Hi, everyone. We are so thrilled to be with you here today at Product Con. I'm Nicole Breskin. I oversee news and entertainment vertical products here at Disney, brands including ABC News, Marvel, Nat Geo, and ABC Entertainment. And data is just such a massive part of everything that we do here to drive our decision making. And I couldn't be more thrilled to be here with this panel today to moderate this discussion on using data to make effective decisions in product management. So without further ado, I'm going to hand it over to our panelists to introduce themselves. And Abby, I'll kick it over to you. Awesome. Great to be here. I'm Abby. I'm a director of product at Amplitude. I focus on essentially helping product teams answer questions with their product data and collaborate around it. So definitely excited about this panel given what we do is help teams make better decisions with data and also managing a team of PMs who are trying to do the same thing. Definitely gets meta, but makes me very excited for the topic today. And Ryan, over to you. Yeah, excited to be here as well as the founder and CEO of Sprigg and we're a product insights platform that complements both analytics tools such as Amplitude as well as AV testing tools such as Chameleon quite well. And what we do is we do in product surveys as well as session replay and concept testing to help product teams and product managers understand the why and backed by Andreessen Horowitz, Excel, and First Run Capital and work with many of the fastest growing tech companies including Loom, Square, Robinhood, Coinbase, Dropbox and Ocean. Amazing. And Colin, great to see you as always. Call us about you. Hi everyone. Great to be here. I'm Colin. I'm leading Chameleon here in North America. Chameleon is known for a couple things. One of which is we're known for all team experimentation. That's where you have multiple teams coming together on a single platform to do experimentation on the web. But you could also do experimentation in the back end with your products. We're also known for our AI, which gives a score to every single visitor that comes to your site based off their propensity to convert on a single KPI. So we are huge lovers of the product world and all of the data that powers it. So happy to be with you all today. Great. Well, we're going to just jump right in. Again, so excited to be here today. So just getting us started. Team, I'd love to hear from you. What are some of the common challenges that product managers face when using data analytics to inform their decision-based making processes? I'm happy to kick off. And my background's always been in product management right out of college. And so the reason why I started Sprig was I was previously the first product manager at Weebly, and we're quickly growing to run 100 million ARR and 400 people. And we were getting all of our data in place. And so we actually were probably relatively late for most companies today for getting that analytics instrumentation in place and that AV testing in place and getting those really crisp revenue dashboards in place as well. And we started to get everything instrumented and started to realize that we didn't really understand the why behind the revenue trends that we were seeing or perhaps the analytics trends that we were seeing or maybe even some of the AV testing trends that we were seeing. And so the reason why I moved on from product management to starting a company in the product insights category is to help companies really understand the why. And so I think a big challenge a lot of companies are facing today is that they might have partial data sets. Maybe they have the analytics data and the revenue data. Maybe they have the AV testing analytics data. But we do see other companies missing the experience insights and really understanding and putting the customer first into understanding their sentiment around whether a feature or product is meeting customer needs. And so I just really encourage a lot of teams and product managers out there to look at the different types of data and see, do you have really that complete holistic picture into not only maybe how much revenue you're making off of a given customer or account, but do you really understand their behavior? Do you understand the why behind their decisions and look at all those data sets together to be data driven? I see a lot of product teams today being data driven around very specific types of data that could be misleading. And so taking that complete picture is really one of the challenges I see today in an area that we've been excited to work with teams with. Yeah, definitely agree with all that. And I think kind of going off of that idea of the complete picture and another challenge that I see people facing is either kind of stopping work when the metric doesn't look good and maybe incorrectly like abandoning initiative too early because you chose the wrong metric or maybe the wrong maturity of metric or on the other hand cherry picking the data that really tells the story that you want it to tell and actually continuing with an initiative when it no longer makes sense. Something interesting that I think kind of going back to that complete picture is especially early on in a product stage, I think a mistake people can make is to set metrics that are just at the wrong maturity level. So for example, a usage metric when you're trying to actually take a big swing with a new persona or maybe investigating into something like AI, maybe metrics aren't going to be the way that you can kind of successfully measure that in which case looking at some of the other signals that Brian mentioned, I think sometimes people forget to do and kind of either abandon initiatives or continue with something that they shouldn't. I think that's all well and true and I just think we also have to be really mindful that one of the biggest challenges that PMs or marketers face anybody that's operating in today is the volume of data that we're getting, and the velocity it comes to us, it's just overwhelming. So I think one of the biggest challenges you have to be ready to face is to know your enemy. What kinds of data should you be looking at precisely? And then being really forward thinking and explore like, okay, well, this data is important to me and my team, but how does it affect other parts of the business? That really separates I think the goods from the greats is that they're not only aware of the data that's important to them, but they're also going to be very informed about how their performance affects another part of the machine. Absolutely, and I think it's so key not only when you set your metrics like what are the metrics like your guardrail metrics that you don't want to mess with, and then also what are the metrics that maybe are not really success factors in what you're looking at. So which dovetails really nicely into just like team, like how should PMs be thinking about setting success metrics for the products they're looking after? And secondly, just an area that I know, Abby, you're really excited about is like, how should PMs be integrating data into their product life cycle? What are some best practices? Yeah, yeah, happy to kick off on that one. I think one thing that we always recommend at Amplitude and that I use on my team too is before you start a project or before you work on a product, really asking yourself, what are the key questions that I want to learn or answer with this initiative? So rather than starting with, hey, let me go ahead and to your point, call and tag every single thing and care about all the pieces of data, what are actually the questions that the team wants to answer with an initiative? And then go to, okay, what data do I already maybe have that I could use for that? Or what data maybe am I going to miss and not track if I don't instrument this now? So I think that's one key thing that I would do is just make sure you're kind of taking a question first approach to data and really going about it in that way. And the other thing that I'd say here in terms of integrating it into the team is also make analytics more of a team sport. So I think analytics is best when you're kind of working and ripping with someone. So something that we tend to do at Amplitude is we actually integrate it, you know, bringing in the team at all stages of the development cycle around data, which actually makes it a really fun exercise as well. So when you're kicking something off, like actually getting the team, the engineers, designers, PM together and actually have them brainstorm around what that set of questions is that you want to answer. Typically, you'll find that they have other questions you haven't thought about and maybe even changes the product that you ended up building. So definitely doing that, bringing data into the design process, actually asking your designer, like what questions could I answer for you that would make the experience better if you knew, which I think can also bring more data driven development. And then finally, when it comes to the results cycle, like one of my favorite meetings that we hold at Amplitude is actually pulling the results and then bringing the team together and actually live looking at all of the results and dashboards and asking them what other questions they have. And if you have a tool like Amplitude, you can even on the spot live answer those questions together, which just gets everybody thinking. And typically, we found a lot of our new hypotheses come out of those sessions. So I was just saying, make sure you take a question first approach and also trying to make it a more collaborative experience around data in general. One area that I think were the biggest tips that I would say for any product manager out there is making sure you're segmenting the right user base. And so your company strategy for the year, your OKRs, your quarterly goals, whatever your North Star is, there's always going to be a specific user persona that you're focused on as a product manager. And a lot of companies will look at their data as if every user is the same. Every user is a focus for the company. And I've seen AB tests where you actually have the test version offer form control, but it's perhaps not with the user segments there can be focused on. I've seen analytics data where trends maybe trend in the right direction, but it's not the specific user segments that your company is focused on and experience data as well. We've seen in product surveys for customers move metrics, but also not the right user segment. And one of our customers, Coinbase, they just published a case study with us. And what they wanted to do is improve their tax center. And crypto taxes is, you can imagine, very scary, very complex. And they wanted to focus on how they can empower more of their advanced users to improve and arm them with the tax information that they needed to actually successfully file their taxes with crypto. And they're able to segment specifically to the power traders and people that had made trades on other platforms. And when they looked and segmented all their data to that specific group, they gave them really key insights into exactly what they needed to do. Now, if they looked at the broader user base, the majority is actually the less advanced users would have actually driven their roadmap in a different direction. And so we look at segmentation, making sure that across all your data sets, your segmenting specific personas that are strategically important for the business is going to give you the best signal on what to do next with your product. Yeah, I mean, I think it always comes back down to what you said earlier, Ryan, which is that you're trying to answer the why. And if you can't easily, sometimes I just recommend to any PM or marketer out there, like just stop with the data for a second, just stop and see if you can tell your friend a story about how your customer or user perform. And if you can't easily articulate the story about why they're behaving a certain way or why that AB test resulted in a certain performance outcome, then you may not have like a complete understanding of what you're trying to solve for. And so, yeah, just sometimes avoiding the data overload can be helpful in getting back to the story. Like one of the features that we've got in our site, which it's one of those like buried features that, you know, it's easy to overlook, but to me, it's really cool because it's a spider chart.  And that's why I'm going to see a huge increase and like add to cart.  And that spider chart is super helpful to that, that, that bigger picture, like you can see that okay, I've added to cart, but I've totally decreased transactions or, you know, I've answered that tax question, but I've completely like spun up a long call list to my call center or something like this. So I just feel like, yeah, you want to make sure you're understanding the story at all times because that's what helps you kind of stay oriented about what you're trying to solve for. One thing I just kind of add on to that or something that we do to kind of, it is leveraging data, but to get to the why is when we do release a new feature, like basically using data to actually take a look at who use the feature, who didn't, you know, what other trends are you seeing and then actually target those users with a research study or a survey to actually follow up and understand what's going on. So actually rather than just setting metrics, just looking at who used who dropped off and then retargeting essentially those users with a study to understand more of like, okay, we are seeing things go up, but we can't explain it. Why might that be? And you can leverage data to do better user research targeting to get at that why. I love it. And I think not only is the why so important defining the why, but telling the why and telling it broadly. Those of us product managers know like your success, there's no I in product. And you know, your success only depends on how well you can get everyone else on the team on board. So you know, for me, at least we work, we work with sales folks, we work with marketers at Disney, we work with a ton of creatives. So, you know, for my next question for this group, how do you make sure teams are working in lock step and how are you how do you tell the story, tell the why to, you know, broad based teams? I want to take a stab at that one, because this is a question that just fascinates me. And it's I think it speaks to like two cool things that are happening in the product today. One is that the world has changed. It used to be that you could have your marketers over here optimizing like their acquisition funnels, get doing really amazing marketing and creating tons of leads that would then be handed off to the product team. And then product would take them and go optimize for retention and adoption. And nary the two sides would ever meet. And that old fashioned way is like, thankfully being obliterated companies that are really doing well today, they either have a single unified growth team, or they least have their product and their marketing teams collaborating. And that way they're able to like, to your point, Nicole, really understand how to stay in lock step together. If you don't do that collaboration, then you really are setting yourself up to not be like one of the leading companies that there's so much great research about this today. And if anyone's interested, ping me and I'll share it with you. But I think that's just so important is if you can't create a feedback loop between product and marketing, if you're not powering those two levers of marketing led growth and product led growth, then you're really missing out on an opportunity to like be a stellar business. So I would say look at how you could create that feedback loop and then you're going to be off to a much more better position. Yeah, I worked at Dropbox prior to Amplitude and we had various configurations of our growth and marketing teams over the time that I was there. But I think one kind of tradition that really helped with that that was tactical was we did have a separate marketing growth and even product team, but we had regular weekly self service business reviews where we looked at that end to end funnel of what are the marketing metrics of the traffic coming in, how are we seeing that convert to signups, and then even looking at trial conversion quality and even refunds from that business. So just really looking at the end to end. So each team felt responsible for the entire end to end funnel, even though they were directly accountable, maybe to one or two of the metrics within that. So it's just kind of a ritual that gets everybody thinking like, Hey, we're all contributing to the same thing. So setting something like that up, even if you're not a single team can be kind of a simple first ritual to get going in that direction. It's amazing that we even say that out loud. And it's like something so that sounds so brilliant and so straightforward. And yet like how many companies don't do that, even it's hard for us. Like I'm not saying it's an easy thing to do, but my God, is it so valuable?  So I think metric definition alignment is actually one of the most challenging parts of this. And actually even aligning of what is that set of metrics that you're going to target and kind of track across the funnel. So that's definitely the first exercise. It's just is everybody even on the same page of what the metrics are, how they're actually defined reporting on them in the same standardized ways and then bringing the teams together to consistently look at that. It's, yeah, I agree with you. It sounds straightforward. It's a lot of behind the scenes work for sure. Well, and it used to go back to like what I was saying earlier is like you used to have in my world of experimentation, I know about you guys, but you'd have web experimentation over here and marketers would have like these KPIs. And then you'd have like back end experimentation or product experiments would be an entirely separate goal library entirely different to your point around like different segments and everything. And you know, for everybody that's listening, that universe is gone. You don't have to be in that pain anymore. Like you can have a single goal library.  And then they use that as a way to like undermine your work. And I think that's what you're, you know, again, you don't have to live in that world anymore. And I think that's what's so exciting about being a product manager today. Yeah. And for the kind of like new product managers out there, what I love about product is there are so many flavors of product. And I think like today's product manager, you can spend like, you can be a PM like data PM, focus precisely on this and this definition, like, you know, at bigger companies like Disney myself, like we have, we have teams focused on data governance and working on these best in class tools. So I think it's really an exciting time to work work in product and work in data product as well too. Switching gears, A.B. testing. A.B. testing is just such a fundamental tool defining A.B. tests, multivariate tests to make decisions. What are some best practices you all think the product managers should have in using A.B. testing? I feel like I have to take that one. But you know, first, here what Ryan and Abby said, like it's just, it's just great that experimentation has reached this maturity now where it's just something that we all understand is that we have to do. So I just want to like recognize that it's great to hear other awesome companies just implicitly talking about experimentation. So, you know, I think that's just pat ourselves in the back that we've reached that stage where, you know, it's just something as normal as SEO, right, that you should be thinking about experimentation. You know, to answer your question, Nicole, I would say that, you know, the coolest thing that has happened in experimentation the last few years is the intersection of like feature management, feature flagging, and experimentation itself. Like again, just an awesome time to be in product. You can work more easily and effectively with engineers today than ever before to like create, you know, they'll be creating variable, they'll be controlling like how products are released when the same time you can be creating like variations of those products more easily than ever. And you can even customize and control like who gets to see what like Ryan makes that really good point about segmentation. And then Abby, you were talking about like choose these goals, like this is so much easier today. And I just feel like if you're not already working closely with your engineers about how to build a better product, then look closer at what's happening at feature experimentation, because you'll just be blown away at like what's possible today versus just a few years ago. So, yeah, I would say, you know, have a chat like first of all, are you doing feature flagging? And if so, you're already in a great shape to like start nurturing like the power of experimentation, which is ultimately all about just we're, you know, creating data that helps you feel like, you know what, this is right, like we need to do more of this. And so that's what we're in the business of is just making data-back decisions and experimentations are fantastic, if not the best way of coming to that conclusion. I do think it's awesome that the experimentation is becoming more and more normalized. And I, you know, maybe five, 10 years ago, it was only Google, only Facebook only is very large mature organizations where a very small change would have a noticeable lift and impact. And now, you know, here at Sprig, every change that we run on our marking site or onboarding flow, everything is A-B tested and, you know, we're relatively early stage. And so it is moving earlier and earlier, you know, do encourage or be out there, regardless of the company size, it's developing the habits, even if it takes, you know, the longer than you'd like to get those results, you know, it's still the team, it's important to run the test, even if you're super, super confident, so we can measure the lift. So you at least know the positive impact if you're 100% confident, let's at least just quantify what that lift is. And so I think it's great to see the maturity of A-B testing when actually surprising use case for us has been a lot of our customers are integrating Sprig into their internal A-B testing homegrown infrastructure or integrating into tools like chameleon or amplitude experimentation and looking at the behavioral data and say, hey, users are we're driving the behavior that we're looking for, but they're also able to what this are in-product survey tool able to actually measure that qualitative impact. And so, you know, if you hide the cancel button for your subscription, of course the cancellations will go down, they're going to have a lot of very frustrated, angry users potentially. And so we see the gold standard is having the behavioral lift. So seeing the analytical impact in a positive direction, but also the qualitative impact also in a positive direction. And if you can get the business metrics up into the right, as well as the user sentiment up to the right, really consider that the gold standard for a successful experiment and feeling very confident, not only the short term, but also long term impacts on the business are positive. Yeah, that makes sense. Oh, sorry Nicole. No, if you were, I was going to jump to the next question, Abby, but please chime in. Sure, sure. I was just going to say something you mentioned Ryan was also measuring the impact. I also think that A.B. testing can be a good tool for disagree and commit as well when teams aren't able to make decisions or have really different ideas on what they think the right path forward is. You know, we've done exercises in the past around how to rethink pricing and packaging. And there's 100 million opinions that people have around those types of decisions. And A.B. testing can help sort of give an answer to that. That's a little bit less biased than a debate back and forth between people. So that's definitely one thing I think about as well. And Colin, you mentioned feature flagging and experimentation. And I think more and more PMs are leveraging experimentation and kind of taking on the mindset of the growth PM. But one thing I do see kind of as a pitfall or something that people then start to think is trying to experiment with every single change, even when perhaps there isn't the right level of data or it's not the right kind of, you know, serve theory to do an experiment on. And then in that case, maybe feature flagging and a slow rollout to manage risk and mitigate risk is actually the better path to take. So I'd also just recommend thinking through when you're thinking about running the experiment, is a feature flag really what you're you're looking for and just trying to actually manage experience and risk. So whether it's trying to measure, you know, success metrics in a static way versus manage risk and just sort of like have a slower rollout of something, like those are questions you would also ask yourself. So make sure you're not waiting eight weeks versus a significantly significant data on a change you were pretty confident in making anyways. That's just one thing I tactically think about. I mean, there's a whole like practice. So like, I mean, there's the experimentation and then there's the art of creating the hypothesis, right? So, you know, we all have to be respectful of like the amount of hard work that goes into like coming up with a great experiment. But yeah, absolutely agree. Like it's just a form of optimization, releasing a feature progressively, right? So I think, yeah, that's an excellent point. One thing that caught my attention this morning is so funny. I was like, okay, this is just great timing. Benjamin Franklin says, I didn't fail the test. I just found a hundred ways to do it wrong. And I'm just raising this point here because, you know, even the best of the best, like, you know, you hire the greatest agencies in the whole world. And guess what? They're going to have like a win rate of like, you know, maybe 80, 20%, excuse me, 80% of the time they're going to get it wrong. And I just want everybody to be aware that, you know, there's this instinct to like go fast and follow your gut. And that isn't going to pay off ultimately. You're going to get lucky a few times, but more often than not, you're going to get it wrong. And so it's really to your point, Abby, like, you know, test where you can test and you've got a great experiment and then control release very, very carefully because you don't have to live the old ways anymore. You have these tools now.  And guess what? That'll just blow doors open for you to like basically get the resources you need to go do the things you want to do. So yeah, I mean, I'm just a huge optimist. I think it's an exciting time to like be in the space. So I encourage everybody to get started. Yeah. And to Ryan's point before it's like, if you can, the wise person once said, if you can't measure it, you can't manage it. So like the key is having these tools in your tool belt. And then, you know, the world is your oyster. But I do want to acknowledge, you know, data hard quantitative data, data is really just one side of the equation of those different tools in the tool belt. Qualitative data and what consumers say and what we feel is also so key in just having a holistic product point of you. I'd love to hear from folks on the panel, how do you use quantitative data in tandem with qualitative data to form a cohesive holistic point of view about your customers? Yeah, happy to kick off here. You know, going back to my experience at Weebly and running the AB test, looking at analytical data, looking at the behavioral data, the revenue data, the, we always looked at those data sets to start to help us understand where to dig in. And that's where the qualitative data fit in when we started to notice a trend that perhaps was pricing or unexpected or concerning or maybe something that really warranted additional investigation. And so, you know, why I started the company, Sprig, and earlier this year, we launched an amplitude integration. And so how it works is that you can connect Sprig and get your end product survey replay session replay data actually right in amplitude. And what's interesting is that you can follow that same jobs to be done that I just ran through in your amplitude dashboard. You can see, you know, perhaps that there is a perhaps an increase in signups or some interesting trends in your behavioral data. And now you can have the Sprig survey data that's being collected for in that exact moment attached to that exact same event or session replay recordings and actually then answer the why. And so we've been making an incredible effort this year to integrate with other leading product insights platforms to, like I mentioned earlier, in the conversation, tie all the data together very easily, but also natively for product teams to be able to really kind of understand not only what the users are doing, but in the same even screen also dig in and understand that why question. Yeah, something we've been talking about there is it's kind of like going from the macro to micro and reverse. So whether it's, you know, watching a session replay and then understanding is that representative of a larger trend and how significant should this be or looking at a larger trend and trying to dig in to understand, you know, Colin, you mentioned showing the CEO like a recording of something that somebody is doing to actually contextualize what you're seeing. So really using both ball and quant in reverse with each other to either validate trends, explain the why, and also when you're kind of, you know, seeing something in the quality data understanding if that actually is as big of an issue or if it's more a one-off. So kind of just using them back and forth going from the micro to the macro is something that we talk about internally. Yeah, and just to add on that, like, again, so much great research out today. So if anyone's interested, let me know, I'll share it with you. But as much as we're excited about the adoption of AB testing, it's still hard. And if you look at the programs that get it right or the companies that get it right, they do one thing. They tell stories. They don't just tell stats. And so I think that's where the qualitative data really comes in. It's so helpful. The executives, they are not going to be interested in your 20 slides about, you know, the wonkiness of your product and the quantitative features that are driving X, Y and Z rates. They want to hear a story. And I think the qualitative data is just an excellent way to help you contextualize it and tell that story. So go for stories sometimes over stats. Couldn't agree more.   Moving to a different agenda topic, the future, it is here now with AI. So, and I can't believe our time is coming short. But last question for this panel, how is AI transforming how PMs work with data today and where you see it going in the future? I'll just quickly take that one. I just want to say in anybody listening, like, you know, AI is a tool. So just be mindful of, like, how to use the tool. Don't think it does anything else than other than what you want it to do as a tool. So I think just taking, you know, step backwards and appreciating it for its feature, for its functionality that is, is a great, you know, perspective.  So if you, as a product manager, are looking to like use AI to understand, okay, what's the likelihood that this user is going to do this particular, or engage in this particular behavior, then great, our AI will basically give you that score.  But AI is great at maybe bringing to your attention some opportunities that you can use to exploit, you know, the large robust sets of data. I would say at Amplitude, the way that we're thinking about it in the short term is really about how can AI accelerate time to value around product analytics? So how can we specifically help you with, you know, basically cutting out the manual task of delving through the data, pulling out what it is you should care about when you look at a chart, or even just proactively sharing with you what are the trends and patterns emerging in your data? You know, we already have features around root cause analysis and anomaly detection, but I think sort of the recent advancements here are just going to be able to take that to the next level, where we can really proactively share with you what it is that you should be caring about. I think another interesting application is using data to tell people what questions they should even be asking about their data and helping them sort of train themselves to be better analysts. So those are a couple of the things we're exploring in the short term. But I'd say in the long term, it's like every company to your point call is sitting on this behavioral data and how can we help other companies become the Netflixes of the world and use that to really optimize their product experiences, you know, whether that's onboarding or eventually even the product, the core product itself is definitely where we see things going in the long run. But I think how that interfaces with what the decisions that humans are making versus the technology is definitely to be seen, but definitely the future we're exploring and figuring out how we're a part of now. Yeah. The first person to join me at Sprague actually was a head of AI. So before you even hired an engineer, it was a very experienced senior data scientist. And so we've been working on AI, you know, since day one of the company, it's always been core of the premise knowing that we're going to enable our customers to collect large volumes of data, millions of survey responses per month, actually. And the scale that the company's going to work with, it quickly knew it would quickly become a large data challenge to understand large volumes of data. And, you know, we built all our in-house models with open source tooling. We had human loop with expert researchers reviewing all the output, tuning the models. It was very, very complex and actually a large endeavor particularly for a company, you know, of our stage. But with the advancements, you know, with open AI leading the way, you know, Bard is quickly emerging as well. There's a lot of other players now. The difficulty of implementing AI in a production grade system and even a system at scale has just gone from probably a 10 out of 10 difficulty to around a 2 out of 10 difficulty. And I think the only remaining last mile is how you can actually really QA and test and ensure reproducibility of the AI output. And once that's solved, I think it's going to drop to down to a 1 out of 10 in terms of difficulty. And so I think every, you know, company and product is expected to have AI integrated at some point. I think GitHub coining it co-pilot is probably the best descriptor that I can think of is that as humans, we're looking for a co-pilot that gives us the control but also augments our abilities and augments the work that we're doing to ensure that we're able to, you know, find time to value faster. And so at Sprig, we actually had to make that decision to switch over to, you know, GPT-4 and now we're rolling it out, you know, at a very large scale. And I think for anyone, you know, who is working with large data sets and understanding large data sets, having AI integrated natively into the tool, whether it's chameleon or amplitude or Sprig, is going to be really critical because you will, as a single person or even a team of people, be unable to analyze all the data that you're collecting and those patterns and anomalies. It really is a needle in a haystack. And AI can actually find that needle in that very, very large data set. And so later this month we're making a big announcement around our vision for AI. And I do expect that, you know, any company in the product insights category, but also for all the product managers working on a product, thinking about how AI can actually fit into your own product and be a co-pilot for your end users is going to be paramount for success in the coming years. Awesome. Well, Ryan, Abby, Colin, thanks so much for being with us here and audience. Thank you for being with us here at ProductCon today. Hope you enjoy the rest of your conference and we'll see you soon. Thank you very much. Thanks, everyone.


Biggest news of the day comes out of Cincinnati, Andy Dalton was released Thursday morning. He was due $17.5 million in 2020 and that is no longer the case as the Bengals are moving forward with Joe Burrow as they're starting quarterback. Not that it wasn't pretty evident at this point but Dalton was a candidate to be traded with multiple teams having interest in him supposedly throughout the offseason but now they don't have to deal with that headache anymore the Bengals at least deal with the contract and the money they just decided to move on at this point and just do what's best for the team and probably what's best for Andy Dalton as well and now he has the option of choosing which organization he wants to play for in 2020. So the question is where is it going to land? We believe that Dalton is still a very good player and he can still play in this league and the lack of success that the Bengals had was not on Andy Dalton by any means. I mean probably some here and there but the lack of talent around him had a big factor in him losing his job in 2020 so we narrow down five specific teams that he has a possibility of playing for in 2020. Now if it's up to us we think that he's capable of playing for all 32 teams maybe not as a starter for all 32 teams but he could be a coveted backup and that's what we're going to talk about with these five teams that we're going to mention. Two of these teams are organizations that he could be the potential starter in 2020. Another couple teams are he could be a backup for these teams but more so a coveted backup like a team that desperately needs a backup quarterback and then the last team that we're going to mention is actually a wildcard team which might be kind of crazy but you know I'll get my explanation on why I believe that he's going to land with these five teams so starting off with the first team on this list this isn't in any order this isn't based off of priority in which he's going to land it's just completely random. A team that he has a potential to be a starter for obviously the New England Patriots and this is pretty evident at this point that Dalton has been a topic of interest for the Patriots for some time. Supposedly there were rumors out there during the free agency period that the Patriots were interested in trading for Andy Dalton but nothing came through so the reason why Dalton would be a good fit for the Patriots is because Bill Belichick he's not so much concerned about your physical talent and how much of a natural athlete you are just get the ball out quick just make your quick reads if you're an intelligent guy don't make mistakes you will be good for that offense and that's exactly what Andy Dalton can do for the New England Patriots. Another potential landing spot that we have the Jacksonville Jaguars and this is mainly because Gardner Mitchell is the quarterback other than that you don't really have anyone else you got rid of Nick Foles decided to move on with him if you sign Andy Dalton to a veteran minimum something that James Winston uh accepted for the New Orleans Saints you could bring in a veteran to back up Gardner Mitchell so if Mitchell is your guy and if Jacksonville has nothing but all the trust in the world for Gardner Mitchell cool go ahead and start him but the moment that he starts to fail Dalton would be uh phenomenal for the Jaguars if they were to get him not only that but from 2011 to 2013 the offensive coordinator for the Cincinnati Bengals when Marvin Lewis was the head coach was Jay Gruden and currently the offensive coordinator for the Jacksonville Jaguars is Jay Gruden so it makes a lot of sense uh for Dalton to come in and potentially compete with Gardner Mitchell for that starting job so the next two teams that we're going to mention are spots where he could be a coveted backup in the NFL like we mentioned earlier he could be a backup for all 32 teams in the NFL well 31 since the Bengals got rid of them but a coveted backup means that a team that was in desperate and desperate need of a backup quarterback as shown in 2019 and the first team that we want to mention the New York Jets because they need a backup quarterback pretty bad who do I think is better Sam Darnold or Andy Dalton I don't know that's for you guys to decide but I think that they're dead set and starting Sam Darnold Dalton's not going to take his job but if you look at the time that Darnold was out with Mono 0 and 3 record with Trevor Simeon and Luke Falk starting those games so they need some depth at that quarterback position and Dalton could be the guy that comes in just like in 2018 Josh McCown was that veteran that helped out Sam Darnold and was that an insurance policy Dalton could be that same guy for the New York Jets and if Darnold were to ever get hurt who knows Dalton could come in and do some pretty good things the fourth team that we want to mention another team where he would be a coveted backup the Pittsburgh Steelers I mean you look at Mason Rudolph you look at Devlin Hodges when Big Ben came out and they came in they didn't really do much with that offense so Dalton coming in with the experience that he has a smart intelligent mind can be a good backup for Ben Rothesberger now Ben Rothesberger is in his late 30s Dalton more so in his early 30s so not that far apart in age difference but you're not really taking a quarterback to be your future of the franchise you're taking a quarterback that can step in once Big Ben were to get hurt but if you look at the history the injury history of Ben Rothesberger three out of the last five seasons he hasn't completed all 16 games so bringing in Dalton for Mike Tomlin would be huge for some depth at quarterback the last team that we're going to mention is it's a wild card team and it's probably not going to happen so don't get upset with me mentioning this but I just wanted to have some fun and make your heads turn make you guys think a little bit like what if Andy Dalton were to get signed by the Dallas Cowboys that's pretty wild to think but let me explain so the Cowboys have had a lot of contract disputes with Dak Prescott I mean you signed Ezekiel Elliott your franchise running back you signed a franchise wide receiver and Amar Cooper both those guys to a long-term deal what's the hesitation with Dak Prescott phenomenal season in 2019 he's proved that he can stay healthy on the field started all 16 games in his career but the thing is these just haven't settled on an agreement is it 30 million 40 million 34.5 million a year we just don't know yet so if I were Jerry Jones I would just sign Dak Prescott and not even think about Andy Dalton I think Prescott is my franchise quarterback but I'm not Jerry Jones and I don't know what he's thinking and I think maybe if I had to guess what he was thinking I think it's going to cross his mind that Andy Dalton could be a quarterback in Dallas if it's taken you this long to to crunch the numbers and come out with a deal for Dak Prescott what makes you think that they're just hesitant to resigning him because they're not sure if he's going to be the franchise quarterback it's wild and like I said it probably would never happen but it's just fun to think about but definitely leave your thoughts in your comments down below what do you think Andy Dalton is landing in 2020 comment interact with us and let us know your thoughts


The following is a presentation of TFNN. The TFNN Bull Bear Trading Hour. Every trading day, live at 10 a.m. Eastern. Call now, toll free at<PHONE_NUMBER> or internationally at<PHONE_NUMBER>. The TFNN Bull Bear Trading Hour. Now, Tom Antt, Tommy O'Brien. Welcome folks, appreciate you growl and a problem with us out here. We have the Dow Industries up 139, NASDAQ up 71, S&P's up 25, Gold Contract down $12.40 at $15.07. You get Silver down 30 cents, $16.89. Light Sweet Crude up a buck, $52.23 a barrel. Notes and bonds, you get the 10-year down 19-six, $129.17, the 30-year down a full point, plus 25 ticks, $160.14. Now the 30-year folks did the full ABC structure on the way up, so it hit the first price projection. You're backing down with a light volume, these things still want a higher price, lower yield. King Dollar, King Dollar up 95 ticks, trading 97.440. That's gonna need more volume to go lower. Bottom line, you get a sideways move out there yesterday, no sellers, no buyers out here yesterday. Euro, Euro's at 111, the end is at 106, and the pound is trading out here at 121 to one U.S. dollar. Let's go over to our man, Mr. Kevin Hinks, at TD Ameritrade Think of Swim, as we do every Tuesday, Wednesday, and Thursday. And don't forget folks, if you wanna see, have a great program, understand option, option strategies, futures, every trading day right here, 11 to 12, Eastern Standard Time. If you haven't test driven yet, the Think of Swim platform, come over to our website, hit that banner, bring it up, they'll allow you to trade with paper money, outstanding professional platform. Kevin Hinks, what's going on? Good morning, Tom, you know, these are, this is the, you know, the day after you get a big move in the market, both down and then back up, it's always interesting to watch how the dust settles. Isn't it? Right, and if we start to return to fundamentals, like for instance, the dollar's stronger, so gold is down pretty hard today. Things like that, I mean, I think the recovery, or not recovery, but the, you know, the little sell-off we're having in the bonds here, you're probably right, it's probably very hesitant, and I'm not on very big volume, because I think there's not a lot of people wanna make a lot of bets up at this level. So, but I think the next couple of days, and some of the data, PPI out Friday, we get CPI not till Tuesday morning of next week, and that'll give us, you know, that's the first time we'll see some data in a couple of days, that'll give us something to trade off, especially in the inflation area. Sure, and you know, folks, if you had listened to Kevin Tommy and myself yesterday, you know, we had a nerve, there's no doubt saying that, yeah, we're gonna have a bounce down to 28, 23 when the market was getting trashed, and it's just so interesting, we were talking about trading markets, Kevin, and this is the ultimate in a trading market.  Right, I mean, you know, there's a lot of green on the board today, and a lot of things are going back to some of the fundamentals.  The fact that that's bouncing back, I like the fact that some of it, I'm looking at some stocks here, it looks like all of the, well, it looks like Amazon's pretty much unchanged, but four of the five fang stocks are up on the day-to-day. Obviously, the NASDAQ's gonna be the most, we're, you know, responsive because of the beta of some of those names, but you know what I'm gonna watch today? I'm gonna watch the financials, and how that affects the Russell, because with yields, you know, solidly firmer from where they were yesterday, I'm gonna see what that dealt to the banks and the financials, see if we get any bouts here, because some of them were pretty beat up the last couple of days. You make a great point, Kevin, because you know what, I hadn't seen that yesterday, and then when I was driving home, I was listening to Bloomberg last night, and they were talking about that, and I just brought JP Morgan up, and this is very unusual, folks. I mean, you know, you're talking about one of the premier banks four days ago was at 116, and the problem is, is that that went into 105, which was going into the last swing point, with sellers, you know, we're talking about, there's some sellers out there, and that's interesting, man, and I guess, fundamentally, it does make sense, meaning that, you know, those rates are so inexpensive, but, man, if I was born again, man, I think I'd be born a banker. You know what, you know what, even better? Insurance. You know what? My father told me, insurance is definitely it. Absolutely.  It's true. You know what Warren Buffett made, is the most of his money, insurance. Yeah, yeah. Collecting, and the parallels between option trading and insurance, unbelievable, right? You're collecting premiums or paying them, and you're either paying it out or not paying it out. Yeah, that's a very supreme thing. The correlation is strong. It is strong. It is, that's so cool, man, it's so true, yeah. Forget being a banker. I'd have a tough time being a banker anyway. Yeah, right. Hey, hey, you know what? If you're good at insurance, you'll use bankers for the other way. Yeah, yeah. For storing your money. Yeah, right. Oh my God, I'm telling you, man. But you know what we're gonna talk about today? We're gonna look at, number one, we're gonna look at Uber, that's got earnings after the bell, and we're gonna cover how, ooh, I'll lift trade yesterday, but then we're gonna take a look at something that I've been kind of not pounded for for a couple of days here, and that's Boeing. We're gonna take a hard look at Boeing, because if you look at the news filter on Boeing, you're starting to get some drips of some, you're starting to have workshops with pilots, and Chinese pilots, which tells me, I think they're getting closer and closer to getting this 737 MAX fixed in the air, because if they're having workshops, that means they're retraining pilots with some of the things in. So we're gonna look at Boeing today, we're gonna look at some, a long-term bullish strategy in Boeing, and a way to do it for less expensive, I mean, Boeing trades $330, we're gonna look at a way to trade it for much less than buying 100 shares of stock and trading and spending $33,000. I just, I had seen that headline too, I think, was it Chinese pilots, Kevin, right? Yes, they're doing workshops with them to kind of re-teach them, which tells me that they're starting to get close on some of these updates. I agree, man, because I said to myself, just I said, you know, there's a lot of hysteria in the U.S. press, right? I don't know what it's like in the Chinese press, and if Boeing's just cool with China, and they start putting planes, the MAX back in there, and maybe we're in a little bit of a bubble here and hearing all the Boeing news, and guess what, of course. And guys, think about this. Boeing had a flight safety issue. What's the difference between that and a food safety issue, like Chipotle had? Right, and when they get through that, and time passes, and safety, and confidence returns, you know, these stocks are beat up pretty big, just like Chipotle was beat up pretty bad, and maybe it's somewhere where we can find some value. I still think they're gonna have to rename that plane at least in the U.S. or something. I don't know, we'll see what happens. And they can. They can. Oh, overnight, they'll just call a different name.  Just so you don't have to say, everyone knows the 737 MAX, that's gotta go out of the vocabulary, I think. You might have something near Tommy, and perception is reality, right? It is. We know that. That would be enough with time, like you say, enough. You know, it's interesting, you can go like, between the Chipotle and Boeing, right? My take would be, you know, that Chipotle may not have come back, okay? Well, Boeing's gonna come back. And that's my own perception now, do you know what I mean? But Chipotle could have went away, Boeing, a duopoly with, they can't go away. They can't go away. It's not gonna happen. The world needs them. We need them in the country. I agree, and they may also make some comments on their defense, part of their business, it's very strong, so we're gonna look at it today and take a good hard look at it. 45 minutes, right from now, folks. Kevin, you have a great one, a safe one, of course, have a great weekend. We look forward to speaking there next Tuesday. Great talking to you guys, have a good day. You too, Kevin. Stay right there, folks. Tom and I are coming right back to you with our 1.41. Now it's like a 76, that's a piece of 27. Come right back. If you're not currently using the TAS Profile Scanner when looking at setting up your trading opportunities, then your arsenal is short a mighty weapon. 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Call now toll free at 1-877-927-6648 internationally at<PHONE_NUMBER>. Welcome back folks. Dow. Dow is up 141. You get the next second 79. S&P is up 27. Let's go to AMD. So this is quite news out here this morning. AMD up 10% right now. Not bad. Yeah. And then the news here folks is that they, they're claiming, well they, they're not just claiming I'm sure it's probably true that they had chips now for the server business is faster than Intel's. Yeah. And they got an order evidently from Google. So let's see advanced micro spike on Thursday after unveil the new server processor that said it performed better than the cheaper and is cheaper than products from Intel. Analysts are positive on the potential AMD chip. And I know there was so better chips, cheaper chips. Yeah. If that's the case, watch out. In the server market. In the server market. So that's, that's quite a, that's. And yeah, Intel, I think it's at down 1.8%. So I don't know when, I don't know when that was written though, we'll see where. So it's paired some of those losses, but quite a move for AMD, AMD mammoth company too. It's only trading at 23 bucks. Can you go into AMD for a sec there market cap because this is where the skew of like, you know, what the price of an equity, yeah, $35 billion company, even though it's only trading at $32 versus, you know, you have some companies trading at $400 that are still $30 billion companies. Sure. Yeah, sure. Kraft Heinz. So let's get over to Kraft Heinz, okay? You said middle of the shopping. Middle of the shopping. People are not going in it. Still going a little bit. Just know what they used to. We pull up still a mammoth company, $30 something billion dollars in revenue a year. This is a one-way trip. I mean, look at the surprises, man. Every time it's like. 2017, you're at $87, you're at 26. That's bananas. And because they renamed this, you know, they didn't rename it, but bottom line is that it's not trading by itself because they kicked it out of a Montalise. Okay. You know, they separated. Montalise, yeah.  It's, well, 26.96 year, 26.87. Just broke a swing. Pretty remarkable, man. I'm guessing that was their last earnings before that. Yeah. And despite, in February. And when you actually look at it, the revenue fundamentally, it looks pretty. That's, I mean, they're a $32 billion company. Look at those earnings. Yeah. But you have seen a decline, right? Zero, not even zero growth. You're losing almost $2 billion in revenue. But we're going to see some growth maybe next year. And earnings, they're still making money. You know, you got a company pulling in $26 billion a year. Yeah. They're making profits. Yeah, it looks like, actually, when we look at this, it looks like cheese and dairy is still growing. This, they're claiming it is anyway, by 23% over a three-year period. Yeah, I know. Ambient meats. What are ambient meats? Is that cut up meats, probably? I'm not sure. Maybe it could be processed meats. Yeah. That's grown by 11%. Frozen and chilled. Meatballs, really. That specific? Check this out, folks. Now this, oh man, if that, if the meatball business is a $2.5 billion business, they get this, if you're in the car and the beautiful West Coast of the United States right now, folks, that we're reading this product segments. And they have frozen and chilled meatballs at $2.5 billion in revenue. It's possible, man. Maybe they own Mama Mia's and, you know, those ads we always hear. I think that's exactly what it has to be. I'm trying to click on it for more info. It's not letting me. But yeah, $2.5 billion and still growing at 5% for every three years. It's not often that you see these product segments be so precise. I know. Maybe it is something that's very particular, pretty remarkable. Mama Mancini's, man. Right? I mean, just a mammoth company still, you know, but, man, 52 week lows, like you said, and yeah, we'll see. Now the other side of that, Roku, right? So get out of the processed food business, get into the streaming business. Get into the streaming business. So this Roku here. Not bad, up about 20% right now. It's easy to calculate percentages. When it closes at 100, it's up 20 bucks. Yeah. And look at those numbers. Look at the revenue folks, okay? So 2015, they did 319 million. Yeah. Million. Yeah. This year, 1.1 billion. Yeah. And what's a, even remarkable, last year they did 742. They're gonna double it in two years to 1.4. That's 100% growth from 2018. And keeping in mind, I was saying to you, we can go into the news for them. I don't understand. What are they gonna make any money though? Well yeah, and they'll lose the money, right? So let's see. Where were we? This one. We couldn't find the revenue growth. That didn't have the revenue growth, didn't it? Yeah, this has all the analysts and what they're saying.  Second straight quarter, where they achieved a trifecta in terms of growing the accounts, hours and average revenue per a user too. That's right. I'll try and dig down to it. Yeah, that's the one. All right, we'll try and find it, but. Cause I saw, I think the average revenue went up like $2 from $21 to $23. That's huge, as you're adding all these people. And is it Roku, so do they charge? This is what I don't understand, to be fair. Why you pay for Roku, I just don't understand. I haven't dug into it myself. In terms of, you know, to have a streaming platform, I know you can buy a Roku box, right? It's kind of like an Apple TV, it's like something that makes sense, but I don't get what, I don't have a fundamental aspect of what they provide for their subscription service. So they must have access to some type of content or so forth. If you're out there, you know what they do? Give us a call,<PHONE_NUMBER>. Seriously, if you got a Roku and you understand it, because that's a lot of money. $23 per person went in reality. It's a lot of money if you're just talking a clicker. Yeah, access to an online platform. I have a smart TV, so I don't even need a Roku box. I can get access to, and then I pay for Netflix, then I pay for Prime, so maybe half. So if we go to the 10-year note folks, you're gonna see both of these, we'll do the 10-year and the 30-year. Bottom line, you can see, 10-year got to 130, 27 yesterday. 2.9 million, guess what? You're backing down with 1.1, you're going into 2.6, you're not gonna do more volume than that. So you're backing down with light volume. The 30 did the full ABC structure up. The price projection was 163, like 20 or something. We did 163.31. Pretty remarkable, and now more than three full points in that 30-year from where we were yesterday. And look at the anemic volume, though. Guess what, you're 244,000, you're going into 4.95, that'll do 400 today, probably. That's, to me, that's a natural retracement, though, and a market that still wants higher price. And I tell you what, let's take a look at natural gas real quick. We're coming up to natural gas inventory numbers. Jump over here, get in the commodities, see how we're trading this natural gas, where we've been at. I haven't taken a look in a while. Seriously. 210, we're sitting at. Cheap natural gas, that's for sure, man. So a little bit of volatility even this morning, man. 8 a.m., we're up there at about 213, so we're trading down to 210. This is yesterday's action, anywhere from about 214 to 208, putting this on a little bit of a longer-term timeframe.  We made it up as high as about 230. So we're gonna take a break in about 30 seconds, and we'll come back with those natural gas numbers right at 1030 on the dot. But that's a lot of volatility, man. It is. The market, of course, tremendous volatility. It seems like everything in the beginning of August, man. You want volatility so much for summer trading in August. 232 down to 204, 30 pennies in the span of four or five days. That's 3,000 a contract, folks. Amazing, right? 3,000 a contract. So that natural gas, we say it on natural gas. Have some defined risk, man. And you know, to go back to Kraft for a second, yes, Buffett still is the huge position in Kraft. We had a question there, in fact, I'll get you. Exactly. Ph.D.C. Hold on a moment. So Kraft's at 26.59, and Berkshire owns 26.7% of it, or 325 million shares with NM. That's a $1.5 billion loss today. That's a hit. That's it. Thank God it's an insurance business. Stay right there, folks. Come right back. Hi, folks. Tom O'Brien here. If you'd like to get my daily newsletter and market insights, then now is a great time to sign up for a 30-day free trial. Every morning, by 9.30, I send out my morning letter to subscribers with market commentary on a variety of markets, currencies, and commodities to keep investors up to date on the day's trading action. Included in Market Insights are specific buy and sell recommendations for stocks, ETFs, and even options, which stops and price targets included for every trade in my newsletter. If you'd like to try my newsletter at risk-free for 30 days, then head over to the front page of TFNN and you'll find Market Insights under Trading Newsletters. I use my years of trading experience to bisect and dissect the market every morning and give my subscribers the most important information they need to know for the day ahead. I even issue afternoon updates for my subscribers whenever warranted with important market action. I'm always scouring the market for the next great trading opportunity. 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The Art of Timing the Trade Chart is designed to help you when scouring the markets for stocks just beginning to form the trading patterns that many investors spend days, weeks, or even months searching to find. And right now, we're offering licenses available at only $79 a month. We are so confident that you're gonna love this new charting software that will even give you a 30-day, unconditional money-back guarantee. Don't miss out on this incredible new piece of software. Get your copy of the Art of Timing the Trade Chart today by visiting TFNN.com. This segment is brought to you by Think or Swim. For more information, just click the Think or Swim banner on the front page of TFNN.com. Folks, so, let's see, Natural Gas Stockpiles Road 55 BCF. So I wonder what we're looking for. Looks like about 60. Okay. So a little bit under that price level, we'll jump back to the chart. Where are we at? Come on, cooperate. It's not coming up. Oh, there we go. Let's pull it over. And Natural Gas, spiking a little bit higher. Looks relatively calm on this chart, but we just went from 209 up to 213.40. Oh, this is an hourly that I had. Remember, I jumped back to it and I was like, why is that look so calm? Yeah, it doesn't look so calm no more. Quite a little jump, going from about 210 to 213, it would make sense. Only at 55 billion cubic feet, Mark was looking for 60 less supply, higher prices, right? But we'll see, we were just at 230 a few days ago, so we'll keep our eye on that contract. Let's go to Zillow. So Zillow's getting smacked this morning. Big time, folks, you're down 20%, down $8.90, you're trading at 40.85. 21% short-percent interest, some happy shorts out there today. I wonder what the expected move was. I bet it was a big number though, look at that chart. Man, you know, yeah, Zillow... Because look at what it did last, I bet that's last year, maybe not, yeah. Some of those earnings moving huge, so I bet that... So Zillow, this can get down to what, $33 pretty easy. So here's the news, right? We were talking about this the last time they came out with numbers because it's blowing my mind that a lot of big companies are trying to get into this, folks, but the thing that's pretty amazing, just we're gonna take the CEO's word on this, and this is where I think this... They're gonna have a hard time making money in this business. So the top of it says Zillow shares fall after forecasting home-flipping losses. And then CEO Barton sees 45% profit from Zillow offers at scale. That's not enough money to, you know, if they think they can do 45% without making the mistakes in a business that you're talking about from 200 to 300 to $400,000 in houses, it's like, that's so tiny. Yeah, all I would say is that number is probably the calculation with the mistakes in it. As in you're making six to seven to 8%, and you know that there's gonna be, when you're flipping that many houses, it's just an average rate of how many you're gonna have all hell break loose, right? As you try and do it for sure. So they lost 14%... The shares fell, right? The shares fell. As they forecast that new home-flipping business would lose as much as 80 million in the third quarter. Overall, the home-search companies were protecting the third quarter, EBITDA between $18 million lost and a $2 million gain. That sounds pretty cool. So here, the company generated 249 million in second quarter revenue from Zillow offers. An algorithm-driven spin at home-flipping, right? Yeah, and received requests from 70,000 consumers who wanted to sell their homes to Zillow over the internet. Chief Executive Richard Barton said in an interview that the revenue growth from Zillow offers show that the business is working, it's being driven by people who want an easy, convenient, hassle-free way to sell a home. He said, we're far from being at what I would call scale. I'm confident that when we get to scale, we'll be able to do four to 5% profit off of this business. Going forward, Zillow will need to show that it can turn a profit in the capital-intensive low-margin business of flipping homes. Consumers are willing to sell their homes at a small discount exchange for speed and certainly selling your home over the internet when fees rise too far beyond what traditional brokers charge. Sellers in return, sellers return to the old methods. So let's bet it. When fees rise too far beyond what traditional brokers charge, sellers return to the old methods. Saying that those fees are gonna be important. They cut into it. Yeah. And I think they're saying they're gonna keep them small, but they're gonna be able to do big numbers, they're thinking, because they're gonna get a process in place that can just be really quick and people will be able to be willing to sell them their house for a little bit less money than they know they could get if you put it on the market and you wait three to six months to nine months, right? Yes. You try and get it. No, I agree with that portion of it. That portion of it I agree with where the problem comes in is that now you have the house, then you're gonna fix the house up and move the house out the other side. Sure. And so what they have been doing, this is how they commit to the losses because I've seen how they do it, and this is public information. Yep. What happens?  And yeah, you're happy. Are you Zillow in this? Yeah, I'm Zillow. You think it's worth 105 grand, right? I get in, the Zillow, we put 10 grand into it. Sure, right. We're at 115, right? The Zillow says, okay, I want 124 for it, right? They put it out at 124. If that thing doesn't sell like, basically a couple of weeks, right? They just bring it right down and then they'll take a loss immediately. Yeah. So that's pretty intense. I think it's, we'll see where it goes, but I think it'll, I think it's gonna keep the real estate market having a bid. That's the cool thing about it. Okay. Meaning the cities that they're in doing this already. Yes. That is competition for anyone buying houses. Sure, and it's straight liquidity. Yeah. Now the counter would be, as a holder of Zillow, the last thing you would actually want, I think, is if you're employing the strategy like Zillow is, is to start just building and holding every house as you're saying that they, they're not getting the price they want. Well, just move it out at the price that the market's at, okay? Don't tell me what you think it's at. Yeah. And tell me that you're gonna keep it at that price for a year or two, because guess what? You ever hit a real downturn, that company could go bankrupt. So I, at least they're actively, they wanna flip them. They don't wanna be real estate investors in the plan that you're talking about. Yeah. So they get them in and they get them out at whatever the price that market's putting on them in two to four weeks or whatever it is, right? Because if they don't have that price, then that means that the price is below where they're saying it is, okay? The market doesn't lie, man. If you can't sell that at the market, guess what? That's not the market price, because if it was the market price, it would sell at that market, you know?  So if you ever had that downturn and they said, ah, we don't wanna sell at this price, we're gonna hold every property we have. It wouldn't take long to empty out that company's coffers. No, no, wait a minute. Well, it won't take long to go keep losing money if they buy and sell them at losses either. That's for sure, yeah.<PHONE_NUMBER>. Let's go take a look at the XAU. Actually, let's go look at Nugget and, because, you know, the rest of the way I got those calls and look at it, it's hanging up here, man. Yeah? It's still doing good. I mean, Gold's still at, what, $150, $150? Yeah, no, it's, you know, for, you know, Nugget got the 41 and 90 yesterday. You're 38 to 28 right now. Yeah. You're pulling back with light volume. This is pretty cool. How about now, can we jump? We had a call, Newmont. Newmont. I was talking to a client this morning, was asking you, maybe if you could take a look at Newmont. Yeah. They said they were maybe in it, looking for a price target or where it could maybe jump, an upside projection of where maybe you could look to sell as it's near those highs. Let's take a look. So, oh, this is nice.  Yesterday, 15.8 million, 39. I love it when it pushes swing points with volume. That's saying that you have more people coming in, hasn't broken the high yet, you are pushing with volume, which is really positive. And now what's gonna happen is that you're backing down a little, so you're gonna be able to see it, I'll be backing down with light volume, which is pretty cool.  Yeah, no, you know, Newmont wants to run this 44 bucks. So maybe that's a projection if you're in there to look at that. Yeah, it's the, and on a lot of these folks, it's the highs of August of 2016. That's what they're trying to run into. Yeah. I know, and that's a big number, man. They're so cool about that, is that, guess what? If you look at that run, we've had, from January to August, this run started, you know, realistically, you can bring it all the way back to October, but yeah, that run started at a much higher level. We're gonna be right back. 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Dow Industries of 174, you get the Nasdaq up 100, S&Ps are up 32, and you get a good bounce going here. And bottom line, what I expect we'll see here folks, is that you're going to get a contraction of volume out here today. What you had yesterday is this. So picture what you had. We had come down hard. Yesterday, you came down hard. You basically almost got to the lows and it gave it up on energy. We went 140 million shares and to 178. So it's like, okay, you know, you can't get below that low. Now the key is going to be, as we go higher, are you going to see that contraction? My take is we are, and guess what, this could get really deviant and get all the way up to 295. If that's what we get, if we get a contraction all the way up there, that's going to be a nice sell. Because my take is that there's a much larger ABC structure on the way down. Now that's a 0.618 retracement. So if you got there, that werely would be deviant because that would be saying that, you know, you wouldn't take out the low the next time down. We'll see how we can handle the bar in the middle versus 0.618, which is not that much higher than we are. It's about three points higher. What's the high? Maybe that guy over there? Down to the low. Yeah, so right in there, 294.39, kind of the low of August 1st to right around that area of the low of the 31st. And then the other one to watch is kind of like where we are right now. I think, yeah, 291, where's that? 291.97 is a 50. I suspect we're going to get, yeah, 293 is game. You know, we'll see how that, today's Thursday, right? It is. This can run, right? Twenty a time, I say it seriously. Exactly. Today you get tomorrow, and if that's what you see, then you get some action. And I heard you talking about the VIX on the news update. Yeah, we're going back to a nine VIX, man. They crushed that. We're going back to a nine in no time. That was quick, man. Seriously. It's always quick. It is. Wow.  You get the Dow off like 600, 800, a thousand points. The VIX is going up and then boom, by the next day everything's forget that happens. Seriously. You know, the strength, the weakness inside the Dow industrial, VISA is putting 21, positive Apple 16, Chevron 16, that, let's go back to the banks a second. This is serious business. Kevin Hicks brought this up. This is telling me that the banks very well could be some of the first ones, folks, that actually get down to the December lows that I'm looking at the S&P to go to, because what you had out here yesterday is that this was, you had some real volume coming into this last swing point. Look at, you know, the last swing point May, $140, $10.9 million. Well, JP Morgan has 17.3. Big number. You know, that's some selling. And now you get the big contraction out here today. Yeah. Bank of America, BAC. Let's take a look at BAC. And it is remarkable. We just had the 10-year go from 3.2 down to 1.59. Ouch, man. Ouch. Seriously. And Bank of America, let's see. That's 76 million. Yeah, there's more selling versus 50. And I mean, look at that drop just from over 31, 3106 down to what is low, 2712. Right. He's talking about $3. He's talking about 10% haircut in a bank. Banks are not supposed to have 10% of swings in a week. Yeah. When, when nothing individual has happened to that bank. Right. It's just an economy rate story. Okay, here it is. This is beautiful. I love it. Berkshire Hathaway already broke it. So that broke its swing point with volume. This is a big one. So Berkshire, yeah, same number. You know, Berks, look at this. Okay. So this is pretty cool. So Berkshire very well is leading the posse down. Okay. So, what is that over there? That's interesting. So December 2017 we're at the same price. Berkshire is going to go after a bottomless consolidation, which is 186. Yeah. Now that would make sense. You know, they're a monster. There's no doubt about that. And they make a fortune on the insurance. There's no doubt. But, you know, that's a portfolio too. So, if the portfolio, if the market's moving down, it's really a portfolio that you're talking about inside of that. And I wonder if service and retailing, I wonder if Kraft falls into that category. I wonder how that shakes out. But 70... I'd say would, yeah.  Railroads and energy. And the energy. Yeah. Yeah. Pretty well. 500 billion dollar company. Conglomerate. Oh, yeah. Not bad. Let's check back on natural gas. You know, that market's reacting. A little bit of a pop. We got that initial thrust right up to almost 214. Paired it a bit. We're sitting at 210, almost as we came into those inventory numbers. So the market jumping around a bit. But in the context even where we were yesterday, we saw that type of action. We were up to the upper bound, kind of right where we spiked to. Pretty cheap natural gas across the board, man. Continuous. Yep. We got plenty of natural gas as we were saying last week. Oh, it seems like it could get even cheaper. It's been there for so long. I mean, it's so wild. Yeah, it has. So some of the higher volume equities out here, what do we got? What's sticking out? Well, we are talking about Zillow. You know what? Let's jump to Uber. Oh, yeah.  We had... Actually, we'll jump to a few. So we had lift earnings, right? Lift up. We had a date initially on that chart on the numbers last night. A quick reaction. You get the conference call at 5 p.m. eastern time last night. We made it back to 65. We're trading at 62, 61 right now on lift with their earnings. We got Uber after the bell. Trading up 6%, probably on whatever Lyft was talking about in terms of the market for rideshares doing well. They're all going to benefit. Get into the Analyze tab. We'll pull up Uber. Now, this is going to have some volatility, I bet. Yeah. One day expected move. $3.37. That is a mammoth move when you're talking about only a $42 stock. $4.20 would be 10%, right? So you're talking about 6%, 7% move on those numbers. We'll see where we get out. I'm sure they're going to expect some mammoth numbers in terms of what they do. And you know what Uber did, too? Yeah, jump into that. What they did is that they... They... They have a 6.1 billion Dutch weapons to avoid taxes. So what they did, folks, is that they... They have a 6.1 billion Dutch weapons to avoid taxes. So what they did, folks, is that they... They have a 6.1 billion Dutch weapons to avoid taxes. So what they did, folks, is that they took their URL, Uber. Okay. And they decided that it's worth 6.1 billion, and they stuffed it inside a company in the Netherlands. Amazing. Before they went public. And so they have to make that back up first. That's true. Let's go to our man, John, in Detroit. What's happening, brother? Hey, how are you guys doing today? Great, man. You're fantastic, right? I'm sorry, what?  So what they did, folks, is that they took their URL, Uber. Okay. And they decided that it's worth 6.1 billion. They're doing fantastic today. We're having a good time. Hey, man. How are you? Hey, I love your show. You know, I heard Carlos talking yesterday when he called in, and he was complimenting Tommy. I never like to be a brown noser, but it was nice to hear someone call in. I was watching your son when he was in with Basil. You were not there. Okay, cool. And Basil was going over a chart, and Tommy said, stop Basil. Wait a minute. What about this, this, and that? And Basil had to go back and say, oh, yeah, wait a minute. Tommy was right on top of everything. He knows everything that these guys are doing, whichever ones they are, that's filling for you. That's awesome. It's time to go back to Tommy. Thanks for listening, man, and we got some great collars, man, out there that would help make the show, man, like yourself. Right. So I really appreciate it, man. Thank you. So thank you very much. Hey, I wanted to ask if you could help me. I want to take a position in Silver Futures and in Gold Futures so if you could look at the Silver Futures. And I've been watching it since yesterday looking for a point to get in. I've been wanting to get in for about a month now, but just waiting for a breakout over that, you know, and the gold, I think it was like around 1487, 1488. Stay right there, John. We'll be coming right back. We'll be coming right back, folks. Down to 173. Now it's 106. S&P's up 33. Come right back. I'm certain you are or strive to be one of the best of the best at everything you do in life. It's the most common trait that we tigers and tigers share. If you're looking to become the best of the best when it comes to managing your money, let me teach you to do what most wealth managers tell you can't be done, which is how to time the markets. 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For more information, just click the Think or Swim banner on the front page of TFNN.com. Detroit, we're talking gold and silver. So this is a tough one, John, because, you know, this run has been pretty incredible, you know, and the gold and silver market.  If it pop back to 1460, yeah. And, you know, it's in an ABC structure on the way up, a confirmed ABC structure on the way up, with a 1575 to 1580 price projection. We almost got there. Yes. We'll get to 1530. We have a lot of room. No, I'm just, yeah, I'm seeing we're still close to that from where we've been, right, in terms of, as in the risk reward, you get the highest 1522 and projection 1575, and you just ran from 1200. Right. And so what you're hearing from me in the future market, this is a tough buy right here, do you know what I mean? If you were in, it'd be a different situation. Silver, same thing. Silver's even more dangerous, man. I mean, it is. It's been quite a run on this.  We were talking about the break, you know, it's tough. Silver's down 31 cents.  So just even the lower extra. Yeah, it'd be the breakout area. I mean, if you can get back into the breakout area with light volume, that's beautiful, man. Because the problem in the middle where we are, it's like where do you put the stop? You know, you don't have anything behind you. So you need some kind of a floor that is traded there for at least, you know, in the best case the breakout area is always a nice area. If it comes back with light of volume and you get a rejection, you know. Cooking. Brother John. Thanks so much for the call. Appreciate the insight. Okay, man. Have a great one. Have a great one on Detroit, man. Stay right there. Folks, we got out mams to Kevin Hanks, TD Ameritrade to think of swim coming up next. And we got out mams to the Basil Chapman Steve Rhodes, Dave Whiteby, back this afternoon. Thanks, pal. Thanks, man. Oh, yeah.