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Weeding Out Sloppy Work: How to Use Automatic and Semi-Automatic Cleanup Tools to Maintain Drawing Accuracy

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Description

Maintaining drawing accuracy is critical to architecture, engineering, and construction designs. However, due to the complexity of collaboration, encountering inaccuracies is almost inevitable. Research indicates that more than 80% of customers have encountered inaccuracies within drawing elements. If not addressed, these inaccuracies could lead to additional time spent on corrections, or even costly overruns if ignored. AutoCAD software and its associated applications offer batch tools to assist customers in rectifying errors individually or in bulk. This guide will offer a detailed review of the current drawing cleanup tools, outlining their advantages and drawbacks. Additionally, we'll explore possibilities for early-stage error identification to prevent wide proliferation of inaccuracies.

Key Learnings

  • Discover a cleanup toolset to rectify various drawing inaccuracies.
  • Discover specific use cases that require extra attention due to the tool's capacity limitations.
  • N/A.

Speakers

  • Kaili Zhu
    Kaili Zhu is an Experience Designer on the AutoCAD desktop team. Since earning her Master's degree in Design Science from Zhejiang University in 2021, she has contributed to the design of several key AutoCAD features, including the Sheet Set Manager for Web, Autodesk Assistant, and updates for AutoCAD for Mac. Besides, Kaili is also actively researching methods for optimizing drawing cleanup solutions in AutoCAD.
  • Nigma Liu
    Nigma Liu is the principal test developer for AutoCAD since 2008. He has involved in many AutoCAD features' development and rich experience in the industry. He was a civil engineer for a long time before entering Autodesk.
  • Jiacheng Li
    Jiacheng Li is a product manager in the AutoCAD team and primarily works on the web application. She used to be a structural engineer and has received education in civil engineering for her bachelor's degree and master's degree. Recently, she completed her MBA at the University of Virginia Darden School of Business. Since joining Autodesk, she has focused on delivering cloud-based solutions for AutoCAD to continue to empower customers with a faster and seamless way to use AutoCAD.
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      Transcript

      JIACHENG LI: Hello, everyone. Welcome to the class. Weeding Out Sloppy Work. How to Use Automatic and Semi-Automatic Cleanup Tools to Maintain Drawing Accuracy. Thank you for taking the time to join us today.

      Click. Before we dive into the details, we want to share a safe harbor statement. If we mention anything related to roadmaps or future development plans, they are just plans, not promises. The development releases and timing of any feature or functionality may change. You should not rely on the presentation today to make purchasing decisions.

      Please allow me to introduce our speakers for today's class. Hand it over to Kaili.

      KAILI ZHU: Hello, everyone. My name is Kaili Zhu and I'm experienced designer from the AutoCAD team working across both Windows and Mac platforms. With a background in industrial design, I contribute to the design of features like [INAUDIBLE] Set Manager and the Autodesk Assistant and more. I want to thank you for showing interest in our topic and in the next hours Jiacheng and I will share knowledge we learn from joint clean up research. Hope this can help your future work. Thanks, and I will hand it over to Jiacheng again.

      JIACHENG LI: Thank you, Kaili. My name is Jaicheng Li. I'm a product manager on the AutoCAD team. I worked as a structural engineer before and studied civil engineering for my bachelor's and master's degree. Since joining Autodesk, I have been working on various solutions for Autodesk, AutoCAD across desktop, web and mobile. I'm very excited to be here with you all today.

      Here's the agenda for today's class. We will start with some joint clean up background and then share some data with you. Then Kaili will walk you through several case studies to deep dive into the joint cleanup tools in AutoCAD. Then we will conclude with some key takeaways.

      Have you ever found-- I'm wondering, have you ever found yourself spending too much time cleaning up geometry in processions? Or worked with large DWG files clustered with overlapping geometry? And what about manually converting exploded blocks? That's pretty frustrating, right? If any of this sounds familiar, you are not alone. These tedious tasks can take up valuable time that could be spent on more important work.

      So we've conducted a survey. In one survey with 410 participants we found out that these issues are incredibly common. Around 85% of users encountered geometry errors in their drawing. And in another survey of 281 participants over 50% of users reported performing cleanup tasks regularly, whether it's consolidating duplicate objects, updating definitions or fixing geometry imprecisions. These tasks are time consuming, but they are key parts of maintaining accurate and efficient designs.

      So what are the most commonly used commands for doing cleanup? Let me share some interesting data points about how many of you are using the top drawing cleanup commands in AutoCAD within just one month.

      The top use command is the Join command. That was used for 692,000 times. The Purge command came into the second, hit, 664,000 users. And then Overkill command. That one was used for the 48,000 times. These numbers show just how often you are relying on these tools to clean up and optimize your joints, highlighting how essential they are to your workflows.

      I hope these resonates with you on how essential it is to use the right tool to save time and maintain an error free drawing environment. Now, I will hand it over to Kaili. She will walk us through the detailed case studies on optimizing the available tools in AutoCAD products.

      KAILI ZHU: Thanks, Jaicheng. Next, I will spend about 30 minutes to introduce seven popular cleanup tools that we can use to improve work efficiency. I hope this tutorial can provide you with a comprehensive understanding of AutoCAD existing cleanup capability.

      So following the drafting timeline, I will focus on introducing tools marked in black. They are Flatten, Overkill, Drawing, Bconvert, Map Clean, Annotation Monitor, and Purge. The other tools marked in white will be mentioned as supplementary features throughout the introduction. Each tool sharing includes its primary users, system requirements, design goals, and common scenarios. Besides, I will mention key considerations to keep in mind when we use these tools.

      The first tool is Flatten. It is an express tool available in AutoCAD, AutoCAD for Mac and all AutoCAD vertical products. As a tool designed to project 3D objects onto a 2D plan while preserving original properties, flatten can help us clean the terrain data provided by surveyors or generate 2D objects from 3D for further design. Next, I will show a demo of how we use flatten to convert a drawing with 3D solids to a 2D floor plan.

      This is a floor plan opened in AutoCAD 2025. In the isometric view, you can see many walls with height. However, since we need to work on the 2D floor plan, so all entities should lie precisely on the xy plane. To ensure this, start by setting the current view to either the top view or bottom view. This is crucial because flatten will always project entities on the current view. After that, launch Flatten.

      Specify the whole floor plan and choose the option to remove hidden lines. Depending on the complexity of the drawing, you may need to wait for the flatten process to complete. And finally, we will get a clean 2D floor plan.

      In the practice, you can see Flatten treats different kinds of objects in different ways. It can fully return the functionality of text and the hatch, but it doesn't retain original blocks. Instead, it creates a new block and appends a flat suffix to the new block name. Regarding to table dimension and emulator, Flatten cannot identify them, so they are flattening results consist of lines and text.

      Additionally, Flatten doesn't work on ADC objects. That means it cannot remove elevation from elements like simple 3D surfaces. For a better performance I recommend using Flatten on a small selection of objects multiple times. Otherwise, the process may take a long time and could even cause the product to crash.

      To convert 3D objects, there is a workaround we can use too. Click Select to modify objects by type. For example, we can select all 3D solids on a specific layer, then set their elevations to 0 in the Properties palette. This approach is less error prone but can take longer to complete.

      Next I will introduce Overkill. Different from Flatten, which works on 3D objects, Overkill is designed to remove 2D overlapping objects of the same type. It can help to clean up unnecessary layers introduced by insert actions or the previous Flatten result. The Overkill result will benefit following drafting since it reduces the chance of snapping to the wrong object.

      As a feature that has been public for many years, Overkill is available in most AutoCAD products except web and mobile. Now I will show a demo of how we use Overkill to batch remove overlapping lines in the floor plan.

      This is the floor plan of an office building. Although the floor plan appears perfect at first glance, it actually contains overlapping lines that were unintentionally introduced during drafting and should not be there. For example, the balcony section is drawn on an aquamarine layer. When selecting its lines we notice that the number of selected lines does not match our expectations. To identify overlapping linework, firstly we should set the system variable selection cycling to value to selection cycling can help us identify the position of the overlapping lines.

      To remove the underlying lines we first launch Overkill and then specify the objects to clean. Overkill offers a rich set of options, but careful attention should be paid to the tolerance setting as it treats parallel lines as overlapping depending on the value. Although the balcony consists of many parallel lines, we don't plan to remove any, so the tolerance value should be zero.

      Overkill also has an ignore section allowing users to remove overlapping lines across different layers, line types and more. However, since we are focusing on cleaning a single layer, I will uncheck all the ignore properties. Once confirmed, click OK and overkill can complete the cleanup almost in real time. This is-- [AUDIO OUT]

      Although Overkill can handle some edge cases with designated options in the dialog, we still need to be aware of some edge cases that Overkill can handle and some constraints of this tool. Firstly, Overkill can handle some edge cases with the self overlap polyline. It can remove overlapping segments of a polyline by checking the option, optimize segments within polyline.

      It can also consolidate partially overlapping lines similar to a joint action by checking the option, combine collinear objects that partially overlap and the option combine collinear objects when aligned end to end. Secondly, Overkill has limitations in identifying overlapping objects. It cannot handle overlaps across different object types. For example, a polyline beneath a line cannot be removed by Overkill.

      Another limitation has something to do with the tolerance setting. It is designed to identify parallel lines that doesn't account for angle deviations. As a result, Overkill cannot remove two lines that looks overlapping, but actually has a 0.5 degree angle between them.

      The third tool I will introduce is Drawing. Like Overkill, drawing is an established tool available in nearly all AutoCAD products except mobile. It is used to connect to separate objects that meet end to end, even if they are on different layers. Drawing is useful for cleaning up line objects from PDF import or combining a set of lines into a single continuous polyline.

      Next, let's look at a demo on how we further clean up the Overkill result by converting lines in the Overkill floor plan in polylines. Let's continue with the balcony section. After running a thorough Overkill on all the balcony objects, we reduced the line work to 130 lines. To further optimize we can convert all connected lines into polylines. To do this, first we should launch Drawing and then select the entire balcony line work. After confirming the selection, 124 lines are successfully converted to polylines, while six remain excluded for some reason.

      The balcony now consists of 22 objects. If we take a closer look, we can find that Drawing does not resolve the line overshot at the connection point. To fix this, we launch p edit. Choose the multiple option and select both polylines. We then use the Drawing option and specify the tolerance by selecting the start point and the endpoint of the overshot. This can connect the vertical polyline to the horizontal polyline successfully.

      There are several things we need to pay attention to when using Drawing. Firstly, Drawing only works on line objects that connect end to end. Unlike overkill, it doesn't have a tolerance setting. Secondly, the joint result preserves the original object type as much as possible. For example, two collinear lines will merge into a single line, while a line collinear with a polyline will convert into a polyline.

      An event similar to Overkill, which returns only the topmost object, the joint operation adopts the properties of the topmost object for all. Finally, as mentioned in the demo, p edit is a workaround for joining line objects, but it first converts all selection to polylines, so the p edit added result will always be a polyline.

      Now let's introduce a new member of the cleanup family, Bconvert. This tool can convert identical instances throughout the drawing into blocks whenever needed, and offers full support for Windows product. Next, I will show a demo of how Bconvert detects and repairs exploded blocks in the floor plan.

      Let's shift our focus from the balcony section to the workspace layout. This area includes duplicate desks, meeting rooms, plans and other elements drafted as blocks. To find and clean any exploded blocks we can use the block converter tool to locate them by type. For example, to find exploded chairs, we first launch Bconvert and specify an existing chair block as the reference. Bconvert will then search the entire drawing for instances that match the chair reference.

      After the search completes, it highlights all detected instances on the canvas. After we confirm all the selected instances, a block convert dialog will appear guiding users on how to convert the detected objects. You can convert them to an existing block in the current drawing, a block from the library, or create a new block. Since a block chain already exists, we select the option to convert the detected instances to the existing chair block and on the same layer, which is layer 0. As a final step, we need to manually adjust the block position to align with the instance representation.

      Once completed block convert automatically adjusts the diverse orientations of the instances. We can repeat the process with plans, tables, et cetera. Let's take some time to delve a bit deeper into this feature. By design Bconvert scans the entire drawing to match the selection and identifies identical instances, whether they are blocks or non-blocks. We can add or remove instances to the initial step of the process. The Bconvert dialogue includes a suggested block section. It is powered by AI and can recommend existing blocks based on their similarity to the selection.

      AutoCAD 2025 has another feature to deal with exploded blocks and detect. It is under Tech Review, meaning that the feature is still updating. Different from the Bconvert, Detect only searches for non-block instances that can be converted into blocks. So with a single detect action, multiple new block candidates may be identified. It is also powered by an AI model and currently it works best with architectural objects. For both Bconvert and Detect, badly drawn instances may be excluded from the detection due to its dramatic difference from other identical instances.

      OK, after discussing so many cleanup tools on geometry objects, I will introduce something different. The Annotation Monitor. It is designed to search for dimensions that lost connection with its origin. While we can know if a dimension is associated by checking the Properties palette or hovering over a specific dimension, Annotation Monitor allows us to see exactly how many disassociative dimensions exist and their locations at all.

      Annotation Monitor enables us to correct inaccurate dimensions that may arise from version 4 back or the object explode. Next is a demo on how we fix dimensions with Annotation Monitor.

      If dimensions have already been added to the drawing, such as this change dimensions for the exterior walls, it's important to verify whether they are linked to regions known as associative dimensions or only associative dimensions will automatically update when regions are modified. Annotation Monitor is turned on by the toggle on the status bar. When it works, all these associative dimensions are marked with a yellow badge beside them. By clicking the badge, we get access to the tile associated action. This allows us to reassociate the dimension by specifying the origin one by one.

      Here we need to notice some system variables in AutoCAD. Besides the UR access on the status bar, we can also turn on the tool by setting system variable Annotation Monitor to visual variable one. When drafting new dimensions, we should pay attention to the value of system variable dimension associate. If it's either zero or one, new dimensions are by default, not associative.

      Last but not least, users sometimes override the values of associative dimensions for convenience, which the annotation dimension cannot detect. However, there's an express tool called Dimension Associate that can revert this associative dimension values.

      When talking about cleanup tools, we must mention Purge. As you know, Purge can remove unused data and styles to reduce the file size. It is available in almost all AutoCAD products except mobile. When working with frequent insert or copy paste, unnecessary layers, blocks and styles can easily accumulate in your drawing, and the Purge can help to clean up this data.

      The following demo will show how we utilize the Purge dialogue to clean items. When we experience poor performance and notice an excessive number of definitions in the drawing, such as hundreds of block definitions, layers, textiles and dimension styles, removing unused definitions can help. Start by launching the Purge command. It will display all purgable items in the initial dialog. These items are categorized by type with individual definitions listed under each category.

      Before confirming, we should deselect any definitions planned for use in the future but are not currently needed, and make sure to confirm each item to be purged in Option is unchecked, otherwise we will be flooded with hundreds of dialog boxes asking if we want to delete some item. Once everything is set, click Purge. Check the items to remove unnecessary data.

      Sometimes a single Purge won't remove everything as definitions may reference each other. By checking the option, Purge nested items, we can eliminate the repetitive purge steps. To maximize data removal we may continue purging until no purgeable items are left.

      Next, reveal the non-purgeable items. Various reasons can prevent an item from being purged. We can learn about this through the messages in the right panel. For example, the chair block has 33 instances after we use Bconvert so it won't be purgable. We can investigate its instances by clicking the Select object control. If we do one or two purge the chair block, erasing all its instances, it's necessary before running Purge again.

      But that's not what I wanted to do here. Press enter to return to the Purge dialog and we can continue reviewing the other definition instances. When we-- [AUDIO OUT]

      The Purge dialog shown in demo doesn't list all purgeable items. The following are popular ones. DGN linetype. It is covered in the option, Orphaned data. Registered application. It is not accessible through the Purge dialog and should be removed with the command version. Invisible AC object. The invisible AutoCAD Architecture and Civil 3D custom objects can be removed by command PURGEAECDATA.

      External reference. Purge cannot clean external reference, but some third party tools can. We need to clean up the respectively if necessary. With Purge I also want to delve deeper on its Purge nested items option. Assume a drawing has a using the style field label. You can view its usage in the dialog right panel. And this [INAUDIBLE] style uses a block named label.

      If we remove all emulator references, the view label style, it would become purgeable and appear in the purgeable items tab when we run Purge again. But the blog label is still in the non-purgeable items tab because it is still referenced by the emulator style. Tracking the option Purge nested items can remove both view, label, style and label block at one time. So it is possible that one Purge operation cleans items from both purgeable items tab and non-purgeable items tab.

      Now comes the last tool in my introduction. Do you remember the line overshoot issue that Join cannot handle in my previous demo? This is where Mapclean comes into play. Basically, Mapclean is only available in Civil 3D and maps 3D. It is designed to simplify line objects in map data by resolving minor linework issues that are not often too subtle to detect visually. In the following demo, we will see how Mapclean can be used to correct linework errors in a sample floor plan.

      In the Join demo, we use the p edit to create a line overshoot issue. However, in Civil 3D and map 3D there is a specialized tool called Mapclean designed to handle similar intersection errors. I've marked the intersection arrows with red circles throughout the drawing. To fix these arrows we start by launching Mapclean. A dialog box then appears prompting us to specify the objects to fix.

      Let's select the lines that contribute to this great region and press Enter. With Mapclean, we can also limit the fix to specific layers, but in this case, the All option will suffice. Next, we move on to specify the types of arrows we want Mapclean to search for by transforming them from the left panel to the right. Since our focus is on removing line overshoot, we will first select break crossing objects and then erase dangling objects.

      The tolerance of erase dangling objects defines the maximum object length to be considered for removal. If we don't know the exact length, we can specify it by selecting a start and endpoint on the canvas. I will add some buffer to the tolerance instead of measuring the exact length of the overshoot segments in case the removal fails.

      Back in the Mapclean dialog there are two modes, Automatic and Interactive. While the automatic modes quickly resolve arrows, the interactive mode allows us to reveal each detected arrows carefully. So I will choose the Interactive mode. We then click the Finish button. Then a new dialog will appear listing all detected arrows by type. By activating each instance, we can either fix, remove or mark it before moving on to the next one.

      Since I don't want to break the great lines into smaller segments, I will only fix intersections at the edges and remove the others. The canvas will guide us through each arrow.

      Once we've reviewed all the instances, we can click Close to accept the changes. Now, the grid no longer has any line overshoot. Mapclean can be a powerful tool when we know how to apply the correct cleanup actions to a selection. Therefore, understanding what each cleanup action does is essential.

      There are 11 types of geometry errors available in the Mapclean action port and I will walk you through each one. Delete Duplicate. It erase duplicate linear objects, points, blocks, text and m text while keeping the topmost one. Erase Shot Objects. It can erase open line objects whose length is within the tolerance. And Break Crossing Objects. Its break line objects at their intersections, regardless of their type.

      Extend Undershoot can snap open line objects to another line object within the tolerance radius. By default, it breaks the snap to line by default. Append Intersection. It extends to open line objects that would intersect if extended along their natural path to their projected intersection point. And the Snap Clustered Nodes. It snaps multiple nodes that are near the same location within a specified tolerance radius distance to a single location. As you can see, the last three actions can handle some line undershoot issues.

      Continue from the previous slide. Dissolve Pseudo Nodes. Convert open line objects that connect end to end, linking two objects into a single polyline. Erase Dangling Object can erase open line objects with at least one endpoint that is not shared by another line object. It works best to following the action break crossing objects. Simplify Object. It can remove all interior nodes that fall within the specified tolerance [INAUDIBLE].

      Zero-Length Object [INAUDIBLE] erase open line objects whose start point and endpoint are at the same location or whose endpoint is missing. By the way, Purge also has this ability. And the last one Weed Polylines. It can remove or add vertices based on distance reading factor or angle weeding factor. It makes sure vertices spread evenly in the polyline.

      With so many cleanup actions, Mapclean respects the order and tolerance defined by the user. For example, in the demo, we specified the sequence as first breaking crossing objects and then erasing dangling objects. On a small scale of selection, sometimes scanning the entire drawing can be challenging as it will be complex to determine an effective sequence of cleanup actions.

      Another interesting fact is that the Remove option available in the Interactive mode. It only works in the current session. So next time you run Mapclean and following the same cleanup settings, the remove the arrow will still be detected. OK, this slide wraps up my introduction to the cleanup tools. I hope the presentation didn't make you feel boring, and you've learned something new to help with your work. Next I will hand it back to Jaicheng. She will wrap up our class contents.

      JIACHENG LI: Great. Thank you so much, Kaili. So as Kaili mentioned, you can see on the left hand side, we have introduced all the tools you will need for your join cleanup. So here are some takeaways to keep in mind while you're using the tools.

      First, know how and know which tools to use and when. It's essential to ensure you're selecting the most effective tools for the tasks at hand to streamline your workflow. Second, understand the limitations of each tool. Being aware of what a tool can and cannot do will help you avoid unexpected results and keep your work on track.

      Lastly, correct arrows promptly. Addressing mistakes early on prevents bigger, more costly problems down the road. With these strategies, I hope you can optimize your efficiency and improve the quality of your work.

      So that wraps us up our content. Next, I want to share with you a great opportunity to join AutoCAD inside the factory event, which is new this year. So in this virtual event, you get a chance to explore new features. So be the first to experience the new features before it's released in its beta version.

      And then you get a chance to also meet directly meet with the product team, including product managers, designers, and developers, so that you can get all your answer, all your questions answered. Lastly, your feedback is really important to us. We want to make sure we hear your voices so that you can share your ideas and help us shape the future of AutoCAD. So if you're interested in this opportunity, please scan the QR code and sign up. So we will notify you shortly. Thank you so much.

      KAILI ZHU: Thank you.

      ______
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      Geo Targetly
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      SpeedCurve
      We use SpeedCurve to monitor and measure the performance of your website experience by measuring web page load times as well as the responsiveness of subsequent elements such as images, scripts, and text.SpeedCurve Privacy Policy
      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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      Improve your experience – allows us to show you what is relevant to you

      Google Optimize
      We use Google Optimize to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Google Optimize Privacy Policy
      ClickTale
      We use ClickTale to better understand where you may encounter difficulties with our sites. We use session recording to help us see how you interact with our sites, including any elements on our pages. Your Personally Identifiable Information is masked and is not collected. ClickTale Privacy Policy
      OneSignal
      We use OneSignal to deploy digital advertising on sites supported by OneSignal. Ads are based on both OneSignal 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 OneSignal has collected from you. We use the data that we provide to OneSignal to better customize your digital advertising experience and present you with more relevant ads. OneSignal Privacy Policy
      Optimizely
      We use Optimizely to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Optimizely Privacy Policy
      Amplitude
      We use Amplitude to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Amplitude Privacy Policy
      Snowplow
      We use Snowplow to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Snowplow Privacy Policy
      UserVoice
      We use UserVoice to collect data about your behaviour on our sites. This may include pages you’ve visited. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our platform to provide the most relevant content. This allows us to enhance your overall user experience. UserVoice Privacy Policy
      Clearbit
      Clearbit allows real-time data enrichment to provide a personalized and relevant experience to our customers. 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.Clearbit Privacy Policy
      YouTube
      YouTube is a video sharing platform which allows users to view and share embedded videos on our websites. YouTube provides viewership metrics on video performance. YouTube Privacy Policy

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      Customize your advertising – permits us to offer targeted advertising to you

      Adobe Analytics
      We use Adobe Analytics to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Adobe Analytics Privacy Policy
      Google Analytics (Web Analytics)
      We use Google Analytics (Web Analytics) to collect data about your behavior on our sites. This 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. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Google Analytics (Web Analytics) Privacy Policy
      AdWords
      We use AdWords to deploy digital advertising on sites supported by AdWords. Ads are based on both AdWords 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 AdWords has collected from you. We use the data that we provide to AdWords to better customize your digital advertising experience and present you with more relevant ads. AdWords Privacy Policy
      Marketo
      We use Marketo to send you more timely and relevant email content. To do this, we collect data about your online behavior and your interaction with the emails we send. Data collected may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, email open rates, links clicked, and others. We may combine this data with data collected from other sources to offer you improved sales or customer service experiences, as well as more relevant content based on advanced analytics processing. Marketo Privacy Policy
      Doubleclick
      We use Doubleclick to deploy digital advertising on sites supported by Doubleclick. Ads are based on both Doubleclick 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 Doubleclick has collected from you. We use the data that we provide to Doubleclick to better customize your digital advertising experience and present you with more relevant ads. Doubleclick Privacy Policy
      HubSpot
      We use HubSpot to send you more timely and relevant email content. To do this, we collect data about your online behavior and your interaction with the emails we send. Data collected may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, email open rates, links clicked, and others. HubSpot Privacy Policy
      Twitter
      We use Twitter to deploy digital advertising on sites supported by Twitter. Ads are based on both Twitter 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 Twitter has collected from you. We use the data that we provide to Twitter to better customize your digital advertising experience and present you with more relevant ads. Twitter Privacy Policy
      Facebook
      We use Facebook to deploy digital advertising on sites supported by Facebook. Ads are based on both Facebook 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 Facebook has collected from you. We use the data that we provide to Facebook to better customize your digital advertising experience and present you with more relevant ads. Facebook Privacy Policy
      LinkedIn
      We use LinkedIn to deploy digital advertising on sites supported by LinkedIn. Ads are based on both LinkedIn 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 LinkedIn has collected from you. We use the data that we provide to LinkedIn to better customize your digital advertising experience and present you with more relevant ads. LinkedIn Privacy Policy
      Yahoo! Japan
      We use Yahoo! Japan to deploy digital advertising on sites supported by Yahoo! Japan. Ads are based on both Yahoo! Japan 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 Yahoo! Japan has collected from you. We use the data that we provide to Yahoo! Japan to better customize your digital advertising experience and present you with more relevant ads. Yahoo! Japan Privacy Policy
      Naver
      We use Naver to deploy digital advertising on sites supported by Naver. Ads are based on both Naver 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 Naver has collected from you. We use the data that we provide to Naver to better customize your digital advertising experience and present you with more relevant ads. Naver Privacy Policy
      Quantcast
      We use Quantcast to deploy digital advertising on sites supported by Quantcast. Ads are based on both Quantcast 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 Quantcast has collected from you. We use the data that we provide to Quantcast to better customize your digital advertising experience and present you with more relevant ads. Quantcast Privacy Policy
      Call Tracking
      We use Call Tracking to provide customized phone numbers for our campaigns. This gives you faster access to our agents and helps us more accurately evaluate our performance. We may collect data about your behavior on our sites based on the phone number provided. Call Tracking Privacy Policy
      Wunderkind
      We use Wunderkind to deploy digital advertising on sites supported by Wunderkind. Ads are based on both Wunderkind 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 Wunderkind has collected from you. We use the data that we provide to Wunderkind to better customize your digital advertising experience and present you with more relevant ads. Wunderkind Privacy Policy
      ADC Media
      We use ADC Media to deploy digital advertising on sites supported by ADC Media. Ads are based on both ADC Media 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 ADC Media has collected from you. We use the data that we provide to ADC Media to better customize your digital advertising experience and present you with more relevant ads. ADC Media Privacy Policy
      AgrantSEM
      We use AgrantSEM to deploy digital advertising on sites supported by AgrantSEM. Ads are based on both AgrantSEM 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 AgrantSEM has collected from you. We use the data that we provide to AgrantSEM to better customize your digital advertising experience and present you with more relevant ads. AgrantSEM Privacy Policy
      Bidtellect
      We use Bidtellect to deploy digital advertising on sites supported by Bidtellect. Ads are based on both Bidtellect 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 Bidtellect has collected from you. We use the data that we provide to Bidtellect to better customize your digital advertising experience and present you with more relevant ads. Bidtellect Privacy Policy
      Bing
      We use Bing to deploy digital advertising on sites supported by Bing. Ads are based on both Bing 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 Bing has collected from you. We use the data that we provide to Bing to better customize your digital advertising experience and present you with more relevant ads. Bing Privacy Policy
      G2Crowd
      We use G2Crowd to deploy digital advertising on sites supported by G2Crowd. Ads are based on both G2Crowd 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 G2Crowd has collected from you. We use the data that we provide to G2Crowd to better customize your digital advertising experience and present you with more relevant ads. G2Crowd Privacy Policy
      NMPI Display
      We use NMPI Display to deploy digital advertising on sites supported by NMPI Display. Ads are based on both NMPI Display 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 NMPI Display has collected from you. We use the data that we provide to NMPI Display to better customize your digital advertising experience and present you with more relevant ads. NMPI Display Privacy Policy
      VK
      We use VK to deploy digital advertising on sites supported by VK. Ads are based on both VK 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 VK has collected from you. We use the data that we provide to VK to better customize your digital advertising experience and present you with more relevant ads. VK Privacy Policy
      Adobe Target
      We use Adobe Target to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Adobe Target Privacy Policy
      Google Analytics (Advertising)
      We use Google Analytics (Advertising) to deploy digital advertising on sites supported by Google Analytics (Advertising). Ads are based on both Google Analytics (Advertising) 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 Google Analytics (Advertising) has collected from you. We use the data that we provide to Google Analytics (Advertising) to better customize your digital advertising experience and present you with more relevant ads. Google Analytics (Advertising) Privacy Policy
      Trendkite
      We use Trendkite to deploy digital advertising on sites supported by Trendkite. Ads are based on both Trendkite 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 Trendkite has collected from you. We use the data that we provide to Trendkite to better customize your digital advertising experience and present you with more relevant ads. Trendkite Privacy Policy
      Hotjar
      We use Hotjar to deploy digital advertising on sites supported by Hotjar. Ads are based on both Hotjar 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 Hotjar has collected from you. We use the data that we provide to Hotjar to better customize your digital advertising experience and present you with more relevant ads. Hotjar Privacy Policy
      6 Sense
      We use 6 Sense to deploy digital advertising on sites supported by 6 Sense. Ads are based on both 6 Sense 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 6 Sense has collected from you. We use the data that we provide to 6 Sense to better customize your digital advertising experience and present you with more relevant ads. 6 Sense Privacy Policy
      Terminus
      We use Terminus to deploy digital advertising on sites supported by Terminus. Ads are based on both Terminus 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 Terminus has collected from you. We use the data that we provide to Terminus to better customize your digital advertising experience and present you with more relevant ads. Terminus Privacy Policy
      StackAdapt
      We use StackAdapt to deploy digital advertising on sites supported by StackAdapt. Ads are based on both StackAdapt 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 StackAdapt has collected from you. We use the data that we provide to StackAdapt to better customize your digital advertising experience and present you with more relevant ads. StackAdapt Privacy Policy
      The Trade Desk
      We use The Trade Desk to deploy digital advertising on sites supported by The Trade Desk. Ads are based on both The Trade Desk 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 The Trade Desk has collected from you. We use the data that we provide to The Trade Desk to better customize your digital advertising experience and present you with more relevant ads. The Trade Desk Privacy Policy
      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

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      We can access your data only if you select "yes" for the categories on the previous screen. This lets us tailor our marketing so that it's more relevant for you. You can change your settings at any time by visiting our privacy statement

      Your experience. Your choice.

      We care about your privacy. The data we collect helps us understand how you use our products, what information you might be interested in, and what we can improve to make your engagement with Autodesk more rewarding.

      May we collect and use your data to tailor your experience?

      Explore the benefits of a customized experience by managing your privacy settings for this site or visit our Privacy Statement to learn more about your options.