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You Have to Believe It Before You See It: Growing a Startup Digitally

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说明

The buzz around artificial intelligence (AI), virtual reality (VR), and digital twins in manufacturing can be overwhelming. In reality, these technologies can add real value to your firm. Even though 73% of manufacturers believe digital technologies will increase ROI, more than half have yet to implement them. The Autodesk Foundation and Microdesk Co-Innovation Lab partnered with Pallet Shelter, a rapidly growing startup with a mission to combat homelessness, expand workforce development, and promote sustainable communities. Through this collaboration, Pallet Shelter is strengthening channels of communication and means of storing and sharing data by implementing solutions from the Autodesk ecosystem. With centrally accessible documentation and built-in business procedures, unifying the firm on a common data environment (CDE) gives key stakeholders insight into the design process. This infrastructure supports the company's rapid and long-term expansion.

主要学习内容

  • Learn about critical lines of communication and cross-departmental workflows.
  • Learn how to implement PDM and PLM solutions to breakdown informational and departmental silos.
  • Learn about integrating collaborative workflows for design review and innovation.
  • Learn about expanding business, technology, and growth opportunities by bolstering data infrastructure.

讲师

  • Tristan Aarons 的头像
    Tristan Aarons
    As an Senior Applications Engineer, Tristan provides support and consulting services to Symetri Customers by optimizing their software utilization and their design processes. He specializes in developing 3D models, implementing generative design, and conducting simulations. His goal is to help companies increase efficiency, improve designs, and promote sustainable manufacturing by utilizing best in practice tools.
  • Shivani Soni
    As the Global Head of Impact and Innovation at Symetri, Shivani is passionate about driving innovation and promoting sustainable solutions that benefit communities worldwide. With a focus on co-innovation practises, she works to develop organisation-wide digital transformation journeys that fuel growth and enable businesses to compete in the global marketplace. Shivani is committed to building strategic partnerships with stakeholders, customers, and innovation communities to deliver compliant and impactful solutions. Through research, creation, and implementation of new business propositions and innovation models, she strives to advance the industry and promote sustainable development. By adopting digital technologies and fostering a culture of innovation, Shivani supports the industry in accelerating growth, improving business activities, and enhancing the experiences of their people, customers, and communities. Her vision is to drive positive change through collaboration, innovation, and impact-driven solutions.
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Transcript

TRISTAN GUNDERSON: Welcome to You Have to Believe It Before You See It-- Growing a Startup Digitally. Before we get started, a little overview of what we'll be covering today. We'll start with introductions of myself and the other key players and then dive right into our case study of Pallet. Pallet is a startup, and like many startups, they've faced many different issues as they've grown from a small company into a much larger and more successful one.

We'll talk about some of those issues they've faced and then how we help develop a digital foundation leveraging the Autodesk ecosystem in order to support that growth and build from there. And lastly, talk about some of those outcomes, the impact, and even future opportunities because of that development and growth.

My name is Tristan Gunderson. I'm an applications engineer at Microdesk. I focus on mechanical design and simulation consulting, always with a eye for sustainable manufacturing and how it relates to Microdesk as well as all of the companies that we work with. I've released several publications from Demystifying General Design to Rapid Prototype to Optimize Telework in Manufacturing, all to help support the growth of sustainable manufacturing and innovation within the industry.

Today, we're going to be talking about Pallet, shelter for the people by the people. I'll start with a quick quote from Pallet, which is, "No one should go unsheltered when a shelter can be built in a day. Pallet is a leader in rapid-response shelter villages that combine the dignity of personal space with the healing of community."

So Pallet is a startup that was founded in 2016. They seek to ultimately end homelessness by providing not only temporary shelter to those who find themselves homeless due to either economic hardships, natural disasters, political or even armed conflicts, and more. But they also provide a pathway and resources for those residents to move on to more permanent housing.

They do this by creating these shelters. It all started with their original 64 square foot shelter that provided accommodations and housing for two individuals. From there, they expanded to a 100-foot shelter that could house four individuals or even a small family and then continued to expand their repertoire with shelters such as hygiene units, so that the residents have access to clean bathrooms, showers, and other essentials for dignified living.

They support this in order to help these communities, be it refugees, or homeless encampments within cities, working with the city planning in order to create not just single units but entire communities, so that the residents can live and thrive within the community and ultimately eventually move on to permanent housing. As stated by members of Pallet, their ultimate goal would be to put themselves out of business by ultimately ending homelessness altogether.

Beyond their work creating these shelters for homeless and refugees, they also work as a second chance employer. This means they provide job opportunities for individuals who might have trouble receiving jobs at other companies due to different things in their past.

This not only provides them with steady income as they work for Pallet. But they also gain access to training, development, and learn new skills that help them grow not only within the company of Pallet but also with the ability to move to other companies and leverage those skills that they learned while working at Pallet.

I work for Microdesk and Symetri. We started working with Pallet as a consultant. At Microdesk, we work as engineering, manufacturing, architecture and technology consultants across the globe thanks to our recent partnership with Symetri.

We provide these consulting services through direct hands-on consulting through our connections with our partners, such as Autodesk, and through training directly to our different partners and clients. We seek to ultimately promote the technological advancement of the industry at large and promote better and more sustainable practices across the industries.

Within Microdesk and Symetri, we partnered through Pallet through the Co-Innovation Lab, which is our internal co-innovation, co-research, co-develop unit. What the Co-Innovation Lab does is we connect with our clients, so that we can achieve better technology. We can co-research, co-develop, perform R&D as a collective unit using sustainability as a catalyst.

Because with sustainability as the catalyst, we're able to push forward these initiatives and find new areas of growth and advancement that not only can benefit the companies, can benefit the working processes, the efficiency, but also support a better world and help us grow and protect our industry and our livelihood.

We would like to thank the Autodesk Foundation. Autodesk Foundation connected us and supports Pallet. And not only did they sponsor this project, but by fostering our relationship with philanthropic and sustainable organizations like Pallet, we're able to use these partnerships to work together to improve how we work and live. The Autodesk Foundation aligns its philanthropic offerings with design and engineering.

They invest in nonprofits and startups helping to de-risk innovation and bring industry transforming solutions to scale. By facilitating a blend of funding technical training and expertise, they bring early stage transformative innovations to market to advance a more sustainable, resilient, and equitable world. So it was the Autodesk Foundation that connected us with Pallet and brought us in on this project to help them grow as a company and move towards seeking their ultimate goal of ending homelessness.

Of course, with that growth comes some growing pains. Now, this isn't something that's unique to Pallet or even unique to startups. This is something that's experienced by all companies, big and small.

We see it very prevalently within startups, growing from a small company to a much larger one, going from little as 10 people in a single office working on a single model to upwards of 100 people, multiple office, and a entire product line. Trying to grow that data, those communications, those workflows, it takes a lot of time and effort. And with the demands of startups, it's hard to take the time out to reflect back and to update those systems.

So from there, some specific examples that Pallet faced is they started with just their single 64 square foot unit. This singular model was designed using CAD. And from there, as their company started grew and their product line started to grew, they started to alter this original model to create the new versions, extending it to the 100 unit and then beyond that point.

However, as their team and their company began to grew-- grow-- this singular model became more and more complex, requiring a series of different suppression states and different dimensions in order to achieve the different versions of the models, ultimately leading to a point that was no longer sustainable.

Beyond this, as all companies do, there are always breakdowns in communication that happen within a company. Whether it's information that's not being communicated, for Pallet, since they had all of their data saved on network there was problems of what people can access, what people can find, and what people shouldn't access.

So you can run into the issues of manufacturing building outdated designs or sales associates finding new designs that haven't been released yet and selling them before they have. For Pallet, a similar problem happened, where they had a huge sale on a design that was still in development.

Of course, this does drive innovation as demand goes up. However, it was clear that they needed to reorganize some structures in order to support this growth in a more sustainable way. So that's where Autodesk came in, and ultimately, we came in. Looking for ways to establish new systems and grow their existing ones, so that they could support this growth and this development.

So the very first thing that needed to happen was to rebuild that original model and those original designs and create them in a program where we could design parametrically and build them out in a way that they could be understood, interacted with, and grown upon by all users.

They also needed to reorganize data, ideally, leveraging a PDM solution, a product data management, in order to organize that data, be able to control permissions, controls, and establish standards across their data, being able to create consistent numbering schemes, be able to control the user access, and ultimately, even promote collaboration.

One of the issues often faced by Pallet and other startups is that all of their engineering data on the drive would be saved by different users in different locations, to the point where trying to find the right part required a system-wide search of the part number. By starting with a new structure and being able to build in that organization from the ground up and create systems to maintain that organization moving forward, it would put them in a place where they could reduce a lot of overwork, redundancies of multiple versions of the same part, and other necessary changes.

And then lastly, developing systems for new product introduction and release workflows and permissions, making sure that the right users have access to the right data and that there's clear communication of where a design sits within the design phase and what is needed of it and of the different users.

So this entire process started with redeveloping that CAD model. We did this using Inventor. So Inventor does have a lot of helpful tools to help bring in existing data and remake it, including any CAD and other feature recognition tools. However, for a project such as this, it was determined the best option was to really build these models from the ground up.

While the full assemblies, to get really complex, individual components could be remodeled relatively quickly and be remodeled with an eye for parametric and modular design. By utilizing parametric design, having dimensions that relate to one another, creating standard naming conventions for not only parameters but also features, and of course, the parts as a whole.

So that anyone could jump into a model at any time and be able to just from a glance understand what each feature is, what each parameter does, and be able to communicate that across departments and across models. So that everything could be updated very easily and that new designs that sprant from those existing ones can also be created with relative ease. So building up these new systems using Inventor, Pallet has been working to rebuild their entire catalog from the ground up. Luckily, this effort has shown a lot of promise, and they have working models for all of their key resources at this point.

Next is developing really workflows and procedures for those new product development and new models. It's standardizing those naming conventions. It's standardizing origins, creating these different requirements. So that when you do bring two models together or two different users are working on the same model, everything is consistent and everything is clear.

Luckily, beyond this point with Inventor, they were provided with the product design and manufacturing collection licenses by the Autodesk Foundation. This means that, while it gives them access to Inventor Pro, it also give them access to a whole lot beyond that, including simulation from Nastran, access to CAM tools, access to Navisworks, which gives them a lot of room to grow their Inventor ecosystem and workflows to meet their, not only current needs, but future needs.

And lastly, to help support that continual growth and development. They were donated the Pinnacle Series licenses by Eagle Point, which gives them access to on-demand learning videos, either through pathways or searching for specific procedures or tools, giving them access to continue to grow and learn for all of their employees and help build those employees' skills to rise within the company and beyond that.

Next came implementing the PDM solution. So within Autodesk, there actually are a couple of different options for this. And it became a very clear turning point as to which direction to go. And for every company, they have different needs, and for Pallet, going into the initial thought was to implement Upchain. Upchain is a PDM and PLM cloud-based solution.

It has a lot of out-of-the-box workflows and processes for change orders, change notices, even requests for quotes that can be sent to clients with the attached engineering data. All of these systems make it really good for startups, especially growing initially, and allows for easy scalability. However, with Pallet, we ended up going towards Vault Pro instead.

While Upchain does provide a lot of very useful tools for startups, it was clear that we wanted to forego the out-of-the-box operations of Upchain and provide for more creativity with the way that they designed their permissions, their workflows, and all of that using Vault Pro. However, Vault Pro is not, by its own nature, cloud-based, which was a very important thing for a company such as Pallet, that's rapidly growing, has people working remote, and has people on site.

Being able to access that data from anywhere, any time, really became important. So luckily, Vault Pro can be implemented on any server, either locally hosted or cloud-based. So using Azure, they were able to host their Vault Pro server on the cloud, providing that access to all of their employees regardless of location. Not to mention, Vault Pro also has the thin client which can be logged into from the web for all of their non-engineering users who need to access it.

From there, next was establishing basic methods of organization and procedures. On the slide here, you can see a basic workflow that was worked out for a lifecycle state of products. This was one of the key reasons moving to Vault Pro is the ability to create a process such as this. In this workflow, we go from work in progress to for review within a design and then has the added step of a pre-release state.

This configuration allows for stages such as pre-release, where data can be released within engineering before it is released to the public for marketing, for sales, for manufacturing. And so it allows for a little more control as they start to roll out new products or updates to existing products.

Next, within the organization provided within Vault Pro, it also has a project history. They're able to maintain, due to the check-in check-out process, a history marker each time a part is checked in. So any changes that are made can always be undone or they can see previous versions of existing files and prevent loss of data due to products being worked on separately in two different versions of the model or being overwritten over each other.

Using that check-in check-out process, they're able to collaborate a lot more efficiently without fear of losing data. Beyond that, being able to initialize those release dates create that history. It also allows for products to be worked on while a version is still in release.

Using the thin client, they're able to set it up so that users, outside of engineering, can only have permission to access items in a released state. So only the last version that was approved for distribution, approved for manufacturing would be accessible by the users such as the sales team. That way, it would prevent any future occurrences of items being sold before they were fully developed and fully ready for market.

And lastly, even with these gates to prevent non-released items from going out to the larger organization, with this system, it actually does provide for better systems of sharing data. Rather than having to know part number and finding it and searching for it and having to have access to either a CAD application or being able to track down the correct PDF file, all of it can be saved in the same place with version history in there.

So you always know that you are seeing the right data. You're seeing the most recent data and have access to what they need at the time. This benefits, again, sales, marketing, manufacturing and engineering having those consistent locations that they can share and receive feedback from the other departments.

And so what does all of this do? It builds better connections. So like most companies, there are always issues with what we call silos within the different departments, lapses in communication. Because no matter how hard you try, email will never be enough to keep everyone on the same page and up to date. So by leveraging Vault Pro as a middle point between departments, it allows for almost silent communication.

Having release dates to control permissions and having other workflows built in and feedback loops, it provides everyone to work on the project simultaneously and to actively contribute to it. Obviously, this starts with engineering developing these new products and releasing them into Vault and releasing them to the other users.

From there, manufacturing can access the drawings or even view the 3D models. They can access any manuals or instructional videos that were created for the assembly. And they're able to also provide feedback, provide red lines on drawing documentations, to communicate back to engineering if there are designs that do not work correctly or even that could be built more efficiently.

From there, we have interactions with marketing and sales who are able to view released products, are able to get information on new updates, and from there, even can view the 3D model within the thin client and be able to actively engage and see and then provide feedback on those models to engineering.

As with many companies, engineering doesn't have direct communication usually with the end user. And especially for something as important as providing housing for individuals, getting that feedback from those end users and from the communities is so vital. And so through sales and marketing, a lot of that feedback is able to reach engineering.

Next, you have finance who need to be able to access your bill of materials to create expense sheets, to do pricing. And from there, Vault can even be connected directly to their ERP system which is a future endeavor in development for Pallet specifically which it's very important to maintain those common part numbering systems to maintain those bill of materials and frame those pricing sheets.

So that you have all of those systems communicating properly. And then lastly, we go to deployment who are actually going to be on site building these structures. And so they ultimately are the final stage of these projects as they roll out.

And they need to be able to access any assembly drawings for how these are put together, any assembly videos or documentation, and also then provide feedback back to engineering on how they're being put together, any feedback they get from the sites that they go to that have already been established, and be able to reflect on how they're working in different environments or how these different products ultimately are performing and the efficiency of the designs.

And so all of that can be pulled from Vault. They can access all of that data, all in standardized locations, always the most up to date information. And then they're able to use that to create a feedback loop and provide the information back to engineering, back to manufacturing, to continuously grow this product and have all the stakeholders have input on designs as they are developed.

And what this does is this places Pallet in an amazing position for future growth. As history has shown, they've continued to grow more and more rapidly and have huge ambitions for the future. And being able to organize that data, being able to access and communicate across all their departments really puts them in a position where they can actualize some of those opportunities.

This includes opportunities within engineering and manufacturing, such as creating workflows and standardization for batch update or new product introduction releases, having controls such as that pre-release. So that they can release everything as a single package and communicate that with marketing.

Also, being able to move into more simulated prototyping rather than physical prototyping, not only to save on materials, but also to really develop those systems before they move into that physical space. They can do this using Nastran and Fusion 360, which they have access to at this point.

Beyond that, developing and optimizing those manufacturing processes ultimately being able to record, simulate and analyze the way that they put these together, the way that the different components are made, and even potentially, leveraging additional tools in the Autodesk portfolio for keeping track of production lines, of lead times. Being able to develop that system and even create standardization to expand to new locations and new factories to develop these shelters as they continue to grow.

It also gives them the opportunity to move into more of a pre-deployment position within the companies. Currently, a lot of their initiatives are working with local city officials and departments. And so while they provide the shelters and they are out there on deployment, they don't have as much say in the structure of the communities or the outline and the site plan as it goes up.

So this gives them a little more opportunity to start to move more into that field. Using tools such as the connections between Inventor and Revit or even Navisworks, they're able to communicate these models of there, and build structures to create entire site plans and communicate and build that team in order to develop best practices.

From there, they invest in research, gather feedback, to optimize the site planning and promote future growth. And lastly, create that documentation, create those site plans, create documentation for best practices, and really help develop and achieve the success of their communities on a much larger scale.

And then lastly, be able to move into product tracking, create systems, such as implementing barcodes on different units. So that you can track the life cycle and the status of all units be able to see, for any individual unit on any site, what different components it has, what doorknob it has, what AC unit it has, and be able to track the efficiency, get feedback on that, and even roll out batch repairs, maintenance or updates as new products come to market and are released within their ecosystem.

And ultimately, it can lead to a system such as a digital twin being able to have live feedback on systems from different communities around the world and gather that data to better improve their product, to make sure that the conditions are improved, and ultimately, develop new systems to help them in their ultimate goal of ending homelessness.

Thank you for joining me on this case study. I hope it gave you a lot of interesting information, not only about the incredible work that Pallet is doing and the systems that they're putting in place to help them improve that growth, but how these systems and these tools can help any company from a startup all the way up to a huge company in breaking down those silos in communication, improving their organization, their efficiency, and better work for a more sustainable future.

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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。