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Digital Twins: The Competitive Advantage

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说明

With 95.5% of all data captured in the design-build process typically unused or lost, digital-twin technology offers a powerful solution to this industry-wide challenge. We'll explore how these virtual replicas can bridge gaps in the handover process, securing data critical to successful facilities management. Architecture, engineering, and construction (AEC) holds a key role in the digital-twin building process. Through digital twins, AEC can deliver added value to customers in innovative ways, solve key problems, extend service value, and gain a competitive advantage. We'll provide guidance on how to introduce digital twins to building operators, paving the way for efficient problem-solving and more-sustainable operations. We'll also highlight success stories from organizations that have mastered digital twins, turning challenges into opportunities. Join the conversation on how to use the digital twin as a value-adding service, strengthening client relationships and fostering sustainability in your operations.

主要学习内容

  • Discover the role and impact of digital twins.
  • Discover how to position the digital twin to customers.
  • Learn how AEC can build digital twins to deliver added value to customers.

讲师

  • Karina Cardenas 的头像
    Karina Cardenas
    As a Customer Adoption Specialist for Autodesk Tandem, I'm driven by a passion for understanding what Design, Construction, and Facility Management teams value in our built environment. I thrive on aligning these insights to achieve common goals and capture key lessons to enhance our processes. With experience in Construction Management, Energy Efficiency Consulting, and Software Account Management, my greatest strength—and joy—lies in collaborating with diverse teams, sharing experiences, and transforming challenges into opportunities. I excel at improving workflows through technology, saving time and boosting efficiency in daily operations.
  • Arundhati Ghosh 的头像
    Arundhati Ghosh
    Arundhati Ghosh is a Customer Success Manager for Autodesk Tandem and an emerging voice as a subject-matter expert in Digital Twins. She is invested in streamlining Facilities Management (FM) workflows using the power of data and applying her skillsets in research, strategy, and technology to impact how facilities of the future will be managed. She has a master's degree in Architecture and a Ph.D. in Construction Management from Arizona State University. Outside of work, Arundhati is learning and developing her skills as a new mom, while making sure she has time to share her love for the great outdoors.
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Transcript

KARINA CARDENAS: Hi, there. You're watching our recorded presentation of Digital Twins, the Competitive Advantage for Autodesk University. Learning objectives for this session are the role and impact of digital twins, how to position the digital twin, and how AEC can build digital twins to deliver added value.

My name is Karina Cardenas, and I'm a customer adoption specialist.

ARUNDHATI GHOSH: And I'm Arundathi Ghosh, customer success manager.

KARINA CARDENAS: So full disclosure, at the time of this recording, we are on the Autodesk Tandem Team, which is Autodesk's digital twin solution.

ARUNDHATI GHOSH: Our role on the Tandem Team is to help customers realize their digital twins vision by guiding them through the journey of implementing a solution that is aligned with their outcomes. We'll talk a little more about Tandem later in this session.

KARINA CARDENAS: Before diving in, we want to share some background on both our personal and professional journeys to Autodesk University, why and how we got here, and to frame the perspectives we represent. Starting with myself, this is my first year presenting at AU.

I was born in Guam, a US territory located in the Western Pacific Ocean about a 3 and 1/2 hour flight from the Philippines where my parents are from. My dad was a jet engine mechanic in the US Navy. We moved to a couple duty stations before settling in the California Central Valley, also, where I went to college at Fresno State Bulldogs and studied construction management.

I worked in a variety of organizations for roofing insulation specialty contractor, a market research survey software provider, an environmental consultant that helped hard-to-reach markets plan and implement energy efficiency projects. Then, I worked for a local health care builder, was introduced to lean construction practices and VDC, and worked on some pretty cool make-ready and TI projects, including a hybrid OR.

The project that had the most impact on me was on a ground-up 200,000 square foot, 120-bed acute care hospital where long after clash detection and coordination, our project team used the model throughout construction for collaboration, building more efficiently, and we started to have early conversations with facilities about how the model could be used post construction.

In that time, I also attended my first AU. I was introduced to BIM Pro FM where I would meet my co-presenter. And I'll pause here and hand it off to her to talk about her journey.

ARUNDHATI GHOSH: Thanks, Karina the route to BIM 5 FM and digital twin seems like a meant to be story for me in retrospect. Born in New Delhi, India, to an architect dad, my first CAD memory is AutoCAD Release 14. Following in his footsteps, I studied architecture and kicked off my career at a small boutique studio, moving from bathroom details to project management.

Craving more, I headed to Arizona State University-- Go Sun Devils-- for grad school. I started in architecture but stayed on for a PhD in construction management. And thanks to my mentor and professor who opened my eyes to owner operations, facility management, and BIM's potential.

Post-graduation, I joined DPR Construction in San Francisco, where I worked with trail blazers in construction tech and [INAUDIBLE]. This is where I took the big leap. I was able to put in practice BIM 4 FM with two major owners in the San Francisco Bay Area, the airport and a large health care owner. And that's how I met Karina.

We both share a passion for empowering facility operators with visually engaging technology that delivers real value, which is why we are here today. In today's presentation, Karina will guide us from the AEC perspective while I provide insights from the owner's viewpoint. We'll alternate between these perspectives throughout the session. Karina, are we forgetting anything?

KARINA CARDENAS: Well, in the spirit of transparency, because this is the Design and Make Conference, we did use generative AI to help write the proposal that was one of 600-plus sessions selected out of 3,000 entries to be here presenting to you all today. Our presentation today is geared towards AEC colleagues, but we welcome all audiences from the owner space and anyone curious about digital twins.

So let's get into the role and impact of digital twins. There are many types of digital twins depending on who you're speaking with. Part of IBM's definition of a digital twin is a virtual representation of an object or a system to accurately reflect a physical object in the real world. It spans the object's life cycle. It's updated from real-time data. And it helps its users to make insightful decisions with a lot more certainty of the outcome.

One of the early digital twins was from the 1970 Apollo 13 mission, that famous quote by astronaut Jack Swigert, "Houston, we've had a problem." 55 hours into a mission intended to be the third lunar landing in the Apollo Space Program, an electrical fault caused a near-fatal explosion of their oxygen tank, also damaging the spacecraft's main engine. A living model or digital twin of Apollo 13 helped NASA Mission Control forensically analyze and explore how to get the astronauts safely home as efficiently as possible, which they did.

There's an emergence in application of digital twins in several industries. A groundbreaking use is NASA OSIRIS-REx mission, the first US mission to collect an asteroid sample from Bennu. The digital twin helped the team navigate the microgravity around the 4.5-billion-year-old asteroid, respond to changes, and adjust based on real-time data.

In health care, heart disease has been the leading cause of death in the US since 1950, and in 2021 alone, accounted for a third of all global deaths. The Living Heart Project brings together experts to develop highly accurate digital heart models, creating a unified foundation for cardiovascular in silicone and computational medicine. These models are revolutionizing medical device design, testing, and drug treatments, accelerating innovation and improving patient access to new, effective treatments for heart disease.

In infrastructure, South Korea-based offshore wind power project uses digital twins to enhance turbine operation visibility. A comprehensive model connected to IoT data and weather forecasts enable effective facility development, performance monitoring, and maintenance. These insights reduce costs, support new energy business opportunities, and environmental sustainability.

And in smart cities, Sweden's fourth largest city's use of the digital twin technology allows city planners to create detailed 3D models for exploring development scenarios and sharing sustainable growth plans. This technology integrates real-world data, including topography and vegetation, to design in context, improving the efficiency and sustainability of urban planning efforts.

ARUNDHATI GHOSH: Digital twin solutions enable a plethora of industry advancements and outcomes. However, the plethora of buzzwords can make it seem like there's a lot of noise. These buzzwords often refer to enabling technologies and emerging tech in an immature market, making the acronyms feel overwhelming. Much like the Great British Baking Show, where too many cooks in the kitchen can complicate the process, the digital twin landscape can also appear cluttered.

In the digital twin ecosystem, several core technologies are essential. Building Information Modeling, or BIM, creates digital representations of physical assets, including geometry, relationships, and metadata. GIS captures, stores, and analyzes geographical data, adding spatial context.

Simulation techniques model system behaviors, while the Internet of Things, IoT, connects physical devices to collect and exchange real-time data. Reality capture technologies create accurate 3D representation of physical spaces. Industry terms like Industry 4.0 refer to integrating digital tech into manufacturing for increased automation.

Industrialized construction enhances construction productivity through automation. And the metaverse introduces virtual worlds where users interact via avatars. And not to forget generative AI that enhances digital twins by generating synthetic data, optimizing processes, predicting outcomes, and facilitating integration. These technologies and more collectively support and enhance the digital twin space, driving innovation across industries.

KARINA CARDENAS: While we'd love to nerd out on all things digital twin, our focus for this discussion is on the competitive advantage of building twins. The concepts from today are based on our expertise in building twins in vertical construction but certainly can be applied to all digital twins.

In all digital twins examples mentioned earlier, all the connected to-- all are connected to a specific problem in the real world. To avoid being a shiny thing, the digital twin has to meet a business need and provide measurable benefit for a specific user or users. Looking at the anatomy of a digital twin, there are physical things in the digital twin and describes the assets, spaces, and systems in the facility and the relationships between them and data on what's happening to those things in the real world.

Together, this provides information about each component and the power to answer questions like, if this room is too hot or too cold, what are all the upstream components? Or if I need to take this component offline for maintenance, who will be affected by that downtime?

We should think about the digital twin not as a destination but a journey. Verdantix maturity model helps us understand that journey as levels. A descriptive twin provides a foundation of normalized data for a facility's assets, spaces, and systems. Leveraging as-built design and construction data creates a digital replica of the facility in a normalized representation curated for operations.

Informative twins augment the descriptive twin with operational and sensor data, both normalizing this data and delivering real-time and historic insights. Predictive twins introduce analytics to provide early fault detection and predictive insights for optimizing building operations. Comprehensive twins add simulation to perform those what-if scenarios. How might the upgrade of the system affect building performance or the reconfiguration of the space affect occupant utilization? And of course, autonomous twins leverage AI models to act on behalf of occupants and/or a self-tuned facility.

So you may have asked, what's in it for us? We know our values, but we also want to identify and align our customer values to drive a shared outcome. The most valuable outcomes are usually the ones where customer need, business opportunity, and our capabilities to deliver intersect. For example, making my project team successful, strengthening our relationship with our owner, enabling innovation and business growth are all valuable outcomes.

To support why AEC should care about digital twins, McKinsey published data where they found that 70% of C-suite technology executives were already exploring and investing in digital twins. Consumer electronic manufacturers found that using digital twins helped reduce scrap waste by 20% and also helped manage waste by reducing the material used in a product's design as well as improving the traceability of a product.

Interest in the digital twins combined with rapidly advancing supportive technologies is spurring market estimates for digital twin investments of more than $48 billion by 2026. Organizations are already using digital twins, including the largest brewer in the world, the team that won the last America's Cup, and Space Force and SpaceX.

ARUNDHATI GHOSH: Statistics represent the potential impact of digital twin. The reality is that when owners navigate the digital transformation journey, they often find themselves at various stages along the spectrum. Even with new projects being delivered in BIM, there will always be legacy data to contend, whether it's 2D CAD, blueprints, or in some cases, non-existent documentation.

The journey typically begins with the initial phase of digitization, converting physical documents and outdated digital formats into BIM. And as technology advances, it unlocks the potential for distributed teams to collaborate more effectively, improve coordination and project control, and even gain real-time insights.

However, the path to digital transformation is not uniform. Each owner's position will dictate the specific challenges and opportunities they face. And recognizing this enables more tailored support and guidance. The International Facilities Management Association, IFMA, and Autodesk recently surveyed a broad range of owner operators. The results were not surprising. 85% of the operators said they still struggle with fragmented data and data quality issues. This leads to additional challenges in space utilization, maintenance efficiency, and wasted energy.

So what are the aspirations of owner operators? Central to this conversation is recognizing that a high-performance facility enables its users to thrive in their business by creating value. Today's project delivery process often focuses on minimizing design and construction costs and duration. This benefits both the project team and the client by allowing them to complete and use the facility sooner.

However, the overall income generated from a facility depends not only on its early opening, but also how well it supports revenue generation over its lifetime. Owners would also like to keep the operating costs as low as possible, including facility maintenance costs, the building operating costs, such as energy, and the business operation costs, often the salaries of staff working in the facility.

Balancing these goals is challenging due to insufficient high-quality data and expertise that often comes too late to achieve an optimal plan. Design and construction teams may not have full control over all aspects of these buckets and often don't, but they have the opportunity to shape them in many ways.

So far, we've introduced what a digital twin is, its potential value to owner operators, and also touched upon some of the known challenges owner operators face. Keeping all this in mind, how can AEC teams come together and deliver value? In the next phase of this presentation, we will share with you some of the tools from our toolbox, which we have found successful when positioning a digital twin to solve the problems that owners give.

KARINA CARDENAS: One does not simply build a digital twin without knowing who your customer is and what their business needs are. We want to think about digital twin as a capability, the skills and tools needed to do a job, then understand, what are the outcomes? What is the business need that that capability will unlock? And what are the owner's value drivers? Then, we can position a solution to support that.

How that conversation can go, starting with the capability-- the owner wants to implement a digital twin. Why? Because at Handover, it takes months to get their work order system and preventative maintenance plan set up. This is important why? Because they want to get their data to their FM teams that they need to get up and running day one and so they can start planning day two and to overall improve the Handover experience for their next project from taking months to only days to set up their systems.

That conversation can also start with the outcome. The owner has an initiative to improve planning for environmental health and safety with faster response times to EH&S issues by 2X. Capabilities needed would be visualization of multiple systems, from BMS alarms to sensor readings, where they're located, what systems they're connected to, what's the last work order? A digital twin.

ARUNDHATI GHOSH: When we refer to an owner in the context of facilities management and construction, it's important to think of them as an organization rather than an individual. Within these organizations, there are typically distinct groups that are responsible for different aspects of their operations.

Often, one group focuses on capital expenditure, or CapEx, which includes planning and executing new projects. This is the team that most architecture, engineering, and construction professionals interact with, often directly or through a project manager or construction manager. Some capital teams even have their own internal design and construction units.

On the other hand, the Operational Expenditure team, or the OpEx, is responsible for ongoing operations and maintenance. This includes Facility Management, FM, which oversees facility engineering, facility services, and other operational tasks. The FM group may report to either the CFO or the CEO.

Supporting both CapEx and OpEx teams are essential departments like IT and finance. In some organizations, Facilities Management is integrated with IT, which is an ideal scenario for streamlined operations. And in some cases, asset management is under finance.

Additionally, there's a growing trend of departments who are focused on strategic initiatives, such as sustainability and analytics and digital trends. These departments often span across multiple organizational units, reflecting the increasing complexity and interconnectivity of modern facility management. Knowing whom you are speaking with and what their value drivers are can be a good starting point to position digital twins in the right context.

In every organization, stakeholders often have overlapping needs and use cases, which can create challenges in managing data efficiently. Frequently, data required for these various use cases is redundant or needs to be recreated, leading to inefficiencies and increased costs.

While it may not be possible to solve everyone's problems or address all their needs comprehensively, where AEC teams can offer their expertise is understanding how a single data set can potentially address multiple challenges. This is a strategic approach to maximize value and establish a strong return on investment.

So how does one go about uncovering the use cases and overlapping needs? Step one, identify who is the beneficiary. Who in the org will benefit from a digital twin? What's their role? What are their KPIs? We often think digital twins are for facility technicians, but remember the org structure. What are the jobs they perform? How do they perform those tasks? And what can be improved?

For this conversation, I reach into my lean handbook and look for the different types of waste in the process. Sometimes mapping the steps visually helps the discussion, for example, when we discovered how one asset manager was retyping asset data into their CMMS because they were receiving asset data sheets as printed documents, since that was what was in their contract.

Sometimes, talking about past experiences can reveal hidden challenges. Bucket them into process, technology, and people. A digital twin cannot solve every pain point, but at least you can help prioritize. For instance, we heard the story of a customer who spent hours locating a shut-off valve because it was hidden inside a column.

Next, do a visioning exercise. What would the future of this role look like? Approaching this conversation with empathy is critical. Some folks might find it threatening to adopt new technology for fear of losing work. True story. And now back to the readiness discussion, what capabilities would one need to support this new way of working? You cannot measure asset performance if you don't have sensors or a building management system.

Keeping the focus on the outcome and thinking about how you might measure that outcome can provide you with a basis for determining the ROI. Now, this may sound like a consultative approach that requires a lot of time. And in many cases, it is. Karina and I engage in the same conversation every day with customers. And often, not everyone has all the answers. And that's totally OK.

The important part here is knowing what questions to ask and how to build a repeatable use case that aligns with the customer's business objectives. For example, this is a use case statement that came out of a conversation we once had with a customer. As a capital project executive, I want to identify opportunities for underutilized space. The outcome-- to be repurposed to generate potential rental revenue. How will you measure it?

So once the customer and their needs are understood, use cases are more or less established, the next steps are understanding the use of the data itself. This is how we begin to align the solution that's the digital twin with the use case. Who will use the data? We just talked about that. What data is needed? And how will you collect it?

This is where the AEC team has to uncover the right data needed to support the use case and how and where it is collected. In the example of the capital project executive, what information do you think they would need to see if a space is underutilized? Maybe they'll need room data like departments, capacity, data from occupancy sensors to see a count of people in a space at any given time.

We have an example of a customer who used pings from their Wi-Fi signals to determine occupancy metrics. How will you collect the data? What data do you need from the BIM, from sensors, and so on? How will the data be maintained? Data integrity is critical to accurate and reliable building operations and maintenance. So what is the plan for data maintenance?

KARINA CARDENAS: To suss out customer technical readiness, we want to understand where they are in these areas. Do they have a need/use case? What's their BIM maturity? You don't actually need to be LOD 500. What's required to be modeled should match up with their use case. FM maturity, do they have a work order system? Are they using sensors and IoT?

Very important, do they have a change management process? Are they going to need a conditions assessment? For example, their asset system data and space management data are up to date, but their floor plans and models are not. We want to identify where the gaps are. The bigger the gap, the more level of effort and risk you take on.

In BIM maturity, for example, think of it as your owner is still in the early stages of their digital transformation journey and may only have 2D CAD workflows where you'll need to advise strategies to level them up, like scan to BIM. There are also tools available like the Digital Twin Requirements Assessment on intandem.autodesk.com.

We've worked with several customers in the AEC space. And based on the playbook we just shared, here are some common outcomes we have seen customers gravitate towards. So during the build, there's the validation twin that deliver what's been specified, meaning substantial completion milestones, including asset data and warranty, sequencing tracking for commissioning activities.

And then beyond the build, turnover on-time budget, on-time budget, supporting warranty management and preventative maintenance planning, and then, preparing for day one operations. And then for future planning, preparing for day two, what's the next set of capital improvements, and then demand-based future planning.

ARUNDHATI GHOSH: Similarly, working with owner operators, we find that the digital twin has the potential to impact process improvements, for example, preparing standard operating procedures for operations and maintenance and planning for staffing, training staff, and providing access.

Digital twins can also impact daily actions, like prioritizing, work, the time to resolution for reactive maintenance scenarios like finding that valve leak, having readily available data for ESG, EHS, regulatory compliance, and reporting. And also, we are starting to see the use of digital twin for smart building operations, like, for example, coming up with maintenance schedules.

Karina, all this sounds like great use cases to implement with digital twins. But how can an AEC firm expand and diversify its services? Any ideas?

KARINA CARDENAS: So many. Our outcome in building digital twins is to expand and diversify our services. Consider this a menu of the service offerings focusing on consulting for BIM standards and BIM for FM, these services can happen throughout the building life cycle, the long game, if you will. The advantage there is having a deep understanding of customer outcomes as well as setting expectations for implementation.

Then, there's implementation to build the descriptive twin close model with asset data, including building out PM plans and managing warranty. And then adding to the descriptive twin is systems integration to build with the customer's custom systems. Additional services include change management, which we talked about earlier, on call maintenance, analytics, and reporting.

There's also a do everything approach. Also getting into the space are HVAC controls and equipment providers. They're all focusing on leveraging cloud platforms and connected services to improve maintenance operations and address labor shortages in the industry. So we're a few slides away from the end of our presentation. We hope you're excited about building digital twins to deliver added value to your customers.

We want to close out this presentation with two case studies that ground this conversation in reality. Quinn Evans, AAA's 2024 Architecture Firm Award winner headquartered in Washington, DC, is dedicated to empowering communities and enriching lives through design. The firm emphasizes collaboration, creativity, and expertise to achieve sustainable, impactful design solutions with a strong commitment to preserving and renewing the built environment.

Furthering their EBIM-- that's Existing Building Information Modeling-- and HBIM-- Historic Building Information Management-- goals with the Michigan State capital's commitment to preserving the building's history, art, and architecture for future generations are realizing the value of combining scan to BIM to twin for building preservation and restoration efforts.

The Michigan State Capital Twin allows for more efficient management of building information, streamlining workflows, and providing significant operational insights to maintain and restore the historic building, and offering a more dynamic and accessible way to manage and preserve these structures. If you haven't already, you should watch Robin Charles's AU presentation, Past Meets Future, Preserving History with Digital Twins.

ARUNDHATI GHOSH: The second case study is of the University of Birmingham, an owner. Their mission is to contribute to the spread of knowledge and ideas to help transform the world. Their campus includes 300 buildings with 8,000 staff, 40,000 students with a variety of space types that include medical and research buildings.

The Estates Team in collaboration with IT services were driven to capitalize on the efficiency gains of better space management to support financial management and carbon reduction. In their digital twin pilot, they found that In Tandem allows them to organize their data in a way that allows the university to unlock complex insights and take action to improve their operations.

Some of the lessons learned were that some of their spaces were significantly underutilized, there was a disconnect between the perceived use of space and actual utilization, and that the campus dynamics change drastically after 5:00 PM. There's also a need to develop capabilities for more complex and dynamic campus management.

The team also shared that benefits of a campus digital twin can be reducing energy and costs, improving the use of the space, informing strategy, and encouraging positive behaviors. Each of these have their own measurable benefits and ROI. We often get asked, what is the ROI for digital twin?

We don't think the market is mature yet to answer this. And it's important to emphasize that ROI is unique to the problem each organization is looking to solve. If you'd like to hear more about the University of Birmingham's presentation, you can watch the webinar on intandem.autodesk.com.

In summary, our call to action for our AEC friends in this room is empathize with your owner customers. Understand their outcomes, their use cases, and their capabilities. Understand where they are today and where they want to go. And then, make a plan to strategically address some of those concerns that the owners often think about, especially with digital twins like data maintenance, change management, and security.

And then assess which combination of solutions is the best for your business, and also, your owner customer. Should you build a bespoke twin with customer [AUDIO OUT]? Or should you buy an off-the-shelf product that offers scalable growth? The answer will depend on your business and the value that your owner seeks.

KARINA CARDENAS: So how do you even begin? First, you can evaluate the digital twin options, do a technical evaluation like twinning your office. You could run a pilot on active projects where data is more readily available. You can also educate your customers through RFPs. RFIs is RFPs.

We're starting to see requests for qualifications and proposals for digital twin providers that includes the owner's specific use cases. We've even seen included in a scope of work specifying a specific digital twin solution, like Autodesk Tandem. It's really exciting to see.

ARUNDHATI GHOSH: The McKinsey article, "Digital Trends and Generative AI, a Powerful Pairing," explores how the combination of digital twins and generative AI can transform organizational operations. Generative AI can streamline the deployment of digital twins, while digital twins can refine and validate the outputs generated by AI. This synergy can enhance decision-making, optimize operations, and drive efficiencies across various industries.

KARINA CARDENAS: We want to leave you with this thought. Consider this. What if AI could create a digital twin, allowing you to focus on what truly matters, designing, constructing, and managing self-tuning self-healing facilities of the future all while leaving no environmental footprints? Thank you for watching our presentation.

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我们通过 Digital River 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Digital River 隐私政策
Dynatrace
我们通过 Dynatrace 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Dynatrace 隐私政策
Khoros
我们通过 Khoros 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Khoros 隐私政策
Launch Darkly
我们通过 Launch Darkly 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Launch Darkly 隐私政策
New Relic
我们通过 New Relic 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. New Relic 隐私政策
Salesforce Live Agent
我们通过 Salesforce Live Agent 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Salesforce Live Agent 隐私政策
Wistia
我们通过 Wistia 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Wistia 隐私政策
Tealium
我们通过 Tealium 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Tealium 隐私政策
Upsellit
我们通过 Upsellit 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Upsellit 隐私政策
CJ Affiliates
我们通过 CJ Affiliates 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. CJ Affiliates 隐私政策
Commission Factory
我们通过 Commission Factory 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Commission Factory 隐私政策
Google Analytics (Strictly Necessary)
我们通过 Google Analytics (Strictly Necessary) 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Google Analytics (Strictly Necessary) 隐私政策
Typepad Stats
我们通过 Typepad Stats 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Typepad Stats 隐私政策
Geo Targetly
我们使用 Geo Targetly 将网站访问者引导至最合适的网页并/或根据他们的位置提供量身定制的内容。 Geo Targetly 使用网站访问者的 IP 地址确定访问者设备的大致位置。 这有助于确保访问者以其(最有可能的)本地语言浏览内容。Geo Targetly 隐私政策
SpeedCurve
我们使用 SpeedCurve 来监控和衡量您的网站体验的性能,具体因素为网页加载时间以及后续元素(如图像、脚本和文本)的响应能力。SpeedCurve 隐私政策
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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改善您的体验 – 使我们能够为您展示与您相关的内容

Google Optimize
我们通过 Google Optimize 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Google Optimize 隐私政策
ClickTale
我们通过 ClickTale 更好地了解您可能会在站点的哪些方面遇到困难。我们通过会话记录来帮助了解您与站点的交互方式,包括页面上的各种元素。将隐藏可能会识别个人身份的信息,而不会收集此信息。. ClickTale 隐私政策
OneSignal
我们通过 OneSignal 在 OneSignal 提供支持的站点上投放数字广告。根据 OneSignal 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 OneSignal 收集的与您相关的数据相整合。我们利用发送给 OneSignal 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. OneSignal 隐私政策
Optimizely
我们通过 Optimizely 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Optimizely 隐私政策
Amplitude
我们通过 Amplitude 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Amplitude 隐私政策
Snowplow
我们通过 Snowplow 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Snowplow 隐私政策
UserVoice
我们通过 UserVoice 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. UserVoice 隐私政策
Clearbit
Clearbit 允许实时数据扩充,为客户提供个性化且相关的体验。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。Clearbit 隐私政策
YouTube
YouTube 是一个视频共享平台,允许用户在我们的网站上查看和共享嵌入视频。YouTube 提供关于视频性能的观看指标。 YouTube 隐私政策

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定制您的广告 – 允许我们为您提供针对性的广告

Adobe Analytics
我们通过 Adobe Analytics 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Adobe Analytics 隐私政策
Google Analytics (Web Analytics)
我们通过 Google Analytics (Web Analytics) 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Google Analytics (Web Analytics) 隐私政策
AdWords
我们通过 AdWords 在 AdWords 提供支持的站点上投放数字广告。根据 AdWords 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 AdWords 收集的与您相关的数据相整合。我们利用发送给 AdWords 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. AdWords 隐私政策
Marketo
我们通过 Marketo 更及时地向您发送相关电子邮件内容。为此,我们收集与以下各项相关的数据:您的网络活动,您对我们所发送电子邮件的响应。收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、电子邮件打开率、单击的链接等。我们可能会将此数据与从其他信息源收集的数据相整合,以根据高级分析处理方法向您提供改进的销售体验或客户服务体验以及更相关的内容。. Marketo 隐私政策
Doubleclick
我们通过 Doubleclick 在 Doubleclick 提供支持的站点上投放数字广告。根据 Doubleclick 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Doubleclick 收集的与您相关的数据相整合。我们利用发送给 Doubleclick 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Doubleclick 隐私政策
HubSpot
我们通过 HubSpot 更及时地向您发送相关电子邮件内容。为此,我们收集与以下各项相关的数据:您的网络活动,您对我们所发送电子邮件的响应。收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、电子邮件打开率、单击的链接等。. HubSpot 隐私政策
Twitter
我们通过 Twitter 在 Twitter 提供支持的站点上投放数字广告。根据 Twitter 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Twitter 收集的与您相关的数据相整合。我们利用发送给 Twitter 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Twitter 隐私政策
Facebook
我们通过 Facebook 在 Facebook 提供支持的站点上投放数字广告。根据 Facebook 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Facebook 收集的与您相关的数据相整合。我们利用发送给 Facebook 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Facebook 隐私政策
LinkedIn
我们通过 LinkedIn 在 LinkedIn 提供支持的站点上投放数字广告。根据 LinkedIn 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 LinkedIn 收集的与您相关的数据相整合。我们利用发送给 LinkedIn 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. LinkedIn 隐私政策
Yahoo! Japan
我们通过 Yahoo! Japan 在 Yahoo! Japan 提供支持的站点上投放数字广告。根据 Yahoo! Japan 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Yahoo! Japan 收集的与您相关的数据相整合。我们利用发送给 Yahoo! Japan 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Yahoo! Japan 隐私政策
Naver
我们通过 Naver 在 Naver 提供支持的站点上投放数字广告。根据 Naver 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Naver 收集的与您相关的数据相整合。我们利用发送给 Naver 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Naver 隐私政策
Quantcast
我们通过 Quantcast 在 Quantcast 提供支持的站点上投放数字广告。根据 Quantcast 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Quantcast 收集的与您相关的数据相整合。我们利用发送给 Quantcast 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Quantcast 隐私政策
Call Tracking
我们通过 Call Tracking 为推广活动提供专属的电话号码。从而,使您可以更快地联系我们的支持人员并帮助我们更精确地评估我们的表现。我们可能会通过提供的电话号码收集与您在站点中的活动相关的数据。. Call Tracking 隐私政策
Wunderkind
我们通过 Wunderkind 在 Wunderkind 提供支持的站点上投放数字广告。根据 Wunderkind 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Wunderkind 收集的与您相关的数据相整合。我们利用发送给 Wunderkind 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Wunderkind 隐私政策
ADC Media
我们通过 ADC Media 在 ADC Media 提供支持的站点上投放数字广告。根据 ADC Media 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 ADC Media 收集的与您相关的数据相整合。我们利用发送给 ADC Media 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. ADC Media 隐私政策
AgrantSEM
我们通过 AgrantSEM 在 AgrantSEM 提供支持的站点上投放数字广告。根据 AgrantSEM 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 AgrantSEM 收集的与您相关的数据相整合。我们利用发送给 AgrantSEM 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. AgrantSEM 隐私政策
Bidtellect
我们通过 Bidtellect 在 Bidtellect 提供支持的站点上投放数字广告。根据 Bidtellect 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Bidtellect 收集的与您相关的数据相整合。我们利用发送给 Bidtellect 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Bidtellect 隐私政策
Bing
我们通过 Bing 在 Bing 提供支持的站点上投放数字广告。根据 Bing 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Bing 收集的与您相关的数据相整合。我们利用发送给 Bing 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Bing 隐私政策
G2Crowd
我们通过 G2Crowd 在 G2Crowd 提供支持的站点上投放数字广告。根据 G2Crowd 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 G2Crowd 收集的与您相关的数据相整合。我们利用发送给 G2Crowd 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. G2Crowd 隐私政策
NMPI Display
我们通过 NMPI Display 在 NMPI Display 提供支持的站点上投放数字广告。根据 NMPI Display 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 NMPI Display 收集的与您相关的数据相整合。我们利用发送给 NMPI Display 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. NMPI Display 隐私政策
VK
我们通过 VK 在 VK 提供支持的站点上投放数字广告。根据 VK 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 VK 收集的与您相关的数据相整合。我们利用发送给 VK 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. VK 隐私政策
Adobe Target
我们通过 Adobe Target 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Adobe Target 隐私政策
Google Analytics (Advertising)
我们通过 Google Analytics (Advertising) 在 Google Analytics (Advertising) 提供支持的站点上投放数字广告。根据 Google Analytics (Advertising) 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Google Analytics (Advertising) 收集的与您相关的数据相整合。我们利用发送给 Google Analytics (Advertising) 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Google Analytics (Advertising) 隐私政策
Trendkite
我们通过 Trendkite 在 Trendkite 提供支持的站点上投放数字广告。根据 Trendkite 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Trendkite 收集的与您相关的数据相整合。我们利用发送给 Trendkite 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Trendkite 隐私政策
Hotjar
我们通过 Hotjar 在 Hotjar 提供支持的站点上投放数字广告。根据 Hotjar 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Hotjar 收集的与您相关的数据相整合。我们利用发送给 Hotjar 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Hotjar 隐私政策
6 Sense
我们通过 6 Sense 在 6 Sense 提供支持的站点上投放数字广告。根据 6 Sense 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 6 Sense 收集的与您相关的数据相整合。我们利用发送给 6 Sense 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. 6 Sense 隐私政策
Terminus
我们通过 Terminus 在 Terminus 提供支持的站点上投放数字广告。根据 Terminus 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Terminus 收集的与您相关的数据相整合。我们利用发送给 Terminus 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Terminus 隐私政策
StackAdapt
我们通过 StackAdapt 在 StackAdapt 提供支持的站点上投放数字广告。根据 StackAdapt 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 StackAdapt 收集的与您相关的数据相整合。我们利用发送给 StackAdapt 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. StackAdapt 隐私政策
The Trade Desk
我们通过 The Trade Desk 在 The Trade Desk 提供支持的站点上投放数字广告。根据 The Trade Desk 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 The Trade Desk 收集的与您相关的数据相整合。我们利用发送给 The Trade Desk 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. The Trade Desk 隐私政策
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

是否确定要简化联机体验?

我们希望您能够从我们这里获得良好体验。对于上一屏幕中的类别,如果选择“是”,我们将收集并使用您的数据以自定义您的体验并为您构建更好的应用程序。您可以访问我们的“隐私声明”,根据需要更改您的设置。

个性化您的体验,选择由您来做。

我们重视隐私权。我们收集的数据可以帮助我们了解您对我们产品的使用情况、您可能感兴趣的信息以及我们可以在哪些方面做出改善以使您与 Autodesk 的沟通更为顺畅。

我们是否可以收集并使用您的数据,从而为您打造个性化的体验?

通过管理您在此站点的隐私设置来了解个性化体验的好处,或访问我们的隐私声明详细了解您的可用选项。