I'm a huge nerd and pretty much write and make videos about things that I find interesting. I'm curious about the world and feel like sometimes I'm interested in some ridiculous topics. With that being said, I was extremely surprised how many of you enjoyed my last video about why the Danny Gonzales TikTok song didn't go viral. Aside from analyzing human behavior and the psyche, I like trying to figure out why things did or didn't happen, so I'm extremely grateful that so many of you are inquisitive as well. With this video, I don't mean to milk the Danny Gonzales TikTok song topic, but this is something that was on my mind throughout watching his video. While watching Danny's video, I just kept thinking, there are so many things wrong with this experiment. I debated on discussing it in my last video, but I figured that'd make it way too long. I love that Danny goes out of his comfort zone and tries new things, and I think that's one of the reasons why he's one of the best YouTubers on the platform right now. It's easy to see that Danny has a curious mind and it's great to see him experiment. So I'm hoping that if Danny sees this, it will help him improve his method for the next experiment. But more importantly, I hope it helps all of you think a little bit more critically about how we conduct experiments to get a little closer to the truth. Scientific literacy is extremely important in this day and age. We're constantly flooded with clickbait headlines that say things like, New study shows breathing air cures cancer, or how drinking a gallon of mayonnaise can extend your life by three and a half years. Yes, I know those examples were exaggerated, but you know what I mean. In a world where people are fighting to get our clicks rather than deliver us the truth, I feel it's important that we understand what a good experiment looks like. Each day, we put our trust in politicians, doctors, and others who tell us about studies. Too often we succumb to confirmation bias while neglecting all of the flaws in the study that we're being informed about. Up until this year, I didn't know how to independently think about different studies and the information I was receiving. So I made it a personal goal to better understand how studies are done and what separates good science from bad science. I'm also extremely fascinated how people can fall for conspiracy theories. So I was able to scratch all of these itches of curiosity with some great books. Some of the books that really helped me better understand the scientific method and good versus bad studies are The Skeptic Sky to the Universe, Science Fictions, and Calling BS. While I personally find this topic extremely interesting, I know learning about scientific studies and research can be pretty boring for some. So this is why I love nerding out by taking pop culture topics like the Danny Gonzalez TikTok song to help people better understand these sometimes boring topics. So in this video, we're going to pretend that Danny hired us to help him make a viral TikTok song. Hopefully by the end, Danny and the rest of us can improve our experimenting process. First, we're going to take a look at some of the research questions we'd want to answer as Danny when trying to make a TikTok song go viral and then we'll form our hypothesis. After that, it's time to scrutinize our hypothesis and variables to try and make sure we're not missing anything with our process. Finally, we'll put it all together to see what a proper experiment would look like as well as some limitations we may face while running it. But before we get started, if you're new to the Rewired Soul, make sure you subscribe and ring that notification bell. Here, we use critical thinking and practice skepticism to better understand the world and improve our overall well-being. And if you're interested in any of the books that I mentioned, the affiliate links are always listed down in the description below. Every experiment should have a goal and most experiments start with a question. Sometimes our questions are too broad or too vague, so it's important to sit down and really see what we want to accomplish with this experiment. We want to help Danny make his TikTok song go viral, but what kind of research will we be doing? The two primary types of studies are quantitative and qualitative. Qualitative studies are often used in psychology, but they're much harder to properly analyze because some of the data is based on subjective experience. With quantitative research, we're looking at numbers. Since we're trying to make a TikTok song go viral, we're going to have clear metrics we can look at, but there may be some additional subjective factors, so it'll be both qualitative and quantitative. Next, we need to narrow this down a bit. What are we going to do? What do we think might work? Well, let's say after consulting with Danny, we think that there's a formula for viral TikTok songs. So the more precise question we want to ask for our research is, can a formula make a TikTok song go viral? Now it's time to form a hypothesis and set up some variables. Our hypothesis is what we want to test, what we're changing, and what we think is going to happen. First, we need to make sure we have an independent and dependent variable. The independent variable is what we're going to change or control, and the dependent variable is what we're hoping to have an effect on. So in this situation, the independent variable is a formula we're going to come up with for Danny's TikTok song, and the dependent variable is the amount of times people use the song in TikToks. When we put it all together, our hypothesis is that you can use a specific formula to make a TikTok song go viral. Next, it's time to get serious and really figure out how we're going to run this experiment. I'm currently taking a course on effective research methods, and something the instructor said was extremely important. She said, a proper experiment is trying to find the truth, but if you're just trying to confirm your hypothesis, you have an agenda. When we hear about research, we often don't want to do the extra work and get the details about who ran the study and why. We often forget that even scientists have biases and agendas, and unsurprisingly, they can also be motivated by money. Decades ago, a group of scientists from Harvard came out saying that facts were the primary danger and not sugar. Years later, it was discovered that the researchers were actually paid by the sugar industry to do this research. Disgraced doctor Andrew Wakefield, the man who started the anti-vax movement, was being paid by the lawyers of parents to prove the MMR vaccine caused autism. Since then, his research has been retracted, but as we all know, the damage has been done. Although we're not making major decisions about health like the above examples, in this hypothetical situation, Danny hired us to help with some research, and since we're ethical scientists, we're going to do some good work. That's why we're going to scrutinize our hypothesis and variables before we get started. First and foremost, we need to ask a very important question. Does the problem underlying our research really matter to society at large? Well, it's easy to say no, helping Danny go viral on TikTok doesn't matter. We need to think about the bigger picture. If we can prove that a formula can make something go viral on TikTok, this is huge for people who are passionate about creating and want to be an influencer. Even more importantly, think about the implications this could have for charity organizations and raising awareness about important global issues. If we were to help the ASPCA go viral on TikTok, think about all the animals that we could help. Or what if the National Alliance on Mental Illness wanted to raise mental health awareness? We can help them out significantly with this formula. Next, we need to ask ourselves if we'll be able to locate evidence for our research. Something that separates real science from pseudoscience is that the real science is falsifiable. In this case, if our hypothesis is that a formula can make Danny's TikTok song get 50,000 uses, we'll have data to know if we failed or succeeded. If this was a pseudoscientific study, we wouldn't be able to falsify it because we'd say something like, the lack of views actually shows that it was a success. It's a heads I win, tails you lose scenario. But we're awesome researchers, so we don't play like that. Now, we need to take a look at the extraneous variables. And I think this is where Danny could have really improved his experiment. An extraneous variable is something that could affect the results of the experiment that we may not be expecting. In this case, the biggest extraneous variable we might face is that people recognize Danny. With 1.5 million followers on TikTok and over 4 million on YouTube, if people find out it's Danny, it's an issue. Why? Due to his popularity, if the song does go viral, we won't know if it was because of our formula or because of the fact that popularity can beget popularity. Like I said, I think this was the biggest one that Danny didn't think about. But if you can think of any other extraneous variables, do me a favor and leave a comment down below. With a proper experiment like this, we're starting from scratch. So in this fictional world where Danny hired us to help him, we're going to pretend he never independently ran his experiment on his own. But at the brainstorming table, Danny brings us some ideas he had for running this experiment, and they sound pretty good. Some of Danny's ideas include, find a common style of beat that works for viral TikTok songs.   Then create consistent content with the song and use some current TikTok trends to try and gain some traction. These are all great ideas and we're going to run with them. But Danny has one last idea. He's going to record the song and the videos while wearing a minimal disguise. Well, this is why Danny pays us the big bucks because we immediately bring up the extraneous variables. Danny has a unique voice and short of a special effects team, but it may not be too hard for people to figure out it's Danny. So, what's a better way to run this experiment? First, we're going to hire an actor to be the song's artist, Ned Flanes, AKA Fox Season. In order to limit other factors, we need to find someone with a similar build to Danny. We want to hire an actor with a slim build about six feet tall and has magnificent hair. It's important that we find someone similar looking to Danny because let's say you cast me and the song flopped. Is it because the formula was bad or because I'm overweight? Or if we hired a woman, we'd have to take those factors into consideration as well. But we'll circle back to this topic during the replication process. Next, we need to find someone with a similar quality of rapping as Danny. Maybe the actor we hired can flow and if that's the case, that's awesome. If not, we need to find someone else. As we all know, Danny can rap. So, we can't just hire someone like your dad to record the track. Even if Danny writes the lyrics, we need someone he can coach to have a similar style and quality. And now that we have everything that we need, we can run the experiment and check the results. Well, the experiment is over and since Danny hired the best team in the business, we not only hit our goal, but we passed it. Within just a couple of weeks, over 75,000 people used this track and it's the latest banger on TikTok. Then, we revealed to the world that this was an experiment and we get Danny Gonzalez a million more followers on TikTok and on YouTube because we did such an epic job. The end, right? Well, not exactly. Now is the most important part of the study. Remember, we wanted to run this research for the greater good. We want to help hopeful influencers go viral and we also want to help organizations that are doing good for the world. So, before we publish our findings, we're going to want to do two important things. One, try to replicate our findings and two, try to disprove our findings. But first, let's start with trying to disprove our findings. We need to step into the role of a competing researcher or investigative journalist and do everything we can to debunk our findings. Then and only then can a researcher have any faith in their results. In the scientific realm, this is where peer reviews come in. When a group of scientists publishes their findings, more people from the scientific community get involved. While running our research, we may have been too narrow-minded and not thought of other factors that may have contributed to our findings or we may have succumbed to our own biases without even realizing it. But in my opinion, before publishing findings, you'll gain a lot more credibility by publishing all the things you did to try and disprove your research rather than confirm it. This not only makes the work easier during the peer review process, but it also shows that you're trying to have scientific integrity. Lastly, it's time to replicate the study. So let's say, since Danny is such a nice guy, he never made a sign in NDA and he wants us to go around helping other influencers with our findings. We give them our formula and see if they can replicate our success. Not only that, but we run our experiment multiple times as well to see if we can replicate it. One of the crucial aspects of analyzing results is having a proper sample size. If we only tested it once and it worked, we wouldn't know if we just got lucky. Maybe the TikTok algorithm just happened to help us more than it normally would or maybe a big influencer just happened to use our song. By running the research multiple times, we could see how legitimate our research actually was. Once replicated, we'd want to try a bunch of other different variables. We want to change different pieces of the formula and I think a great place to start is with the actor. We should try to replicate it with actors of various heights, weights, nationalities, clothing styles, and more. Then, we should also record tracks with a female rapper and hire actresses to see if gender played a role. Interestingly enough, there are companies that actually do this. For any of you who watch the social dilemma on Netflix, you know there's a lot of work that goes into the data that's collected. And hopefully, now that you've got a better understanding of the process, you can also better understand how algorithms are used to grab your attention for various agendas. But my hope is that you take this knowledge and use it to satisfy your own curiosity and run some proper experiments to help you in other areas of your life. All right, everybody. Thank you once again for nerding out with me. I think this is really important, right?  Like, I use this kind of stuff at my job. Like, I have a very cool position where I get to run different experiments and try different things to help our company, to help our clients, and I look at data and stuff like that. And I want to make sure that I'm looking at the data correctly. And here's the thing, here's the thing. This is something that I just started educating myself about like thoroughly, like this year, right? And I'm learning so, so, so much. Something that I didn't really dive into in this is biases, right? Like, I think one of the most important things, and I talk about it all the time when I talk about critical thinking and all of that, is like we need to educate ourselves about all the different biases we have. All the different biases. Because if not, we can just go down the wrong pathway. Like you remember in Dumb and Dumber, right? When they go on the wrong road for like hours or whatever and that's when they end up getting a little moped. Anyways, you know what I'm talking about. And that's why we need to be mindful of our own biases because our biases can make us feel like we're on the right path and we're just totally screwing everything up. But again, more importantly, we're constantly fed different studies and research and everything like that and educating ourselves about how proper research is done. We can go a step further and be like, is this really a credible study? What does the scientific community actually say? So like I said, I've listed those books down below, The Skeptics Guide to the Universe, Calling BS and Science Fictions. Those are all great if you're interested in this topic and how research is properly done, the difference between pseudoscience and regular science and all that stuff. So check out the description down below. All right, but anyways, that's all I got for this video. If you like this video, please give it a thumbs up if you're new. Make sure you subscribe and ring that notification bell and a huge, huge thank you to everybody who supports the channel over on Patreon or getting the books that I've written over at therewiresole.com or using my affiliate links to get the books that I recommend. That all helps, all right? You're all awesome. Thanks again for watching. I'll see you next time.


Welcome! Today we're on board the Tournament 234. The Tournament 234 will take your shallow water fishing to the next level. It features a tournament style deck layout with ample casting deck, a full console with electronics and room for 8. It measures in at 23 feet 4 inches with an 8 foot 5 inch beam, 15 degrees of dead rice at the transom, 71 gallons of fuel and just 13 inches of draft. So let's start at the bow. At the bow of the Tournament 234, plenty of room up here for casting and plenty of storage as well. For rod lockers we've got two of them. On either side they hold up to five rods. The stepbox also doubles up as cooler and if the boat is equipped with freshwater the freshwater hookup is in there. In forward of that we have a large fishbox. It is insulated and can also serve as dry storage or a cooler. Forward of that we have an oversized anchor locker compartment with the trolling motor harness.  So let's take a look at the front of the console now. Here in front of the console a comfortable two-person seat and opening the bottom reveals a 12 gallon live well. Nice feature if you're fishing up front. Again if the boat is equipped with freshwater the fill is actually right here on the left hand side. The upholstery up here does feature the hourglass pattern and there is a courtesy light on the floor. Let's take a look inside the console now. Now the head in this boat plenty of room for storage as well as easy access to the back of your electronics. Removing the mesh gives you full access. This boat can also be equipped with a porta potty if you need it one and the door is lockable. Now for leaning post on the tournament 234 this is our deluxe leaning post. Now it does have two adjustable boasters and of course this allows the captain to be standing up while passenger is seated or any position of that combination. Two grab handles on both sides as well as plenty of storage underneath. Now the boat we're on today's got two additional options. It's got the Yeti slide out cooler and the under leaning post tackle storage. You can add those if you want some additional storage as well as the slide out track. Now for rod holders we've got four across the back and that completes the leaning post. So let's take a look at the rear seating area of the tournament 234. Now the rear deck of the tournament 234 is functional and comfortable starting with a two person rear bench which does fold away and the coolest thing about it of course is our total access hatch. Opening up the bottom reveals best in class access to your bilge for any maintenance or service needed. Additional storage inside with a lockable lid. Now for live woes we've got two in the rear deck they're both 20 gallons and insulated. On the port side we've got that live well and then over on the starboard side we've got the same live well but this one has the pro air bubbler system. Both of these boxes can double up as insulated cooler and dry storage. Now closing the back deck will reveal a totally flush rear deck. Nice place for casting as well as entertainment. And for power you see here we've got the 250 VMAX SHO but we do offer the 200s and the 250s in mechanical digital and the VMAX SHO. Out back we've got a swim platform with a three-step boarding ladder we've got rod holders on the gunnel as well as pull-up cleats and additional cup holders. Everything nice and laid out for you. Thank you for spending some time with us today on the tournament 234. I think you'll agree that the layout on the tournament 234 will suit any tournament minded angler as well as families. This boat as with every other sportsman boat is NMMA certified and built to ABYC standards representing the highest in safety standards in the boating industry. If you have any questions on this boat or any other sportsman model visit our website at sportsmanboatsmfg.com or contact your local dealer. Thanks for watching.


In this video, we're going to take a look at finding the minimum and maximum attribute value, a couple of techniques for that, and then how to remap that so we can actually find the slope of this particular terrain here. All right, so just a couple of cool techniques inside of Houdini, so let's take a look. To start, I went ahead and created a grid here that has 500 rows, 500 columns, dropped down a mountain node, set it to simplex, and just changed the height and the element size. So, to get this started, we need to create an attribute that we can remap, so I'm just going to use the measure node. I'm going to then set it to gradient, and we're going to do the Y component of the point position. And I'm going to set this to the points. All right, so if you actually hit enter on the keyboard, you can see the visualization of that. So, basically, we're going to be getting the slope of this particular terrain, and I want to get the length of each one of those vectors, because the measure node outputs a gradient attribute, and it is a vector. All right, so let's come down here, and I'm going to say f at slope, actually, is equal to the length of v at gradient, like so, so that's all we need to do there. So call this get length, and now all we need to do is drop down an attribute remap node, like so. And what we can do is provide the slope attribute, and then I'm just going to pass it into a new name called slope, so it just overrides itself, and I'm going to compute the range and then output them in max to zero and one, and now we have the ability to remap it. So drop down a color node here, and set this to ramp for attribute, go get that slope value. You can see now we have the ability to map our slope, not too toned, it's kind of cool. So now we can actually see where all of our cliff sides are. Now, one thing I want to do is I want to make this dynamic, because I don't want to have to constantly hit this compute range, so we need to calculate the min and max. So there's two ways that I typically do to do this.  So inside of our min value, let's take our slope attribute, it's going to go from point to a detail, because we just want to store just the minimum value, and I'm going to set the promotion method to minimum. I'm going to change the new name and not delete the original, I'm going to call this min slope, there we go. And then we'll do the same thing for the maximum value. So slope, point to detail, we want to get the maximum, there we go. So now we have our two values here, and we're going to change the name, we're not going to delete the original, call this max slope, there we go. So now in our detail attributes here, we have a max and a min slope. So now we can feed that into our attribute remap here, and rather than having to compute this range all the time, we'll just use an expression to get that detail value. So we'll say detail, get it from the incoming geometry, I want to get the min slope and zero for the first index there, then we'll just copy this, and we'll paste it down here, and we'll do the max slope, there we go, that's all we need to do. So now we have those values, so you can just left click on the labels here to see the result value. Now if I were to take a look at my color, and hit escape on the keyboard, you can see now if I were to change the noise at any point here, it dynamically will update that remapping for us. So that's one way to do it, another way that I commonly use to perform this right here is the sort points trick. So you can actually sort your point numbering, so it's going to be kind of hard to see here because we have so many points here, but we can actually sort our point numbering by that particular attribute. So I can say point sort by attribute and slope, and that basically makes it so that point zero has the lowest value, and the last point in this geometry has the highest value. So all you need to do is then drop down our angle node and get those values. So if I run over detail, I'm going to say that my F at min slope is equal to point, the incoming geometry, we want to get the slope value, and we want to get it from point zero. Now for the last point, we're going to need the number of points, so I'm going to say npts for number of points for the variable name, and then we'll say n points to get our vex function here, and then we can just copy this entire line and change this out for the max slope, like so, and we'll say npts minus one. That's the last value. So you can see now we have our min and max slope, and if we actually were to replace the attribute remap node with this guy, you can see we'll get the same results. So just a couple ways to go about it inside of Houdini for your min and max values and attribute remapping. Thanks so much.


So Tara asked about how I prepare my course sessions or webinars. Basically, how do I do course content prep for presentation, especially when there are so many ideas, you know, we might have originally do a brain dump, you know, writing down, oh, everything I could talk about in this session. What do we do with all that information to turn it into either slideshow or resource document, basically an outline of the presentation.  So a temporary constraint is basically using questions such as if there was only one thing that I could communicate to them in this session, what must it be. So that's for me a temporary constraint because it's, it's, it's a constraint and a temporary because I could go on to ask the next question. Okay, what would one more thing be if I had to communicate a second thing. Okay, what would one more thing be if I could only communicate a third thing. Okay, so that's using camp. Okay, so that's in terms of ideas or community three ideas. I also like to ask myself the question. If there was one exercise I could do with them during the webinar if it was a kind of a more interactive situation, then that would be a good question if there was one exercise I could do with them. What must that one exercise be. And there may not be a time for a second exercise but if there was a second time for a second exercise what must that second exercise be. Okay, and then a third question that I ask is, if there was one homework assignment that I can give them. What must that one homework assignment be. And then this again, if there was a second homework assignment what must that one be. Another good question would be if there was only, well similar to the first one if there was one takeaway that they imagine at the end of the webinar or session. I asked them, what was your takeaway. What would I want some of them to chat, you know to type in what that one takeaway was. Okay, if there was a second takeaway that I noticed people typing what would I want that second one to be. So asking these questions then gives me a filtering of my humongous pile of ideas into these are the most important three ideas. This is these are the most important two exercises this is the most important three homework assignments, and the homework assignments can further be further be asked if if I were to give them this homework assignment. So if this was one homework assignment, focus on one at a time if I gave them this homework assignment. What must they understand in order to do that homework assignment. And so therefore that's what I must teach them in the session, so that they can do the homework assignment adequately. So, Tara is that is anything else you want to say about that. Yeah, that's great. I mean I think what I'm hearing is that I have down by like 80%. Yeah, as always, that's the case, because your, your whole collection of ideas, probably deserve several webinars or several more sessions. Right. Yeah, and they really only need just a few powerful tidbits at like a higher level. I think, you know I'm sort of doing one of those like let me tell them everything I know about this and then I'm just confusing and overwhelming myself. Yeah, and I have and this is a lesson I'm still learning is to prepare less material per session. And I think I, then I would naturally, then I would naturally, because I would naturally for for one hour session I naturally seem to prepare two to three hours of material. And it's like I'm still challenging myself and I challenge all of us to consider this. It's like, what if I ran out of material to teach, and I just had extra time for Q&A, or extra time for some kind of exercise interactive experience. Wouldn't that be great? What if I ran out of material? What if I ran out of material? What if I only prepared 15 minutes and my cat totally agrees? What if I only prepared 15 minutes of material for an hour long webinar? That 15 minutes probably is going to take me 40 minutes to really deliver, you know, or half an hour to deliver and then I still have 20, 30 minutes left for interaction Q&A, and they probably will feel very spacious. And so if I only had 15 minutes of material, what must those 15 minutes appear to be? So here's another question, Tara, that's good for to ask is, what's something that would really wow them to learn? Or what's something that they can't just easily learn somewhere else? Right, because you might say, like, if I were, if I were to be teaching an overall marketing thing, right? Let's say I'm just going to use that. One thing that they must know about marketing. Oh, that they must know that Facebook ads important or they must know that collaborations outreach is important. Okay, but if they only walked away with that, it's like, yeah, it's not, yeah, George's webinar was, yeah, blah, I mean, I could have learned that anywhere else. But if I said, marketing is authentic marketing is the process of building is a process of building friendships at scale. That was that one takeaway. They'd be like, the fuck, I couldn't have heard that anywhere else. That's really unique. You know, I mean, so, so that's the question I asked myself is what's like something that would wow them to take away. And then I work back first from there. So if they had to understand that, and what most, what else must they understand that that would be kind of unique to learn so that they get to that conclusion, you know. And then, oh yeah, right. And then, and then the last thing I do very important is to, is to try to, well, we haven't even talked about ordering the ideas now now that we've gotten some ideas, what order would they go into, you know, so maybe the exercise would go somewhere in the middle, you know, obviously the homework assignment would go towards the end. And then timing out the session, you know, the last thing I do is like, okay, so maybe I should spend 10 minutes on this topic and five minutes on that one 15 minutes on that one. Oh my God, now I have 75 minutes for a 60 minutes, which then makes me having to prune some things out. And you gave thank you for the even that last part because now I have a really clear idea about what that one thing is that they couldn't learn someplace else. So now I can. Yeah, it's not that it's not that they could never learn someplace else but it's not it's not easy. It's not easy. Yeah, yeah, it's not that they were here at everywhere, you know. Right. Yeah, exactly. Yeah, they wouldn't hear it everywhere. All right. Thank you. Yeah, thank you. Appreciate that. Thank you. So Katie, Raver has this good idea in the chat there. So Katie what she does is she talks to the people around her about ideas and see what they respond to and resonate with what this is why I use content right content is essentially a continual focus group right content is continually market research. So you talk to people around you see what they resonate with and that's how you get to your temporary constraint as a starting point for a new class to teach or a new webinar. It's often surprisingly different Katie wrote or something I think of as a mundane or obvious. And they are really in love with that idea. Yes, because by definition, you as a teacher expert, you are, you've thought about this stuff more than the people you're teaching or thought about it more deeply or in a more advanced way. So things that have become obvious to you are still amazing to them sometimes. So yeah, it's nice to find that.


For May, 1985, President Reagan arriving at the Federal Chancellery and walking down the foyer to the summit room. Open coverage, right on camera, cockling on sound. Mr. President, can you persuade Mr. Meteor on to get in your playground, in the background, so you'll be able to do that? This way, please. This way. This way, please. This way. This way. This way, please. He's just in town. We don't see him.


Hello everyone. Welcome to my webinar for product school called when your customers have customers. My name is very right. I'm a group product manager at Spotify and I'm excited to be talking to you today about a topic that has been near and dear to a lot of my product management career. As mentioned, I'm currently a group product manager at Spotify and my career has spanned a few different iterations all kind of leading through the product management space that are relevant to today's topic which is related to B2B product management and the unique qualities that come to light in managing a B2B product management relationship. My experience begins in university. I went to Duke University, have a degree in mathematics where I spent a lot of time learning both mathematical research techniques which I did not want to continue my career in but also teaching techniques which have been really relevant to my product management approach over the past decade. In particular, thinking about how different people in the room are able to understand things how they take different information from how a single presentation might come across to a broad group and how to integrate different perspectives and different methodologies into getting ideas across whether that's in a one-on-one session or in a much larger context. I began my career technology at a company called Hawks Learning Systems. They do educational software primarily based in mathematics courseware which was the through line between my school experience and my first work experience. I started there as a textbook editor and eventually moved into product management. That's where I learned how to do my first product PRDs, my first testing experience, my first customer interviews and got a really interesting lens into B2B product management beginning here in selling software to large universities, large community college systems, organizations which have a lot of other end customers and a broad reach with the products that we were selling to them. Following that, I moved into the ad tech space. I wanted something that was a little faster paced that moved a little bit more quickly. Math has been kind of the same for the last few centuries although how people teach it changes quite a lot. Ad tech was a really exciting, volatile, changing space that really caught my interest and I joined a startup called Videology in the Baltimore area doing video advertising technology and stay with that group through an acquisition by a company called Moby. For almost 10 years spent time learning more individual product management skills as well as building product teams and here had another really formative experience in the B2B space in that we sold software both to advertising agencies who have individual customers and advertisers who have end customers themselves and also TV broadcasters who were selling advertising space to these agencies who sold services to advertisers who were trying to please their own end customers. So really long chain between us and the end customer which really informs a lot of the thinking that you'll see here today. And most recently I started working at Spotify where obviously Spotify puts forth a number of different products to a very large customer base but I actually work on a team who serves internal customers through a platform of Spotify and so now have a third lens on what it's like to have customers who have their own customers. And that is kind of the crux of the topics of today's talk as you can see in the bottom section here I also have a personal lens to my career trajectory and that I've been working in the improv comedy space for a long time and actually it's opened up a theater in the last year and that has brought a different lens to how I think about collaboration really thinking about how to listen to different perspectives in the room and how to incorporate everybody's ideas into a holistic picture for how we move forward with decision making. And you'll see that in some of the examples that we talked through for managing these complicated relationships that happen within the B2B space. So agenda for today really breaking this down into three pieces. The first is just this overarching concept that all roads lead to the customer. We'll talk about what that means or what it implies for what you do in a B2B product management situation. And then let's talk about two mental frameworks that they use for B2B product companies that I think can be helpful in different problems scenarios if you pull back and abstract what you're doing to these structural frameworks you can find often the source of tension or problems in how you're working with other teams or in how you're planning and delivering value. And then finally I talked about three specific techniques that manage the complexity of the B2B experience and how you can apply those to problems ranging from user interviews to road mapping to stakeholder management. Let's dive in. So the first thing I want to start with is whether you're in a B2C company making an application direct for consumers whether you're B2B or whether you're B2B to B2B to B2C or more all roads end up leading to the customer. The chain always ends with a C. There's no point in having B2B software if there's not somebody at the end of the day using it and getting value from it. And what creates a lot of complexity in the B2B space is really understanding where that chain goes and where it might branch off and how it's being considered because everybody along that chain has different goals motivations and strategy that ultimately lead to serving the end customer. And the complexity of everything from relationships to metrics to planning goes up exponentially when you have to consider the fact that your customers have customers themselves and those customers might even have their own customers, which creates a really, really complicated dynamic. But if you zoom back out and think at the end of the day who the end customer is, that can really drive a lot of clarity in how you think about product design and how you think about what every person in the room is really being measured against, which often can make something that seems very, very tense or very, very misaligned reveal an underlying theme or an underlying goal that we can all realign around. And the first framework that I'll introduce here is built off of the three horizons model. You'll see this in a lot of consulting presentations and it's usually presented with respect to the research and development aspect of a company and how you invest in products which are on the far horizon. They may potentially provide a large amount of future value, but they're speculative. Or you have things on the near horizon and sure products that are generating cash generating profit for a company that you want to invest and maintain in with the middle being these growth products that you've already got some traction towards, but you need to invest resources into actually scale. And we can think of a similar framework when considering the different stages of customers in a B2B customer relationship. So if you think of yourself as having a product software company or you're selling software to another business who has their end customers, that business is taking on your software to achieve some goal within their organization that ultimately motivated by whatever their business model is itself. And you can think of the relationship maturity between your company selling software and theirs as reflected by the degree of end customer focus. At the very onset, while there may be an initial spike of this in terms of why they're even looking to contract with you at all, the first horizon of a relationship between you and another company is a pipeline focus on pre-contract sales products. These are customers or potential customers who either in the RFP process, in the diligence process, they're out there looking for a solution to their problem and it might be you. And at that time, the focus is really on, will this be a fit for the business? Will the business be able to integrate the software? Will they be able to take on this project? Do they have the budget to do so? And there's a really high focus between the company selling software and the company buying the software and not a lot of immediate discussion or action that goes to what the end client is doing. There may be, of course, a strategic pitch or a vision for why this software might help the end customer or drive end customer metrics. But in this moment, there's a lot of project management. There's a lot of organizational discussions about how to actually try this software out. And it's very focused on the two businesses working together. After you get over that initial hump of signing the contracts, sending the first payments and actually, you know, maybe sending some credentials over to start working, we move into the second horizon of adoption where the onboarded clients are integrating this new software into their business. They're figuring out what it's like to use the software to do their own job to deliver value to their end clients. And at this point, we start to see a shift where some conversations are going to be really focused on how do I get this software to work? How do I log in? How do I get support if I need it? But more and more, you're going to start to see conversations shift to how do I use this software to derive end customer value? How do I justify bringing more teams on board of the software? How do I justify spending more of my time day in and day out using this product? What does it benefit me in my role as delivering value to the end customer? And then finally, we get to this third horizon of relationship maturity where if everything is going well, then the conversations between the two businesses in this B2B example start to realign almost entirely around end customer value. Is the product delivering good efficiency? Is it delivering good results? What can we do together to change processes or to introduce new features that turn into end customer value? If you hit this point, you get a really, really great team relationship that is focused on just doing better work and you really gain stickiness, you really gain stability in this relationship because both companies are getting what they want out of the situation. The other framework I'll introduce is actually around the three stages of a B2B products company growth. And as you can see on the screen, they're pretty straightforward. They will revolve around how many different customers you have. This is a problem for platform businesses and for general B2B companies in that there are two pretty difficult transitions between your first customer to several customers and from several customers to many customers. I always tell people the easiest thing to do as a product manager is have one customer because you can succeed pretty effectively by just listening to what they do, what they ask for. It's not maybe the best way to build software, but it is an effective one to maintain a relationship and grow the company. And it works for a time, but eventually if you're successful with one customer, you'll have more than one. You'll have several customers who all kind of feel like you're their number one concern and they all act like they're the one customer in the first example. And that is really, really hard to deal with. I'll come back to that in a second because once you make the leap to many customers, things actually get a little bit easier. You have diversified revenue streams and so if one client is being particularly demanding and you can't have the resources to cater to their every whim, you can afford to let them languish in the priority queue. And if they leave, you have 45 other customers to make up the slack. And in fact, you're probably growing those customers. You also have the opportunity to more easily segment your customers into manageable groups. Whereas with several customers, you may have seven different clients that all sort of feel like the same but have their own unique differences and that creates a lot of switching costs and mental complexity in figuring out what to do next because it doesn't really line up in any really obvious meaningful groups because there's not enough data. There's not enough similarity among different customer groups to make any heads or tails of it. And so thinking about where you are in this journey can really inform how you act as a product manager and we'll see that come through in a couple of the different techniques that we'll talk about in a few moments. But it's really just important to step back and assess where you are as a company. Are you at one customer? Are you at several or are you at many? And think about what that implies for how your sales team thinks, how your marketing team thinks, how your engineers have to deal with support requests and new features and how you are assessing the market and growth opportunities. So the first technique I'll talk about is customer and stakeholder mapping. This is particularly challenging in the world of B2B2B to see customer groups. The longer this chain gets, the more complexity is introduced. And it's represented by the diagram that you kind of see on the screen here where we have the major stakeholders, your software company, the client you're selling software to and the end client they're delivering value to hopefully. But you can imagine this chain extending if necessary. And within each company you have different stakeholder groups. And we all have internal working models to our own organizations. There's a lot been written about stakeholder management. And there are a lot of great techniques for how you keep different groups of people aligned, especially in a product management context. But when multiple companies get involved, several new problems come up that make this work exponentially more difficult and can lead to really what feels like good work actually producing bad or misaligned results. And the obvious challenge from this diagram here is there are really pretty standard processes for each company. Each individual company communicating among its different functions. Your software company has a support team, a sales team, a project management team, an engineering team. And you know who to talk to. And there are probably pretty well-established ways of working among those different groups. And that's going to be true of your client and going to be true of your end client as well. And there's also a pretty well-worn pathway from software company to client and from client to end client. There are account managers. There are project managers who have weekly meetings and QBRs and all these different ceremonies to exchange information. But those lines don't really connect with the individual team lines that you see in this diagram. And that can cause a few problems to have. The first is what I describe as the bloated telephone where you have really effectively two large meetings in this structure. One between all of the teams at the software company and most of the teams at the client. And then a separate one between some of the teams at the client and all the teams at the end client. And you have two really big expensive meetings, disconnected project teams. And a lot can get lost in translation, both internal to each meeting represented in the red and blue circles here. Both because there are so many teams involved. There's so much to get through that everything has to be really written down in the lowest common denominator if we're going to get through everything in 30 minutes or 60 minutes. And then because there's such a big communication gap between the red meeting and the blue meeting, only what is absorbed by the person in the room who's having that transition call is going to make it to the next meeting and vice versa. And this can lead to what feels like a really effective relationship between the software company and the client, the B2B situation. But that turns out after two or three quarters, it's not actually delivering the results that the client bought the software for. And that can be really surprising. It can lead to the client switching software frequently and it can lead to a lot of churn for you as the software company product manager. The second version of this, which a lot of organizations end up in is they recognize the challenge of not meeting with the end customer. But they fail to put in enough structure to coordinate work streams. So they end up with these siloed work streams where the engineers and the engineers are all talking to each other. They have good working relationship. The sales teams are all meeting together to make sure that we're talking about the right things to deliver to the end client. Maybe have operations and support working together in a shared Slack channel or through a shared ticketing system. And so you've established these good functional working relationships, but you haven't invested in understanding the impact back to the individual organizations. This can cause another set of misalignment where each team thinks they have control of the relationship or the overall roadmap for the project. And then when they come back internally, they find everybody wants to do something a little bit different. And then the internal machinery within the organization works. And maybe it doesn't spit out the same result at the software company and the client and the end client. They try and bring that back and you just have a cycle of negotiation that doesn't end up going anywhere. So this is also another problem. And further, there's so many important conversations that really do need multiple functions in the room. If sales is just talking to sales, you're going to get a lot of really interesting features that are generated and not a lot of assessment about whether those are realistic to build in a certain timeframe. And so the model I like to encourage people to consider is what I describe as aligned flywheels where you have both the work stream and the functional based communication on a more informal, more frequent basis to work through the day to day aspects of using the product or selling the product. Or building the product. But there are regular syncs that happen consistently across the different members of this value chain software company and the client and the end client. So that a small group of people at each organization can come together and talk about the problems that they're having and what each of their experts has brought to the table. And they can easily and with context importantly bring that back out to the individual organizations. And I find this works really well when each organization brings a product manager who's focused on the market and kind of has the same connections internally. And a program manager or project manager depending on what your organization calls them to help align the project planning and the organizational, you know, management of all of these different functions together. The second technique is to consider metrics in particular product metrics by the customer motivation and these map to the stages we talked about in the first framework. If we think about what customers need while they're in pipeline, while they're in the adoption phase and whether in the performance phase, they're very different and they're very different things to measure. So if I think about a customer who is in pipeline, they are thinking about buying a new software that they're going to integrate into their business. And that's a pretty scary proposition. That's often a very expensive decision. It's one that comes with a lot of political risk. And it's also one that has a lot of uncertainty compared to improving an existing process or trying out a new sales model potentially. And so what they want to do in that stage is to de-risk the purchase, ensure that they can integrate smoothly, and they also want to have the tools to sell that new concept internally. And so as a product manager, I want to be thinking about things like what's my level of engagement in the test environment? What's my time to activation? What are my lead conversion metrics? What are these leading indicators that will tell me that the pipeline stage is going smoothly and that can tell me whether I need to invest further in making onboarding easier, making testing easier, making demonstrating the software to internal teams easier to get more people into the system? For clients that have moved on to the adoption phase, they're talking about figuring out how to make that product part of their business as usual. They're creating stickiness via process adoption at various teams in their organization, and they're trying to remove questions and barriers to continue to use because they want this product to be successful. So here I'm looking at what are the metrics that are demonstrating that things are getting easier for the client and things are getting ready to scale? That could be integration support tickets dying down, going from rapid pace during the integration phase down to zero. That could be measuring how long does it take each customer to launch their first whatever it is that you do, whether that's an advertising campaign or a cloud computing instance, or a sale of a product on an e-commerce site? How long does it take to get those first one out? How long does it take to get the 100th one out? How long does it take to get the first active user and the 10th active user? All these things can kind of give you a sense of the shape of adoption. Often we can get misled by the first thing that happens because they have some advocate at the company who's really excited to use this product. I think a more effective tool is to understand the fifth user or the 10th sale or the 10th sale from a unique sales person. That's going to tell you when something's really caught on and when you've achieved kind of a fit within that organization. Then finally, for customers that are in this performance stage, the conceptual goals shift to end customers almost entirely, delivering value, maintaining stability, and then opening up avenues to demonstrate potential new value and grow the business. Here, again, depending on what your software does, you should be thinking about things like cost for end customer action, clients, sales growth, and even simple operational things like how often are people copying the workflow that they used for a successful sale? And that people copying a particular campaign or a particular instance of how something was set up. That can really tell you things are coming along, things are working, and people are just using the software to execute. Finally, the third technique, which is near and dear to my heart, is to invest in configuration to deliver a customized experience. One of the really, really difficult things, especially as you transition from one customer to several. And if you're not careful from several to many is that each customer wants a slightly different version of the product. They talk about that as a custom product, but really, you don't have the resources or the time to manage 50 custom products.  The two biggest tools in my view for this are investing in strong permissions and admin workflows and investing in onboarding workflows and products. On the left hand version of the diagram, you can see kind of what happens if everybody asks for things on their own, you get a lot of one off features that maybe only one or two clients use. And you have a lot of confusion in terms of how you segment customers and market to them because each experience has been bespoke. Each journey to a particular configuration of the product or even customization of the product can be very, very complicated and hard to untangle. But if you invest ahead of time in saying, hey, we're going to turn these features into configuration tools that were exposed to our clients, then you start to see things in terms of sets of features that can be turned on and off and combinations of features that can be packaged and sold. And if you have that in place, you can take four or five different features and combine them into a much broader set of use cases if you so choose. This is a simple exponential scale problem where if I have two features independently controlled, that's four versions of the product, four features to 16 versions of the product and eight features to 256 versions of the product. And that can start to really feel like something that was tailored to me. And alongside this, the complexity of managing those eight different switches is very different than 256 versions of the product. What you see in an organization that gets stuck on a custom software loop is overhead scales linearly and sometimes super linearly because of challenges with writing contracts and training operations teams and training sales teams to do what normally would be single elements in an onboarding manual or the work that a sales engineer would do to customize the experience of a product based on a set of pre-built configuration options. And so you need to think about what time in my product's life cycle, what time in my company's life cycle is it right to invest in these tools? You don't have to do it right at the beginning with one customer, but pretty soon you should start to be thinking about how you can build feature flagging, how you can build permissions and add in workflows, and how you can build self-serve onboarding workflows that help people add logos or UI white labeling or load their data from another system so that you don't have to be doing this every single time you bring on a new customer and you don't have to be rethinking what your product packaging is every time somebody asks for something new. All right. So in summary, we've talked about a few different concepts here. We've talked about how in B2B product management, really everything ends up leading to the end customer. And if you ever get stuck, the way to think about what everybody in the room is thinking about is to go back to the end customer and see what the value they're supposed to be getting is. We talked about two frameworks for B2B product companies. One is based in the level of maturity of the client relationship and how that changes from focusing on how do I get the software on board to how do I scale the value that it's providing to my end customers. And then we talked about three techniques to manage the complexity of all of these stakeholders and all of these people involved in a B2B to C company experience that includes stakeholder and customer mapping that includes looking at how different metrics come into play as companies evolve and clients evolve and it looks at how do we use customization techniques and configuration techniques to build and create a custom experience at scale. Thank you for listening. I really enjoyed talking about this today. If you have any questions, please do reach out. You can reach me on LinkedIn or via email and looking forward to continuing the discussion. Thank you.