-- to your left. My right. It occurs to me-- Lynelle, you're kind of talking about the context in which we're designing, thinking about the future. Like the demographics, social, etc. And Heather, you're talking about the tech trends. So me, as customer, thinking about strategic planning for the future, the next five to 10 years, where do those two meet? And how is Autodesk thinking about the convergence of these technology trends and the social and demographic trends that are happening?

LYNELLE CAMERON: Maybe you can talk about the work that you're doing-- how you're thinking about climate change from the--

HEATHER KERRICK: Yeah, and this is one that we don't have a good hands on project for. But thinking about with climate change and sea level rising, we've been sort of dabbling in Maritime related research, because oceans are a big part of Earth. And most of our-- a lot of people live in coastal cities. And when sea level rise happens, my office will be under water. I'm on Pier 9. And Autodesk software is what's used to design a lot of infrastructure, to design a lot of cities, those cities that aren't yet built yet for all of those billions of people that aren't yet born.

And so with climate change, we're going to have to start thinking differently about how cities are involved, how cities are designed newly, but also how to evolve our existing cities. Do we do we fight it? Do we build a seawall? Do we have some way that we work well with nature and absorb it with some like breathing reef or something? There's going to be design challenges that no one's faced before that's going to need some sort of tool set to solve. So I think a lot of the things we don't necessarily have a say in is like how much my sea level's going to rise, and then-- it's going to happen at me, assuming that we don't get everyone in the world to drastically alter their carbon emissions and reverse climate change.

If you sort of assume that we're on our current path, and it's going to happen, we're going to need entirely new tools-- or at least new buttons in our existing tools-- for, oh, let me model my city with a foot of sea level rise. And same with the impact that the technology has. I work with robots, and everyone's worried about robots stealing their jobs. And robots might steal your job. I can't promise you that's not going to happen. And it's not just a manuel job. Machine learning might steal your software job. Nobody is safe. The future is coming, and it has-- there are casualties.

But I don't think the right answer to acknowledging the casualties of future technology is to try to stop it. Like, OK, we'll put all the robots in a closet. We'll never use a robot again. No one will use a computer. We will stop progress today, and all jobs will be safe. That's not the right way forward. And even if you do that, someone else isn't going to. And that person is the person who doesn't care that there are casualties to the technology. So you need people who are worried about the implications of their stuff early. I would rather have someone who's worried about an implication carry that thing forward than someone who doesn't care.

LYNELLE CAMERON: Can I just add onto that? Another way that we're bridging that gap between what the technology can-- you talked about some new buttons that we might have. The good news is that the technology today can address many of these challenges that we're facing. And so really showing how these different workflows can solve these problems through education. So Mooney mentioned the sustainability workshop that was translated in Vietnamese, and that's a way that we are showing not just the next generation, but customers how to use existing technology in really important ways to plan for sea level rise, to plan for a very different future. So education and the learning materials has a big role to play in bridging that gap.

MOONHIE CHIN: I think I'd like to actually add totally non-Autodesk answer. I have a high confidence on actually people. Because at the end of it, whether it's the technology or social aspect of it, it was always the people and their ideas that actually became not just new actually themes and came up with the solutions of actually of the world. So I'm hoping that our next generation and many more to come will actually use all these things available for them and come up with a different way. So maybe we can live under the world someday.

MINETTE NORMAN: There were some more questions. There's one.

AUDIENCE: Thanks So this is more of a question about product development and kind of the agile experience. I'm an Autodesk employee, but I've also been an Autodesk customer for about 20 years. And it seems like, Maria, I know your team-- you're really focused on user experience in the more malleable realms of our product portfolio right now, so the cloud enabled and kind of newer online offerings that we have. But when you look at some of our older tools, I think we follow this tradition of engineering tools that we deliver these monolithic solutions that do thousands of different things.

And in my own experience-- I'm a 3DS Macs user-- I know like 10% of that software program, and I've been using it for 20 years. So it's like-- I wonder if a more modular approach to being able to pick little bits out of different types of solutions that we have is kind of the way forward for us. And that allows us-- that kind of frees up the agile development idea in a lot easier of a way. So I'm kind of curious if you guys are thinking about it that way.

MARIA GIUDICE: Yeah. Totally. The way I like to describe our older products that were developed in the early days is we really ship a 10 course meal to our customers at the same time. We say, OK, here's a huge meal. You can figure out where to get the potatoes and where to eat the cupcakes. And we put the burden entirely on our customers to figure out the complexity of our products, depending on who they are and what they need to do. And that's because we're not-- they weren't built with the intelligence of really understanding specifically who our customers are, what they need, and what they need to do next.

And that's just the way product development was done in the past. We didn't-- but with where we are right now as we're moving from thinking about Autodesk as a company of products to a platform company, where the nirvana is having a common platform where we can create capabilities that people can pick and choose depending on who they are and what they need to do next. I'm not only giving them the ability to pick capabilities, but for our Autodeskers to be a lot more-- using data to better understand who our customers specifically are and to give them more custom experiences based on what we know they're using.

And so that's where we're moving. That's what's making it exciting. That we're going to be able to deliver smaller, more relevant experiences for people and give them a much clearer journey so that they don't get confused and have to-- and put the burden, cognitive burden, on them to get through our products. And Autodesk and AutoCAD and Revit, they're incredible programs. Very powerful. And they're older, and they are still loved and used by many, many people.

But we also will support that and with an eye towards the future. So we can develop more products that are going to be a little bit more easy to consume and also develop against.

ALICIA WONG: The democratization of a large monolithic codebase is absolutely front and center for every development team-- product development team out there in our ecosphere. You've nailed it on the head. We truly are trying to focus on this, how do we deliver capabilities and services that are the thin slice of that value? So impact, large impact, large value.

And so it is-- and we've got what we call our hero products that are really trying to turn the needle, because it's been 34 years of this is how we've built it, and that's how it's delivered. It is not the way we're looking at that path forward. So we are shaking things up pretty big and bold here at Autodesk.

MARIA GIUDICE: That's where machine learning and data science come in. So we-- to kind of tie the future to the present is we're not going to be delivering customer experiences if we're not smart about the data that we're collecting and how we're going to benefit our customers directly through the product experience.

LEEANN MANON: And I just want to put one more lens on that. Looking to Maria's point about the journey of really that lifetime journey, and particularly with the group that I'm in, how folks may start out learning in a product like Tinkercad. And they're really developing some skills. And how do we leveraging data and creating these experiences that are not monoliths? Where we're showing our organization that this product team over here created this experience, and this product team over here created this other experience. But we're able to say, hey, you're exhibiting the skill. You're working on this thing in this entry level product. And you're starting to bump up against the higher end of what that product can do and turn those light bulbs on and show that path. Hey, have you seen this next thing that you could go do and make that experience and that path seamless and natural so that our customers can go on from product to product?

MINETTE NORMAN: There's another question here in the middle of the room.

AUDIENCE: Hi. Jeff Kowalsky talked this morning about the need for continuous lifelong learning, because technology is changing so quickly. No one can expect to learn everything they need without one monolithic degree that they get. So what is Autodesk doing to support the lifelong learner, particularly the one that is out of school?

LEEANN MANON: Yeah, absolutely. So we are looking at lots of different ways. People learn in very different ways. And so making sure that there is a path for learning all the way from-- what we're saying now is from K to gray. Whatever it is that you're doing, as the technology advances, as your job changes, because trends are changing and the workplace is changing, that there's all these different opportunities to pick up that learning.

Whether it's in person at an event like this, as Moonhie mentioned. This is a learning community here at AU. If it's online in a MOOC, where you're going to go in on your own, take it on yourself to learn, or peer to peer learning, there's a lot of different ways that people want to acquire knowledge. And we're looking at ensuring that we can get the content out there in small pieces so that they can be consumed in the way that the individual is looking for.

MOONHIE CHIN: I think one thing I'd like to actually add is there are things that we can do directly, and there are things that we need to broker. So when it comes to a foundation learning or business transaction, we are on the hook to actually do that really well. But when we actually get to a learning, especially industry practice learning on more higher end, we do not actually have expertise internally. That means we need to actually make sure that we facilitate that to be really great.

So one thing I didn't talk about in AKN is we are creating a profile. So if you're an individual, you can come in, and you can create a profile, and you can get a reputation over time. So in some ways, we become a broker of connecting expertise outside. And I think that's where I think we can do a lot better. And once this reputation is really visible and common across this type of ecosystem, I think people can actually find them-- find other people easily. And I think that's where we can actually add value.

LEEANN MANON: Badging and micro credentialling really show the light for people to be able to connect with each other and understand who knows and who can help them out.

MOONHIE CHIN: Now, some of the backstage stuff is the [INAUDIBLE], and some stuff is a problem that we have that we can openly share. So not long ago, we actually created a unified profile with Maria's help and many people in the company. And we were many online properties. So if I was actually a customer, and I'm in AU online, and I'm in AKN, and I'm in ADN, you'd actually have all different profiles. We're trying to unify that.

So we started with the three properties, AKN, AU online, and our support community. Yesterday, same place that I learned about this Reddit blog customer, he actually told me-- he said, we have seven other properties that we need to go and unify. So we still have work to do. But it's the beginning. And I think the fact that we have a goal like that is actually a first step.

MINETTE NORMAN: Yeah. So I think I'm going to wrap it up. We have time for lots of interaction with you over a drink, so I hope you'll all stay for that. First, I want to just thank our panelists for the insights to what's really going on behind the scenes. So thank you all.

I also want to thank-- this event was sponsored, and it was sponsored by two organizations. One is what we call AWIL, Autodesk Women in Leadership. And as you notice, there are a few of them on the stage here, a few Women in Leadership. We're also sponsored by the Women in BIM, and especially Phil Bernstein who is here today. So shout out to Phil. Thank you.

And before we all go have a drink, I just want to tell you about one more event. Tomorrow evening from six to seven in The Hub, there is a Women at AU Networking Reception. Just an informal place for women who were here. Always the minority. Would love to get together. So please join us. Send all your women friends tomorrow from six to seven to The Hub.

MARIA GIUDICE: Or friendly men.

MINETTE NORMAN: Or friendly men I guess. Maybe. All right. Thank you. And please join us for a drink and a chat. Thank you.

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반드시 필요 - 사이트가 제대로 작동하고 사용자에게 서비스를 원활하게 제공하기 위해 필수적임

Qualtrics
오토데스크는 고객에게 더욱 시의적절하며 관련 있는 이메일 컨텐츠를 제공하기 위해 Qualtrics를 이용합니다. 이를 위해, 고객의 온라인 행동 및 오토데스크에서 전송하는 이메일과의 상호 작용에 관한 데이터를 수집합니다. 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID, 이메일 확인율, 클릭한 링크 등이 포함될 수 있습니다. 오토데스크는 이 데이터를 다른 소스에서 수집된 데이터와 결합하여 고객의 판매 또는 고객 서비스 경험을 개선하며, 고급 분석 처리에 기초하여 보다 관련 있는 컨텐츠를 제공합니다. Qualtrics 개인정보취급방침
Akamai mPulse
오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 Akamai mPulse를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID 및 오토데스크 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. Akamai mPulse 개인정보취급방침
Digital River
오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 Digital River를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID 및 오토데스크 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. Digital River 개인정보취급방침
Dynatrace
오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 Dynatrace를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID 및 오토데스크 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. Dynatrace 개인정보취급방침
Khoros
오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 Khoros를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID 및 오토데스크 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. Khoros 개인정보취급방침
Launch Darkly
오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 Launch Darkly를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID 및 오토데스크 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. Launch Darkly 개인정보취급방침
New Relic
오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 New Relic를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID 및 오토데스크 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. New Relic 개인정보취급방침
Salesforce Live Agent
오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 Salesforce Live Agent를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID 및 오토데스크 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. Salesforce Live Agent 개인정보취급방침
Wistia
오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 Wistia를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID 및 오토데스크 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. Wistia 개인정보취급방침
Tealium
오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 Tealium를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. Upsellit
오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 Upsellit를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. CJ Affiliates
오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 CJ Affiliates를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. Commission Factory
Typepad Stats
오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 Typepad Stats를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID 및 오토데스크 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. Typepad Stats 개인정보취급방침
Geo Targetly
Autodesk는 Geo Targetly를 사용하여 웹 사이트 방문자를 가장 적합한 웹 페이지로 안내하거나 위치를 기반으로 맞춤형 콘텐츠를 제공합니다. Geo Targetly는 웹 사이트 방문자의 IP 주소를 사용하여 방문자 장치의 대략적인 위치를 파악합니다. 이렇게 하면 방문자가 (대부분의 경우) 현지 언어로 된 콘텐츠를 볼 수 있습니다.Geo Targetly 개인정보취급방침
SpeedCurve
Autodesk에서는 SpeedCurve를 사용하여 웹 페이지 로드 시간과 이미지, 스크립트, 텍스트 등의 후속 요소 응답성을 측정하여 웹 사이트 환경의 성능을 모니터링하고 측정합니다. SpeedCurve 개인정보취급방침
Qualified
Qualified is the Autodesk Live Chat agent platform. This platform provides services to allow our customers to communicate in real-time with Autodesk support. We may collect unique ID for specific browser sessions during a chat. Qualified Privacy Policy

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사용자 경험 향상 – 사용자와 관련된 항목을 표시할 수 있게 해 줌

Google Optimize
오토데스크는 사이트의 새 기능을 테스트하고 이러한 기능의 고객 경험을 사용자화하기 위해 Google Optimize을 이용합니다. 이를 위해, 고객이 사이트를 방문해 있는 동안 행동 데이터를 수집합니다. 이 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID, 오토데스크 ID 등이 포함될 수 있습니다. 고객은 기능 테스트를 바탕으로 여러 버전의 오토데스크 사이트를 경험하거나 방문자 특성을 바탕으로 개인화된 컨텐츠를 보게 될 수 있습니다. Google Optimize 개인정보취급방침
ClickTale
오토데스크는 고객이 사이트에서 겪을 수 있는 어려움을 더 잘 파악하기 위해 ClickTale을 이용합니다. 페이지의 모든 요소를 포함해 고객이 오토데스크 사이트와 상호 작용하는 방식을 이해하기 위해 세션 녹화를 사용합니다. 개인적으로 식별 가능한 정보는 가려지며 수집되지 않습니다. ClickTale 개인정보취급방침
OneSignal
오토데스크는 OneSignal가 지원하는 사이트에 디지털 광고를 배포하기 위해 OneSignal를 이용합니다. 광고는 OneSignal 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 OneSignal에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 OneSignal에 제공하는 데이터를 사용합니다. OneSignal 개인정보취급방침
Optimizely
오토데스크는 사이트의 새 기능을 테스트하고 이러한 기능의 고객 경험을 사용자화하기 위해 Optimizely을 이용합니다. 이를 위해, 고객이 사이트를 방문해 있는 동안 행동 데이터를 수집합니다. 이 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID, 오토데스크 ID 등이 포함될 수 있습니다. 고객은 기능 테스트를 바탕으로 여러 버전의 오토데스크 사이트를 경험하거나 방문자 특성을 바탕으로 개인화된 컨텐츠를 보게 될 수 있습니다. Optimizely 개인정보취급방침
Amplitude
오토데스크는 사이트의 새 기능을 테스트하고 이러한 기능의 고객 경험을 사용자화하기 위해 Amplitude을 이용합니다. 이를 위해, 고객이 사이트를 방문해 있는 동안 행동 데이터를 수집합니다. 이 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID, 오토데스크 ID 등이 포함될 수 있습니다. 고객은 기능 테스트를 바탕으로 여러 버전의 오토데스크 사이트를 경험하거나 방문자 특성을 바탕으로 개인화된 컨텐츠를 보게 될 수 있습니다. Amplitude 개인정보취급방침
Snowplow
오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 Snowplow를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID 및 오토데스크 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. Snowplow 개인정보취급방침
UserVoice
오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 UserVoice를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID 및 오토데스크 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. UserVoice 개인정보취급방침
Clearbit
Clearbit를 사용하면 실시간 데이터 보강 기능을 통해 고객에게 개인화되고 관련 있는 환경을 제공할 수 있습니다. Autodesk가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. Clearbit 개인정보취급방침
YouTube
YouTube는 사용자가 웹 사이트에 포함된 비디오를 보고 공유할 수 있도록 해주는 비디오 공유 플랫폼입니다. YouTube는 비디오 성능에 대한 시청 지표를 제공합니다. YouTube 개인정보보호 정책

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광고 수신 설정 – 사용자에게 타겟팅된 광고를 제공할 수 있게 해 줌

Adobe Analytics
오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 Adobe Analytics를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID 및 오토데스크 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. Adobe Analytics 개인정보취급방침
Google Analytics (Web Analytics)
오토데스크 사이트에서 고객의 행동에 관한 데이터를 수집하기 위해 Google Analytics (Web Analytics)를 이용합니다. 여기에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 오토데스크는 사이트 성과를 측정하고 고객의 온라인 경험의 편리함을 평가하여 기능을 개선하기 위해 이러한 데이터를 이용합니다. 또한, 이메일, 고객 지원 및 판매와 관련된 고객 경험을 최적화하기 위해 고급 분석 방법도 사용하고 있습니다. AdWords
Marketo
오토데스크는 고객에게 더욱 시의적절하며 관련 있는 이메일 컨텐츠를 제공하기 위해 Marketo를 이용합니다. 이를 위해, 고객의 온라인 행동 및 오토데스크에서 전송하는 이메일과의 상호 작용에 관한 데이터를 수집합니다. 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID, 이메일 확인율, 클릭한 링크 등이 포함될 수 있습니다. 오토데스크는 이 데이터를 다른 소스에서 수집된 데이터와 결합하여 고객의 판매 또는 고객 서비스 경험을 개선하며, 고급 분석 처리에 기초하여 보다 관련 있는 컨텐츠를 제공합니다. Marketo 개인정보취급방침
Doubleclick
오토데스크는 Doubleclick가 지원하는 사이트에 디지털 광고를 배포하기 위해 Doubleclick를 이용합니다. 광고는 Doubleclick 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 Doubleclick에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 Doubleclick에 제공하는 데이터를 사용합니다. Doubleclick 개인정보취급방침
HubSpot
오토데스크는 고객에게 더욱 시의적절하며 관련 있는 이메일 컨텐츠를 제공하기 위해 HubSpot을 이용합니다. 이를 위해, 고객의 온라인 행동 및 오토데스크에서 전송하는 이메일과의 상호 작용에 관한 데이터를 수집합니다. 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID, 이메일 확인율, 클릭한 링크 등이 포함될 수 있습니다. HubSpot 개인정보취급방침
Twitter
오토데스크는 Twitter가 지원하는 사이트에 디지털 광고를 배포하기 위해 Twitter를 이용합니다. 광고는 Twitter 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 Twitter에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 Twitter에 제공하는 데이터를 사용합니다. Twitter 개인정보취급방침
Facebook
오토데스크는 Facebook가 지원하는 사이트에 디지털 광고를 배포하기 위해 Facebook를 이용합니다. 광고는 Facebook 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 Facebook에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 Facebook에 제공하는 데이터를 사용합니다. Facebook 개인정보취급방침
LinkedIn
오토데스크는 LinkedIn가 지원하는 사이트에 디지털 광고를 배포하기 위해 LinkedIn를 이용합니다. 광고는 LinkedIn 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 LinkedIn에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 LinkedIn에 제공하는 데이터를 사용합니다. LinkedIn 개인정보취급방침
Yahoo! Japan
오토데스크는 Yahoo! Japan가 지원하는 사이트에 디지털 광고를 배포하기 위해 Yahoo! Japan를 이용합니다. 광고는 Yahoo! Japan 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 Yahoo! Japan에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 Yahoo! Japan에 제공하는 데이터를 사용합니다. Yahoo! Japan 개인정보취급방침
Naver
오토데스크는 Naver가 지원하는 사이트에 디지털 광고를 배포하기 위해 Naver를 이용합니다. 광고는 Naver 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 Naver에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 Naver에 제공하는 데이터를 사용합니다. Naver 개인정보취급방침
Quantcast
오토데스크는 Quantcast가 지원하는 사이트에 디지털 광고를 배포하기 위해 Quantcast를 이용합니다. 광고는 Quantcast 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 Quantcast에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 Quantcast에 제공하는 데이터를 사용합니다. Quantcast 개인정보취급방침
Call Tracking
오토데스크는 캠페인을 위해 사용자화된 전화번호를 제공하기 위하여 Call Tracking을 이용합니다. 그렇게 하면 고객이 오토데스크 담당자에게 더욱 빠르게 액세스할 수 있으며, 오토데스크의 성과를 더욱 정확하게 평가하는 데 도움이 됩니다. 제공된 전화번호를 기준으로 사이트에서 고객 행동에 관한 데이터를 수집할 수도 있습니다. Call Tracking 개인정보취급방침
Wunderkind
오토데스크는 Wunderkind가 지원하는 사이트에 디지털 광고를 배포하기 위해 Wunderkind를 이용합니다. 광고는 Wunderkind 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 Wunderkind에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 Wunderkind에 제공하는 데이터를 사용합니다. Wunderkind 개인정보취급방침
ADC Media
오토데스크는 ADC Media가 지원하는 사이트에 디지털 광고를 배포하기 위해 ADC Media를 이용합니다. 광고는 ADC Media 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 ADC Media에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 ADC Media에 제공하는 데이터를 사용합니다. ADC Media 개인정보취급방침
AgrantSEM
오토데스크는 AgrantSEM가 지원하는 사이트에 디지털 광고를 배포하기 위해 AgrantSEM를 이용합니다. 광고는 AgrantSEM 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 AgrantSEM에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 AgrantSEM에 제공하는 데이터를 사용합니다. AgrantSEM 개인정보취급방침
Bidtellect
오토데스크는 Bidtellect가 지원하는 사이트에 디지털 광고를 배포하기 위해 Bidtellect를 이용합니다. 광고는 Bidtellect 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 Bidtellect에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 Bidtellect에 제공하는 데이터를 사용합니다. Bidtellect 개인정보취급방침
Bing
오토데스크는 Bing가 지원하는 사이트에 디지털 광고를 배포하기 위해 Bing를 이용합니다. 광고는 Bing 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 Bing에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 Bing에 제공하는 데이터를 사용합니다. Bing 개인정보취급방침
G2Crowd
오토데스크는 G2Crowd가 지원하는 사이트에 디지털 광고를 배포하기 위해 G2Crowd를 이용합니다. 광고는 G2Crowd 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 G2Crowd에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 G2Crowd에 제공하는 데이터를 사용합니다. G2Crowd 개인정보취급방침
NMPI Display
오토데스크는 NMPI Display가 지원하는 사이트에 디지털 광고를 배포하기 위해 NMPI Display를 이용합니다. 광고는 NMPI Display 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 NMPI Display에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 NMPI Display에 제공하는 데이터를 사용합니다. NMPI Display 개인정보취급방침
VK
오토데스크는 VK가 지원하는 사이트에 디지털 광고를 배포하기 위해 VK를 이용합니다. 광고는 VK 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 VK에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 VK에 제공하는 데이터를 사용합니다. VK 개인정보취급방침
Adobe Target
오토데스크는 사이트의 새 기능을 테스트하고 이러한 기능의 고객 경험을 사용자화하기 위해 Adobe Target을 이용합니다. 이를 위해, 고객이 사이트를 방문해 있는 동안 행동 데이터를 수집합니다. 이 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역, IP 주소 또는 장치 ID, 오토데스크 ID 등이 포함될 수 있습니다. 고객은 기능 테스트를 바탕으로 여러 버전의 오토데스크 사이트를 경험하거나 방문자 특성을 바탕으로 개인화된 컨텐츠를 보게 될 수 있습니다. Adobe Target 개인정보취급방침
Google Analytics (Advertising)
오토데스크는 Google Analytics (Advertising)가 지원하는 사이트에 디지털 광고를 배포하기 위해 Google Analytics (Advertising)를 이용합니다. 광고는 Google Analytics (Advertising) 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 Google Analytics (Advertising)에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 Google Analytics (Advertising)에 제공하는 데이터를 사용합니다. Google Analytics (Advertising) 개인정보취급방침
Trendkite
오토데스크는 Trendkite가 지원하는 사이트에 디지털 광고를 배포하기 위해 Trendkite를 이용합니다. 광고는 Trendkite 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 Trendkite에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 Trendkite에 제공하는 데이터를 사용합니다. Trendkite 개인정보취급방침
Hotjar
오토데스크는 Hotjar가 지원하는 사이트에 디지털 광고를 배포하기 위해 Hotjar를 이용합니다. 광고는 Hotjar 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 Hotjar에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 Hotjar에 제공하는 데이터를 사용합니다. Hotjar 개인정보취급방침
6 Sense
오토데스크는 6 Sense가 지원하는 사이트에 디지털 광고를 배포하기 위해 6 Sense를 이용합니다. 광고는 6 Sense 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 6 Sense에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 6 Sense에 제공하는 데이터를 사용합니다. 6 Sense 개인정보취급방침
Terminus
오토데스크는 Terminus가 지원하는 사이트에 디지털 광고를 배포하기 위해 Terminus를 이용합니다. 광고는 Terminus 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 Terminus에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 Terminus에 제공하는 데이터를 사용합니다. Terminus 개인정보취급방침
StackAdapt
오토데스크는 StackAdapt가 지원하는 사이트에 디지털 광고를 배포하기 위해 StackAdapt를 이용합니다. 광고는 StackAdapt 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 StackAdapt에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 StackAdapt에 제공하는 데이터를 사용합니다. StackAdapt 개인정보취급방침
The Trade Desk
오토데스크는 The Trade Desk가 지원하는 사이트에 디지털 광고를 배포하기 위해 The Trade Desk를 이용합니다. 광고는 The Trade Desk 데이터와 고객이 사이트를 방문하는 동안 오토데스크가 수집하는 행동 데이터 모두에 기초하여 제공됩니다. 오토데스크가 수집하는 데이터에는 고객이 방문한 페이지, 시작한 체험판, 재생한 동영상, 구매 내역 및 IP 주소 또는 장치 ID가 포함될 수 있습니다. 이 정보는 The Trade Desk에서 고객으로부터 수집한 데이터와 결합될 수 있습니다. 오토데스크는 디지털 광고 경험에 대한 사용자화를 개선하고 고객에게 더욱 관련 있는 광고를 제시하기 위해 The Trade Desk에 제공하는 데이터를 사용합니다. The Trade Desk 개인정보취급방침
RollWorks
We use RollWorks to deploy digital advertising on sites supported by RollWorks. Ads are based on both RollWorks data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that RollWorks has collected from you. We use the data that we provide to RollWorks to better customize your digital advertising experience and present you with more relevant ads. RollWorks Privacy Policy

정말 더 적은 온라인 경험을 원하십니까?

오토데스크는 고객 여러분에게 좋은 경험을 드리고 싶습니다. 이전 화면의 범주에 대해 "예"를 선택하셨다면 오토데스크는 고객을 위해 고객 경험을 사용자화하고 향상된 응용프로그램을 제작하기 위해 귀하의 데이터를 수집하고 사용합니다. 언제든지 개인정보 처리방침을 방문해 설정을 변경할 수 있습니다.

고객의 경험. 고객의 선택.

오토데스크는 고객의 개인 정보 보호를 중요시합니다. 오토데스크에서 수집하는 정보는 오토데스크 제품 사용 방법, 고객이 관심을 가질 만한 정보, 오토데스크에서 더욱 뜻깊은 경험을 제공하기 위한 개선 사항을 이해하는 데 도움이 됩니다.

오토데스크에서 고객님께 적합한 경험을 제공해 드리기 위해 고객님의 데이터를 수집하고 사용하도록 허용하시겠습니까?

선택할 수 있는 옵션을 자세히 알아보려면 이 사이트의 개인 정보 설정을 관리해 사용자화된 경험으로 어떤 이점을 얻을 수 있는지 살펴보거나 오토데스크 개인정보 처리방침 정책을 확인해 보십시오.