The Importance of Data Quality in 2020

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Now more than ever, it is critical for agencies and brands to ensure that they are leveraging high quality data for their marketing efforts.

In this video Q&A, Michael Shields talks with two experts in data quality - Timur Yarnall, CEO and Co-Founder of Neutronian, and Dan Scudder, CEO and Co-Founder of Highland Math - about why data quality has become so important in 2020.

Watch now to learn why they are focused on data quality and what their companies are doing to bring more clarity and transparency to our ecosystem. Full video transcript is also provided below the video.


Video Transcript

Michael Shields: Hi everybody - we've got a couple of great guests today that are two experts in the field of data, data marketing, data compliance, consent - all these hot button topics that are hugely important in so many industries, becoming bigger by the day. We've got two companies that share a philosophy and a mission and we want to talk about what they're seeing in the marketplace, how they came together and where they see things are headed. So we've got Dan Scudder and Timur Yarnall. I'm gonna let you guys both introduce yourselves. Timur, let's start with you. Give us a little bit about who you are, your background, and then let's get into the concept of Neutronian and why you thought it was time.

Timur Yarnall: Yeah, sure. So Timur Yarnall, I'm the CEO and co-founder of Neutronian and this is my fourth time as a co-founder so I'm very passionate about entrepreneurship, just addicted to entrepreneurship, and I think generally the positive things that it can do in all aspects for the ecosystems we're working on, what it is for employees and people involved in the business. So I'm just a passionate entrepreneur in that and for Neutronian specifically...my co-founder and CTO, Tom DiGrazia had great background in cloud computing and otherwise so we could've gone in a lot of directions...but for Neutronian, we think we have a chance here to have a very positive impact on the MarTech ecosystem. And the, the idea behind the company is that we've built a SaaS platform that ingests data and then delivers the equivalent of a credit score for marketing tech data and covers everything from compliance to performance, to data processing security, et cetera. So we think it's a long overdue need and we're excited to have launched the company and to fulfill it and excited to be partnering with Dan and Highland Math.

Michael Shields: So it's probably important to note Timur that you're not...cause I think people will hear some of the words you say and assume you sell data or use it or you're a broker or you're an ad company. You really meant, your aspiration is to be a real neutral party that is an arbiter, not somebody who's involved in transactions or has a side in either case. Correct?

Timur Yarnall: Right. That's exactly right. So Neutronian is a fairly geeky name. We're proud of our geekiness. And, it is supposed to mean neutral and independent. And we are focused on measurement of data quality so we're not selling data and we're not taking data ourselves and using it. We're literally measuring and scoring the quality of data in our definition of quality that we think is very expansive. That's exactly right.

Michael Shields: And Dan can you give us a little bit about your background and what Highland Math is all about and maybe how you guys might intersect?

Dan Scudder: Yeah, absolutely. Thanks Mike and Timur for having me on. So my background, I'm currently CEO and cofounder of Highland Math. We've been doing this for about two years and our business is a data monetization as a service business. So what we do is we help companies of all types who often create interesting data as a byproduct of their core business offering. So it could be a publisher, a retailer, a financial services firm. We help them take raw data and package it into data products. And those data products often materialize themselves as audiences, for example, in the marketing ecosystem or insights for financial services or healthcare, but really helping companies build interesting data products. Like Timur, I like entrepreneurship. Prior to this I was a co-founder at LiveRamp. Spent many years there, ran their data platform and data division, prior to leaving and starting this current company. And obviously through that experience, got a lot of deep knowledge about the ad tech and data ecosystem. And that's translated well into what we're doing at Highland Math. It's nice to be working with Neutronian because what they're able to do is, with the data products that we create and the process that we follow to create some of these data products, they can actually validate and help ensure that the data products are high quality when they're brought to market.

Michael Shields: So Dan you kind of touched on this, but if we can maybe probe into that a little bit more. If you're in the digital marketing, MarTech industry or media and you've been following for the last couple of years you might assume that, okay, every company has like five data scientists, they've brought in, they've hired all these teams or if they want to extract more value out of their data, they can surely just plug into a couple of tools and make that happen. But that's obviously not the case of what you've encountered.

Dan Scudder: Yeah, there's sort of like the top of the pyramid, the biggest brands, biggest retailers, they certainly can attract top tier data talent, and afford to stand up these larger internal teams that can sort of wrangle data. But you quickly get to a group of marketers below that in terms of spend size, who don't have the internal data science capabilities, they're not necessarily able to attract PhDs out of the top data science programs to come join them. So they actually need a lot of help as more and more data becomes available in these DMPs and marketplaces. How do they use data more effectively? How do they put their data to work for them? And so that's really part of our vision is helping these companies who don't have the internal data chops.

Michael Shields: And I imagine it's the same with media, like a Warner Media or an NBCUniversal, probably has a whole huge team that tries to make tons of money off all their audience data and their insights but the average digital publisher probably doesn't have that.

Dan Scudder: Exactly. I'd say it's even less on the media side whereas finding data competencies and in the data science capabilities you'll see a lot less of them on the media side.

Michael Shields: Right. And then do you guys go way back? Do you know each other from the industry or have you just come together recently?

Dan Scudder: I would say Timur we met in the last year, introduced through some industry folks. I think we may have crossed paths over the years while he was at Comscore and some of his other past roles and I was at LiveRamp but it was really in the last year that we sort of got to know each other and aligned on the common missions and ways we can work together to improve the data ecosystem.

Timur Yarnall: Yeah. I would say it's a great example of shared philosophical background. And I do think that there is a fairly rapidly forming ecosystem of companies like Highland and Neutronian that are focused on quality and all it's aspects. And it's a group that sees that this is going to be beneficial and much needed for MarTech. And so I think Dan and I sync on that pretty fast.

Michael Shields: So let's go back to like maybe trying to try and figure out where that ecosystem was coming from and why. So if you can go back...it's hard to do right now in these crazy times, but let's go back to being beginning of the year, you know pre COVID explosion...The talk at that time was privacy laws are getting stricter, consumers are more wary of getting tracked, they've heard a lot of data breaches, you had CCPA coming. I would hear things like "Oh, no brands are not gonna use third party data at all anymore, that's over." What was the climate like at that time? Am I assessing it right? And then we can get into what's changed since. And that's for both of you guys.

Dan Scudder: Yeah, I think you're absolutely right. So kind of turning into the new year of 2020, the big talk was third party cookies going away so that's gonna put more demands on the use of first party data for brands. And then third party data under pressure from CCPA and what's that going to do to the data industry. I think a lot of what started happening has continued through COVID but I think what you're seeing more of is actually people who are saying "hey, we actually need data more than ever." And whether it's third party data, or first party data, or second party data sharing, data connections should be very valuable because it drives more accountable media spend, it allows everything to be measured and more effective. And so the pressure on budgets that COVID has caused has actually been sort of a boon for the use of data in the marketing industry.

Timur Yarnall: Yep. I think that it does feel like several lifetimes ago the beginning of the year. But I think in addition to what you mentioned Mike, in terms of the buyers looking to move away from first party data and the idea that the accepted wisdom now on the street is that all third party data is kind of bad. I think Dan and I philosophically agree that while some of that is much deserved because there have been lots of issues with data processing. I think there is a skepticism on the buy side that is maybe well-deserved. I think we also have to say that everything is evaluated kind of purely on scale and there hasn't been much of a metric around quality. And I think one of the areas where we philosophically aligned the most is that dialogue around first party versus third party. It's almost a bit of a false premise because every dataset needs to be modeled to a certain extent. And one of the biggest problems with the perception of third party data now is that buyers are aware that some vendors are literally throwing spaghetti at the wall and taking a small dataset and expanding it massively with no real statistical reason to do so and that's where some of the skepticism has come in. But every first party data set also needs to be complemented with additional qualities and so there's tons of work to do on first party data as well. And that's I think a key area of value here where we're talking about bringing transparency and bringing some dialogue and framework to modeling methods. My perception is that Dan and his team are approaching it the right way and we want to pull additional partners into looking at that.

Michael Shields: It's interesting you brought up the first party data thing because there was you're right in the last go back six months ago, there was a fervor for "first party data is going to rule every company." Whether they are a brand or media company, wanted to become a direct to consumer company as fast as possible and build up their own database. That was going to be the way forward but I'm sure that has limitations and challenges as well as there's probably a limited set of companies that can get it and can build a large set of data that's useful on their own. Would you agree with that Dan?

Dan Scudder: Yeah, I think that's totally right. I think everyone is trying to build those first party databases, but it's gonna be varying degrees of success. I mean, if you're in the pharmaceutical business you have very little consumer data because you're sort of in the background doing research and everything is sold through pharmacies so your ability to collect consumer data is going to be a lot harder than say a financial services firm where every single customer registers for an account and you have their information. And so third party data definitely still has value along the chain of needs of these marketers. And to say data is going away is just not, it's not going to happen. Marketers need efficient media spending and they need to be able to measure their media spending and data is the sort of lubricant for all of that.

Michael Shields: Timur, there must be examples of before there was a real way to kind of gauge who's who, there must've been some real quality data companies out there that were just not getting enough deals or being pushed aside often that had a lot of valuable information and insights that brands just weren't tapping into. Were you seeing that?

Timur Yarnall: We're absolutely seeing that. I think that the thing we're pointing to here, as well as on top of with what Dan is saying, I think that the problems with first party versus third party and the modeling methodology behind it, there's quality players that have not been allowed to stand out and I would say I think there's actually a ton of really good data that is sitting on the sidelines right now because there is no framework for quality that will properly reward somebody for coming into the market. I think that the market can be fairly described in a number of analogies. One good analogy might be it's like the 1920s in the stock market right now where there was really no audit mechanisms so a buyer had no idea if a company financials were true or were they faking their books. Another very good analogy, very relevant today for what a high quality data provider can experience, is this concept of the market for lemons. The lemon theory is an economic theory that was first quoted in the 1970s around the market for automobiles and it turned into a Nobel prize winning economic theory, where at the time there was very little information about car quality and as you remember there was a high record of traffic accidents. And so buyers didn't know and they would end up only paying a price kind of in between the middle of what high quality and low quality really was. And that effect ended up rewarding all the low quality players for staying in the market because they actually got a higher than average price they thought and all the high quality players actually ended up getting less than they deserved and they ended up exiting the market. So that market for lemons shows this continuing cycle of punishing high quality and getting them out of the market. And that has been significantly I think played out in the data marketplace, especially for high quality panel providers that have invested in what they're doing because there's been unethical players that have harvested data for free with browser toolbar injectors or things like that. And of course, any panel company is going to look expensive when compared to that type of harvest. So that's a good example of a type of player that has been punished and we're looking to benefit. High quality ethical panel providers that you could pull together to model data sets that is not being done now.

Dan Scudder: Yeah and even simply looking at the way data is priced in online advertising, there's sort of two prices, like a $1.00 or a $1.50, and there's not a lot of sort of science behind the pricing. And Timur to your point, that's kind of like the lemon theory which is just everyone has sort of settled on a common price. And if you talk to data providers today with really high quality data they'll always say, "Oh, I don't sell my data like that because I'm not getting the value from it." Whereas other companies who have low quality are happy to get all these riches from the perception of quality that they're able to benefit from.

Michael Shields: Okay. So we were kind of talking about this pre-COVID time. Let's fast forward to today. Dan, you hinted at this a little bit. You know obviously brands are, most companies are going to be cautious in a time when the economy temporarily freezes, right? And people are just not buying stuff. And they're not sure if they should even advertise at all. They're cautious about taking risks. But at the same time you're right, there's a tilt toward performance and needing to prove every dollar and effectiveness. What have you guys seen in terms of are brands more wary than they used to be? Are they not talking to you guys? Are they not taking calls? What's, the state of things lately?

Dan Scudder: As of late certainly there's been a bit of a thaw and I think everyone is planning, at least in most categories, planning for the reopening and how do they spend and especially spend some of those budgets that maybe were paused for a bit so they have some extra spending that they can push into the market. But for a lot of these brands, I think the pause, the COVID pause, actually gave them an ability to turn off some legacy non-performing channels and instead reallocate those budgets to channels that are more measurable and data-driven. Connected TV is a great example. Cord cutting and the rise of connected TV that was accelerated during the shutdown and that allows brands to move all these linear dollars, which may be harder to measure, directly into CTV dollars, which are much more measurable. And I think that's going to drive again more use of data going forward.

Michael Shields: Yeah. You're seeing a lot of "should we be doing the upfronts anymore? Does this make sense?" And then it'd be interesting to see whether that pushes the industry to be more data-driven in television. Timur, you were going to jump in.

Timur Yarnall: I think it's been such a volatile time. It was almost like a knockout punch the first three to four weeks. And in a sense, I think probably what Dan is hearing and I'm hearing too is that the focus on quality and Dan's services on actual modeling and getting those monetization baselines is more important than ever because the cost of being wrong for a marketer now has gone up significantly in the last bit. If you acquire the wrong customer now as a marketer it's very expensive. Think about any credit agency or credit product, anything like that it's bad. And so from that sense, we've actually seen a significant uptick in interest and we've had a number of folks come to us and say "This is long overdue. What can we do to partner and help you roll this out in a positive way and adjust it to specific areas?" And in that sense, I think Dan and I frankly have already started referring partners and customers back and forth. So I think this partnership is very organic in the sense that it's happened due to a partner and client demand. And there's times that I'm talking to a customer and they're like "Well, this is great, but I don't even have a data business yet. Can you help me get estimates on the revenue we could drive?" And I'm like "yeah, actually we're not doing that because we're measurement but here, there's a partner over here who's really focused on the monetization angle." And it's been very seamless from that perspective.

Michael Shields: On that note, does it worry you at all that whether during this period of uncertainty and everyone's kind of being really cautious, is that more quote unquote bad guys might try and pull some stuff off while they can? Like you know, the shadier data guys are gonna come out of the woodwork?

Timur Yarnall: That's always a concern yeah and I think you know given your background Mike on following the market closely. I think that's certainly a concern and there are potential risks and there are potential vulnerabilities that aren't being talked about enough. And so I think for us and with Dan we want to highlight the good players but by doing that we also need to spell out what can happen. If people are missing things, what are the bad things that are gonna happen? We've talked about consent frameworks and how important that is but who is fact checking or actually checking the type of consent that's being used. In terms of testing and looking at the composition of an audience segment, I think the ecosystem now knows to look at the audience composition of inventory but actually looking at the underlying composition of data, is it coming from a high quality site, is it, coming from a site that has viable, overt consent from its users, et cetera, I don't think enough of that is happening and I'm sure it has ties into monetization. Interestingly, I don't think anyone has really done a study yet on the impact of consent and GDPR type consent or CCPA type consent on performance and monetization. So there's a whole world of exploration that has to be done and there's definitely a lot of risk if it doesn't happen.

Michael Shields: You know it's interesting, you mentioned CCPA. Do you guys think now that we're in the economic downturn, maybe we're turning the corner on the pandemic but just a lot of crisis in the world, I wonder if you think consumers are less concerned now. That they're all of a sudden maybe thinking "well, we need data to track things like COVID and I'm not as hesitant to share." Or I wonder if regulators are gonna be less focused on this right now because there's so many other things going on. You know it was at one point this was in the presidential race and now no one's talking about this at all, it's interesting. What do you guys think is gonna happen?

Dan Scudder: Yeah, definitely COVID raised the awareness among the population and sort of the value of data and the prevalence of data in our everyday lives. I mean even COVID itself, every day you turn on the news the first thing you see is data, you know, number of deaths, number of cases and there's contact tracing using mobile phone data and so the awareness of data and some of the societal good that it can bring I think has actually increased a lot in the last few months. And some of the data products that maybe were only for these "scary marketers" can actually again drive greater societal value than just targeting ads. But nonetheless, I still think CCPA will continue to exist and be enforced appropriately. And so I think for the marketing use case, I think consumers may be less scared but I think CCPA is going to provide the standard that the industry can use and reference as a way to protect data but still drive value from it for marketing purposes.

Timur Yarnall: Yeah, a hundred percent agree. I actually wouldn't have too much to add there. I agree on the positive aspects of it and I'm quite certain that there will be a bit of pushback and kind of a flashback to the concerns about data usage. And my guess is that when...I hope the positive use cases play out but I'm also quite certain unfortunately based on experience, that somebody may use that data the wrong way. And it's likely going to be an employer using that tracking information to quietly turn down somebody for a job or set some risk assessment and that's going to come out in the press. So it's a really tough balancing act but I personally go towards the privacy angle and data privacy as being critical. And I think it's of essence to a free and functioning democracy. And so that's my concern.

Michael Shields: Timur, I know this is gonna be hard to answer because I imagine there's such a wide range in the continuum for brands, but if you think about the average CMO or even a high ranking digital advertising executive at a big agency, what is their knowledge of the data marketplace in terms of like, do they ask the right questions? Do they understand that you should ask about methodology and modeling? And do they know what red flags to look for when they're evaluating data? Is it all over the place? What do you find?

Timur Yarnall: What we find is that there are smart buyers out there and that buyers need to hit their performance metrics obviously, it's their livelihood, so they care about it and they're passionate about it. Generally. I don't think the tools are available and the tools have not been available so the buyer has to trust what the data seller is telling them. So I think the way that plays out is that most data buyers have really narrowed down their sources. And other than the big three of Facebook, Google, and Amazon, which are continuing to dominate the ecosystem and for good reason. I think there is a ton of quality there but they are expensive on a relative basis. But I think it's making it harder and harder for a CMO to trust new sources because the onboarding unfortunately has to come with a lot of individual tests and control. And every marketer is essentially having to create their own evaluation method. They're having to create their own test. And I don't think that they're gonna relinquish that control completely but I do think that we can make that quite a bit simpler by having a framework that is accepted across the ecosystem.

Dan Scudder: Yeah. And to Timur's point, what you might see in a large agency is they may say "okay, we're going to go vet and sign three data providers who are gonna just sort of be our master service provider of all the data we need." And they do this deep vetting process to ensure compliance and quality and all of that. What they're missing ultimately is there's dozens of other high quality data providers out there but they're just not set up to kind of measure and sort of scale the compliance and quality audit auditing very well. So the agency's missing out on good data and obviously the data provider's missing out on that agency budget. And then the marketer's missing out on good performing data. And so that should change over time with things that Neutronian is doing.

Michael Shields: To your point, I imagine what also clouds their decision making in the market is that so many of the big holding companies, who may have made investments in their own giant data provider or data clearinghouse...I'm thinking about Axiom and there are a couple of other really large deals of that scale in the last six months...I wonder if those guys are going to favor their own products and that's gonna make the market tougher to open up. I don't know if either of you guys have a thought on that.

Dan Scudder: Yeah, I mean there's certainly corporate dynamics like that, that I think can be priced into commercials and things which makes things challenging. But I think in the end, transparency is gonna win and so companies that have the best data and can surface the quality of that data, marketers are gonna demand that not sort of a one stop shop for a lower quality data.

Michael Shields: They want the best data, not just your agency's best data?

Dan Scudder: Correct.

Timur Yarnall: I agree the transparency will drive that and I think you'd have a hard time pointing to a hundred billion or trillion dollar markets elsewhere that are not facilitated by a third party metric or third party auditor. You can't imagine the credit markets, financial markets, or even healthcare markets operating without it but here we find ourselves in the data markets with really no auditor of power. I think that the transparency will drive that but ultimately what marketers care about too is having a customized fit of their needs, their taxonomy, their understanding of their consumer and they're not going to get that in today's world because there is no let alone baseline set of quality and compliance, there is no dialogue around a fit for purpose. There's no dialogue around "well, this dataset could be really useful for a CPG or FinTech, but probably isn't great for an auto intender." And I think when you have marketers aware that, you know, Harvard business review published a study a month and a half ago that noted the average demographic age and gender segment that they tested was only accurate a little over 42% of the time, which is worse than flipping a coin. That's gonna drive the analytics. And you know, some of those segments may have actually been really accurate for certain demographics and certain aspects of the population but if you try and apply them across the entire population, they're going to go back down to actually being less than a coin toss. So all of that ties into performance and ultimately quality will boost performance and we're in the early innings of talking about that.

Michael Shields: In the grand scheme of things, if the vision is a more transparent market, better quality, and then better results for brands, how big of an issue is the cookie going away in your mind? Is it more noise? Is it really a big problem? Is it yesterday's problem anyway? What do you guys both think?

Dan Scudder: Yeah, it's definitely a hot topic that everyone is figuring out and I don't think anyone really knows what the answer is. There's solutions that LiveRamp is putting out there with their ID graph alternative, there's browser based solutions emerging, but I sort of look at that as a sideshow to the use of data. Data will still be used regardless of what the common identifier is and the third party cookie is just an identifier that's going away. There'll be something that replaces it in some form and there'll be some type of data that's associated with it so that the need for data is not gonna evaporate with cookies.

Michael Shields: Timur is it Armageddon or is it just something left over from the desktop era that doesn't matter that much?

Timur Yarnall: Yeah, I mean, it could be be Armageddon but one of the things I love about MarTech, as much as it can be a maligned ecosystem, I love it because there's tons of smart people, there's tons of ethical people. I mean, there are some bad actors. But it has the potential to be Armageddon and we could all be left working for Facebook, Google, and Amazon, concentrated there. But every time the industry has been challenged this way, and I know that even Facebook and them want to facilitate some alternatives, so I'm confident that it will be answered and it'll be based on the data usage piece. And I agree with Dan that the data will be used. The evolution of first party data and the pending crisis here will open up the idea of sharing first party data in a safe way. I think there will be the emergence of the mythical first party data consortium at some point in the next two to three years, maybe sooner. So it's going to be a good driver of change. And I think any crisis will weed out a lot of the noise and it will actually drive a true solution to come to bear.

Michael Shields: Guys, I want to make sure we're conscious of time here. Dan, I want to make sure I asked you...we keep talking about applying all this stuff to marketing and I imagine everything that we've described here it can also be applied to other industries in a big way. Can you maybe talk about where you see some potential for better data clarity in finance, banking, other worlds?

Dan Scudder: Absolutely. So, you know, the world I come from at LiveRamp, and Timur, is very much the marketing and advertising world, which is really the tip of the spear for data usage and data liquidity, sales and marketing use cases. And so it's a very in some ways mature market in terms of the volume of data getting piped through it. But increasingly you've got other markets, Healthcare is a huge one and Financial Services, where data is being used to help make decisions. So they call it alternative data in the financial community but helping hedge funds use, for example, location data or transactional data to better understand investment opportunities. Or in healthcare, you've got more and more data being used to understand healthcare outcomes. I mean, we saw all of that in the COVID crisis that we had. So the liquidity of data across different markets is only going to increase in the need for data and the thirst for data is going to be there. And so for companies to expose their data assets, not just in marketing, but they can be available for Financial Services for Healthcare. There's going to be lots of ways to create value with data but then also the need for real sort of quality measurement of that data as well.

Michael Shields: Let's maybe wrap on this idea. I'll ask both of you...if you can project forward in a year, what is your collective end game or vision if you had one and where do you think we are? What do you think it is headed at? Timur let's start with you.

Timur Yarnall: Yeah, well, as a seed stage company, I don't think I'll be at my end game in a year. I want to make sure that my investors are aware of my roadmap and have been properly. But I believe that the end game, the concept of a quality framework which takes into account performance and accuracy as key components but isn't the only thing that's evolved, which unfortunately, I think the ecosystem has really only focused on performance and not on consumer engagement, et cetera. I think the idea of a quality framework will actually be fairly well accepted and you'll have it common that marketers will ask for a third party check and will use that when building out their strategies and taxonomies. And I would bet that within a year the question we just touched on around identity will not be solved but I think it'll be quite a bit more clear. And then the final prediction I'd make that within a year the concept of consumer consent and the types of compensation that consumers get for giving consent, not just monetary value, but in terms of application value and usage of certain other data, et cetera, we'll also be at the forefront. I think that's going to be a very interesting area of evolution in terms of how consumers are incentivized to give consent and in an ethical, you know, non just driving clicks type of manner. Those would be mine.

Michael Shields: Dan, what about you?

Dan Scudder: Yeah, I very much agree with Timur on the trends that are going on. I think the continued democratization of monetizing data. So 20 years ago data was controlled by really a handful of sort of conglomerates that weren't necessarily transparent and it was a lot harder to really understand the data market, whereas, fast forward a year from now there's gonna be hundreds and hundreds of companies who aren't in the business of selling data as their primary business but they're going to be participating in the data markets, both as buyers and sellers. And tools like what Neutronian is doing is really going to help them feel comfortable about making sure they're getting the right value exchange for their data products.

Michael Shields: Everybody's going to be in the data business eventually.

Dan Scudder: Exactly.

Michael Shields: All right. Well, we could probably talk all afternoon, but I figured this is a perfect moment to kind of stop on a hopeful note. Thank you guys so much for great conversation and looking forward to talking again down the road.

Dan Scudder: Thank you, Mike. This was great.

Timur Yarnall: Thanks Mike.

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