food systems specialist for FAO. We'll talk to us about multi-stakeholder platforms as a best practice for supporting sustainable agriculture in fragile ecosystems. Oh, good afternoon, everyone. I do realize it is only me that is keeping me away from the wine and drinks after, so I'll try to be as brief as possible. First of all, I'll present myself. My name is Federico Mattei. As mentioned, I work for the Mountain Partnership, which is an FAO institution. We work mostly with mountain agriculture, also through the Gillespa, which is the global island and fragile ecosystem partnership, also on coastlands and deltas and these kind of things. And I have to say that last week or a couple of weeks ago when my office told me I had to come here, I was initially not skeptical, but initially confused. And I thought, why would theoretical physicists be to having an event on sustainable food systems? And then first of one of the first things I did was to Google the definition of physics. And apparently it is a branch of science that deals with how the fundamental constitutes of the universe interact with interact being the main word there. And also listening this morning to some of the speeches when we were talking about the sustainability of everything, I did realize and in fact physicists might be the most pertinent to talk about the complexity that we are facing because you are one of the few or one of the few people who are specifically interested in looking at the minuscule, so how things interact at a very, very small level, but then how these things interact in the complexity of something very huge. And this is exactly the challenge that we need to face. And I think so it is very pertinent that you are having this discussion. I was then surprised I have to say during this day because I had taken a few notes of what I was going to say and I kept noticing that everyone was making my points.  It's like okay I'll talk about it. That's the problem of speaking last. Exactly. So about you know externalities and about the complexity and about so many things. So I have to keep changing changing my my my thing. Multi-stakeholder platforms, I will say something about this. And I think this is a multi-stakeholder platform. There is nothing new about this. And I think there is a kind of change in the last in the last decades in the last years of bringing together all the different stakeholders in food systems to a table and trying to define programs projects and how to implement them together. There is there is word coins I think by slow food if I'm not mistaken which is the co-producer. So it is bringing is the act of bringing consumers into the discussion of production methods as though they were co-producers because it is through their consumption patterns that they really create and and define production practices. And maybe this could also be used in a way for for science. I think you know science is neither bad nor nor good. Inherently it is a tool. Sometimes we really need to understand how the science or what the objective of the scientific instruments and tools what are their objectives. And I think by bringing in the people who then are going to use these scientific tools into the discussion as early as possible we can kind of co-create scientific approaches, tools and methodologies. So maybe co-scientists could be could be the term you could take from this. One thing that was mentioned this morning which I would like to touch upon is the price versus the cost of food. And I think this is a very very crucial point. I am an economist unfortunately so I tend to think in economic terms and one of the first things I learned as a young man studying economics was externalities. Externalities I won't go into too much detail of the economic theory because it's apart from fact it's economics 101 but you can find it quite easily on the internet but it's really the when we do a price cost function some of the benefits or some of the costs of any single economic operation are external to the actor who does this. Let me make a specific example so you might find it easier to understand. If I have to build cars I would look at per unit cost what is my cost of production so the materials the steel the workers and so forth the electricity and obviously how much I can sell those cars for. I will come to an equilibrium so if I produce enough cars I will able to break even and get enough profit. The problem is that a lot of the costs and sometimes the benefits are externalised and so when we look at things like pollution in the in the sense of the cars the pollution the the serious the negative effects on the population these are not borne by the car producer but rather by the collective. Someone today mentioned that no one is paying for these external costs but right in fact everyone is paying for them to a varying degree and so one of the things we need to understand is that when we go into a supermarket a shop or whatever it is and we see the price of a food the price is what we see on the label that is not real cost food in most cases there is cost which is much superior to that price this cost can come from environmental degradation from health from social aspects and so forth sometimes there is an extra benefit which is not part of that cost either so if we look at some of the more for example I found it fascinating Dr Edie Mr Edie was talking about before regenerative agriculture some of the benefits of that regenerative agriculture are not included in that price so and I think economists and I think scientists in general really need to find ways to re-internalise these negative and positive externalities and by including them in the price then the consumer is able to make let's say informed or rather real decisions on what they want to do I'm very much against dictating what people should buy or should not buy how they went to spend their own money but the price of those goods should respect or should reflect all the different externalities in that product. One thing I've noticed is there has been a lot of talk today about really kind of large-scale agriculture I found some of the presentations fascinating especially the one I'm thinking on now is the one for Professor Basso and I was trying to think how could this be used I am a farmer myself I have a small-holder farm how could I use this and I thought you know it's kind of difficult I couldn't get the magnitude and we have to kind of remember that depends how we consider a small-holder farmer but anywhere between 30 and 80 percent of global food production comes from small-holder farms 30 is if we consider under two hectares I think but two hectares is a very small farm in many contexts and something like 30 percent of the world's population is occupied is employed in agriculture directly or indirectly so how do we then respond and many of these of course are in small-holder farms especially in the global south and how do we use technology to also provide them benefits and to really tailor the technology to their specific situations I think this is a challenge for the future. So for example when today agriculture has been very much defined as a source of CO2 we've looked a bit less as agriculture as a source of livelihoods and how many people worldwide depend on agriculture. One of the things that I think science can be very very useful in this respect is one of the main disadvantages of small-holder farmers is the inability to have for example economies of scale obviously if you have a very small smart you won't have the money to buy certain kinds of machineries for transport for stocking and so forth and traditionally this has been in many ways not resolved but through cooperatives so putting a lot of small-holder farmers together you can then have much more economies of scale you can have investment opportunities and so forth but maybe we can also see how science specifically tailored science can help those small-holder farmers and can maybe limit some of the disadvantages they have from a lesser economies of scale like lesser economies of scope and I think we've come to a point where physics is science is very mature in that respect in which it can be tailored things like the internet of things we've talked about them a bit today and how can we make it a lot more flexible a lot more pertinent for the small-holder farmer. When we were talking about multi-stakeholder platforms and in general science and scientific innovation I think there's different ways that we need to then use this so for example we talked about a lot about environmental sustainability a bit less about social sustainability health has been a very important topic but we also have to see how for example we can really understand certain things so we've talked about land use for example and how agriculture is always seen as degrading the quality of land this is not necessarily true we had a fascinating conversation at runtime with about alpeggio alpeggio is is a practice as a cultural practice here in Italy where mount or cows were brought up into the mountains and alps especially during the summer months and then brought back down to the villages in the winter and this the conversation we were having about this was how some scientists or many scientists seem to believe that this actually increases the biodiversity of these ecosystems because through grazing they open up meadows in what are fundamentally coniferous forests and these meadows seem to have after our conversation higher biodiversity both of plants and insects there's more lights coming in there's more interaction these kind of cultural practices can be important sources of regeneration same thing for example I spent quite a lot of time in the Philippines working with rice terraces up in the in the Cordillera province and they have these terraces and there's a whole cultural a set of cultural norms associated to these kind of food systems which are very important so for example one you can imagine the the management of the water obviously the person who has a farm on the top of or they'll plot on the top of the terrace if he uses all the water it will not be enough to come to the to the lower levels this causes social tension and so there's cultural norms which have been present for generations which manage and which monitor the use of this water another example is for example when when when a daughter is married the family of the daughter plants, tendries up above the rice paddies and these are clearly attempts to avoid soil erosion because obviously if you deforest the parts of land just above the rice terraces leave it one generation or two and it all comes down another for example link between and I think this is very important that food is very different to other things for a number of or for two fundamental reasons one is culture and so we've touched upon it a bit now another example which is more of a local example has to do with pelagra pelagra is is a disease that was prevalent in 1800 up until the 1800s and it was a vitamin deficiency which was very prevalent here in what was before the ocean Hungarian empire but the Italian part and it arose because when corn was brought from the new world to to the old world it's proved extremely beneficial for food security for for yields for income it it was massively planted here in the in the Padanian plains in the Paw Valley but one of the cultural norms associated with it was not brought to Europe which was an externalization which was a way of cutting the the the carbohydrates so that they were then accessible by our human body and this caused pelagra and it took them quite a long time to realize that pelagra this debilitating disease was not some kind of airborne virus or something something in the water but it was a nutritional deficiency and this nutritional deficiency came from a lack of cultural understanding of the crop this obviously is no longer pertinent but and it shows you how sometimes we try to detach food and especially the genetics of plants from these cultural norms and sometimes we cause problems let's say the other one and i've promised i was going to be as brief as possible and so i will shut up in a few seconds is that food is desire and this is something even less it's even more not understood by scientists i worked for quite a long time for the CGR which is a very scientific based institution and the and then i moved to to slow food which was an NGO working in a very very different way and i realized that one of the things i did learn about in slow food was that food is passion food is desire food is taste and we tend to forget this and so for example you know when we go to i myself sometimes go and eat fast food or drink a cocoa cola and just the pleasure it gives you the sugar the the chemicals inside is makes it harder for you to make a rational decision which is very different from most products in the same way food is linked to culture food is linked to conviviality we tend to eat together there tends to be traditions social traditions on how we eat and what we eat and and so the last thing i'll say is one of the first speakers today i think it was dr sergo talked about michael polin and the omnivorous dilemma which i think is a wonderful book i've actually based one of my farm on one of the farms in the book but i would like to to mention another book by polin which is the botany of desire which is a much less known book by polin but i think it's just as worthwhile especially for people who are very scientifically approached because it shows you all the different links between these four different agricultural products i think it's apple it's apple to potatoes and another two about the link between foods desire and culture and pleasure and these kind of things and i think in such a scientific environment i wanted to add this because maybe i can add it and others can't to always remember that food is very very much linked to pleasure to desire to conviviality to culture and without taking into consideration these aspects it is very hard to then change consumer behavior the last thing i want to do i want to say is though i do think consumers and working with consumers or consumers have a very very large responsibility in how the the food system is shaped i think it can the responsibility of sustainability cannot be left 100 in the hands of consumers and there has to be policy there has to be a legislative environment that allows consumers to make the right sources or points them into the right direction and so i do think that for example once we have once we are able to measure externalities we need to re-internalize them through prices things like subsidies we need to subsidize positive externalities we need to tax negative externalities because we need to create a living a level playing field when when we go to the supermarket and see those two prices and see the price of for example traditional Filipino terrorist rice and you know important GMO rice from Thailand it's not the fact that it's GMO is the problem is the fact that that we the consumer does not really understand that price differential what it entails and for example one thing that's quite useful which quite a lot of different institutions have been using right now is tourism and so bringing consumers to the productive places to see the farms to talk to the farmers to eat with them and they kind of understand a lot more what they are subsidizing with that different price so they understand that those ecosystems those farms those people because we often forget that there's people there's literally i said about 30 percent of the world's population working in agriculture and sure we can maximize yields we can create economies of scale but then we have to find something for these people to do so i think there is a balance of course we don't want an inefficient food system just to keep people occupied but we need to take a take into consideration these billions of people that work in in small order farm and provide solutions for them we do not have to go back in time there is you know the anti-science is is one of the worst case scenarios for the future even worse would be going back to some sort of itadak past which doesn't exist or maybe it did exist before the before agriculture when we were still hunter gatherers but since then it hasn't it hasn't existed we need to move forward we need to leverage science and we need to count on scientists more than politicians in guiding us but the science has to be targeted to provide solutions for the smallholder farmers for the consumers for the companies for the private companies rather than for those huge huge for the large multinationals or rather for those who have money enough money to spend on research so there's a lot of people that cannot do research and i think it is the responsibility of science to also find solutions for them thank you thank you so i'll start with one question about FAO views i mean one of the things that we hear a lot lately are these big programs to reforestate the planet the 1000 billion trees that was pushed forward by the g20 initiative and i was at the an international meeting in Rome at the academia delinche where this topic was discussed and one of the issues was okay if we reforested in europe that will involve a very small surface the real problem is to reforestate in latin america for example and the issue was who is going to tell the farmer that his land is no longer going to be farmland and that it will become a forest and who is going to compensate him for the lost income that is a very good question i sometimes think i come from i have a farm in central italy and sometimes when they talk about reforestation it's you know we planted i don't know a million half a million trees and i always think to myself who's going to water them who's going to take care of them until they actually live because i mean anyone who has planted trees not in alaska or you know in places where there is a lot of water knows that if you don't take care of trees they'll die very quickly i think that's there's two different approaches to this one is what you are saying of saying we need to reforest this we need to create this as a kind of a green lung and so we need to move people out of it and and the another one is trying to find solutions which have a space for all of these stakeholders and so for example we were talking about coffee before shaded coffee is a very good example of this forested coffee we can choose between coffee which is grown in monocrop in fields with no trees with no forest but coffee as a plant is a forest product comes from this forest plant and so by working with the with coffee producers in ensuring a they don't cut down forests to plant higher yields coffee or if they already have those higher youth coffees how can they can transition back to forest agriculture to shade the kind of coffees is an example of how you can sequester carbon re recreate forest without negatively affecting the producer if anything we can if we also manage to then trigger a price premium on his coffee because it is forested coffee then the producer is even happier because he has a more fortified livelihoods FAO in general i think is a very seen from inside rather than from seen from outside is very heterogeneous so there's a lot of different thoughts in FAO i think FAO recently has taken more of this approach but i think inside there's a lot of different voices and sometimes it's fine it's hard to understand where these what these voices are and who the the people you can talk to these things that are about have a question about prices because it's in theory it's it's very tempting the idea of internalizing of taking externalities into account when making the prices of things but just imagine how difficult it is who decide about these prices how do you protect the system of pricing from lobbying on all from all sides how you can distort the markets because prices are an essential signals in the economy you're an economist and how would you for example handle situations such as the one was mentioned by Michele this morning about animal husbandry being six times more efficient in an intensive way than in Africa so how do you value all this competing interest i think it's it's fascinating but incredibly impractical i'm afraid up to a certain point i think authority an all-powerful authority that doesn't have to be i think you're looking at is a kind of a truth which comes down from god and we need to find that that's not exactly what i'm talking about it's more trying to understand what i talk to a lot about with his government officials so ministers and i look at but unfortunately they're the ones that tend to create a digestive environment and they tend to think the cheaper food is in supermarkets the happier my people will be it's a question of food security we don't want people starving we don't people wanting malnutrition and so when we talk about the sustainability of food prices go up and so they're afraid of not having enough food for everyone you know however if they then go look how much are you spending on your medical bills so on on the on the medical industry to solve all those problems that that cheap food is creating when you're surviving mostly on high fructose corn syrup as a source of of calories and then you're spending a huge amount of money for obesity for childhood childhood obesity for these kind of things you're paying a lot more when then your ministry of environment comes in and says look we are losing quite a lot of money every year due to deforestation due to soil erosion and so forth all of these things need to put people together so the decision cannot be taken only by looking at how can i get cheap food for my people how for your question is how do we determine this is what i ask you no this is what i what is the amount of litigation that would no it's i mean it's you know you can look at it right now on on the common agricultural policy there is quite a bit of subsidies for agri for sustainable agricultural policies who decides how many what are those subsidies who decides who gets the group of panels a group of experts it is the the the policy makers that decide these we will never arrive at a true price of something but we cannot just avoid the question because we are scared of of of getting precise measurements look at for example the the tax on carbonated drinks in Mexico okay we don't know if that tax is exactly equivalent to the negative externalities due to those carbonated drinks we do know there is a huge problem of obesity in Mexico we do know that that's obesity problem is at least to a point linked to an inadequate nutrition and a use an excessive use of carbonated sugary drinks so by taxing those we reduce the consumption of them and so we reduce the negative externalities that's why i need that's why i need theoretical physicists like you which are used to looking at the complexity of the universe and telling me this is how we should do it i can identify there is a problem and that we need to move into that direction i don't have the expertise of course to say to determine exactly what that price is this i need to ask people like you people who are used to measuring complexity and who are used to doing an analysis which has because the problem it is complex it has so many different factors which affect that price that we can as you said if we only look at a certain of them we risk being unfair because as he was as they were saying before you know the organic farm the organic farm might be more biodiverse it might have a better use of certain certain resources but then it might have certain disadvantages so doing is it just because it's organic we pay more no it's much more complex that i agree with and that is the difficulty we are facing before we move on to the next question i just want to remind you that our latest Nobel Prize winner for physics georgia parisi won his Nobel Prize for research on complex systems so you see and he's a theoretical physicist okay thank you sir um i'm looking at water financing for a small holder farming and it is a big problem for a dry region like Africa since Africa is one of the dry continent so uh what modalities is f a we're taking regarding water financing for small-scale farmer because that comes with a huge loan and uh majority of the small-scale farmer do not have that money so uh what what what are you people doing thank you first of all once again it's very hard for me to speak for all of FAO because uh you can imagine it's a very complex institution what i can say from my personal point of view is for example one of the uses of technology the kind of use for technology which i think would be very useful for small holder farmers is this kind of thing so using for example precision gps technology to put water exactly where it's needed if you look at most of the irrigation in farm systems is wasted and you can see this driving up and down the port valley uh fields and fields of tomatoes in and i saw them in july in august of this year when in italy we had a huge drought spraying water up into there how much of that water is going to hit the ground when it hits the ground with 40 degrees we're talking about you know i saw them do it uh midday in in july how much of that water is going to the plants 10 percent five percent i have no idea so if you're using for example i think the israelis developed a lot of these kind of techniques because of the kind of of you know desert agriculture they sometimes have to do if you're managed to put that exact water on exactly that plant you need your cost for that water is much less and so someone like a small holder farmer can access some certain things you can use a lot less resources in a much more efficient way so technology can help you being more efficient and and this is extremely important for a small holder farmer yeah i think if i can make a comment that the same concept applies also for the use of uh plant protection products uh if you have adequate modeling of pathogen populations coupled with uh analysis of precipitations you can time the application of plant protection products much better and greatly decrease their utilization and i think this goes to the advantage of small holder farmers if you set up a system where this information becomes available to everybody and not just to the big farmers that can afford to use those fancier models exactly or for example i have a i'm an olive farmer on my free time when i'm not at f a o and i see there that when the the fly the olive fly comes you need to you need to treat it either biologically whatever but you never know when it's there and when it's when you do realize it's there at least me from uh from a farmer point of view it's kind of too late and so most people will spray regardless of whether there is a fly or not already a system which can be used by a small holder farmer which tells me yes the fly has arrived and yes there is the pheromone traps there's things like this but trying to push more into that makes then i can spray when there is a problem it's the same thing as the antibiotic resistance we were talking about before you give antibiotics to to livestock when there is a problem not in general i'll give it to you because i don't care if there is a problem so i'll and it's that same kind of logic it's trying to bring big big systems big technological innovation to a very kind of personal small level which can be used by the the Ethiopian farmer by the by the herder up in in the Andes or or even by myself for example because i'm a small farmer and and that calls for a lot of training and retraining of these farmers because they do not understand these yes you have to bring it down bring it down to a level they can take it in and apply it yes for for the scientists we can always do it yes education and and raising awareness let's say our our key are you cannot there is no innovation without or you cannot spread innovation without then raising awareness and and building capacity on how to use this innovation thanks a lot i think we have come to the end of a very interesting day thanks to everybody to the speakers that gave excellent presentations as well as as to the attendees who were very participative in asking questions and remember if you want to take a copy of the book we have now the cocktail drinks and see you tomorrow morning at nine sharp we'll start to talk about nutrition diets and health


Good morning to CMC Espresso from the Frankfurt office of CMC Markets. The acting oil minister of Kuwait last week already said that an oil price between $50 and $60 per barrel for print crude oil would be an appropriate price. Yesterday, his colleague from Abu Dhabi joined in with a forecast that crude oil prices could climb as high as $60 a barrel amid a clot that's twindling more quickly than projected. Print futures rose firmly above $50 yesterday amid those concerns, those comments, and they also profited from a weaker dollar and the expectation that low rates in the US will be here for longer, so the liquidity behind that is also driving crude oil prices higher. At the UBS, the Swiss Bank, they published a research note and said that the journey from an oversupplied to a sustainably balanced oil market is not yet over. Speculators cut their total long and short positions on WTI crude to the lowest since January of 2015 before the OPEC meeting, which was on 2nd of June last week. That's according to Commodity Futures and Trading Commission, the CFTC. It will be interesting to see if they jump back into the bandwagon in this running week and as the oil prices went above $50, it will be interesting to see how the commercials and speculators acted and reacted on this. Interestingly, the price targets Middle Eastern Oil Minister C for crude oil, so that is $50 to $60 per barrel. They are roughly where everyone thinks US American fraction production costs are, that is between $50 and $60. As long as prices won't rise above that range, there will be no real incentive given from the Middle East to the US producers. It will be key to watch the number of active US oil drilling rigs. They just increased now from the lowest level in more than six years according to data from Baker use that was published on Friday, so it will be interesting to see if there is any upside reaction on active drilling rigs in the United States. Those statistics will give us a good indication if the US oil industry is ready or able to strike back. Chinese Finance Minister Lu yesterday have published his own opinion about the US economy. He said there should be or there should be not too much worry about another US interest rate hike despite the fact that it could have a broad impact on financial markets and added that US economic recovery remains fragile. The rate rise issue would not be a so is seen from in his perspective is like a sword hanging over people's heads. Its impact has on the other hand already been largely digested by the market, so people should not worry too much about it. On the other side of the planet, there was later on Janet Yellen, the Fed president, was half a day later talking about Chinese rebalancing risks and how they pose a threat to world financial market stability. All in all, Janet Yellen didn't really say something meaningfully yesterday, she tried to spread some optimism after Friday's dismal chop starter. In the end, she was sounding like a dovish hawk and it was interesting what she didn't say though. Unlike two weeks ago, Yellen didn't give a timetable for a rate hike, she didn't repeat that she thinks it is appropriate to hike rates in the coming months, she just said that she thinks it's probably appropriate to do so but didn't give any timetable for that. There was as expected good news for US stocks which have been in some kind of tug of war with gold yesterday in trying to find out who will profit most from the specter of lower rates for longer. It seems that yesterday stocks took the winning point over gold which might be the sheer result of technicals. In the end, the S&P 500, while richly valued, is close to its all-time high and that is not something that you can say about gold. The question remains though how much more stamina the liquidity driven bull market in US stocks still has before there will be a top coming.


A cue of the duckboats, the Vince Lombardi trophy is back in Boston. As Titletown secured yet another championship, the fleet of 25 World War II era amphibious duckboats were called to action. You know, it's considered bad luck to even mention a parade before the Super Bowl actually takes place. Obviously, we have to consider that this might happen, but there is so much preparation for this that we don't actually start doing that work until we know there's going to be a parade. And it usually takes about 24 hours to get ready. The boats notched their ninth championship parade in 13 years, with the same team whose success started the tradition. Well, it all started with the first Super Bowl win. The city of Boston decided that we should have a big parade, and we were asked to carry the players along the tour route. And since then, it's sort of become a tradition. Ever since, the duckboats have become a staple of championships, parading around Boston's most prized and elite athletes. Along with the Patriots, the Boston Red Sox, Celtics and the Bruins have all ridden atop the infamous ducks. I think it's really unique because of duckboats, and I think for every city you have the most parade to sit on, the car or the Boston, all the players and the team sit on the duckboats. That's very unique. It's my favorite.  I'm here just outside City Hall Plaza where the duckboats rounded out the parade, dropping off the Patriots at their buses. From here, the boats will go straight to their winter haven in Dorchester until the spring. For BU News Service, I'm Christina Lo.


My name is Robert Ouma. I am a project manager for Pico Eastern Africa, which is an organizational development organization based here in Nairobi. Simply put, an innovation platform is a safe space where actors drone from an industry come together and co-create solutions to a challenge that face that industry. They create innovations. They work together to develop solutions to specific problems. This task required us to look at the entire delivery chain for breeds holistically. This then seemed amenable to an innovation platform approach, which brings all the stakeholders together. The innovation platform allows you to take a systemic approach, a multi-dimensional approach to a specific challenge, and this really really fitted well with the challenge that we had for the DGA project. We faced a lot of constraints as well accessing services and for that particular project we were obviously interested in breeding services. How do farmers access breeding services? What kinds of services do they require and do they need and are they willing to pay for and identifying entry points on where, how and where development partners can intervene to unlock some of the bottlenecks that would then make farmers being more able to access the services. The field activities were linked with the platform activities very very closely in that our key participants and enumerators were participating in the platform. So through that the interaction was neat and clean and in real time busy. Well, they are quite a number. Earlier on when we started the farming system, I think even in East Africa, there were some subsidies in constructing the deep, those tanks for the water, the planting and quite a number of things. Even the drugs there were some, you know, subsidies. Now those were removed. We managed to develop a lot of models for delivery of semen, of hayfas, of bulls in the region. So that was a significant contribution of the innovation platform. I think the platform is a very useful place to grow ideas. I didn't have the, we didn't have the idea of wombs for hire before the platform, but the component of the platform of wombs for hire we were completely aware of, but to put it together as an idea of wombs for hire, that happened at the platform. The idea was to approach a rancher doing Boran and ask to hire wombs to produce crossbred, dairy crossbreds with Boran. And for this, for the very, the idea at the outset was to produce Boran frisian crosses, which in this country I think have a market. Several interesting models were developed for businesses within the context of the platform. A number of this have been developed into business plans and taken up by entrepreneurs. The forum was useful in furthering ideas. So just to sit together, to brainstorm some more was useful, but I would also say the interaction between investors and the members who had ideas, I think could have been more. Interaction with fellow farmers and sharing the experiences, I think that's the way to go. You can't work in an island.


Another important procedure in SPSS, when you're analyzing data, is something called factor analysis. Now, I like to think of it as looking at your data and trying to find shadows. In this picture, what you have are shadows, those are the black figures that you see. It takes a moment to figure out that you're looking down and there actually are people but kind of sticking straight out. And so in this photo, where you're going from is sort of a three dimensional origin, that's the person itself, to a two dimensional variation with the shadow. What's interesting about that is you maintain most of the useful data. You can tell that they're people that they're walking, you can probably even tell some things about how tall they are, what they're wearing and so on. What you've done is you've made things more efficient. Now, in the data world, that's called dimensionality reduction, where each variable is a dimension. And too many variables can actually be really problematic. You're trying to boil things down a little bit. And you can think about the saying less is more less equals more. More specifically, that is less noise, and fewer unhelpful variables in your data set equal more meaning, because that's what you're trying to do, you're trying to extract meaning. Now, when it comes to factor analysis and related techniques, I have one very important piece of advice and that is to be practical. At all points, you want to remember, what is your goal? So what is the goal? Well, the goal of factor analysis, I'll tell you what it's not. It's not an exercise in analytical purity. You're not there to show that you know how to go through all the steps in the approved format. Really, you're working with your data because you're trying to get some understanding. So the goal of a procedure like factor analysis is useful insight. Try to follow the rules. Do what you can to make sure you don't make any obvious mistakes. But remember, you're not bound by the mathematics, you're bound by what the data tells you about the people. Another way of looking at that is use factor analysis or really any other procedure for its heuristic value. That is, it suggests possibilities to you as you analyze the data, as you're trying to get insight to people. Now, that's sort of a philosophical discretion. Let me show you how this actually works in SPSS. You're going to need to download from the course files a folder that says data here at the end, and from it the cars dot save data set. This is the one that we use in hierarchical clustering as well. And then you want to open up the SPSS syntax file that goes with this particular section. Now, the easiest way to open the data set is simply to double click on it and you'll be ready to go. I do have some syntax you can use if you saved it to your desktop. I've got it open already. So let's take a quick look at the data set. We have a collection of cars listed down the side and attributes like miles per gallon and so on and gears and the transmission and carburetors. That's great. Now I will have to make a very important confession here. This is a very, very small data set for factor analysis. It only has nine variables other than the identifier and it only has 32 cases. Really you would want to have at least several hundred cases and let's say several dozen variables before you can do this really reliably. But this example works and it actually is really easy to see how it's happening and how to interpret the results. The first thing we're going to do if you look at the syntax is we're going to do a default factor analysis and it's actually a misnomer because it's not a factor analysis, it's principal components analysis, but it's in the factor analysis command within SPSS. So let's come up here to analyze and down to dimension reduction. Remember I said that's what this is called. Well pick factor it's our only choice there. And what we need to do is choose the variables that we're going to use to see what we can compress what goes into what so we don't need the name of the car that's just an identifier. We can take the rest of these however and we can put them under variables. Now we've got a lot of options here I'm not going to do any of them I'm just going to hit okay for right now. I'll make the output window bigger and here's what we get from the default analysis we get a text output of the commands that were generated by the drop down menus. We get something called communalities. Each variable brings with it one unit of standardized variants. That's based on how spread out the scores are. And if you standardize them, then you have a variance and a standard deviation of one for each. And the extraction tells us how much of that variance is really able to get constituted through the process that we're doing. An important one right here is the total variance explained because what this has done is it has created components remember I said this is actually a principal components analysis here, which while it has profoundly different philosophical underpinnings from factor analysis, the difference has to do with which came first the factors or the observed variables and truthfully, most people treat them as relatively interchangeable. And if you're using them for heuristic value, it's not going to be a big difference. But what we have here are two components. We have one with 5.472 units of variance that 61% of the original variance of the nine variables. And then another one with 2.341 I'm getting those numbers from right here. And you can see it held on to these two which collectively add up to about 87% of the variance. Now the component matrix shows the relationship between the original variables and the two components, these are like correlation coefficients. You can see that miles per gallon is strongly negatively associated with the first component and really not associated with the second. But number of carburetors has a pretty strong association with each. And so that's a way to start to look at it. But it's going to be a lot easier if we do certain modifications to this. In fact, I'm going to just delete this output right here. And we're going to start over, I'm going to make a few changes. Let's go through each of these options. First we go to descriptives. And I don't really feel like I need the initial solution. So I'm going to unselect that I'll hit continue extraction. This is the actual algorithm that SPSS uses to work through the relationships in the multi dimensional space. You'll see right here, it's principal components. That's why I said this is really a principal components analysis. You've got a lot of options here. Now in many situations, maximum likelihood would be a very good answer. I'm going to choose principal access factor and simply because it's the classical version of factor analysis. I don't need to see the unrotated factor solution, but I do want to see something called a scree plot. And that is a graph that shows me maybe how many factors I should keep. I'm going to come down here and change the maximum iterations for convergence that has to do with the math that's done, I'm going to change it to 50. Then I'm going to come to rotation. What you get here is a multi dimensional space. And sometimes it's a little easier. If you rotate the axes, it can increase interpretability. Now, there are a lot of different methods. Varimax is a method that maintains orthogonal relationships that makes all of your axes perpendicular to each other. There are situations where that's really good. But truthfully, for exploratory purposes, which is what we're doing, I like to use what's called an oblique rotation. That allows your factors to be correlated with each other. They don't have to be totally perpendicular. I'm going to use direct oblimate. Promax is another really good choice. But it usually is for larger data sets. And I've got a tiny one here. Now here I can get a rotated solution. I don't think I really need that. But I do want to see the loading plot. And I'm going to increase the maximum number of iterations to 50. I'll hit continue. We'll come down to scores. And you can save the factor loadings as scores. And there might be situations where you want to do that. But because I'm using factor analysis where it's heuristic value as a way of suggesting what variables go with others, I'm actually not going to do that. So I'm going to hit cancel. And then finally options. This is where you get to talk about excluding cases. I have a complete data set. So I don't need to worry about that. But the coefficient display format. Now, I'm going to sort it and then I'm actually going to have it completely erase small coefficients. Now I've done this one before. So I happen to know that a value of 0.6 under normal circumstances, that's really high. But given my very small data set, this seems like a reasonable choice. And it makes the solution very, very clear when we look at it. So I'm going to hit continue. And then there I'm going to hit OK. I've got my output here. And the first part's pretty similar, except it doesn't start with unit variants for each of these. That's because I'm not doing principal components anymore. I'm doing principal access factoring. And so the math behind it's a little bit different, but we don't need to dwell on that one. Total variance explained, you see that we still have two factors. And the first one accounts for a lot of the variance. The second one accounts for a fair amount. Also, and these are very close to what we had with the principal components. The screen plot is a very simple line plot that suggests how many factors we might want to keep. Now there are several different rules you can use for interpreting this. One is anything that's above a value of one, because one is what it would be if a variable explained simply one unit of variance, but that's what it brought with it. You want factors that can explain more than that. And you see we have two that do a lot more than one. These others are sort of straggling down. The other rule is to look for a bend in the line. And you do see a strong bend right here. So three is where the bend is, we're justified and staying with two. There are other methods that get more involved about checking for the slope of this line and finding things that are above that slope. You can do those at another time. This is a quick demonstration. Now what we get next are three matrices, we get a factor matrix, a pattern matrix, and a structure matrix. They're all associated with each other. And I've got a little note here in the syntax that explains them. I'll come down here. The factor matrix is the association of each variable with each factor. And it's similar in nature. It's analogous to are the correlation coefficient. That's the one that we're going to be focusing on. The structure matrix tells us how much each variable is predicted by the factors because the idea here is that factors come first and variables come second, using what are called the unique and common contributions. So a factor might contribute something on its own, compared to the other factors, or it contributes together. And then the pattern matrix is an indication of each factor's unique contribution to variables variance, those can both be important in different situations, they can help you interpret things. But for right now, I'm just going to focus on this first one. There we go, the factor matrix. So let me go back to where I was. And when we come up to the factor matrix, what you see here is because I suppress values with an absolute value of less than 0.6, we have this totally clear separation. Factor one is strongly associated with the number of cylinders in the car. So more cylinders higher on factor one. And then displacement, very high, miles per gallon is negative, but very strong. And then we have weight in tons, very strong in horsepower. This is really the big factor cars that are really big are going to score heavily on factor one. Factor two is composed of the number of gears more gears, the quarter mile time so the less time it takes to get through the quarter mile that is the faster it is, that's because it's negative here the higher it is automatic or manual, you have to know that zero is automatic and one is manual. So these are manual transmission cars and those with more carburetors. This is really the fast factor. And that's where sports cars are going to this one, this one has the Cadillacs and the Lincoln's and this one has the Ferraris and the Lotuses and so on. And that makes perfect sense. It's really easy to see why that would be the way it is. And then if you come down here, this plot is also really helpful. It's got the two factors we have factor one across the bottom. That's our big factor. And you can see that weight goes on that one, displacement goes on that one cylinder. And then we have number of gears and miles per gallon. Obviously you're on the low end factor two is the fast factor, more carburetors, more horsepower, more cylinders, and lower quarter mile times. And that makes a lot of sense. And so this lets us know that we could boil down our data to really just these two factors sort of how big is the car and how fast is it. And that can give us a much more concise image of our data and allows us to extract more meaning. And that is the overall purpose of a procedure like factor analysis or principal components in SPSS.


This is a presentation that is brand new. I've been working on it for over a year, and there's some data that I have today that's gonna make it worth it. So, you know, I'm super excited that you're here. A little bit of background about me. I've been on YouTube since the beginning, 2005. I own a company that focuses primarily on audience development and growth, and we work on monetization strategies. We do a lot of paid strategies as well. We get that world. I'm pretty much certified in everything to be certified in on YouTube and Google. I generated 33 billion views, 21 gold play buttons. Got me 21st the other day. It was really fun, and 19 billion views on Facebook. Here's something that you don't know about the 21 gold play buttons. I have goals in my life, and it's not necessarily putting the gold play button on the wall or anything, but I wanted to get it in every different vertical that I possibly could on YouTube just to prove that it can be done in every vertical. I truly do believe it, and we're gonna talk about that today, but we're gonna start with misconceptions on YouTube. There's a lot of different misconceptions on YouTube, and I get a lot of people reaching out to me as YouTube support, and they're like, hey, Daryl, there's something's going on with my channel. And I hear the terms all the time. My channel, my channel's dying. My channel, my channel, my channel.  It's not about the channel anymore. It's not about your YouTube channel. Has it been about your YouTube channel for a very long time? What you need to do is start really understanding what it's truly about. When you switch the mindset of what it actually is, and you start delivering what YouTube actually wants, then it changes it. This is the key right here, that channels are no longer the dominant as they must were, but it's all about something, and the key is this. It's all about video, the YouTube video, and the viewer. And more importantly, getting the right type of viewer to watch your video. And what we're gonna kind of talk about this is really going over the algorithm and what it's looking for and helping you. And I can truly show you what you can actually do to improve. And a big applause to YouTube. I know YouTube has gone through some difficult times, but some of these that they're introducing now are game changers for you as creators and also brands. And I'm gonna talk about that specifically in this presentation. So, let's kind of go off of this. The algorithm, I know a lot of people really get frustrated with the algorithm. There are multiple algorithms on the YouTube. What makes up the different things that are happening on YouTube is the YouTube AI. That's basically machine learning. The machine is trying to learn and predict behavior for achieving the goals of YouTube. So, what do they want to do? Well, they're gonna learn and grow, and so there's a lot of updates that happen. There's over 200 updates that occurred this last year. And 2,000 split testing experiments that they go out and test things and try to gather more data to get the results. So, they actually set goals, let the AI do its thing, comes back and they see the results. And based off of that, they'll pivot a little bit and before you know it, it becomes an update. These updates are pretty big and they can affect us as creators if we're focusing in on the wrong things. And I think that a lot of creators that are creating content on YouTube really focus in on the wrong things and they're really missing the mark. And I'm gonna show you some of the things you can even look at. Goal number one for the AI is to predict what the viewer will watch. It's all about the video and it's all about the viewer. Now, when you can start figuring out who your viewer type is and kind of understanding that target audience and that target demo and really understanding what's there, then YouTube will help promote your stuff. It'll promote your videos out to the right type of viewer. So the number one goal that the AI has is try to predict what people watch. Why is that? Well, it's to maximize watch time because if they can predict what people will watch, they'll keep the viewers on the platform longer. Now, this is the key, is creators that understand this. Really just understand, look, I understand my target niche. I'm very localized on my channel. I understand what's going on and you're giving content that resonates really well with an audience and you get them to come back to YouTube day after day, then you are going to be blessed by the YouTube gods and you will literally start getting views. But today I'm gonna explain to you that it's changed a little bit and it's good for content creators, really, really good because understanding these goals will help you achieve your overall objective. Now, there's a paper that was released a couple of years ago by some engineers really talking about the algorithm, really going in depth on Google Brain, which is the engine for the machine learning on YouTube. There's a paper you can find online, really, really in depth. I'm still, my head's still spinning from some of the stuff that they're actually talking about in some of the equations. But ultimately it's the goal of predicting what viewers want. So I want to kind of explain an example of how the AI interacts. Now, let's just say that we have a viewer. This viewer loves to watch YouTube on their mobile device. Okay, so when they go on their mobile device, YouTube's starting to gather data on them specifically and they're starting to figure out their viewing behaviors and patterns. So they actually have viewing behavior and patterns for all of us and they're starting to identify what we're going to watch. What is the higher probability for us to watch next? So that viewer goes on the mobile device, looks at their phone and says, okay, these are the results that I get. I got video A, video C, and video B that's being suggested to me because I'm on the mobile device. Well, they get home, they turn on their Apple TV and it's get different results. Why did they get different results? Is because the viewing behavior of that viewer. Even though they're on a different device, they know, oh, when they're on mobile, they actually only do shorter videos and they have a lower tolerance for these types of videos. So let's suggest these types of videos but on Apple TV, the app, let's go ahead and give them different results because he actually did this person, this viewer has a longer view duration and will tolerate longer videos. And so what are we gonna do? We're gonna suggest them longer videos. So it's really, really intelligent of what it is. This is just an example of how the AI will work and think is really trying to predict what's gonna be best for the viewer. So it's gonna recommend shorter videos for this specific viewer in a specific case because of how they view on mobile and also they're gonna send longer videos for them on the YouTube app because of how they view YouTube on the YouTube app. So I hope that makes sense because what they're trying to do is predict that behavior and I can't reiterate this enough. It's always about the video and the viewer and if you can really start understanding and getting in the heads of your target audience and really knowing who they are, that will give you a better idea of how to actually use YouTube to start suggesting your videos. So what is the rule and traffic source on YouTube? Okay. What is the fastest way to go on YouTube? Suggestive videos. Seriously, it is suggested videos.  But I don't want you to get so fixated on subscribers. I know that seems really odd because everyone has this and it's, I think it's just like the social status. I go like four million subscribers or whatever it is. But it's always about the engagement of the viewer and when you understand how to trigger that, then all the success will come with that as well as long as you understand the metrics and the triggers that will help YouTube decide and predict for your ideal target viewer. Okay. And so suggested videos is the fastest way to grow. In fact, I just saw a friend of mine started a YouTube channel and did it for years, but he had a breakout hit that picked up and he got 400,000 subscribers in a matter of a few weeks just off of one video. And so it's real. So there is a huge shift right now happening how YouTube suggests videos. And this is something I've been studying for years and I gotta put a disclaimer out. We manage a lot of channels and we only have data that we understand. And so I needed more data. I needed more data to draw the conclusions of what I was actually looking for. And I've seen a huge shift of how YouTube actually suggests videos. And I know a lot of you have reached out to YouTube and you've been into your frustration on Twitter because of some of the changes that occurred and you don't really understand what's going on. And so today my goal is to show you how YouTube is shifted and how to leverage it. Does that sound good? Okay. Big thanks to VidIQ Rob Sandy. Literally saved my bacon because I needed a whole bunch of information. And so he collectively gave me a huge sample size that I could deal with. So it wasn't just my small little 50 channel sample size. We had a huge sample size of information. Then let me show you what YouTube is looking at last year for suggestions. So on this there's a graph. The blue is suggested video. The red is subscriber. Now last year in April, the YouTube was suggesting a lot of specific videos in the first seven days. In fact, I was sitting on the stage or presenting on the stage talking about a seven day deterioration rate from your suggestion. You can see exactly what was happening in seven days. It was deteriorating. But things changed. And I wanna show you how things have flipped around and it's gonna help you change your strategy from it. In June, it goes up and this is on all the channels that were under 100,000. We'll show you some other results here in a second. You can see that where it changed here in September. There's a lot of people that are like, oh man, my subscribers are being notified and there's a lot of, my subscribers aren't seeing my videos. Look at that, they literally dropped. And then come, the big one was actually right around Thanksgiving. There's a huge change to happen in December. Notice that the blue line now is below, literally below and the subscriber is up higher. And then finally, April, here is the data. Now, this is what's interesting. If you were looking to the chart before in that first 24 hours, suggested a year ago, YouTube would suggest your video, 66% of those views would come in the first 24 hours. And then you can see the percentage just go down. However, in April, this year, look, it's only 28, 28%, but then you have 50, they're getting it out more to your subscribers. And so from doing this, I wanna show you the different things. We don't have a lot of time here, but it does change just a little bit for your size of the channel, but it doesn't change that much. And the big thing about it is YouTube is now normalizing this and really getting it in a way to suggest it in a way to get us all more views if you understand how to actually make that trigger. So that being said, this is probably the most fascinating one is the million subscriber one. Notice suggested videos was 66.7% in that first 24 hours last April. This April, it's 16%. But the subscribers numbers is 60%. So the more subscribers are actually viewing the videos, we're not gonna get into the whole notification debacle. Okay, so here's the conclusions to this. Views are being suggested more after 14 to 120 days. What does this mean for you as a creator? This means that you have a really long-tail strategy that you can get a lot more views after 14 days than you can before 14 days. You can actually start taking breaks now, you don't have to kill yourself trying to upload every day because a lot of the views are gonna be on the tail end. And if you do the strategy right, you can get a ton more views in less uploads. Also, this is probably the biggest thing for me is data gathering is now delayed in minutes instead of days. Now before, what you do is when you actually upload a video, YouTube would look at your metadata, they'd look at your title, your description, your tags, your closed captioning and then literally start to suggest that out to your own library and get suggested views off of that. And last year, it was really heavily pushed in that first seven days. Well now it shifted where they're able to gather the data that you need, disregard, I would say all the meta, but most of the meta and look at the next data points that they're looking at. And let me kind of talk about these data triggers because once you understand the data triggers that helps you understand how to shift your strategy and how you need to release your videos and such. So they're looking at the metadata in the first few hours. They're looking heavily, heavily, heavily, heavily on the viewer history data. And so if you have a viewer that's notoriously like religiously looking at your back catalog on a certain topic of videos and maybe watch two or three times the same video, well there, if you release something similar to that, of course that's going to be heavily suggested in that first seven day period to that subscriber because they're going to watch it. And it's really going to follow them around until they watch it because they're highly engaged with that. They're also going to look at people that are similar to that and help grow that and expand that, but that's more on the tail end of the suggestions. We're going to talk about impressions versus click through. There's only a couple things that ever got me really, really excited about the things that YouTube released and this is one of them. I'm here to tell you this right here is literally a game changer for everyone sitting in the audience.  And so it's really, really important to understand this. And seriously, I don't know if there's anybody from YouTube here, but honestly my hats off, this makes everything all worth it because this data is what I've been just craving for because we never knew the impression versus click through rate. We could only guess and now we can actually make strategic data-driven decisions to make better content to get it more suggested. Now there's a couple of things that we're going to look at. We're going to go in depth on this and really break it down. But I want to show you the results. This is one of the channels that we had. The only thing that we did was have the data of understanding the split testing. Like we could only guess, oh maybe this thumbnail is not performing well, because all we were doing is guessing before. But all we did was change the thumbnail. That's it. There was no other strategy. We didn't change our content. We didn't do anything like that. We just changed the thumbnail and we had three times the amount of views just based off of that. That is huge. We didn't do anything to the content. All we did is spend a little bit more time on our back catalog, our underperforming thumbnails, made them better thumbnails and YouTube started to recommend them more. So much so that we got three times the traffic. The views on this is ridiculous too. So what is a good click-through rate? I know a lot of people says, hey I got this data down now. What is a good click-through rate? Is 5% good? Is 12% good? What's a good click-through rate? Now for me, I'm going to answer it a little bit differently. To understand YouTube, you've got to understand that everything's individualized and very niche-specific with video. So it's going to look at similar videos that are out there and see the click-through rate and see what their average is. And if you're higher than that average, then that's a good click-through rate. But for me, I always want to get a higher click-through rate because if I get a higher click-through rate, that means I'm going to have a higher average and YouTube's going to give me a higher percentage of recommending my content. And so what we're going to talk about is the long-tail approach. And this is something that... I was just talking with my friend at WWE. Like, this is a strategy that bigger brands and stuff actually do is the long-tail approach. They're not all putting out new content, but they're going to go through their back library and figure out how to maximize it because YouTube is now promoting older content really, really heavily. And if you can optimize that, you can get more views without even increasing your workload. So that being said, there's a couple methods, but after 28 days, I found that that's a good time to do A.B. testing on your thumbnails. Now, YouTube used to have a beta a long time ago on thumbnail A.B. testing. I don't know if they currently have that. So you might want to reach out to your partner manager and ask them if that beta is still open or where that's at. YouTube, if you're listening, if there's anything that would ever last the community of YouTube, it would be this, that we could actually do A.B. testing on our thumbnails. You provided the data for the impression you clicked through, but if we can pick winners of what thumbnails, then we can be more like Netflix if we could change the thumbnail for one demographic to the other. I would love you forever. And I wouldn't go to Instagram. Okay, going back to this, but the 28 days is really, really important because that's kind of what you get a ton of views and you can actually do some good split tests. Here is a split test that we get internally. You can see our click through rate was really good. I think anything above 12 is really good, but for me, I'm never satisfied because we can always do better. So with this, we had 14.2%. You can see it equated to over 100,000 views and so on by just changing the thumbnail. The thumbnail, no title, no description, no tags, just the thumbnail, it started getting recommended more where we're getting 23.1 click through rate. And notice the graph that YouTube's preventing 99.8% out to potential people that would be interested in that. That's huge. And what I would encourage everyone to do is have a strategy and it's worth hiring someone to design your thumbnails, it's worth hiring someone to implement this if you don't have the time to go back and literally do some split testing through your older content that's 28 days to 45 days or even older. What I like to do is go in, this is a Ninja tactic, but go into your real-time analytics, see what your top performing videos you can sort by last 60 minutes, 48 hours, and see which one's the 48 hours and which the videos that's on the rise that's a little bit older, it could be a year old or two years old or whatever. Just do this there and go up through the click through rate on that and then I literally will change that. I'll do an AB test on that one and I've seen it just go through the roof. Like literally get tripled the amount of views that I would have gotten otherwise. Peter Hollins, if you don't know who he is, he's on YouTube, he's pretty big. I really like him a lot. He sent me this graph. If you go to TubeBuddy, go to TubeBuddy.com. You can get this tool. It does split testing for you and it does it in a way that's okay. It's not the best way, but it's the only way that I found possible is to actually do good thumbnail testing, AB testing. Now what I do is I run these tests on my older content. I do not do it on the newer content and I'll kind of talk about that strategy of how you actually need to do that. So triggering data suggested video views. It's all about the metadata, your viewer history, your impressions versus click through rates. But then it's about audience retention and this is something that every content creator needs to pay really close together. Now, the new creator studio is amazing. I love it. It's like literally organizing in a way that common creators really understand how to optimize. And we need to really understand that and also true viewer engagement. I'm gonna talk about that here right now. I'm gonna give you a real example. I actually started a brand new YouTube channel and I have some partners in it. We got our first upload in May, May 30th, 2018. Zero views, zero subscribers. We didn't do any tactics. They aren't real YouTubers yet. Our target audience is very specific. Five year olds to 13 year old boys like we're really hyper focused in on that. We released some videos. This is one of our videos of the most powerful nerf gun mod that we did. It's two twin brothers that are my partners on it. Thumbnail is super, super engaging for sure. It's kind of telling the stories, very interactive. It's everything best practices that YouTube tells you to do. Well, here's the real thing is right here, we had 643 subscribers. And what we were able to do and what I really like to pay attention to is the average views per viewer is 2.7. And we'll talk about that because really understanding what that means can help you literally leverage it in a way that you need to. So here's their click through data. You're able to see that we're getting 50% recommended. It's a brand new channel and YouTube's recommending 50% of it. So when someone watches it, half of it's coming from YouTube suggestion right there. Our click through rate is decent. I wanna be in the 20s because I like to win. And then also our average view duration isn't as high as I like it. I like it around 50%. And so they're still learning and we're still growing from there. But the engagement is the key. Have you guys ever seen the audience retouching graph or are you looking at your data when you're releasing a video? What you wanna see is these little spikes that happen in the video. That is true engagement. It's not a like, it's not a share, but it's what the algorithm's looking at is a true engagement. That means they literally ring loud in the video and watch that part again. Okay, that is super powerful. Now, I've seen content creators get really creative with this to engage the community to as they're watching the videos that they catch certain things that might have something pop up after they wanted to do it. They get pretty creative with it. That's what you need to be looking at is how can we get these little pops to get higher than normal true engagement? Because when you get this, that's when you have massive growth. So really to understand how to actually get suggested views, you need to look at your impression versus click-through data about four days into it. If you do it earlier than that, it's going to be skewed the wrong way. You need to give it about four days and enough time to collect some data. And what I would do is if it's under the percentage of what you average, you get on an average, change the thumbnail immediately. When you're doing your thumbnails, I would design maybe two or three different versions of it, have it ready to go so that you can switch that out. I have literally seen channels that literally has stumped growth in that first four days but they changed out the thumbnail and the video took off. Does a couple of things. People re-watch it because they think it's a new video and they're able to do it. I'm not saying be deceptive, it's just saying let's get a higher click-through rate. Next, I would do an AB test. I would do an AB test at 28, 45 days. I would literally go back through a past catalog and literally pick videos that you're cherry picking to do AB tests. Don't go hog wild where you're doing your whole inventory. Like literally be strategic of like 10, 15 videos that you're always just testing and improving. I would go with some of your top performing videos. Do not, I reiterate, do not mess with the metadata. Just change the thumbnail. Has no problem. If you start changing the metadata then there's some other things that you don't wanna have happen. Focus in on audience retention. Try to get it in the Goldilocks zone. The Goldilocks zone is 50% of the people that actually started the video finishes the video and be very strategic with that. I found the drop-off rate, if you will just fix the last 30 seconds to 40 seconds of all your videos, you can get a higher retention rate. Some people draw it out way too long and they should just end it like within 10 seconds and be really, really engaging. There's even some content creators that just end and they're like, what, what, what did I just end? But it's like literally getting that retention to happen. And so the only way you can do that is look at the data, look at the videos that perform higher, look at the data that YouTube's providing us and seeing what's going on. You can literally play the video and see what's going on. You can make some assumptions, you can see what's being commented and so on. Really, really important with that. The next is try to trigger true engagement. Now, what I like to do, this new channel, like we're all about true engagement because I truly believe that's a way to get suggested more. You saw this new channel, it's got a ton of views. Ton of subscribers in a short amount of time based off of that and it's being more interactive with the audience and to engage. There were some ways to do that in the past that we can't necessarily do now but you can't be more connected organically with your viewer where they'll want to be more involved with your content. So in this, all this is, it's not new, it's best practices guys. Really at the end of the day, YouTube literally has given us the keys to the kingdom with giving our impression through click through and having that first data metric, that first trigger that we need to really make good data driven decisions so that we can actually say, oh, now we're getting a higher suggestion. Now, wait, we're getting some drop off. We need to work on our videos to actually get our videos to be a little bit better. It's a way that we can re-edit them or cut them in a different way. They'll be more engaging. And truly, I want everyone start thinking of, this is probably the biggest tip that I can give you, is think in video series where you have like four or five or six videos that all relate to each other. That is super important because what it's going to do, it's gonna feed off each other and start going from there. And if you can actually get it or similar channels that have a similar type of audience is doing the similar type of things, then you can start feeding each other suggestions as long as you have a lot of crossover viewer data. And so you're able to see a lot of channels. Like one of the ones that I really like is Steven Carter's share of Lizzie Sharer's channels. And that's what they're doing. They literally do videos that compliment each other and they're able to grow from there. And so realistically, at the end of the day, check your information. Don't overanalyze where you have paralysis but really be very strategic of looking at your click-through data. Whatever the percentage is, let's make it go up and then really look at your audience retention and go from there. Now, I've had a couple people that says, hey, I got 78% click-through rate. No one sees 78% click-through rate. I'm doing pretty good. I says, well, there's a little graph above that of how YouTube's actually promoting that. If you're not getting it to the 80%, 90%, 99% of YouTube's suggestion, then there's a problem with that. So yeah, your click-through rate's good but your other problem is in the other data that YouTube's actually looking at. So guys, thank you so much for coming. There's so much you can learn here. There's a lot of creators that can really do it.  That's why I'm here at VidCon. I really wanna answer personally your questions and so on. Thank you so much for coming. I hope you have a great time.


Members of a small community in Malaysia gather for a celebration. The Royal Malaysian Navy and the U.S. Navy teamed up to build a new conference room for the town's community center. Their efforts are a part of exercise cooperation of float readiness and training 2014. What we do is provide humanitarian assistance for the locals and at the same time work side by side with the engineers from Malaysia in sharing ideas and construction and they also share our ideas as well. These CBs are also working with other nations. It's our unit that is actually going around providing our construction assistance and sharing our construction ideas with whole nations with Thailand, Malaysia and the next step will be coming Philippines. The unit will be using something new for this year's exercise, a cold-form steel machine. It's actually provide us a cold-forming steel studs that we can actually use for framing and be able to erect buildings in a faster and more efficient way. Pretty much it feel like we might probably make a little bit of history, something that actually we can take pride on if it gets adopted and accepted to our command that we can actually look at it and maybe somewhere in our near future that hey look I was part of this. The CBs are the first unit to ever take the machine out to sea. You're Airman Brandy Durr, Southeast Asia.


Pensioners in Ogun State have protested the non-payment of their 12 years' gratuities by the state government, which is estimated at 68 billion era. The senior citizens, under the aegis of the Nigeria Union of Pensioners, took off from their secretariat in Lemme and marched to the governor's office in Okemosa, Bioputa. Blimindi governor for his failed promises to alleviate their sufferance through prompt payment of their gratuities and other entitlements. Speaking on behalf of the protesters, the chairman of the NUP, Comrade Wahid Oloyode, accused the governor of deliberately punishing pensioners by denying them of their entitlements. Addressing the protesters, the secretary to the state government, Tocumbo Talabi, assured the pensioners of a quick response to their demands. We are at the end of September 2022, and no release has yet been made. Added to the above is the reason I put lateness in the release of monthly pension, which has been caused on top in Nigeria-Hashib to the senior citizens who spend all day on various old aegis. It is an indispensable fact that the state's internal aegis has increased autonomically in periods over the years as we live and reported on media on several occasions by the commissioners of the NAC. Yet, they have never reflected in the partial assessment of their due pensioners. From their perspective, it becomes obvious that this excellent sprint of Dr. Abiyadu MFR is incestuous to our flag, and it's helping to sustain its nonchalant attitude towards the vulnerable. This administration is trying its best to make sure that even the existing one, we meet them, and we thank God for that, but I'm sure that with this due now, everybody's seeing it. The Excellency, if you have been around, we have organized another work before, where you express yourself to the Excellency, but the Excellency is not around now. The only commitment that I can give to you is you have the legitimate right to make this demand. Nobody's going to say it is wrong, but when the Excellency comes back, as soon as he gets back, we will organize a team of five, six, sit with him, put them on a chair, get off of you, and from that meeting, we will also see what can be done.


Our 26th president of the United States, Teddy Roosevelt, he once stated, speak softly and carry a big stick. Speak softly as diplomacy, but diplomacy will only work if you have the strength to back it up. Ladies and gentlemen, behind me, to the right, to the left, is the big stick. The ones who do the work, who put in the sacrifice, every day to make sure that this country, this most beautiful, great nation still stands. During my time here in the MEPH, gosh, I could go on and on. So much has happened over the last little over three years. And first off, we have 53,000 Marines and Saders who every day are just training to prepare to do what someday our nation may ask them to do and need them to do here in one MEPH. We have the aviation combat element who drops bombs from the skies and provides a close air support, direct support, and provides lift and capabilities. We have the ground combat element from our infantrymen who cross the objective to our tanks and artillery to provide fire support and our logistics Marines who keep it and sustain us for the long fight. And every day, all of those elements of the MAGTF are training and preparing and deploying. And right now as we speak, many of them are in harm's way.  I think it's critical to conduct a great turnover because as Marines, we always want to leave whatever we receive in better condition than we received it. We want to turn it over in better condition. Everything from our gear to our weapons to our facilities and most importantly, our people. As the SAR major, I owe it to those Marines to do a great turnover because the people in this organization are what's important and a better turnover than I can do and set my replacement, SAR Major Porterfield up for success. It helps those Marines and Saders who is the backbone of what we do every day here in one MEPH. I'm both honored and humbled to continue to lead the legacy of one MEPH. Throughout our history, one MEPH has been the warfighting organization that our country and our nation has leaned on. And that's important. So I'm just honored and humbled to be in replacing one of my mentors in SAR Major Castle. Throughout my career, I've been pretty diverse in opportunities and different billets. And for that, I mean, it's kind of really helped shape me who I am today, along with some exceptional mentors and guidance that I've received throughout my career. So I think all those together over 29 years has kind of been my secret of success. One of my main priorities is for all Marines and Sailors to really live up to our, continue to live up to our core values of honor, courage and commitment, but more importantly to take care of each other both on and off duty and not have a bystander mentality because we need to make sure that we truly protect what we've earned.


Building on last year's success, Defender Europe 21 will build readiness and interoperability between allies and partners and prepare our forces to rapidly respond to crisis and conduct large-scale combat operations if called upon. It will exercise US Army Europe and Africa's ability to serve as a combined joint force land component command and as a security partner in the strategically important Balkans and Black Sea regions, while sustaining our activities in Northern Europe and Africa. Defender Europe 21 will feature the participation of more than 30,000 multinational forces from 26 nations conducting nearly simultaneous operations across more than 30 training areas in 14 countries. Critical to this endeavor will be the strict COVID prevention and mitigation strategy implemented by US and participating nations. Exercises like Defender Europe 21 demonstrates that the US commitment to NATO is ironclad and that NATO allies and partners stand stronger together.