anything else whether it's a piece of electronics or it's a piece of software there are ways you can go ahead and look at things look at the behavior of things and figure out what works what doesn't work what seems to affect things what seems not to affect things um sometimes you come up with some interesting side effects that you didn't expect and we'll actually talk about some of those um you know everyone's you know experience may not also be the same so uh I'm going to caveat all the information I'm sharing as not necessarily a recipe because you know the point of this session is really to try to get you people to be able to go ahead and look at your data because everybody you know we're all writing different books different genres you know maybe different stores your focus is in French or whatever um the you know each of these stores each of these genres everybody's experience is going to be a little different but you know I've talked with a lot of people I've pulled a lot of data and I've got a lot of my own personal data as well so um so I think you know from a statistical point of view I I do have some information that I think is relatively true now um for those of you who may have seen my session last year um some things have changed and that's kind of the point these things aren't static you know it's it's the engineers at Amazon in this case that you know occasionally how they tweak things evolves so how do you deal with you know you've got a recipe and you go my recipe isn't working well the answer is you need to understand how how how do you develop a recipe for you so that's really what this session is really going to be all about so again caveator don't blame me if it doesn't work for you I'm trying to give you the tools to figure out how it would work for you my thing may not work for you but I think it'll get you very close to something maybe better than what you have maybe not we'll see okay um and it's strange for a physics guy here or data analyst guy to be talking about marketing funnels but here we are um so you know what one of the takeaways you know what what is a campaign all about you know what are you even trying to advertise to you're you're trying to you know people who are established like like for instance let's say Stephen King Stephen King has an audience ideally marketing spend spend for Stephen King is going to be to people who maybe aren't reading him you know his readers his big fans they're they're waiting for his second book already or his next book already so you don't have to Market to those people they're sold you know they're sold before you the book was even written you know so you're really marketing the people who don't know you you know ultimately you know but you want to evolve those people into those fans that you don't even have to Market on you know too so you know so so you the concept of cold warm and hot really does apply um you know you know and I kind of enumerate my goal on these slides as much as possible I've uploaded them to the schedule app so anyone should be able to download them um is they should be Standalone though I I will I'm not going to read the slides to you I'm talking to them so what I say may augment the slides but they should be good enough standing alone so I I'll refer to some of the things specifically though you know cold yeah you know is a is a familiar Concept in marketing where you know it's like a cold call yeah you you know you've never talked to this person they don't don't know who you are but you're trying to offer them something to buy um that's that's really what campaigns are about and then once you have a little bit of information you know maybe they've bought a previous book you know and you know they're not necessarily fans yet then you know you know we got the concept of of warm um you know that they might be aware of you but you know it's like your book was eh okay but they might be willing to give you another try and that Mark marketing campaign suddenly pops up and they say oh yeah I read one of those books it was okay um oh a new one let me look at it oh that looks interesting I'll go buy it and then you know then hot fans are the ones you don't have to spend any money on they're already they're signed up they they're on board so I mean we're going to talk about this marketing funnel more later but before we go really very far let's start talking about the nuts and bolts um yeah my I I like cartoons um so we we need to think about Amazon from from the point of view of Amazon what are they trying to do they really you know sure sure they make money on us buying advertisement But ultimately that they they make money if they sell product on their store and if they don't sell product on their store they're really they don't have a business model so they're trying to find you know if you're advertising a techno through or you're finding you're advertising fantasy whatever um they're trying to find the right person to you know um to to buy it so they they only want to present ads to the people who are likely to be interested um you know and I and I I'll give an anecdote like one of the worst things people can do and it's and it's it's a very common problem and it's not intuitive what you would think would be an issue issue so imagine you're just starting off and you're creating a campaign and you realize oh okay um well yeah I don't have any fans yet this is my first book um you know hey Mom Dad uncle aunt you know you reach out to all your friends and neighbors and whatever to buy your book I mean it's a natural instinct but I'd say it's one of the worst things you can actually do um why because think of what Amazon does you know the back and processing of the of Amazon is an algorithm it's a program so it's learning from what you do or what happens with the thing you're offering so imagine you're offering some hackin slh horror novel and yeah your grandma buys it because you know it's like she's not not going to read it she's doing it because of you but what does the algorithm learn from that the algorithm learns that okay Grandma what does she normally buy well she's into knitting and she buys yarn and and crochet needles and other things like that and like oh well she bought the this book well maybe this book is interesting to the yarning the yarn Community obviously then that's going to be a major failure ultimately because you you have friends and family that may not normally be a reader of your book and you don't want them buying you don't want people who wouldn't normally be a reader of your type of book to be buying it because it's teaching the algorithm something that's wrong it's it's it's misleading it and ultimately that's when the algorithm you a lot of people experience you know and I'll actually talk about this you know I can't get Amazon to spend any money it's a common problem a lot of people have it and it usually has something to do with that where the algorithm is just so confused by what you what it's been told about this book it just doesn't know what to do um you know and it starts off on a bad foot with regards to you know who who are your initial purchasers and and it and it's like trying to you know steer a boat you know you can course correct but it takes a while so let's start talking about that um yeah yeah I mean I talked about this a bit so you know I'm I'm going to give you an idea and and and in this specifics of what I'm talking about with regards to the algorithm and I'm even going to give a formula and those who are here last year um will be familiar with it the details of the formula aren't important um but the key elements of what we're talking about here are um so and I Bo boil it down at the at the bottom so you know the things that Amazon tends to look at or the algorithm tends to look at is you know what what what's what's the sales history you know so did Grandma buy it okay and and what did she buy you know so so it starts to create this web of information you know trying to correlate who might be interesting buyers for this thing that they have to sell um keywords you know there's various types of campaigns so you know are there keywords that are you know when when you put a book up for sale It'll ask you for some keywords that you think are relevant you personally the author thinks are relevant um you know and then it's going to you know sales history uh includes a sales count like you know sales history um is interesting you know but it gets more more and more interesting the more sales you have it gets more and more data um you know and then obviously a bid you know how much how much are you willing to pay for a click is relevant so all these things you know come into play um and yeah so I I I I put this together to give an example of what I'm talking about a lot of the details you know you know a lot of you aren't math people you know so you know we won't nerd out over the over the specifics of the numbers this is just to give you an idea I'm trying to storyboard what we're talking about so you know and so let's walk through this so imagine someone searching for a thriller um you know thriller book sold to someone who buys chocolate diet food and protein powder Book Two Sold to someone Thrillers video games gardening supplies then science fiction and batteries you know you you can read the rest so you know I'm going to say like book one you so let's see um yeah how many of them ticked off on the Thriller topic all right so book sale one you you know let's say your F your first sale had nothing to do with Thriller um so you're like all right the relevant score there is a zero I'm like you so you're teaching the algorithm something and going you know is this book associated with Thrillers even if you say it is it's trying to get a positive affirmation from the sales history so you you give it hints up front when you check in the book what you think it is and then the algorithm is going to go ahead and say all right that's interesting data I'll take that as under under consultation and then I'll look at what I see and it's going to start learning okay well you know the book The the person who bought you know the second book yeah it was a thriller so let's give it a 0. five and and no for Thriller on the third sale four sale wasn't having anything to do with Thriller background you know book five sale was so you start seeing a number kind you know if you thinking about a program as some like you know you know mathematical thing it starts to calculate a number um so you know the number itself is not that not the point but it is using the information and doing something with it it's it's creating it's got a formula it's plugging it into um so uh you know does the book have a direct hit so you know and I and I mean it's not important for this discussion but you know for for those who are going to read through the entire thing you know I'm I'm talking about how would a formula actually work when using this information now imagine you know when a reader is searching for a book it's looking through an entire database now imagine yourself as the reader I'm looking for a book um and you know and each book it finds it checks the book sales history calculates relevance score calculates a keyword relevance and that you know you know creates ultimately a match score so what you're seeing is a situation where you know when you check in a book you you you tell it a lot of things um you tell it with keywords you tell it um you know because there's a specific section actually like seven keyword or whatever you tell it what categories um you know so like the genres that you you think it's associated with and um you know and then it starts to use you know live data from what it you know from what it generates um you know the Sal that occur and it starts to build a score you know and if you just imagine it doesn't matter the details really about the relevancy score but it creates a score it's kind of like you know you know I've never done any of these dating apps but I'm assuming that in a dating app you you you'd have a match score it's like oh you're like 70% compatible with somebody that's really what you're doing between the Amazon algorithm you know the the reader is trying to make a love connection between the reader and the person who's trying to sell a book so what's your love you you your match score there um and so we'll we'll take a couple of case examples um and it's you know at least in my angle it's hard to read that so yeah so you know case one two 3 4 um so yeah and I used a couple of examples that I think are indicative of what I'm talking about um so you know so a book with a solid history has sales um you know bids 40 40 cents so you know the you know the person who wrote the marketing campaign bid 40 cents to match up um you know he he's bidding on Thrillers let's say um and and you know ultimately there's a direct hit on a keyword in the book description you you've described yourself as a thriller um and so you come up with some magic match score 7 okay you know so so and and that you know cost you you know a 40 Cent click um you know now these match scores don't necessarily mean you know so if you got to click obviously that doesn't mean you got to sell you got someone's interest um you know the the other one maybe has the same thing but you know and you know the mat score for case one was A7 for example bidding 40 cents um so you paid 40 cents um yeah or or you would pay 40 cents um um you know and the other one is you know they the lower bid you know but you know has more relevant data and you know match scores higher um and then you got a case of a new book with no history you know um you you're you're bidding 50 cents you're like bidding a lot and um and you end up having a025 match score so you know what what I'm indicating here is yeah go to the right I guess um you know when the reader searches and the algorithm finds four books they're going to be presented to the reader in this kind of order so um you know and think about it if you look at this example the person who was bidding you know was willing to pay the most for clicks didn't actually win the bid and and let me tell you how I got to this scenario because I I I learned something very quickly when I started trying to do marketing as a data analyst um you know when I was trying to you know work on my marketing campaign on Amazon and it was okay and and I hired a professional marketing person and they didn't do any better um and you know so I'm like is this the best that can happen so I I I I went ahead and talked to one of my my friends who who's a s figure author and you know and and has been for a long time which is a key point of this anecdote um you know so since like 20 it was in the beginning of the Kindle Rush Etc and I sat side by side with him and compared because we we literally I created a campaign he created a campaign we both write largely the same kind of stuff and um you know yeah his top you know I I match his readers and he matches mine um and so I put a I don't remember the exact bid but you know I I put a 30 Cent bid in for you I'm willing to pay 30 cents for clicks he did the same thing yeah and when those campaigns activated we looked to see where do we land on on like the carousel most of you are probably familiar with I I'll show examples but uh of the carousel where you're seeing the spons ads he ended up on like page one or two I was on page like 17 you same bid you know so this is kind of just showing you you know the the ele it's not just the bid you know there's history you know so you you'll find that over time the more sales you get the more data you the the more track record you have the better campaigns tend to do um and it and it isn't just Associated directly with the campaign has also to do with the um you know the author account you the publishing account so um you know so in this example um you know the person who got you know who would be top of the food chain presented to a reader would be the guy who bid bid the least um because he had a solid history and lots of sales um you know whereas you know someone who literally had no history and no sales just starting off and was bidding higher didn't get in um you know wasn't getting an impression so to speak um you know and then obviously people with Messy history and some sales are going to have problems as well even if they're bidding high so these are all things that you know Drive the behavior of what we all see um obviously and I talked a little ahead about this you know where do we see these ads you know anywhere you're seeing the sponsored tag you're seeing ads um you know and in this case you know when I was searching for um you know one of my titles yeah I showed up twice you know my sponsored ad kicked in because it's like oh you're looking for something factor and you know lo and behold there it is you know my sponsored ad popped up right at the top and then um you know and then then it actually found one of mine um you know and then some other yeah whatever um yeah and this is also you know you know a demonstration of of the carousel is um you know and I I will actually emphasize something I didn't emphasize at all last year is um I'm a big fan of advertising paperbacks and I'm going to I'm going to go into why um I whether I have that in session one or session two so stay tuned but um but but you know briefly speaking paperback most of you probably don't advertise paperbacks because you're like I don't sell any paperback so why bother um there's a whole lot of reasons that you want to and and in some cases because some of the categories that exist only exist for paperback they don't exist for Kindle so um you know so so I've you know the there there are things that show up that are um you know uh you we got huge huge competition well there's a lot of books out there in paperback and if you think about it what is a campaign a campaign you're trying to associate what you're advertising to a target audience that target audience is other books other people's books um you know because that's what Amazon really is it's selling stuff so if there's only 12 of your genre you're only going to show up on 12 books it's usually not a good idea um there are a lot of paperbacks out there you you we're blinded to that because we have a bias you know we all collectively do um there's a lot of paperbacks I'll I'll show that data later um you know obviously there's brand advertising I won't really touch on to that at all today um and then this is coming back it went away for a while and it's coming back I'm seeing it more V in various Stores um the more you sell most people's experience is the more you sell the quicker the ramp is and why is that um well you're getting more more history on your campaigns um and then there's also features like this where you know again Amazon's Amazon's the Fiddler On The Roof yenta is trying to it's a Matchmaker it's trying to match the reader to the B book and you know like hey customers who viewed Whatever item you're looking at also like this and you know like one of my books showed up in Mark Dawson Etc um so and and that's free I didn't pay for that you know that's Amazon going ahead and saying with the algorithm and going you know what you're looking at a particular book well if this doesn't catch your fancy you know maybe some of these are none of us pay for that you know that's that's gold um and and helps expand Word of Mouth you know where where where some of the sales come from this is one of my key points at the very end of this the second session is um ultimately what we Market is a small percentage of our overall sales or at least it should be um because ultimately we're trying to bring people into this funnel and um and sales occur there but we're over time growing a larger and larger set of fans um um larger set of readers and then as we put stuff out those those people they're not up here anymore we're not marketing to them they're they're buying our books so in reflection when we look at our earnings versus what we're spending or or the sales associated with a campaign you know our earnings are much higher than the sales from the from the ads you know it's a you know for me it's a very small percentage um but it's it's just feeding the trough it's it's it's just build building you know building the bunker so to speak of all readers um okay we've got an algorithm we we we kind of have an idea of what it's doing uh so what do we do with it so this is where I'm going to get into the I don't know when I where where where I've I'm transitioning into session to so you know bear with me here um but we did I did introduce the marketing funnel thing um you know again cold warm hot um the the analog to the cold orm hot thing is and this is this is certainly new for this session um is category automatic and as and keywords um and these are type of marketing campaigns in in Amazon um yeah and I I explained it here so you know essentially category is is the easiest way for you without being like you know a lot of people fret when they're creating campaigns oh what which author do I have to Target you know what is the right keyword that I need to use and my argument is you're putting the cart before the horse you you don't I mean yes you might have an idea of what keywords and and and you know and what authors or whatever you know or or or what books to Target that that's and a lot of people do that and and they're successful and God bless them um but my my point here is that you may be wrong you might be you might be right category perspective is is a lot easier to be right about um because it controls a bunch of things like it's easier to say am I confident that my book is in this particular genre probably versus is it associated with this keyword is this best keyword to use I don't know um you know or is this the Au best author to you know you can probably be more confident with the category and oh by the way remember when we were talking about we want our ads to show up as many places as possible when you're targeting a keyword it's the specific books that seem to be associated with a keyword that's the only places it'll show up or if you're you know targeting a particular book it's only going to show up for that book so anyone who looks at that book great but when you're like targeting Thrillers or you know whatever the giant category is you might have like 40,000 targets that it's suddenly you know targeting um and you'd be surprised the cost per clicks on those yeah we'll talk about the specifics of that certainly in session two but um this is what I use to get my new people in because it's easy and it's cost effective in my opinion for me again these are all things that you have to experiment with I'm just kind of give you a point that I've had success with um and then the thing that most people don't realize is the automatic campaigns often don't work very well like for instance that that sun figure guy that I had compared notes with yeah I was in shock that how well his automatic campaigns worked and you and I it just blew my mind you know and now I I I I completely understand because it's all about that track record you know automatic campaigns are really about what does the algorithm think is the best choice where where should I advertise this to um so you know like I say here is it you know it's the corollary to warm you know Amazon has a clue what to do with your book so let it try you know that's a obviously a secondary C category but it only gets a clue once you've had sales so you know when you're starting off you're like bring in you again it's not the mom and family and friends thing you know it's the people you don't know it's the wide swath and once you have those and you have some proof of interest and there's some trend lines then we've got the algorithm getting warmed up and going okay I think I know what to do with this so so I've got automatic categories as well and then hot the coral are there is as and keyword targeting and note a lot of people start off with that I I I don't I actually do not do as or keyword targeting until I've gathered data from my sales in the top two tiers because I get affirmation about these you know like I I actually have a formula for myself um that says okay uh you know if I'm getting lots of clicks but no sales these are things that I'm going to say don't advertise to this stuff anymore because I'm losing money it's it's a bleeder um but if I'm getting a lot of sales associated with a particular you know keyword sure why not I I'll start a keyword campaign based on that um same thing for as Sometimes some books really correlate well to one of my books I'm like why not okay I I'll Target that book and those usually have a higher conversion rate you know as you're going down that funnel it's a higher and higher conversion rate um yeah key learnings let's see if I've gone over this uh allow you to cast a wide net category um yeah the red doesn't at least for my angle doesn't come through real um I also do one book per campaign and I'll actually talk about that in session two as to why um um largely because when you run the reports it allows you to gather data very cleanly uh so like for instance if I have a particular book that I'm running a campaign on and um you know and I've got sales data and I have keyword you know you know this keyword seems to be very popular I've gotten lots of sales associated with this keyword and and one of the reports will tell you what search term brought that reader to your book you go okay that's relevant and that's I understand but if you create a campaign with many books the problem is you still have the same data so you're like oh I got a lot of sales on that keyword but you don't know which book it was associated with so to me that's really important because now you're stuck with was that keyword associated with you know my Thriller my fantasy my this my that it's hard to tell sometimes so I I I like to be able to measure things and then do something with it um I'm actually getting close to this this I recall is I think one of my La last ones then we'll go for questions um yeah so also you know when you're when you're advertising you know what kind of customers do you want I mean BookBub is actually very popular and I highly recommend it not the ads but the feature deal if you can get one um yeah and I make that a very strong distinction BookBub ads I'm not so much of a fan of uh BookBub feature deals are and basically it's the largest mailing list in the world you know for the most part for the English language and um you know if you can get that that's great now those readers tend to be KU oriented just as data um and and if I ever do a book bub ad I don't personally but some people have a lot of success with it I choose to do it in this way or even uh or even if I'm doing a Facebook ad um yeah I know I'm going on tangent but you know even if I do a Facebook ad where you get an opportunity to put up a graphic you know and I have something on Kindle unlimited I advertise that read for free on Kindle unlimited even though my book might be $6.99 yeah because if you're Kindle unlimited subscriber that'll be interesting so yeah yeah there's little things I personally do that are useful or I've I've found to be useful uh Facebook ads are great um because they they can Target a very wide audience um and it doesn't it's not stuck to one store but you're going to run into problems with um you know they're very willing to spend a million dollars a day if if you let them um and it's it's the opposite problem of Amazon Amazon you I hear a lot of people say Amazon won't spend my money you know for a lot of the reasons I talked about Facebook has no problem spending your money yeah they'll they'll spend your money um and it may not be doing you Hill beans good and and in session two I definitely talk about I I'm I'm not a fan of Facebook absent the attribution feature of Amazon if you can't measure it you don't really know how good it's doing is My Strong assertion so I do talk about that in session two um and last but not least any open for questions uh is you really want to keep in mind efficiency you're you're in a situation where you under you need to understand your cost basis for any book you obviously for ebooks it's it's usually pretty simple if if you're at a normal price it's 70% um you know paperback you know I like I broke down one of my books is like you know I might be offering it for $17.99 you know my print cost is six you know 60% you know my royalty is 475 you know so my break even point is a 26% acos on that book on a paperback so you know these are things that you just have to keep in mind now obviously I I'm also a big fan of telling people some people are not ready for marketing spent you know if you have one book it's really hard to make profit um you know it's very unusual you know this is where read through really does come into play you know the the ab ability to actually earn you know significant you know because because you might spend more to get the initial reader but if you got like an eight book series or whatever you know like I think I give an example here five book series um you know you can calculate as an example a five book series getting a sale is worth $15 for a $7 book that's you know Based on data you can figure that out so now you have an understanding of your cost basis difference and that is uh uh I'm I'm gonna put this in session too so so any questions yes as uh an author that spans different genre do you find that the auto in uh uh Amazon advert sometimes picks background information from the wrong genre for the particular book you're trying to advertise so you're talking about multi- genre book uh no no I'm talking about an author who has several genre oh puts up a book got it in science fiction and finds he's getting clicks from urban fantasy uh so so so I'm in that situation where I I primarily put out Thrillers but I've got some science fiction and I even got some fantasy um and I don't tend to see crossover but you just have to be very conscious of now I have a lot of crossover readers so that's where you may see some you know yeah the algorithm is learning what it's learning so it's seeing data from your fans so if you've got a reader who is very willing to read Science Fiction and Fantasy you know so you may see some crossover but yeah the best you can do is actually Target your genres correctly on each book individually and then if you have readers who will read anything you put out yeah that's great so you know and things tend to get more efficient over time let's go to this so an online person asked when you were talking about an Amazon budget that wouldn't spend what is budget slamming budget slamming I'm not I'm not familiar with that term does anybody know uh so someone answered online maybe that would be helpful um lower the budget to a couple dollars and then slowly raise it we were talking about how can you get Amazon to spend oh oh so so the budget overall well I okay so I do go into how to get Amazon to spend and and it really has a lot to do with using the category field and I have an example where I actually did this where I tested it literally a couple days ago and I was like all right let me take one of my existing campaigns category ones and I was like all right let me just double the bid just to see and I increase the budget to like $500 a day and I was like you know and I'm like and it didn't spend the $500 but it suddenly went to like you know you know imagine a single book in a single day had 500,000 Impressions so yeah know it's stupid amount of Impressions so you know I wouldn't you know and in session two I say I wouldn't recommend that process but it requires analysis to figure out it didn't look efficient but I'd have to figure out why and you know and it's using all the same tools that I'd use for any of the other analysis uh we're going to go ping bong thank you yes um is there any way to negate the families that buy your book you know with the knitting needles and stuff do don't tell them about it I mean in all seriousness that that's usually the best way you and and some people have have friends and family and um and you you tell them oh it'll be coming out you know some other time you know give it a couple weeks after it's really coming out Goa and and you know yeah just don't tell them because they want to help you but yeah yes I was just curious so when we're creating our separate keyword campaigns let's say a phrase match versus a broad match and the same keyword is appearing on in those separate campaigns for your same book how does that bidding process work like are you bidding against yourself for the keyword so I actually talk about that very specifically in uhu in session two yeah you you you can bid against yourself and and yeah I talk about it yeah at like perfect yeah that's slightly related sorry to what I was going to ask um so what happens or what do you do if your pen name keeps coming up on your cold campaigns uh yeah your pen name comes up on the what on your cold campaigns or your warm would you negatively Target them if you're getting lots of clicks against them um if if you find those are not converting to sales yes if they're converting to sales then okay you're spending OB obviously the money on your your own name so say say it again because you're spending the money you know in your own name so like the Cod Amazon is sending the um using the cold campaigns for hot people if you know me oh sure sure I mean the got is if if you're you know I mean some people do do advocate for you know like doing doing a negative on your own name and and you know which is basically excluding you know certain phrases keywords or otherwise from being targeted um I tend to not have any rule with that I look literally at the at my sales data and go what's performing you know and and just go by that because I may have an opinion that it's wrong you know so I I try to go by data yes so use the term solid sales history and I'm one of the people that has old series that have been kind of derel I'd like to to freshen those up what does algorithm do for something that's had really great really good U sales history but it's been some time in the past what sort of um degradation do you see in the numbers on that how do I goose it so so uh I would say that you know this is like steering a boat anything you know anything that occurs it's it's kind of like a a a you know it takes a while to convert you know to convert something you know from moving One Direction to another and also if you get no sales data for a long period of time you know that data may go stale I don't know about you know you know I'll freely admit I I don't know what it does about you know aging out old data so that would be something you'd have to find out uh because have a 15 minute break yes uh so we're at the end of the session we have a 15minute break and we'll be going uh you right at the hour I guess or 10 oh sorry 10:30 so thank you [Applause] everybody