WEBVTT 00:00.110 --> 00:06.560 In this video, I want to talk to you about how to get your products recommended next to other similar 00:06.560 --> 00:07.520 kinds of products. 00:07.520 --> 00:13.130 So my book, for example, is the business plan book, but in my niche there's this one page marketing 00:13.130 --> 00:16.520 plan book, which right now it says bestseller and it's selling well. 00:16.520 --> 00:22.850 You can look at the seller rank, and it's only 1567 and all of the Kindle store. 00:22.850 --> 00:24.650 That's a really high ranking. 00:24.650 --> 00:26.690 And it's number one in a couple of categories. 00:26.690 --> 00:28.520 So it's a really high selling book. 00:28.520 --> 00:32.240 And what I want to do is make sure that my book appears here. 00:32.240 --> 00:33.590 And in fact, it does. 00:33.590 --> 00:36.770 You see, if I go next, next, this is my business plan book. 00:36.770 --> 00:37.670 How to do this? 00:37.670 --> 00:42.980 Obviously, Amazon recommends books that have similar numbers of reviews, similar numbers of sales, 00:42.980 --> 00:43.790 things like this. 00:43.790 --> 00:47.480 That's harder to influence, but there are some things that are easier to influence. 00:47.480 --> 00:54.320 For example, when I promote my book, this book, if I also promote this book at the same time, let's 00:54.320 --> 00:58.940 say I run an email campaign and I say, hey guys, you know, if you're planning a business, get my 00:58.940 --> 00:59.660 business plan book. 00:59.660 --> 01:03.500 And if you're doing a business, a marketing plan, you can either get my marketing book or you can 01:03.500 --> 01:09.860 get this marketing plan book that's going to make a lot of people get this book, The Yellow one and 01:09.860 --> 01:11.540 my book at the same time. 01:11.540 --> 01:14.090 And so customers who bought this item also bought. 01:14.090 --> 01:16.550 So that's going to influence that algorithm. 01:16.550 --> 01:19.160 And if you can do this consistently, that's even better. 01:19.160 --> 01:23.690 And if what if I say, hey Alan, like this author right here, his name is Alan. 01:23.690 --> 01:27.380 I can message him and I can say, hey, what about doing a collaboration? 01:27.380 --> 01:29.270 Like, why don't we promote our books together? 01:29.270 --> 01:34.820 And he would promote his book together with mine because he would want to get promoted next on my page. 01:34.820 --> 01:36.410 There is benefit in this for him. 01:36.410 --> 01:41.120 So we would do some kind of collaboration, maybe some kind of a long term partnership. 01:41.120 --> 01:46.130 And then we would promote each other's books and then pretty soon we would get recommended on each other's 01:46.130 --> 01:48.560 books and push all the competitors out. 01:48.560 --> 01:50.870 And then you can do this with other people too. 01:50.870 --> 01:56.810 And the cool thing is that, again, as you start getting recommended more making more sales, your 01:56.810 --> 02:03.170 book will naturally get recommended next to other books that have a lot of sales and reviews. 02:03.170 --> 02:05.840 Just because your sales and reviews will be growing. 02:05.840 --> 02:12.770 So you see, it's all little by little, building up this snowball effect that will ultimately build 02:12.770 --> 02:15.710 up your sales and get you recommended next to more books. 02:15.710 --> 02:21.920 Now, one caveat, of course, is that this book probably sells 20, 30, 40, 50 copies a day. 02:21.920 --> 02:26.960 So if you just influence 1 or 2 sales, it's not enough to influence the algorithm. 02:26.960 --> 02:32.810 So if you want to get recommended next to a book that's really popular and your book isn't selling that 02:32.810 --> 02:34.790 much, pick smaller books at first. 02:34.790 --> 02:36.410 Don't pick like runaway books. 02:36.410 --> 02:43.550 Pick books that at least are attainable and similar in sales so that you can influence the recommendation 02:43.550 --> 02:50.150 algorithms so that the sales you can influence will be a little more statistically significant to the 02:50.150 --> 02:51.710 recommendation algorithm.