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How Outcome-Based Design Can Lead to More-Sustainable Projects

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Description

Sustainability is emerging as the main value driver of the future of building. Reducing a building's carbon footprint decreases its running costs, improves the workforce's sense of purpose, and raises property value. Buildings become also socially, economically, and environmentally responsible. In turn, they become more profitable, and are healthier places to live and work. In this class, we’ll focus on an outcome-based design workflow from schematic design in Spacemaker to design development in Revit and Insight software. The discussion is centered on concrete milestones and frameworks connected to sustainable KPIs in early phase development. We’ll explore a small mixed-use plot in central London with views of the River Thames and HMS Belfast.

Key Learnings

  • Learn how to set up objectives and key results for sustainability in early phase development.
  • Discover ways to optimize massing for density and living qualities with generative design in Spacemaker.
  • Learn about data flow between Spacemaker and Revit with reduced data loss.
  • Learn about optimizing building performance with real-time feedback in Insight.

Speakers

  • Avatar for Daniel Gameiro
    Daniel Gameiro
    Daniel Gameiro is a tech-savvy architect with 9 years of experience in Real Estate Development and Sales in renowned companies like Reiulf Ramstad Arkitekter, Spacemaker, and Autodesk. In his formative years, he founded a non-profit which developed humanitarian projects in Europe, Africa, and the Americas. His contributions at Spacemaker include the best practice method entitled The Spacemaker Way; instituting outsourcing processes to scale the customer success and technical sales teams; and assisting with the acquisition process driven by Autodesk.
  • Avatar for Justin Taylor
    Justin Taylor
    Justin has more than 30 years’ experience working with Autodesk solutions across the globe. Having previously focused on helping AEC firms digitize their workflows, he is now super excited to join the Autodesk Sustainability Practice and support customers as they strive to meet their Net Zero goals. “Our customers design and build the world, so we are in the perfect position to influence and enable more sustainable design practices” He brings along expertise in areas such as reality capture for refurb and retrofit, low carbon design and material circularity, health & wellbeing design and analysis in buildings. Outside of work Justin enjoys spending time with his family and his hyper-active Cocker Spaniel, Diego, in the great outdoors, exploring the countryside and the UK’s historical sites of interest. He is also a bookworm, amateur bonsai grower and trying to become a better guitar player. Challenges don’t get bigger than this and we all need to work together to build a #BETTERWORLD
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Transcript

DANIEL GAMEIRO: Hello, everyone. Welcome to the lecture on how outcome-based design can lead to more sustainable projects. This is the Safe Harbor Statement. Make sure to pause for a few seconds to read it through.

My name is Daniel, and I am an architect and longtime Spacemaker technical sales specialist. I have dedicated my career to accelerate the advent of sustainability in architecture and construction, starting when it's cheaper at the very early design phase. And I have the honor of getting Justin's support for this lecture. Justin Taylor is a principal sustainability consultant and has helped Autodesk clients implement sustainable workflows to ensure low carbon design and material circularity.

And in today's lecture, we'll be designing a sustainable project. However, we will do it in an outcome-based way. So all the insights we will collect along the way will be the premise and the driver for all iterations. And we will use various Autodesk software as decision support tools.

And we want to make this session as useful and as real as possible. So that's why we come up with a fictitious client. This task is very typical on early stage development. The client wants to conduct a feasibility study for a small plot in London City Center.

There is, of course, a target-- 26,500 square meters gross external area. And they also want to maximize value and minimize risk, while ensuring that the project is as sustainable as possible. The desired outputs are all the key figures necessary to build up a strong business case, as well as KPIs on energy and daylight. And finally, we need to deliver a 3D model for the client to discuss the project with other stakeholders like investors and planning authorities.

And the workflow grows from scratch to a pretty high-performing detailed model. And we will start by solving for mass distribution and then deep dive and populate the volumes with inner units. And once we have a good insight about the interior, we will stress test the model with different window configurations to understand how we can meet the client's daylight expectations. And finally, we want to understand what kind of opportunities exist to optimize the architecture element buildups for low energy consumption and high production.

So this workflow requires three solutions-- Spacemaker, Revit, and Insight. And I want to emphasize that this is not a linear workflow. You need to go back and forth to utilize each solution on what they allow you to do best.

And this is a total overview of all the steps. But we will take it slowly, step by step, for each milestone. We will be leveraging the Spacemaker way to solve the mass distribution. The process is three-fold and starts with going wide.

We want to open up the solution room with generative design in Spacemaker. And the most important thing in this step is to keep an open mind. Believe me, you want to focus on strategies rather than shapes because then we will go deep once we agree on which concept we want to pursue.

And, of course, we will map all the qualities and challenges. And we will iterate that concept live, based on insight generated by Spacemaker rapid and golden standard analysis. And finally, we will see how we can go out, meaning sending information to another software to continue our workflow. I will now show you the demo.

So let's kick it off. We go wide. Spacemaker is the launchpad for all digital workflows. And we will be working with this plot in London, which has about 6,400 square meters. Then we want to move into explore modes to populate the plot with a lot of masses.

Make sure that you are running a site study. Then configure some basic parameters, such as the width of the buildings, internal streets, what kind of urban layouts are adequate for these projects. And we will set the height to eight stories for all solutions so that we can compare apples to apples.

Once you click Generate, you will see a lot of solutions popping up. And over here we've got 27 solutions because the plot is quite small. But remember, it's all about strategy, not shapes. So let's just make sure we add all the relevant concepts to our proposal list.

And then we want to edit these in Design mode. Remember, you want to compare apples to apples. So we will change all solutions to achieve 26,500 square meters gross external area.

And Spacemaker will do the heavy lifting for us. We will get an immediate overview of how many square meters we have on the top right corner. And you want to repeat this process for all the solutions and then compare them side by side.

So here, we have four solutions. Note that all have identical key figures so that we can compare and focus on the living conditions. Remember, apples to apples. Let's start with some.

Spend always two seconds looking at the gradient scale in Spacemaker to understand what the color maps intend to show you. Dark blue in this case means zero to one hour of direct sun. Bright yellow stands for between nine and 10 hours. And we can immediately see that concept A is the one with the most sun exposure in the outdoor area.

What about daylight? Well, Spacemaker runs a vertical sky component analysis, which measures the exposure of each point to the facade, of the facade to the sky. We have three outputs.

Light green means no problems at all. Light blue means that we will need big windows to achieve good daylight. And dark blue points out to difficulties to provide adequate daylight.

And you can see that concept D performs very poorly because of the tower buildings that block the daylight. And note that all of these analogies, Spacemaker runs those for our proposal, but also for selected neighbor buildings so that you can evaluate the impact of your design in the surroundings. We'll focus on this building over here, and all solutions seem to impact it very badly. So we want to consider that when we go deeper into the concept iteration.

Now let's have a look at noise. All solutions perform similarly, except concept D, which allows for noise to come in and be reflected between the towers. Looking at the view towards the River Thames and the Golden Hind, we can see that concept B is by far the best. It has 57% of the facades that can see at least one area of interest.

Now let's have a look at the wind comfort scale. Light green stands for good conditions for sitting. So that's where you want to place restaurants and any public program. Yellow indicates that it's only comfortable for strolling.

So just by looking at this comparison, we can learn that the solutions with enclosed or semi-enclosed courtyards have a much better level of comfort. And my hunch is that we will see the same when it comes to microclimate because wind is a huge part of it.

So when we consider the expected temperature in the 21st of March, we can see, again, that concept A performs the best. It's expected a ground temperature between 5 and 8 degrees Celsius. And on the other end, we have concept B, where the temperature varies from -1 to 2 degrees. That's a huge difference.

And lastly, we want to understand what the potential for energy production with solar panels is. Once again, concept A stands out. It has the potential to generate 504,000 kilowatt hours per year, which is 100 kilowatts thousand more than the second best solution.

So we can conclude that concept A is by far the best when it comes to all of these tradeoffs. Although it performed poorly in a view towards a point of interest, it did really well in the other living conditions. And that's the kind of discussion you want to have with Spacemaker, so that you can discuss with your colleagues, external stakeholders, and base the design development of the project on sustainable outcomes.

Now let's go deep in this concept A and understand how we can improve daylight, especially the impact on the neighbor building. So we probably want to make sure there is as much space as possible between these two. We also want to make sure the street is wide enough for better daylight access. It starts looking quite nice.

Now let's leverage our rapid analyses, starting with sun. We can improve these dark, dark areas extremely fast if we lower it to [INAUDIBLE] And you can see that it gets sunnier immediately.

I will now focus a bit on the shape of the building, and I will make sure to improve its performance. So I would like it to be a step up to allow for more sun in the courtyard and also to improve the number of units with a view to the river. Note that our line building is fully parametric. It takes just a few clicks to change the mass without losing the smartness. That's super convenient.

Let's now split the model into different programs. And Spacemaker will again provide us with live control of the key figure's outcomes while designing. So first we want to change the whole ground floor to 5 meters high. And we will then change the program to commercial.

I see the area is a bit low, so let's pump this up. Awesome. Let's now tag the volumes by the water as offices, as well as the last two stories in this volume. We also want to rearrange our sub buildings so that we get a proper program distribution. Now let's look at noise. Well, it looks like this last iteration did not change the good conditions we have seen before. Same goes for wind. So both look really good.

And now there is something I'm quite excited to show you. We have just released in beta the new operational energy analysis, which predicts the energy use for HVAC, plug loads, and lightning in kilowatt hours per square meter per year. So you can define a window to our ratio.

Let's leave it at 60%, as well as roof and windows, thermal transmission based on a library of buildups. And in just a few seconds, you can see that our building will be spending between 74 and 112 kilowatt hours per square meter per year. However, I'm sure Justin will show you how we can outperform these later on.

And now it's time to move to the last step of these workflow, go out. So Spacemaker allows you to export the solution in different formats. Here, you can see IFC and OBJ. Or you can stay in an Autodesk workflow by leveraging our recent, powerful, and on to Revit.

So right now we have a mass that performs very well. And we want to populate that volume with inner units. Firstly, we will load the data in Revit and see how we can draw plan layout in such a way that we can then bring the information back to Spacemaker to have a proper discussion with all the stakeholders on which alternative will perform best, and note, I mention, more than one plan layout. I said alternatives.

And this is just something about the mindset, right? We want to always go wide, to open up the solution room so that we make sure we don't leave any money on the table. Let's have a look on how to do it.

So firstly, you want to create a new project in Revit. By the way, make sure to use the system analysis template. It will set you up for success with all insight analysis. And we will also make it available in the lecture handouts.

Then go to the Spacemaker tab, click Loads. Make sure to tick the Create generic models for units option. And there you go. After some minutes, Revit creates a 3D model with all the information you have in Spacemaker. All geometries are Revit native. And you even get a grid system automatically.

Now you want to add some project parameters to be able to inform Spacemaker of the function of the units that you are modeling. And I won't explain every detail of it, but I will make sure to include a step-by-step guide on the lecture handout. And now it's time to start drawing our plan.

We will use Components, Model in Place, and choose Generic Models as the family. Now draw an [INAUDIBLE] for each room. And then you will see that the parameters that we just added will show on the Properties menu under Text. The function for this unit will be commercial, and it is a living unit, not a core.

And once you have modeled all the rooms, you will end up with a 3D model just like this one. It is important that you create more than one alternative to make sure that you don't miss the opportunity to maximize value. And we will use Spacemaker to compare those.

Let's now export this model as an IFC. And now in Spacemaker, use the Tab Assets to import it. And make sure that you simplify the model. Because the workflow started in Spacemaker, the model is already correctly referenced in the world.

Then you click Finish, and you want to do this for all the alternatives that you have developed. I created two, so I will now compare them side by side. At this point, again, you want to invite everyone in your team and other stakeholders to discuss which alternative creates the most value according to your criteria.

Note that both models have the same envelope, but a little bit different plan layouts. Alternative 1 is a short corridor per core, while alternative 2 is a long corridor which connects to all cores. So in this case, we will be prioritizing view to the water because we saw earlier that this concept was not performing very well in this living quality.

Alternative 1 is 85 apartments that can see at least one area of interest, versus alternative 2, which has only 67. So the Delta is 18 units. And if you consider that an apartment is worth 20,000 pounds more because it has a view towards the point of interest, we are talking about an impact of 360,000 pounds on our clients' bottom line, which is quite significant. I'm sure our fictitious clients would be smiling at this point. And we will once again send our model into Revit to continue our Autodesk workflow.

So where do we stand in our workflow? We have a model with inner units, and we want now to understand what kind of window configuration we need in order to achieve our clients' expectations when it comes to daylight. And there are different standards we can use. Of course, you will need to adapt for your own region.

This slide shows a sample of just some of the sustainability certification standards around the world. And basically, the standards indicate that a building was designed and constructed to a certain level of environmental responsibility. And our project, as you have seen, is located in London, in the UK. So we would be leveraging the BREEAM method.

And visual comfort is assessed under the Hea 01, which is for health and well being. And we can see that the daylight requirements differ, based on a building type and the room type. And this is where we see the 2% average daylight factor required for a residential dwelling in the latitude of London. We can also see that this percentage is required over a minimum of 80% of the floor area.

So back to our workflow, this is the early stage, right? So we don't have the capacity, the bandwidth to run a full daylight analysis for the whole project and try multiple configurations. So what we want to do is to limit the scope. We want to choose some representative apartments in Spacemaker, as you can see over here on the left-hand side, according to the vertical sky component analysis.

Then we want to module those apartments in Revit in order to get a realistic depth of the apartments, but also the rooms. We then want to run multiple daylight analyses with different window configurations. And we want to synthesize those insights into a table, which we then will leverage to detail the facades accordingly.

These are a lot of words. Let's see how this works. Some technicalities-- so before any analysis in insight is carried out, it's really important to set up the model correctly. And this includes applying the standards for ceilings, walls, and floor reflectance, as well as the visual transmission for glass. As part of our supplementary notes for this class, we will be providing a detailed document on this.

We will also need to, of course, locate our model in the world because this provides insight with the relevant weather data, as well as setting whether the sun will be to the north or to the south. Finally, we need to orientate the building correctly according to the true north. Now Justin will show us how does this work

JUSTIN TAYLOR: Here we can see Daniel's Revit model. We're going to run a lighting analysis. So moving to level 2, we can see the room in question, room 372. We're just going to check that the various building elements such as the walls, ceilings, and floors have got the right material with the reflectance values assigned to their RGB value.

So here we can see that this affects the light, the amount of light that's going to be reflected back into the room. And these are standards, the 80%, 50%, 20%. So this is looking good. The ceiling is set at 80% and the floor and also the glass. We need to set the visual transmittance via the RGB value.

So 190 is about 70% visual transmittance, all looking good. We're going to go now to the Analysis tab, and we're going to click Lighting. And we're going to run a new analysis.

OK, so now we get to choose our type. So we can go from illuminance to daylight to lead, solar axis. We're going to choose daylight factor, and we're going to pick the specific level 2.

You can't do the whole model. This will cost more [? credit, ?] so we're just picking level 2 at the moment. We don't need to choose the date all the time, but we are setting the illuminance settings. We want to go between 1.5% and 2%, and that's what's required through BREEAM.

I'm going to start the analysis. And it will upload the model to the cloud processor and then notify you when the data is ready. So moving through, we're going to accept and update the model, save the project. And we're now going to pull in the analysis back into the model so it loads in the lighting data.

And you'll see there's new floorplans created for the lighting analysis. We can see now we've got the legend, and it's showing us the percentage via a heat map of the daylight penetrating that room, average daylight factor. We can adjust those values if we want to create a greater segregation between the colors. It also generates a couple of schedules. This is the room schedule, so we can see room 372 is achieving 2.1 average daylight factor.

As we switch now to a perspective view of the room, we can run typical simulations such as shadow studies. And here we're going to run a single day analysis. I'm going to run it over the winter solstice, sunrise to sunset. Just set the year. There we go. We set the year as 50-minute time intervals, and we can play a preview of that.

We can also export it as an animation. And this is useful to see, as I said, shadow simulations and where direct sunlight is falling. But it's not really telling us about the illuminates in that room in a 3D environment.

What we can do, though, is go to the Render in the Cloud option, and there is a choice that we can set to render as an illuminance, rather than as a still panoramic. Choosing illluminance, you can set the image size. We want this one in Lux, and you type in your minimum-maximum range.

Choose the sky models-- so we're going to go for a uniform sky-- and the location and time. So you can either set it or use the settings that are coming from the view in Revit. And simply click Start Render.

That will continue in the background, and again, you'll be notified once that rendering has finished. And your image will be available in the Render Gallery, so clicking on that link will take me through to the gallery. And we can see now a perspective rendering of that room at the given time and the various lux levels throughout the room.

DANIEL GAMEIRO: Awesome. So what did we just see? Well, in this slide, the daylight analysis shows that the room 372 is meeting the required 2% average daylight factor over 80% of the floor area. Great, so we are good to go. We are passed on this one.

And what we want to do is basically to try to achieve that 2% for all the rooms that we have for all the apartments. And in this table, we can see the correlation between rooms, vertical sky component, and window configurations. In the last row, you can see the average daylight factor for that room, as well.

And note that this table is specific for this typology and geography. You could, however, develop your own tables, which would enrich and accelerate your early phase designs for the typologies and programs and geos where you operate.

So once you have that table, what you can do is start applying the window configurations on the model overall. And this is a screenshot of the work we did in Revit. And what we see here is our original Spacemaker model with the daylight vertical sky component analysis. And we will now focus on a specific area where we would see a wide range of performance.

And what we will see, the result is obviously that when we have the low vertical sky component, we will need a lot of windows in order to achieve the daylight threshold that we are trying to do. So we will see a high window to wall ratio. And when we have a high vertical sky component performance, of course, we will need less glazing.

And now we come onto our last step of the full workflow, and that's about energy. What we want to do is, of course, to reduce consumption and maximize production. So what do we want to do first is to understand the baseline, then explore optimization opportunities in insights to reduce operational energy.

And finally, we want to conclude on the energy production potential and PV placement. And as energy efficiency standards also vary quite a lot all around the world, in Europe, it's mainly mandatory. And that's a trend that is accelerating globally.

So what we do here is, by running an analysis in insight with the model, with the very detailed model that we just had, we had a baseline of 222 kilowatt hours per square meter per year. However, after adjusting a number of influencing factors, this was brought down to a potential 105 kilowatt hours per square meter per year.

That's quite insane, right? It's a 50% cut. So how was this done? Let's have a look.

JUSTIN TAYLOR: Here we can see the model that Daniel has put together. And as I switch to level 2 and into level 1, we can see that the building has been properly orientated to true north, which is great.

And if I go into Manage and Location, I can see he's set the coordinates, and this should pull up London. It does indeed. If you want to make adjustments, you can zoom in and drag the little icon to the exact location. And it will pick up the nearest weather stations and apply that data when it's carrying out the analysis.

With that done, we can now switch to analyze and then over to the configuration settings. It's possible to analyze everything from a conceptual design through to fully detailed model, which is the case we have here.

Going into the advanced settings, we don't need to set the glazing ratio or the percentage and the skylights, because we're working with a fully modeled building. We are going to switch, though, to a single valve duct. Making sure that the infiltration-- we're going to set that to Tight, and the building type, we're going to select Multifamily.

HVAC system-- you can see there's various options in there, but we're going to leave that on the default. Down here we can see conceptual types. Now, these are what would be used if we were using a massing study or we hadn't specified any compound elements such as walls, doors, and windows inside of Revit and applied thermal properties to them.

The schematic allows us to override that and create a list of our own configurations if we want. But as the model has been fully detailed by Daniel, we're going to select detailed elements. And it will use the thermal properties of the walls, floors roofs et cetera.

So now we're going to go and create the energy model. This takes a few seconds. And there we go. And it's possible to go into the View settings, Analytical, and switch on the Analytical Services. And you can see easily whether there are any errors in the model, whether there's any gaps.

So it's always advisable to check the model and make sure that it looks right, that the surfaces are tight, there's no obvious gaps, before we generate the results. So we're going to use the existing analytical model. And we're going to upload that now to insight and let that process.

Once the model is finished processing, you'll get an email, and it will take you through to the insight portal, and you can click on your insight. Here we have the model. Select, and it will take us through to the analysis results. And we can see the model in detail, we can rotate it around, we can see the analytical surfaces.

And first off, I'm going to check the PV analysis. This will show me the surfaces where photovoltaics can be and the kind of energy that the individual areas on the roof can produce, coverage area, et cetera. Moving back out, I'm just going to check. We can see the overall energy usage intensity of the building as it stands is 222 kilowatt hours per meter squared over the year.

Now let's see what we can do to make a difference. Opening up the building orientation, we can see that changes could be made to the energy uses, but that's not a factor we can play with. The building orientation is set, as is the window wall ratio.

So whilst insight is saying that we could save energy by changing this ratio, Daniel has already set it based on the results that are required for the daylight factor. But maybe we can make some changes by applying some shading. And here insight shows us the kind of savings we can make, depending on the shading percentage compared to the window. So we can add those in.

What else can we make a change to? Let's look at the glazing type. So at the moment, the little triangle shows you the information is modeled. But if we switch to triple OE, then we can bring that energy usage factor down. So that will make a difference.

And we carry on. We work our way through each of these little factor cards, looking at what can make a significant difference and adjusting the scale to incorporate those factors. And each time, we should start to see the energy usage intensity dropping.

So we work our way through. If we look at the wall construction, we can see what's modeled. And we can see the great improvement if we switch over to a timber. So updating that drops us down to 212 kilowatt hours.

The roof construction, again, onto the daylighting-- now, because this is mixed use office and residential, if we add in some daylight in occupancy controls-- so automated lighting-- that should make a difference. Yes, it does. And we can look at lighting efficiency again.

We can make some significant improvement by opting for more efficient lighting. Again, with the HVAC, it looks like the ASHRAE heat pump is our best option. So let's select that, and that brings the value way down.

We carry on, and we adjust each of these cards. And we can see now that we're down to 105 kilowatt hours per meter squared over the course of the year. So insight allows us to play around with these different factors and determine how best we can improve the overall efficiency of the building.

DANIEL GAMEIRO: This was awesome. It's a huge efficiency gain. So now, let's look at the renewable energy potential with this building, and in particular, with photovoltaics. We have sold for consumption, now we want to understand production. And in the instant energy analysis in Spacemaker, we saw an indication of a potential energy requirement of 112 kilowatt hours. And we have just seen how that could be achieved in detail in our Revit and insight analysis.

So Spacemaker also showed potential generation of over 162 kilowatt hours per square meter for 90% of the overall roof area. And we can see there are some areas where this potential is lower, due to being in shade at various times of the day. So by sending the model to Revit and then running an energy analysis in insight, we can obtain a much more granular information on the PV potential.

So insight shows us a detailed breakdown of the roofs in the building and the PV potential of each one, and including even the payback time is a great feature. And this allows us to make more informed decisions on exactly where to place the PV arrays and also what percentage of the roof can be utilized. And looking at the energy requirements of our buildings and the potential energy that could be generated via PV, we can now see that we are able to provide 18.5% of the building's requirement through solar. That's awesome.

So we just went through the whole workflow, from massing to energy. And what are the outcomes of this workflow? What have you achieved? Well, our client would have not the data to build a solid business case, although it's very early stage.

Construction cost calculations could be enriched with the right wall and roof buildups, HVAC system, plug loads, lighting, windows, and PVs. And we also got a precise estimation on the operational energy, as well as energy production. And we have optimized the living conditions in the project to achieve high performing, sustainable KPIs.

Finally, our client could meet with investors and the planning authorities to discuss the feasibility of this project, based on a very detailed 3D model, as well as sustainability analysis. I believe we are just scratching the surface of the potential of enriching our early-stage designs with this very detailed analysis that we do later on.

And this demonstrates a lot for energy and daylight, but I'm sure next year we will be able to show you even more. Thank you so much for your attention. I really appreciate this time.

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We use Dynatrace 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. Dynatrace Privacy Policy
Khoros
We use Khoros 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. Khoros Privacy Policy
Launch Darkly
We use Launch Darkly 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. Launch Darkly Privacy Policy
New Relic
We use New Relic 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. New Relic Privacy Policy
Salesforce Live Agent
We use Salesforce Live Agent 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. Salesforce Live Agent Privacy Policy
Wistia
We use Wistia 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. Wistia Privacy Policy
Tealium
We use Tealium 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. Tealium Privacy Policy
Upsellit
We use Upsellit 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. Upsellit Privacy Policy
CJ Affiliates
We use CJ Affiliates 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. CJ Affiliates Privacy Policy
Commission Factory
We use Commission Factory 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. Commission Factory Privacy Policy
Google Analytics (Strictly Necessary)
We use Google Analytics (Strictly Necessary) 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. Google Analytics (Strictly Necessary) Privacy Policy
Typepad Stats
We use Typepad Stats 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. Typepad Stats Privacy Policy
Geo Targetly
We use Geo Targetly to direct website visitors to the most appropriate web page and/or serve tailored content based on their location. Geo Targetly uses the IP address of a website visitor to determine the approximate location of the visitor’s device. This helps ensure that the visitor views content in their (most likely) local language.Geo Targetly Privacy Policy
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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