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These are the user uploaded subtitles that are being translated: 1 00:00:00,910 --> 00:00:04,850 OK so you've got your Facebook page set up which is fantastic. 2 00:00:05,110 --> 00:00:10,370 And that's not going to give you access to the audience insights to. 3 00:00:10,490 --> 00:00:11,470 Great piquancy. 4 00:00:11,510 --> 00:00:18,490 Audience insights now how do you get this just depends on how your Facebook is set up. 5 00:00:18,660 --> 00:00:23,200 So it's kind of difficult for me to give you a complete one stop shop on how to get this place but basically 6 00:00:23,200 --> 00:00:29,210 just either look up in the menu you might have a top menu looks like this with your ads manager audiences. 7 00:00:29,230 --> 00:00:31,160 Audience insites this kind of thing. 8 00:00:31,420 --> 00:00:37,360 Or it might be on your personal page or maybe just type audience insights into the search bar. 9 00:00:37,380 --> 00:00:39,210 Either way you're going to find it pretty quickly. 10 00:00:39,270 --> 00:00:39,570 OK. 11 00:00:39,580 --> 00:00:43,200 And you're going to land on a page that looks like this. 12 00:00:43,300 --> 00:00:49,660 And essentially what it is is a massive search engine of everybody on Facebook if you like. 13 00:00:49,660 --> 00:00:54,690 And what we have down here on the left hand side is a column where we can put in all kinds of criteria 14 00:00:54,700 --> 00:00:57,070 so we got location legal age and gender. 15 00:00:57,070 --> 00:01:01,870 We call interes connections and pages we can leave that for the moment is these three women you really 16 00:01:01,870 --> 00:01:06,660 want to focus on right here on the right hand side is basically giving us the results. 17 00:01:06,670 --> 00:01:09,690 So let me give a quick demo location. 18 00:01:09,700 --> 00:01:11,030 United States. 19 00:01:11,050 --> 00:01:11,340 All right. 20 00:01:11,340 --> 00:01:16,300 So remember when we were thinking about customer Avatar we were thinking about age and gender and likes 21 00:01:16,300 --> 00:01:17,340 and all this kind of stuff. 22 00:01:17,590 --> 00:01:22,750 So here I've chosen United States just for the moment I could put UK or Australia or whatever I'm looking 23 00:01:22,750 --> 00:01:23,080 for. 24 00:01:23,140 --> 00:01:25,510 I'll stick with the United States age. 25 00:01:25,530 --> 00:01:29,650 For the moment are chosen 18 to any and gender are just chosen. 26 00:01:29,660 --> 00:01:31,010 All right. 27 00:01:31,150 --> 00:01:37,420 Now imagine I'm I've got that piece of jewelry that dog jewelry that we've been that I've been looking 28 00:01:37,420 --> 00:01:44,950 at with you and I want to see what sort of people I can target on Facebook. 29 00:01:44,950 --> 00:01:52,120 So in the interest here I can just simply type jewelry selected. 30 00:01:52,260 --> 00:01:55,010 And over here this information is now updated. 31 00:01:55,270 --> 00:02:01,050 MACKESY straight straightaway that 72 percent of them are women 28 percent of them are men and I can 32 00:02:01,050 --> 00:02:10,170 see the age groups which are you know mostly interacting with jewelry the general huge category of jewelry. 33 00:02:10,170 --> 00:02:16,380 So 26 percent of them that's the major one of between 25 and 34 and so on and so forth you can see that 34 00:02:16,380 --> 00:02:18,640 hopefully quite easily. 35 00:02:18,690 --> 00:02:23,770 Now this is part of this audience insight. 36 00:02:23,810 --> 00:02:27,980 Is a huge amount of information and it's quite fun to go through it all. 37 00:02:27,990 --> 00:02:36,150 But frankly I find some of it perhaps of limited interest limited use but you might be different. 38 00:02:36,330 --> 00:02:39,350 If I scroll down a bit here I've got things like lifestyle. 39 00:02:39,510 --> 00:02:44,850 Apparently 3 percent of them are rural parents this kind of stuff their education level their relationship 40 00:02:44,850 --> 00:02:47,310 status their job titles. 41 00:02:47,310 --> 00:02:49,640 You know I don't find this particularly useful. 42 00:02:49,670 --> 00:02:51,470 You may find a use for it now. 43 00:02:51,750 --> 00:02:54,660 The thing that I do find incredibly useful is this part here. 44 00:02:54,660 --> 00:02:57,770 Page Likes For Click click on page likes. 45 00:02:57,780 --> 00:03:05,410 It's starting to tell me straightaway sourcecode are a bit quicker if I just come down to hear the the 46 00:03:05,790 --> 00:03:13,530 most popular pages on Facebook that relate to jewelry that people like so we can see here for example 47 00:03:13,530 --> 00:03:23,610 the mint julep boutique or just fab or inspired So the so we can do is we can target people for example 48 00:03:23,640 --> 00:03:30,630 who have liked the page inspired silver as you know that's basically somebody saying yes I'm interested 49 00:03:30,630 --> 00:03:32,730 in jewelry now. 50 00:03:34,590 --> 00:03:41,610 What I can do is well obviously is if I just come back to demographics I might want to now just focus 51 00:03:41,610 --> 00:03:44,710 on women on women. 52 00:03:44,730 --> 00:03:45,290 All right. 53 00:03:45,320 --> 00:03:46,250 So there we go. 54 00:03:46,250 --> 00:03:47,790 The men have disappeared. 55 00:03:48,050 --> 00:03:54,840 And I said to you before I would generally focus in my example on women aged 30 and above. 56 00:03:54,900 --> 00:04:02,310 So now we start to see the demographics changes maybe the page likes now are different because we're 57 00:04:02,310 --> 00:04:05,860 looking at a you know 30 plus as opposed to all women. 58 00:04:06,150 --> 00:04:08,120 So if I scroll down here now. 59 00:04:08,370 --> 00:04:10,410 Yeah we've got some different stuff in here. 60 00:04:10,410 --> 00:04:15,330 We got what is it 12 tomatoes I don't even know what that is tip hero by the way if you click on any 61 00:04:15,330 --> 00:04:19,730 of these it's going to take you to the page to the Facebook page you can see exactly what it's like. 62 00:04:21,110 --> 00:04:27,680 If I start to click on some of these other ones here location and I talk about your being location dependent. 63 00:04:27,800 --> 00:04:29,700 You know there's not much to be said there. 64 00:04:29,840 --> 00:04:32,440 And as we go through here I mean it's just not what's available. 65 00:04:32,460 --> 00:04:40,760 But you know frequency of activities devices that users use We've got things like household income and 66 00:04:40,760 --> 00:04:42,530 it goes on and on and on. 67 00:04:42,560 --> 00:04:47,540 Personally I focus on the demographics and the page likes. 68 00:04:47,540 --> 00:04:56,220 Now just to sort of you know perhaps take another interest let's just go back here to all ages. 69 00:04:56,270 --> 00:05:00,220 I just want to just pick another interest just to illustrate the point a bit more. 70 00:05:00,420 --> 00:05:05,340 Let's say you're in the skiing business. 71 00:05:05,340 --> 00:05:12,750 All right let's take an alpine skiing click and demographics and 72 00:05:15,190 --> 00:05:15,840 sure enough. 73 00:05:15,880 --> 00:05:23,050 We've got a nice sort of fairly even spread between men and women who ski 50 percent 56 percent of women 74 00:05:23,380 --> 00:05:27,020 44 percent of men click on here on page links. 75 00:05:27,550 --> 00:05:30,430 And you know what have I got I've got. 76 00:05:30,670 --> 00:05:31,140 OK. 77 00:05:31,180 --> 00:05:32,690 Lindsey Vonn is risky. 78 00:05:32,700 --> 00:05:37,890 That's the big famous name that you know so people are liking Lindsey Vonn which demonstrates they are 79 00:05:37,900 --> 00:05:40,540 skills we might want to target those people the U.S. ski team. 80 00:05:40,540 --> 00:05:43,570 Michael Phelps the swimmer I'm not sure what he's doing in there anyway. 81 00:05:43,600 --> 00:05:53,170 You start to get a feel for how this page can spark off ideas of what people are interested in and therefore 82 00:05:53,200 --> 00:05:55,330 how to target them. 83 00:05:55,330 --> 00:05:55,620 All right. 84 00:05:55,630 --> 00:05:56,960 I'll see you in the next lecture. 8741