1 00:00:04,240 --> 00:00:07,240 Speaker 1: Get in tescht with technology with tech Stuff from how 2 00:00:07,280 --> 00:00:13,960 Speaker 1: stuff works dot com. Hey there, everyone, and welcome to 3 00:00:14,160 --> 00:00:17,080 Speaker 1: tech Stuff. I'm Jonathan Strickland and I'm Lauren foc Obama, 4 00:00:17,079 --> 00:00:19,639 Speaker 1: and you know, we're starting to wind down the year 5 00:00:19,760 --> 00:00:22,880 Speaker 1: often and we thought it might be cool for us 6 00:00:22,920 --> 00:00:26,280 Speaker 1: to take a look at some of the big tech companies, 7 00:00:26,360 --> 00:00:29,880 Speaker 1: the best tech companies to work for in Yeah, because 8 00:00:29,880 --> 00:00:31,720 Speaker 1: some of them are actually really small. Yeah, and some 9 00:00:31,800 --> 00:00:33,840 Speaker 1: of them you may not have heard of because they're 10 00:00:33,840 --> 00:00:38,840 Speaker 1: not necessarily companies that average consumers would end up interacting with. 11 00:00:38,880 --> 00:00:42,560 Speaker 1: They're more like companies that enterprises interact with. And we 12 00:00:43,479 --> 00:00:46,200 Speaker 1: managed to get this list. It was from an article 13 00:00:46,240 --> 00:00:49,680 Speaker 1: that was published in Business Insider by Megan Rose Dickey, 14 00:00:49,800 --> 00:00:53,640 Speaker 1: who put together an amazing list of twenty five companies. 15 00:00:53,640 --> 00:00:57,120 Speaker 1: We're looking at the top ten. Business Insider does this 16 00:00:57,200 --> 00:00:59,680 Speaker 1: list every year, and I think a competition this year 17 00:00:59,720 --> 00:01:02,360 Speaker 1: was a little but stiffer the lowest ranked. Okay, so 18 00:01:02,360 --> 00:01:04,360 Speaker 1: so what this is looking at. It's based on at 19 00:01:04,440 --> 00:01:08,720 Speaker 1: least twenty company reviews on glass door um from from 20 00:01:08,920 --> 00:01:11,679 Speaker 1: a certain date, range from from from a good year 21 00:01:11,720 --> 00:01:14,679 Speaker 1: long range. Yeah. They look over a stretch of twelve 22 00:01:14,760 --> 00:01:16,840 Speaker 1: months end of the year, and then an extra from 23 00:01:16,880 --> 00:01:18,560 Speaker 1: the beginning, and in case you want to know what 24 00:01:18,720 --> 00:01:21,240 Speaker 1: glass door is if you haven't been searching for a 25 00:01:21,319 --> 00:01:25,280 Speaker 1: job recently. Glass door is a job seeking kind of tool, 26 00:01:25,440 --> 00:01:27,560 Speaker 1: and it'll lets you not only look to see what 27 00:01:27,640 --> 00:01:30,479 Speaker 1: jobs are available, but also gives you some insight as 28 00:01:30,520 --> 00:01:32,360 Speaker 1: to what it's like to work with those companies based 29 00:01:32,400 --> 00:01:36,240 Speaker 1: on actual employee comments about those companies. Right, employees can 30 00:01:36,280 --> 00:01:40,280 Speaker 1: go on there and give some pretty honest and sometimes 31 00:01:40,319 --> 00:01:42,800 Speaker 1: brutal and sometimes wonderful reviews of what it's like that 32 00:01:42,880 --> 00:01:45,480 Speaker 1: what corporate life there's like. Right, it might say something 33 00:01:45,600 --> 00:01:50,040 Speaker 1: like the benefits are amazing, work life balance is fantastic, 34 00:01:50,120 --> 00:01:52,440 Speaker 1: I really enjoy my work, and others might say things 35 00:01:52,440 --> 00:01:57,120 Speaker 1: like I really wish that my my supervisor would stop 36 00:01:57,160 --> 00:01:59,560 Speaker 1: buying a new whip every week so that maybe the 37 00:01:59,560 --> 00:02:04,840 Speaker 1: old whip would start feeling less painful. Yeah, obviously that 38 00:02:05,000 --> 00:02:06,960 Speaker 1: second type of company would be the one that I 39 00:02:06,960 --> 00:02:10,680 Speaker 1: think most people would wish to avoid most people most people. 40 00:02:10,840 --> 00:02:14,240 Speaker 1: I'm not going to paint as with a completely broad 41 00:02:14,320 --> 00:02:16,520 Speaker 1: brush on that one. So, but so, these company ratings 42 00:02:16,560 --> 00:02:18,480 Speaker 1: are in a five point scale, with with one being 43 00:02:18,520 --> 00:02:21,360 Speaker 1: the worst in five being the best and uh, this 44 00:02:21,360 --> 00:02:23,360 Speaker 1: this year, the lowest in our top ten is ranked 45 00:02:23,360 --> 00:02:26,080 Speaker 1: four point one. Last year the winner was only a 46 00:02:26,120 --> 00:02:30,079 Speaker 1: four point four, So there's there's been a lot of upsets, right, 47 00:02:30,320 --> 00:02:33,280 Speaker 1: And we're going to look at the top ten, but 48 00:02:33,400 --> 00:02:35,680 Speaker 1: in this particular part, we're gonna look at numbers ten 49 00:02:35,760 --> 00:02:40,120 Speaker 1: through six so that we can really kind of give 50 00:02:40,160 --> 00:02:42,160 Speaker 1: a little bit of an overview of each company, because 51 00:02:42,200 --> 00:02:43,919 Speaker 1: we could just tell you the name and the rating, 52 00:02:44,000 --> 00:02:45,840 Speaker 1: but you could read the article for that, and you 53 00:02:45,840 --> 00:02:48,120 Speaker 1: should go to the article. Like we said, there are 54 00:02:48,120 --> 00:02:50,000 Speaker 1: other entries in there that we're not going to cover. 55 00:02:50,400 --> 00:02:52,440 Speaker 1: I'll give a little honorable mention at the end of 56 00:02:52,639 --> 00:02:54,640 Speaker 1: the next episode for some of the companies that you 57 00:02:54,680 --> 00:02:56,560 Speaker 1: may have heard of that that made the list, but 58 00:02:56,639 --> 00:02:58,760 Speaker 1: we're not in the top ten. But we wanted to 59 00:02:58,760 --> 00:03:02,280 Speaker 1: actually explain kind of these companies were and uh and 60 00:03:02,360 --> 00:03:04,399 Speaker 1: what they do. A couple of them I hadn't really 61 00:03:04,440 --> 00:03:06,400 Speaker 1: heard of before, had only heard of kind of in 62 00:03:06,480 --> 00:03:08,760 Speaker 1: passing a couple of them, I had not Not only 63 00:03:08,800 --> 00:03:12,000 Speaker 1: did I not know what they were. When I read 64 00:03:12,040 --> 00:03:15,280 Speaker 1: the corporate speak for what they did, I still wasn't 65 00:03:15,280 --> 00:03:17,680 Speaker 1: sure what was happening. And I had to keep digging 66 00:03:17,720 --> 00:03:21,720 Speaker 1: to figure it out. Um full disclosure. Years and years 67 00:03:21,720 --> 00:03:24,440 Speaker 1: and years ago, I worked for a human resources management 68 00:03:24,440 --> 00:03:28,440 Speaker 1: consulting firm and uh, and I learned the the art 69 00:03:28,560 --> 00:03:31,560 Speaker 1: of corpse speak. But it has been a long time 70 00:03:31,760 --> 00:03:34,200 Speaker 1: and I have lost a lot of that ability. And 71 00:03:34,280 --> 00:03:36,640 Speaker 1: also different corps speak is different, I mean you get 72 00:03:36,680 --> 00:03:38,760 Speaker 1: I mean the ones that I was kind of like, 73 00:03:38,840 --> 00:03:41,160 Speaker 1: what does your company do? Or the kind of new 74 00:03:41,200 --> 00:03:43,880 Speaker 1: marketing sort of yes, where I just like, so you 75 00:03:44,000 --> 00:03:47,560 Speaker 1: do colors on websites that are really shiny and I 76 00:03:47,600 --> 00:03:50,720 Speaker 1: don't understand what's going on. And and yeah, back when 77 00:03:50,720 --> 00:03:53,440 Speaker 1: I was working for a consulting firm, cloud based was 78 00:03:53,480 --> 00:03:56,120 Speaker 1: not a thing. That was that So everything now is 79 00:03:56,120 --> 00:03:59,480 Speaker 1: cloud based apparently. But last year a couple of the 80 00:03:59,520 --> 00:04:05,040 Speaker 1: companies made it in included Miter and LinkedIn and Google, 81 00:04:06,240 --> 00:04:08,880 Speaker 1: Apple Yep, yep. And some of these also made it 82 00:04:08,920 --> 00:04:11,360 Speaker 1: into the list this year, but in different rankings than 83 00:04:11,440 --> 00:04:15,440 Speaker 1: they did in years before. So let's kick this all off, Lauren. 84 00:04:16,000 --> 00:04:19,200 Speaker 1: What company came in at number ten? Number ten would 85 00:04:19,240 --> 00:04:22,520 Speaker 1: be Orbits. Now, this was one that I was familiar with. 86 00:04:23,120 --> 00:04:24,640 Speaker 1: I think anyone who has done a lot of travel 87 00:04:24,800 --> 00:04:26,880 Speaker 1: is familiar with this company. It is of course an 88 00:04:26,920 --> 00:04:30,440 Speaker 1: online booking agent system for all kinds of travel stuff, 89 00:04:30,440 --> 00:04:33,080 Speaker 1: you know, from from the hotels to the tickets themselves, 90 00:04:33,120 --> 00:04:37,640 Speaker 1: to entire packages like cruise, ships or articles, vehicles, car rental, yeah, 91 00:04:38,080 --> 00:04:40,400 Speaker 1: all that kind of stuff. And then you know, this 92 00:04:40,480 --> 00:04:43,080 Speaker 1: is one of those things where it was like a 93 00:04:43,120 --> 00:04:46,440 Speaker 1: no brainer for the internet, right. It was something that 94 00:04:46,520 --> 00:04:49,640 Speaker 1: allowed you to have access to all the tools that 95 00:04:49,680 --> 00:04:52,880 Speaker 1: a travel agent would have for the average consumer. And 96 00:04:52,960 --> 00:04:56,120 Speaker 1: once you had some companies put that together and really 97 00:04:56,240 --> 00:04:59,880 Speaker 1: organize it, it really made a great deal of sen 98 00:05:00,440 --> 00:05:03,680 Speaker 1: gave empowerment to the consumer. They had a lot more choices, 99 00:05:03,720 --> 00:05:07,520 Speaker 1: they got to see, uh, some some great savings as well. 100 00:05:07,839 --> 00:05:11,240 Speaker 1: Sometimes the savings are kind of hidden behind a veil, right, 101 00:05:11,320 --> 00:05:13,880 Speaker 1: Like you, if you book with a certain amount, you're 102 00:05:14,000 --> 00:05:16,440 Speaker 1: you might get a great deal, but you don't know 103 00:05:16,600 --> 00:05:18,960 Speaker 1: what hotel you're going to get until after the deal 104 00:05:19,040 --> 00:05:21,719 Speaker 1: comes through. All right, if you've got flexible travel plans 105 00:05:21,800 --> 00:05:24,599 Speaker 1: or don't mind that element of surprise for for slightly 106 00:05:24,640 --> 00:05:27,080 Speaker 1: anxious people like me, I'm like, please just let me 107 00:05:27,120 --> 00:05:29,960 Speaker 1: pick the thing that I want to pick. Um For 108 00:05:30,000 --> 00:05:33,880 Speaker 1: people like me, I'm like, where's the cardboard? Box. Okay, 109 00:05:34,000 --> 00:05:37,080 Speaker 1: as long as I can get there. But yeah, So 110 00:05:37,080 --> 00:05:40,560 Speaker 1: so the company was founded back in and, um, that's 111 00:05:40,600 --> 00:05:44,240 Speaker 1: by a group of airlines. Yeah. In fact, American Airlines 112 00:05:44,520 --> 00:05:47,880 Speaker 1: was one of those companies. Yes, uh that yeah. In 113 00:05:47,920 --> 00:05:51,640 Speaker 1: addition to them, we've got Delta, United, Northwest, and Continental. Yeah. 114 00:05:51,640 --> 00:05:53,800 Speaker 1: Not all of those are around. Some of them, like 115 00:05:53,839 --> 00:05:58,080 Speaker 1: Delta acquired Northwest for example. So there, But at any rate, 116 00:05:58,520 --> 00:06:01,320 Speaker 1: it was kind of cool these airlines all got together 117 00:06:01,360 --> 00:06:05,120 Speaker 1: and said, let's try and create this this tool that 118 00:06:05,160 --> 00:06:07,960 Speaker 1: would be really useful. I mean, obviously it's served them 119 00:06:08,120 --> 00:06:10,400 Speaker 1: as well as the customers. It's not like it was 120 00:06:10,440 --> 00:06:14,680 Speaker 1: an altruistic move necessarily, but the benefit was incredible for 121 00:06:14,720 --> 00:06:17,720 Speaker 1: everyone certainly. They the website launched in two thousand one, 122 00:06:17,880 --> 00:06:20,640 Speaker 1: and then the company was acquired by two thousand four 123 00:06:20,839 --> 00:06:25,159 Speaker 1: by another company called um Sant. Sendant, I think, yeah, 124 00:06:25,200 --> 00:06:27,240 Speaker 1: it's a C E N D A N T. And 125 00:06:27,279 --> 00:06:30,840 Speaker 1: I have obviously I never have heard that words spoken aloud, 126 00:06:30,920 --> 00:06:33,400 Speaker 1: so I'm assuming Sendant, but I don't know things that 127 00:06:33,400 --> 00:06:35,240 Speaker 1: we should have looked up before he came into the room. 128 00:06:35,360 --> 00:06:37,160 Speaker 1: Um and they had an I P O in two 129 00:06:37,160 --> 00:06:39,919 Speaker 1: thousand seven. Yep, so this is a publicly traded company. 130 00:06:40,000 --> 00:06:43,080 Speaker 1: Some of the ones we're talking about are publicly traded 131 00:06:43,200 --> 00:06:46,200 Speaker 1: a couple or private, and then some of them are subsidiaries. 132 00:06:46,440 --> 00:06:49,479 Speaker 1: Technically this is a publicly traded company that um that 133 00:06:49,720 --> 00:06:53,680 Speaker 1: hasn't a parent, uh kind of company. The scendant would 134 00:06:53,680 --> 00:06:57,760 Speaker 1: be the parent here. But um, yeah, the company was 135 00:06:57,839 --> 00:07:01,279 Speaker 1: rated pretty highly. As you said, it's the lowest rated 136 00:07:01,320 --> 00:07:03,880 Speaker 1: of all the ones we look looking at four point 137 00:07:03,920 --> 00:07:09,440 Speaker 1: one and they're CEO approval percentage rating. That's for Barney Harford. 138 00:07:11,120 --> 00:07:12,880 Speaker 1: So yeah, that's not bad. That's not bad. And the 139 00:07:13,200 --> 00:07:18,680 Speaker 1: CEO percentage approvals UM bounce around. You'll hear in the 140 00:07:18,760 --> 00:07:21,040 Speaker 1: n or so. Yeah, you'll hear as we go on 141 00:07:21,320 --> 00:07:23,600 Speaker 1: that some of them that the company may be rated 142 00:07:23,680 --> 00:07:27,040 Speaker 1: higher and a CEO may be rated lower. But you know, 143 00:07:27,320 --> 00:07:30,440 Speaker 1: it happens. Uh. It turns out that the employees say 144 00:07:30,480 --> 00:07:32,920 Speaker 1: that there are a lot of learning opportunities to work 145 00:07:33,000 --> 00:07:34,920 Speaker 1: when you're working at Orbits, and that there are good 146 00:07:34,920 --> 00:07:38,520 Speaker 1: benefits and lots of room for growth, which is great. Uh. 147 00:07:38,600 --> 00:07:40,480 Speaker 1: And then you know, I decided that it would be 148 00:07:40,520 --> 00:07:42,560 Speaker 1: kind of neat to look in the news because, first 149 00:07:42,560 --> 00:07:45,760 Speaker 1: of all, this article that was written for Business Insider 150 00:07:45,840 --> 00:07:50,040 Speaker 1: came out in the summer of because it was looking 151 00:07:50,040 --> 00:07:52,200 Speaker 1: over the past twelve months, which actually started in the 152 00:07:52,240 --> 00:07:56,160 Speaker 1: summer of twelve obviously, so since then I thought it'd 153 00:07:56,160 --> 00:07:57,920 Speaker 1: be neat to look and see what kind of news 154 00:07:58,120 --> 00:08:02,080 Speaker 1: articles had popped up about these companies. So with the Orbits, 155 00:08:02,120 --> 00:08:04,560 Speaker 1: there were some there's some you know news and some 156 00:08:04,640 --> 00:08:08,000 Speaker 1: bad news. Um. For instance, there was a bit of 157 00:08:08,120 --> 00:08:11,200 Speaker 1: a kerfuffle, you might say, a couple of counties in 158 00:08:11,280 --> 00:08:16,240 Speaker 1: Maryland had brought a suit against Orbits claiming that had 159 00:08:16,320 --> 00:08:20,480 Speaker 1: not paid taxes properly in those counties. And the taxes 160 00:08:20,560 --> 00:08:25,520 Speaker 1: in question were in response to booking fees for hotel rooms, 161 00:08:25,560 --> 00:08:29,080 Speaker 1: something that the Orbit says it should not be held 162 00:08:29,120 --> 00:08:32,079 Speaker 1: accountable for, and things the county say you should totally 163 00:08:32,080 --> 00:08:34,640 Speaker 1: be held accountable for this. And actually the article I 164 00:08:34,679 --> 00:08:39,040 Speaker 1: read was pretty um, kind of cynical, because I was 165 00:08:39,080 --> 00:08:43,040 Speaker 1: talking about how a lot of governments, specifically like local governments, 166 00:08:43,080 --> 00:08:46,839 Speaker 1: county governments and city governments, we're looking at companies as 167 00:08:46,880 --> 00:08:51,200 Speaker 1: a potential revenue source by going after these things that 168 00:08:51,360 --> 00:08:54,320 Speaker 1: you know didn't exist before because of the online world 169 00:08:54,400 --> 00:08:58,760 Speaker 1: is so stills wherein right you're doing business with people 170 00:08:58,760 --> 00:09:01,240 Speaker 1: all over the place, right, So it's almost that same 171 00:09:01,240 --> 00:09:03,800 Speaker 1: sort of mentality, at least according to the person who 172 00:09:03,840 --> 00:09:06,480 Speaker 1: wrote this article, the same sort of mentality as someone 173 00:09:06,480 --> 00:09:08,960 Speaker 1: who would claim that the police force in your local 174 00:09:09,000 --> 00:09:13,960 Speaker 1: area is stepping up uh roadblocks and and speed traps 175 00:09:14,120 --> 00:09:16,520 Speaker 1: in order to fill a quota. It's that kind of 176 00:09:16,640 --> 00:09:19,960 Speaker 1: same message I was getting. Whether or not that's the case, 177 00:09:20,240 --> 00:09:23,120 Speaker 1: I can't say, but that was that was certainly the 178 00:09:23,160 --> 00:09:26,400 Speaker 1: implication that I was getting from this particular author. But 179 00:09:26,480 --> 00:09:30,720 Speaker 1: another interesting bit of news, so Orbits also suffered a 180 00:09:30,760 --> 00:09:34,880 Speaker 1: twenty percent drop in their share prices after an earnings 181 00:09:34,920 --> 00:09:38,520 Speaker 1: call back in November of That earnings call revealed that 182 00:09:38,559 --> 00:09:42,160 Speaker 1: company performance fell below projections. Uh. They said that it 183 00:09:42,200 --> 00:09:45,040 Speaker 1: was mostly because there was a drop in airline revenue. 184 00:09:45,120 --> 00:09:47,960 Speaker 1: Even though hotel revenue is increasing, there's been overall this 185 00:09:48,040 --> 00:09:52,160 Speaker 1: year a pretty drastic drop in airline Yeah. So, but 186 00:09:52,160 --> 00:09:55,840 Speaker 1: but the good news is that executives say they feel 187 00:09:55,880 --> 00:09:59,440 Speaker 1: there's there's a very optimistic chance that revenue growth will return, 188 00:10:00,559 --> 00:10:03,360 Speaker 1: maybe not quite at the level they had projected originally, 189 00:10:03,840 --> 00:10:06,960 Speaker 1: but they they're seeing an upswing, so it's not all 190 00:10:07,000 --> 00:10:10,000 Speaker 1: bad news. So yeah, that's ah, that's our number ten, 191 00:10:10,160 --> 00:10:12,560 Speaker 1: So I guess we need to move on. Yeah, number 192 00:10:12,679 --> 00:10:16,080 Speaker 1: nine would be Exact Target. Now this is one that 193 00:10:16,240 --> 00:10:20,360 Speaker 1: I had never heard of or I was completely unfamiliar with, 194 00:10:20,440 --> 00:10:23,360 Speaker 1: and partially because again, this is a company that is 195 00:10:23,400 --> 00:10:27,920 Speaker 1: a tech company, but it's not creating stuff. Yeah, it's 196 00:10:27,920 --> 00:10:30,320 Speaker 1: not like it's coming out with a video game console 197 00:10:30,600 --> 00:10:34,920 Speaker 1: or a smart watch or even a website that most 198 00:10:34,960 --> 00:10:38,120 Speaker 1: people would go to. This instead is a digital marketing 199 00:10:38,360 --> 00:10:42,360 Speaker 1: software as a service company s a a S. Right. 200 00:10:42,600 --> 00:10:46,000 Speaker 1: They do they do software for for email, mobile, social media, 201 00:10:46,040 --> 00:10:49,880 Speaker 1: and web marketing specifically, so you might if you're a 202 00:10:49,880 --> 00:10:54,480 Speaker 1: company and you don't have your own marketing department, then 203 00:10:54,520 --> 00:10:57,360 Speaker 1: you may work with a company like Exact Target to 204 00:10:57,559 --> 00:11:01,360 Speaker 1: handle the marketing strategies for your company. Um, this is 205 00:11:01,400 --> 00:11:04,000 Speaker 1: something we're seeing more and more of today. Like you 206 00:11:04,040 --> 00:11:06,920 Speaker 1: think back in the old days of business, where you 207 00:11:06,960 --> 00:11:11,239 Speaker 1: had this monolithic building that housed dozens of different departments 208 00:11:11,280 --> 00:11:15,600 Speaker 1: that never talked to each other and had terrible, uh 209 00:11:15,640 --> 00:11:20,000 Speaker 1: competitive relationships with one another. I've been in actually a 210 00:11:20,080 --> 00:11:22,240 Speaker 1: couple of couple of companies that worked like that. I 211 00:11:22,280 --> 00:11:24,280 Speaker 1: just think of things like mad Men. You know, you 212 00:11:24,320 --> 00:11:26,360 Speaker 1: watch shows like that and you're like, Oh, that's what 213 00:11:26,400 --> 00:11:28,600 Speaker 1: a marketing company is like, right, because it's you know, 214 00:11:28,640 --> 00:11:33,480 Speaker 1: everything is very siloed and competitive and cutthroat. H Well, 215 00:11:33,600 --> 00:11:37,439 Speaker 1: these days, a lot of companies are looking to other 216 00:11:37,559 --> 00:11:40,880 Speaker 1: organizations to handle certain things that they need to do 217 00:11:41,440 --> 00:11:43,520 Speaker 1: but they don't want to do with under their own 218 00:11:43,760 --> 00:11:48,560 Speaker 1: roof because it's not their focus. Right, particularly with startup companies, 219 00:11:48,600 --> 00:11:51,160 Speaker 1: You've got these big startup companies where they might be 220 00:11:51,240 --> 00:11:54,000 Speaker 1: engineers who are behind the startup company, and the engineer 221 00:11:54,080 --> 00:11:57,040 Speaker 1: is really good at making something that people want to use, 222 00:11:57,520 --> 00:12:00,880 Speaker 1: but not necessarily so good at everything else that's required 223 00:12:00,920 --> 00:12:03,160 Speaker 1: to run a business, right, And frequently the kind of 224 00:12:03,160 --> 00:12:05,600 Speaker 1: people who are really good at talking up a product 225 00:12:05,640 --> 00:12:08,480 Speaker 1: are not the same kind of people who necessarily created it. 226 00:12:08,600 --> 00:12:12,400 Speaker 1: So I think that that exists across many industries. Oh yeah, yeah. 227 00:12:12,559 --> 00:12:15,640 Speaker 1: So this particular company was founded in two thousand. It 228 00:12:15,880 --> 00:12:20,040 Speaker 1: started on a two hundred thousand dollar investment, and specifically 229 00:12:20,040 --> 00:12:23,440 Speaker 1: they offer a quote cloud based marketing software in quote 230 00:12:23,480 --> 00:12:26,520 Speaker 1: to help brands reach consumers. So cloud based meaning that 231 00:12:26,640 --> 00:12:28,840 Speaker 1: you would be able to interface with this no matter 232 00:12:28,880 --> 00:12:31,080 Speaker 1: where you happen to be. If you were a customer 233 00:12:31,200 --> 00:12:34,000 Speaker 1: of exact target, you could end up logging in and 234 00:12:34,080 --> 00:12:37,680 Speaker 1: using their tools, includes analytic tools, which are really important 235 00:12:37,760 --> 00:12:40,480 Speaker 1: these days to make sure you are doing the right 236 00:12:40,520 --> 00:12:43,000 Speaker 1: thing right, that you're reaching the people you want to reach, 237 00:12:43,360 --> 00:12:46,400 Speaker 1: and that your message is having the intended effect right. 238 00:12:46,480 --> 00:12:50,520 Speaker 1: And since since exact Target does more software than the 239 00:12:50,559 --> 00:12:55,280 Speaker 1: implementation of of a marketing campaign for its for its customers, 240 00:12:55,400 --> 00:12:58,120 Speaker 1: that's a pretty important thing to have those analytics built 241 00:12:58,160 --> 00:13:01,000 Speaker 1: in right, right. So there they're doing is they're giving 242 00:13:01,040 --> 00:13:04,200 Speaker 1: all the tools that your company would need in order 243 00:13:04,240 --> 00:13:06,960 Speaker 1: to get your message that you have crafted out to 244 00:13:07,000 --> 00:13:12,239 Speaker 1: your customers. Because it's one thing to create your brand's identity, 245 00:13:12,320 --> 00:13:15,920 Speaker 1: it's another thing to get that identity out there. In fact, 246 00:13:15,920 --> 00:13:18,440 Speaker 1: we're gonna be talking more about that a couple more 247 00:13:18,440 --> 00:13:23,760 Speaker 1: times in this list. So yeah, uh, an interesting company 248 00:13:23,800 --> 00:13:25,520 Speaker 1: to talk about because again it's one of those that 249 00:13:26,120 --> 00:13:28,360 Speaker 1: otherwise I don't think I would have ever mentioned. I 250 00:13:28,360 --> 00:13:30,760 Speaker 1: wouldn't have been aware of it because I don't own 251 00:13:30,800 --> 00:13:33,600 Speaker 1: a huge company that needs marketing. But but yeah, they've 252 00:13:33,600 --> 00:13:35,880 Speaker 1: got a really high rating, this kind of same four 253 00:13:35,920 --> 00:13:40,680 Speaker 1: point one that Orbits has. But it's CEO approval of 254 00:13:40,679 --> 00:13:44,240 Speaker 1: of Mr Scott D. Dorsey is yes, and I believe 255 00:13:44,400 --> 00:13:47,400 Speaker 1: Mr Dorsey is also one of the co founders of 256 00:13:47,440 --> 00:13:49,600 Speaker 1: the company. So that's another thing that we're gonna be 257 00:13:49,600 --> 00:13:51,360 Speaker 1: You know, a lot of these companies were talking about 258 00:13:51,400 --> 00:13:55,520 Speaker 1: here are relatively young, and so the people who made 259 00:13:55,559 --> 00:13:58,360 Speaker 1: the companies are still very much an active part. You know, 260 00:13:58,679 --> 00:14:01,319 Speaker 1: there are some legacy companies out there. I'm gonna go 261 00:14:01,360 --> 00:14:03,719 Speaker 1: ahead and give you a spoiler. Guys, there aren't very 262 00:14:03,760 --> 00:14:06,240 Speaker 1: many on this list. You're not gonna hear HP, You're 263 00:14:06,240 --> 00:14:08,280 Speaker 1: not gonna hear IBM, You're not going to hear Intel. 264 00:14:08,360 --> 00:14:11,840 Speaker 1: These companies that have decades and decades of history. So 265 00:14:11,880 --> 00:14:15,280 Speaker 1: a lot of the companies are very young, still very 266 00:14:15,320 --> 00:14:20,200 Speaker 1: flexible and and and able to make big changes. Plus 267 00:14:20,240 --> 00:14:22,680 Speaker 1: they have some of the original people still very much 268 00:14:22,720 --> 00:14:25,280 Speaker 1: involved on a day to day basis in the operations. Yeah, 269 00:14:25,520 --> 00:14:29,080 Speaker 1: going through this list, it's interesting. I found that. I mean, 270 00:14:29,080 --> 00:14:32,640 Speaker 1: it's just easy to see where where that kind of 271 00:14:32,720 --> 00:14:35,800 Speaker 1: environment would lead to happier employees than the kind of 272 00:14:35,840 --> 00:14:40,560 Speaker 1: thing that gets so huge, right, because once you get 273 00:14:40,560 --> 00:14:43,000 Speaker 1: to that level, you have to put systems in place, 274 00:14:43,040 --> 00:14:45,920 Speaker 1: otherwise you just have chaos. Right. Although there is one 275 00:14:46,240 --> 00:14:49,480 Speaker 1: mega mega mega company, actually a couple of mega companies 276 00:14:49,520 --> 00:14:52,080 Speaker 1: that will be talking about in this episode that you 277 00:14:52,080 --> 00:14:55,000 Speaker 1: know are still pretty good at keeping everything organized. Yeah, 278 00:14:55,000 --> 00:14:57,360 Speaker 1: but this one is pretty small. It's only about two 279 00:14:57,400 --> 00:15:01,080 Speaker 1: thousand employees or so. Um and uh, it sounds like 280 00:15:01,400 --> 00:15:03,240 Speaker 1: one of the perks of working there is that they 281 00:15:03,320 --> 00:15:06,520 Speaker 1: let their employees be pretty independent. Um, but that comes 282 00:15:06,560 --> 00:15:09,320 Speaker 1: with the caveat of you're expected to keep up. Yeah. Yeah, 283 00:15:09,440 --> 00:15:12,360 Speaker 1: you are given a lot of autonomy, but that company 284 00:15:12,560 --> 00:15:17,440 Speaker 1: with great power comes great responsibility always. Yeah. So they 285 00:15:17,480 --> 00:15:21,160 Speaker 1: also have listed core values on their website, which includes 286 00:15:21,520 --> 00:15:23,480 Speaker 1: pretty simple things. I mean, these are kind of like 287 00:15:23,520 --> 00:15:27,800 Speaker 1: the Golden Rule broken down into a corporate approach, So 288 00:15:27,920 --> 00:15:31,080 Speaker 1: things like treat people well and be easy to do 289 00:15:31,200 --> 00:15:35,680 Speaker 1: business with and uh and make clients look like heroes. 290 00:15:36,000 --> 00:15:40,200 Speaker 1: These all seem like very you know, obvious kind of things. 291 00:15:41,440 --> 00:15:43,800 Speaker 1: But when you when you make it a core part 292 00:15:43,880 --> 00:15:46,120 Speaker 1: of what your company is all about, and you and 293 00:15:46,200 --> 00:15:50,360 Speaker 1: you truly try to stick with that, then obviously that 294 00:15:50,360 --> 00:15:53,200 Speaker 1: that can trickle down into other elements that make it 295 00:15:53,240 --> 00:15:56,360 Speaker 1: a great place to work. Um. They also have a 296 00:15:56,400 --> 00:16:00,480 Speaker 1: philanthropic arm, the Exact Target Foundation, which was founded in 297 00:16:00,560 --> 00:16:04,440 Speaker 1: twenty eleven, and they that's dedicated to doing lots of 298 00:16:04,480 --> 00:16:08,680 Speaker 1: stuff like helping with hunger relief, increasing educational efforts, and 299 00:16:08,720 --> 00:16:13,560 Speaker 1: even supporting entrepreneurship across the world. So it's a company 300 00:16:13,600 --> 00:16:17,240 Speaker 1: that involves itself in multiple ways with its community. So 301 00:16:17,320 --> 00:16:19,280 Speaker 1: that's good. Yeah, it was doing so well for itself 302 00:16:19,280 --> 00:16:21,640 Speaker 1: at Salesforce dot Com announced that it was going to 303 00:16:21,720 --> 00:16:24,960 Speaker 1: acquire the company for two point five billion in June 304 00:16:25,000 --> 00:16:28,120 Speaker 1: of this year, yep, and completed that acquisition in July. 305 00:16:28,400 --> 00:16:31,880 Speaker 1: So technically this company is now part of another company. 306 00:16:31,880 --> 00:16:33,320 Speaker 1: It's kind of funny because when I was looking at 307 00:16:33,360 --> 00:16:36,360 Speaker 1: this list, Uh, some of the other ones further up 308 00:16:36,400 --> 00:16:39,720 Speaker 1: the list above number ten are companies that now are 309 00:16:39,760 --> 00:16:43,080 Speaker 1: the same company. I think it was like numbers fourteen 310 00:16:43,080 --> 00:16:45,400 Speaker 1: and thirteen or something like that are now part of 311 00:16:45,440 --> 00:16:48,640 Speaker 1: the same company. So yeah, salesforce dot Com also was 312 00:16:48,840 --> 00:16:54,040 Speaker 1: number nine on last year's list. And uh apparently you know, 313 00:16:54,720 --> 00:16:59,160 Speaker 1: uh exact target has actually boosted the sales forecast for 314 00:16:59,440 --> 00:17:02,720 Speaker 1: sales force dot Com. So salesforce dot Com had a 315 00:17:02,760 --> 00:17:06,840 Speaker 1: certain number that was projected out by its analysts right saying, 316 00:17:07,040 --> 00:17:08,760 Speaker 1: this is what we expect to hit by the end 317 00:17:08,800 --> 00:17:12,520 Speaker 1: of the year. By acquiring, uh this this company, they've 318 00:17:12,560 --> 00:17:16,080 Speaker 1: actually managed to boost that up, so now they're performing 319 00:17:16,119 --> 00:17:20,119 Speaker 1: above what they had projected. So in fact, exact target 320 00:17:20,160 --> 00:17:23,560 Speaker 1: has really been a benefit to Salesforce already in the 321 00:17:23,600 --> 00:17:26,800 Speaker 1: short term financial scale of things. It remains to be 322 00:17:26,840 --> 00:17:29,919 Speaker 1: seen how this plays out over time, because anytime you 323 00:17:29,960 --> 00:17:33,160 Speaker 1: have an acquisition there are some issues to work out 324 00:17:33,200 --> 00:17:36,560 Speaker 1: with cultural differences between the two different or two or 325 00:17:36,560 --> 00:17:40,719 Speaker 1: more different companies different entities. But one would hope that 326 00:17:40,800 --> 00:17:43,359 Speaker 1: since Salesforce has been on this list before and exact 327 00:17:43,359 --> 00:17:47,320 Speaker 1: targets on it this year, that it wouldn't change too much. Hopefully. Yeah, 328 00:17:47,359 --> 00:17:50,800 Speaker 1: although definitely some of the some of the reasons that 329 00:17:50,880 --> 00:17:54,000 Speaker 1: people gave for enjoying working at some of these places 330 00:17:54,080 --> 00:17:57,320 Speaker 1: varied hugely among different companies on the list. You know, 331 00:17:57,359 --> 00:18:00,520 Speaker 1: some people said, I love this company because you get 332 00:18:00,520 --> 00:18:02,840 Speaker 1: to act like a crazy college kid, and others are like, 333 00:18:02,880 --> 00:18:05,040 Speaker 1: I love this company because they don't make you act 334 00:18:05,080 --> 00:18:08,360 Speaker 1: like a crazy college kid. Right, so yeah, So it's 335 00:18:08,400 --> 00:18:10,400 Speaker 1: also one of the things that really benefits you when 336 00:18:10,400 --> 00:18:13,000 Speaker 1: you do your own research, because you have to take 337 00:18:13,080 --> 00:18:16,919 Speaker 1: into consideration your own ideal working situation, right, Like, if 338 00:18:16,920 --> 00:18:20,359 Speaker 1: you're one of those people who really thrives on collaboration, 339 00:18:20,920 --> 00:18:23,359 Speaker 1: and you you have to be around other people, and 340 00:18:23,359 --> 00:18:25,840 Speaker 1: you love working on projects with people, and maybe maybe 341 00:18:25,880 --> 00:18:28,399 Speaker 1: even working on projects with different groups of people throughout 342 00:18:28,400 --> 00:18:30,440 Speaker 1: your career, so it's not like you're part of a 343 00:18:30,600 --> 00:18:34,040 Speaker 1: team that's really cohesive. You your team changes, you know, 344 00:18:34,080 --> 00:18:37,359 Speaker 1: project a project. Then obviously one type of company is 345 00:18:37,400 --> 00:18:39,479 Speaker 1: going to be a better fit for you than some 346 00:18:39,560 --> 00:18:41,359 Speaker 1: other company where you're sitting at a desk and you're 347 00:18:41,359 --> 00:18:43,800 Speaker 1: always doing the same thing all the time always. However, 348 00:18:43,960 --> 00:18:47,280 Speaker 1: if you like stability, that other version sounds way more 349 00:18:47,840 --> 00:18:50,479 Speaker 1: your speed than some crazy one where you have no 350 00:18:50,600 --> 00:18:52,520 Speaker 1: idea who you'll be working with from one day to 351 00:18:52,560 --> 00:18:57,359 Speaker 1: the next. I'm I'm kind of in both camps on 352 00:18:57,400 --> 00:18:59,560 Speaker 1: that one, but I mostly work with the same people 353 00:18:59,560 --> 00:19:02,359 Speaker 1: from data day, so I guess I have that benefit mostly. 354 00:19:02,359 --> 00:19:05,600 Speaker 1: I mean, we've got a wide team of similarly crazy 355 00:19:05,640 --> 00:19:08,040 Speaker 1: people running around. Let me put to you this way, 356 00:19:08,200 --> 00:19:10,480 Speaker 1: if Josh Clark ever comes up to me and says, hey, Strick, 357 00:19:10,600 --> 00:19:12,399 Speaker 1: I need your help with something, I ask a lot 358 00:19:12,480 --> 00:19:15,080 Speaker 1: of questions before I agree. The last time that I 359 00:19:15,160 --> 00:19:17,800 Speaker 1: ran into Josh Clark on the elevator, he was carrying 360 00:19:17,920 --> 00:19:21,199 Speaker 1: like like three packages of rope, like industrial rope and 361 00:19:21,200 --> 00:19:24,320 Speaker 1: I was like, Hey, good morning, Josh, how are you doing. Yeah, 362 00:19:24,359 --> 00:19:27,080 Speaker 1: so it pays to ask questions around here, that's what 363 00:19:27,119 --> 00:19:30,359 Speaker 1: we're saying. Let's move on to number eight. Number eight 364 00:19:30,480 --> 00:19:34,040 Speaker 1: is is another digital marketing company called Responses. Yeah, this 365 00:19:34,080 --> 00:19:36,760 Speaker 1: one again. This was another one. Both Exact Target and 366 00:19:36,800 --> 00:19:40,040 Speaker 1: Responses were companies where I had to dig a little 367 00:19:40,080 --> 00:19:42,879 Speaker 1: deeper to really understand what they do because Lauren and 368 00:19:42,920 --> 00:19:45,360 Speaker 1: I do a little bit of marketing on a very 369 00:19:45,440 --> 00:19:49,399 Speaker 1: surface level, very surface. We like to interact with people 370 00:19:49,400 --> 00:19:52,800 Speaker 1: on social networks, which technically falls under the category of marketing, 371 00:19:52,800 --> 00:19:54,600 Speaker 1: but we think of it as being able to like 372 00:19:54,720 --> 00:19:57,919 Speaker 1: share awesome stuff with our fans and find out what 373 00:19:57,960 --> 00:20:00,800 Speaker 1: they like, so we don't really necessarily think of it 374 00:20:00,840 --> 00:20:03,119 Speaker 1: in the same terms as a marketing department would. So 375 00:20:03,160 --> 00:20:05,360 Speaker 1: a lot of this is like foreign language to us. 376 00:20:05,600 --> 00:20:08,760 Speaker 1: But Responses is one of the companies that will do 377 00:20:08,880 --> 00:20:11,280 Speaker 1: more of this stuff for you. They also work in 378 00:20:11,400 --> 00:20:14,119 Speaker 1: you know, email, mobile, social, and web, but with a 379 00:20:14,200 --> 00:20:17,720 Speaker 1: full like software planning and implementation kind of package. Yeah, 380 00:20:17,800 --> 00:20:20,720 Speaker 1: and they were founded in n Their headquarters are in 381 00:20:20,800 --> 00:20:24,520 Speaker 1: San Bruno, California. It turns out California is a great 382 00:20:24,520 --> 00:20:27,960 Speaker 1: place to work if you're in tech weird right you 383 00:20:28,080 --> 00:20:30,240 Speaker 1: never thought of it in Silicon Valley and all that 384 00:20:30,320 --> 00:20:34,120 Speaker 1: kind of stuff. Um, So they also do a lot 385 00:20:34,119 --> 00:20:36,639 Speaker 1: of research on what are the most effective means of 386 00:20:36,680 --> 00:20:39,760 Speaker 1: reaching consumers. Uh that if you go to the website, 387 00:20:39,760 --> 00:20:42,600 Speaker 1: one of the taglines on there is your customers want experiences, 388 00:20:42,720 --> 00:20:45,480 Speaker 1: not campaigns. So the idea being that, you know, it's 389 00:20:45,480 --> 00:20:48,560 Speaker 1: not just not just the delivery method, but also what's 390 00:20:48,600 --> 00:20:51,159 Speaker 1: the actual message, what what are you trying, what's the 391 00:20:51,200 --> 00:20:53,879 Speaker 1: effect you're trying to get besides just people interested in 392 00:20:53,920 --> 00:20:57,439 Speaker 1: your product, and they they try and construct an entire 393 00:20:57,520 --> 00:21:02,200 Speaker 1: approach from attracted the consumer, making them aware of who 394 00:21:02,240 --> 00:21:05,120 Speaker 1: you are and what you do, getting them to purchase 395 00:21:05,800 --> 00:21:08,600 Speaker 1: the whatever product or service you offer, and then getting 396 00:21:08,680 --> 00:21:11,400 Speaker 1: them to repurchase later on. So the idea being that 397 00:21:11,680 --> 00:21:16,080 Speaker 1: you convert a customer into a loyal customer. That sort 398 00:21:16,119 --> 00:21:19,879 Speaker 1: of conversion is obviously really important for a lot of businesses. 399 00:21:19,920 --> 00:21:21,960 Speaker 1: I mean, it's great if you can make a sale, 400 00:21:22,240 --> 00:21:25,160 Speaker 1: it's better if you can make a lifelong customer. So 401 00:21:25,240 --> 00:21:27,720 Speaker 1: that's kind of what their approaches is to try and 402 00:21:27,960 --> 00:21:33,800 Speaker 1: help their customers, their corporate customers achieve that. Another thing 403 00:21:34,080 --> 00:21:39,560 Speaker 1: they actually refer to their strategy as marketing orchestration, which 404 00:21:39,840 --> 00:21:42,280 Speaker 1: if a marketing company can't come up with really goofy 405 00:21:42,359 --> 00:21:44,480 Speaker 1: like taglines like that, but they're not a very good 406 00:21:44,520 --> 00:21:47,520 Speaker 1: marketing Yeah. So those another way, those where I was like, huh, 407 00:21:47,600 --> 00:21:50,320 Speaker 1: But again it was this idea of a customized experience, 408 00:21:50,640 --> 00:21:54,399 Speaker 1: a personalized experience, so that uh, the idea being that 409 00:21:54,480 --> 00:21:58,920 Speaker 1: if you are a customer of of responses, they will 410 00:21:59,359 --> 00:22:02,280 Speaker 1: craft their their approach in such a way that every 411 00:22:02,280 --> 00:22:05,880 Speaker 1: one of your customers will get a personalized experience, which 412 00:22:05,880 --> 00:22:09,000 Speaker 1: will make them feel valued as a customer and therefore 413 00:22:09,240 --> 00:22:13,360 Speaker 1: improve the chances of them coming becoming a repeat customer. Say, yeah, so, 414 00:22:14,080 --> 00:22:16,080 Speaker 1: I mean it's important work. It's one of those things 415 00:22:16,080 --> 00:22:17,640 Speaker 1: where you know, again a lot of us just sort 416 00:22:17,640 --> 00:22:19,399 Speaker 1: of take it for granted because we are on the 417 00:22:19,440 --> 00:22:22,600 Speaker 1: receiving end of this marketing more often than we're on 418 00:22:22,680 --> 00:22:24,760 Speaker 1: the generation. And unless you have to work for a 419 00:22:24,840 --> 00:22:27,600 Speaker 1: marketing sure, and and it's easy to tell where marketing 420 00:22:27,680 --> 00:22:29,760 Speaker 1: has gone wrong, but it's a little bit harder to 421 00:22:29,800 --> 00:22:32,119 Speaker 1: identify when it goes right, because then you just have 422 00:22:32,240 --> 00:22:35,680 Speaker 1: good feelings about stuff that things you know, stuff that 423 00:22:35,720 --> 00:22:39,439 Speaker 1: people want you to feel good about, which is I 424 00:22:39,440 --> 00:22:41,040 Speaker 1: don't know. It can be swell and it can be 425 00:22:41,160 --> 00:22:43,439 Speaker 1: terrifically creepy, it can be It all depends on the 426 00:22:43,480 --> 00:22:46,840 Speaker 1: implementation and the message that you're making. UM. So Yeah, 427 00:22:46,880 --> 00:22:49,160 Speaker 1: so they had their I p O in twenty eleven 428 00:22:49,240 --> 00:22:52,000 Speaker 1: and raised seventy nine point two million. Not bad for 429 00:22:52,000 --> 00:22:54,880 Speaker 1: for a small company, although they are no longer quite 430 00:22:54,880 --> 00:22:58,320 Speaker 1: so small. They have grown to have offices worldwide and 431 00:22:58,359 --> 00:23:01,480 Speaker 1: they seem to be UM just really writing that changing 432 00:23:01,520 --> 00:23:04,000 Speaker 1: marketing industry really well, because it's a space that a 433 00:23:04,000 --> 00:23:07,520 Speaker 1: lot of companies aren't sure in these you know, brave 434 00:23:07,560 --> 00:23:11,440 Speaker 1: new digital times how to reach people? And so how 435 00:23:11,440 --> 00:23:14,480 Speaker 1: did they come out in this um in this this test, 436 00:23:14,600 --> 00:23:17,080 Speaker 1: like what what was their rating? It was a four 437 00:23:17,359 --> 00:23:20,600 Speaker 1: point two point two four point two and point one 438 00:23:20,680 --> 00:23:24,359 Speaker 1: better than the other two. Yes, stiff competition and CEO 439 00:23:24,480 --> 00:23:28,600 Speaker 1: approval rating of Mr Dan Springer at they're really good. Yeah. 440 00:23:28,600 --> 00:23:31,359 Speaker 1: They actually had a lot of employees giving comments to 441 00:23:31,640 --> 00:23:36,160 Speaker 1: things about you know, there's a lot of growth opportunity, 442 00:23:37,040 --> 00:23:41,480 Speaker 1: but sometimes according to some employees, the starting positions might 443 00:23:41,520 --> 00:23:45,680 Speaker 1: have lower salaries than what you would find in competing companies. Yeah, 444 00:23:45,720 --> 00:23:47,479 Speaker 1: a lot of people were saying that it's, you know, 445 00:23:48,160 --> 00:23:49,720 Speaker 1: the company is still growing and so a lot of 446 00:23:49,720 --> 00:23:51,679 Speaker 1: the problems are still kind of being ironed out, and 447 00:23:51,680 --> 00:23:55,360 Speaker 1: some sometimes communication gets lost in between different management tiers. Yeah, 448 00:23:55,359 --> 00:23:57,600 Speaker 1: I mean it's it's tough when you are a small 449 00:23:57,640 --> 00:24:00,119 Speaker 1: startup and you're really nimble and then you're making that 450 00:24:00,160 --> 00:24:02,200 Speaker 1: transition and then all of a sudden you're global. Yeah, 451 00:24:02,240 --> 00:24:05,159 Speaker 1: that's that. There are huge challenges that come with that, 452 00:24:05,280 --> 00:24:08,400 Speaker 1: just like the challenges that you know, an acquiring company 453 00:24:08,440 --> 00:24:11,480 Speaker 1: gets when they get this awesome new property and then 454 00:24:11,520 --> 00:24:13,000 Speaker 1: have to figure out how to make it work within 455 00:24:13,040 --> 00:24:16,040 Speaker 1: their own culture. These are these are big issues and 456 00:24:16,119 --> 00:24:18,639 Speaker 1: it's been big growth, hasn't it. Yeah. Yeah, Actually, uh, 457 00:24:18,680 --> 00:24:22,440 Speaker 1: Wall Street Journal reports that responses had twenty seven percent 458 00:24:22,600 --> 00:24:26,439 Speaker 1: growth in the third quarter of UH and they also 459 00:24:26,920 --> 00:24:28,920 Speaker 1: did a survey responses to the survey, they were the 460 00:24:28,920 --> 00:24:33,640 Speaker 1: actual ones conducting the survey and discovered that marketers are 461 00:24:33,640 --> 00:24:37,800 Speaker 1: not leveraging mobile platforms as effectively as they could. They 462 00:24:37,800 --> 00:24:40,120 Speaker 1: were looking at how many people were starting to use 463 00:24:40,160 --> 00:24:42,920 Speaker 1: mobile platforms to do some shopping, which is something we'll 464 00:24:42,960 --> 00:24:46,879 Speaker 1: talk about in an upcoming podcast. But uh, it's you know, 465 00:24:47,000 --> 00:24:49,359 Speaker 1: they said, you know, considering how many people are using this. 466 00:24:49,520 --> 00:24:53,160 Speaker 1: We are not leveraging our marketing money nearly well enough 467 00:24:53,200 --> 00:24:56,320 Speaker 1: across multiple industries. We've got to figure that out. And 468 00:24:56,359 --> 00:24:58,119 Speaker 1: so that was more of a you know kind of 469 00:24:58,160 --> 00:25:01,040 Speaker 1: I mean, it helps drum up business for am marketing firm, obviously, 470 00:25:01,359 --> 00:25:04,199 Speaker 1: but it also is something that's true. You know, the mobile, 471 00:25:04,480 --> 00:25:08,280 Speaker 1: the mobile browsing world is relatively young, and just as 472 00:25:08,320 --> 00:25:10,720 Speaker 1: marketing departments were starting to finally get a feel for 473 00:25:10,800 --> 00:25:13,359 Speaker 1: the web, now you've got this new implementation that you 474 00:25:13,359 --> 00:25:15,159 Speaker 1: have to worry about. Yeah, it's very tricky. We we 475 00:25:15,200 --> 00:25:16,960 Speaker 1: talked a little bit about that in that mobile ads 476 00:25:17,359 --> 00:25:20,040 Speaker 1: episode that we did. And I think that the shopping 477 00:25:20,080 --> 00:25:22,320 Speaker 1: episode that you're talking about is coming up on forward 478 00:25:22,359 --> 00:25:26,080 Speaker 1: Thinking not TEXTFF. Actually, it's one of the number of 479 00:25:26,200 --> 00:25:30,160 Speaker 1: predictions that we made for that. I'm thinking, oh that 480 00:25:30,200 --> 00:25:33,080 Speaker 1: one our annual wrap up. Yeah, it'll be a small 481 00:25:33,200 --> 00:25:36,199 Speaker 1: part of it. Well, before we get into the last 482 00:25:36,320 --> 00:25:39,920 Speaker 1: couple of the the first section of the top ten, 483 00:25:40,000 --> 00:25:42,120 Speaker 1: let's see how many propositions I can throw into one 484 00:25:42,200 --> 00:25:45,040 Speaker 1: sentence because it's a preposition. Now, did you know, I know, 485 00:25:45,160 --> 00:25:47,760 Speaker 1: I saw that It's actually exciting. Okay, grammar geeks, right, 486 00:25:47,760 --> 00:25:51,120 Speaker 1: here we're gonna geek out, but before we do, let's 487 00:25:51,160 --> 00:25:55,399 Speaker 1: take a quick break to thank our sponsor. Okay, we're back. 488 00:25:55,880 --> 00:25:59,000 Speaker 1: Let's see we're up to number seven, I think right, yes, 489 00:25:59,040 --> 00:26:03,440 Speaker 1: and that would be a company workday, work work day? Okay, 490 00:26:03,920 --> 00:26:05,800 Speaker 1: what is work day? This is another one that I 491 00:26:05,840 --> 00:26:10,440 Speaker 1: had never heard. Yeah, they do HR software. Okay, alright, well, 492 00:26:10,600 --> 00:26:12,359 Speaker 1: all right now I got it because I worked for 493 00:26:12,400 --> 00:26:16,200 Speaker 1: that human resources management consulting firm. So now we're speaking 494 00:26:16,760 --> 00:26:19,480 Speaker 1: my language. Okay, so let's a build as cloud based. 495 00:26:19,800 --> 00:26:23,560 Speaker 1: They lost me. That didn't exist when I worked in 496 00:26:23,600 --> 00:26:27,880 Speaker 1: that world. But human capital management and financial management, human 497 00:26:27,920 --> 00:26:33,080 Speaker 1: capital management is like you know, no, no slight against 498 00:26:33,240 --> 00:26:37,760 Speaker 1: work day. But that particular phrase is not one that 499 00:26:37,840 --> 00:26:40,320 Speaker 1: fills me with the warm fuzzies. What about you human 500 00:26:40,480 --> 00:26:43,200 Speaker 1: capital managed? I can't imagine anyone other than like Cat 501 00:26:43,280 --> 00:26:48,960 Speaker 1: Birch saying, where you talk about not employees but their assets. 502 00:26:49,000 --> 00:26:51,679 Speaker 1: These are things that can be treated and sold and 503 00:26:51,760 --> 00:26:55,800 Speaker 1: bought on the market. However, I do appreciate the insinuation 504 00:26:55,840 --> 00:27:01,040 Speaker 1: that employees have intrinsic value that you want to um love. Yes, 505 00:27:01,160 --> 00:27:03,879 Speaker 1: that part makes perfect sen and yes it's hard to 506 00:27:03,880 --> 00:27:06,160 Speaker 1: say this in a succinct way that doesn't come out 507 00:27:06,200 --> 00:27:09,800 Speaker 1: too touchy feely, but it's also really easy to say 508 00:27:09,840 --> 00:27:11,480 Speaker 1: in a way that makes you sound like a robot. 509 00:27:11,560 --> 00:27:13,000 Speaker 1: I would I would be a lot more offended if 510 00:27:13,000 --> 00:27:17,239 Speaker 1: it was called like like human marshmallow or I don't know, 511 00:27:17,320 --> 00:27:20,359 Speaker 1: I'm gonna make that my next my next title on 512 00:27:20,400 --> 00:27:23,520 Speaker 1: my next business card. I certainly need to make one 513 00:27:23,920 --> 00:27:26,040 Speaker 1: so you can do what you want. Yeah, it's true. 514 00:27:26,560 --> 00:27:29,800 Speaker 1: What this actually means is that the company uses creates 515 00:27:29,800 --> 00:27:33,160 Speaker 1: tools for other companies to use to monitor everything from 516 00:27:33,280 --> 00:27:37,400 Speaker 1: financial department type stuff like expenses and pay roll and 517 00:27:37,440 --> 00:27:40,200 Speaker 1: all of that kind of thing, to the human resources side. 518 00:27:40,240 --> 00:27:44,520 Speaker 1: So you're talking about talent management, organization, UM benefits, all 519 00:27:44,520 --> 00:27:47,280 Speaker 1: that kind of stuff, all the things that these different 520 00:27:47,280 --> 00:27:50,280 Speaker 1: departments would. You know, we talked about that mega company 521 00:27:50,400 --> 00:27:52,600 Speaker 1: from way back when, where it would have all the 522 00:27:52,640 --> 00:27:56,920 Speaker 1: different distinct departments. In this case, it's this company workday 523 00:27:57,160 --> 00:27:59,920 Speaker 1: is trying to kind of fill the roles of finance 524 00:28:00,119 --> 00:28:03,520 Speaker 1: departments and human resources departments. Yeah, just just doing that 525 00:28:03,560 --> 00:28:06,119 Speaker 1: saying hey, we do this really good, let us do 526 00:28:06,119 --> 00:28:08,480 Speaker 1: do it for you. Yeah. Because again, if if Lauren 527 00:28:08,480 --> 00:28:10,320 Speaker 1: and I decide that we want to start a company 528 00:28:10,320 --> 00:28:13,359 Speaker 1: together and we end up raising the capital somehow because 529 00:28:13,440 --> 00:28:16,960 Speaker 1: kickstartered went nuts, and uh, we haven't even figured out 530 00:28:17,040 --> 00:28:18,639 Speaker 1: how we're gonna build the thing we're gonna build, but 531 00:28:18,680 --> 00:28:21,960 Speaker 1: we've already got like millions of dollars. Here's the thing 532 00:28:22,000 --> 00:28:24,159 Speaker 1: we're gonna have. One day, you just wake up and go, Lauren, 533 00:28:24,240 --> 00:28:27,639 Speaker 1: do you do you know how to fill out any 534 00:28:27,720 --> 00:28:31,120 Speaker 1: of these forms? I don't even know what quick books is. Yeah. Yeah, 535 00:28:31,160 --> 00:28:32,760 Speaker 1: See at that point, we were like, we need to 536 00:28:32,840 --> 00:28:35,359 Speaker 1: hire people who know what they're doing so that we 537 00:28:35,480 --> 00:28:38,120 Speaker 1: do everything correctly. And that's again what work day does. 538 00:28:38,160 --> 00:28:41,480 Speaker 1: They're looking at the finance side and the human resources side, 539 00:28:41,680 --> 00:28:44,000 Speaker 1: and and again all these tools are involved on the 540 00:28:44,040 --> 00:28:47,200 Speaker 1: cloud so that you can access them from anywhere and 541 00:28:47,400 --> 00:28:50,239 Speaker 1: you know, yeah, which you know makes great sense if 542 00:28:50,280 --> 00:28:53,320 Speaker 1: you if you are these days really Yeah, if you're 543 00:28:53,320 --> 00:28:56,160 Speaker 1: a mobile executive, if you're moving around doing lots of 544 00:28:56,200 --> 00:28:58,040 Speaker 1: meetings and stuff and you want to be able to 545 00:28:58,160 --> 00:29:00,360 Speaker 1: check in, uh, you know, and and see things on 546 00:29:00,360 --> 00:29:03,480 Speaker 1: a granular level in whatever department, whether it's finance or 547 00:29:03,520 --> 00:29:07,160 Speaker 1: human resources or whatever, then tools like this make that possible. 548 00:29:07,160 --> 00:29:09,600 Speaker 1: Where you can you know, you even have like smartphone 549 00:29:09,600 --> 00:29:13,600 Speaker 1: app implementation here so that you can see and and 550 00:29:13,640 --> 00:29:16,800 Speaker 1: maybe you're doing a presentation for a potential client or 551 00:29:16,880 --> 00:29:19,479 Speaker 1: maybe even a potential partner, and you can pull up 552 00:29:19,520 --> 00:29:22,480 Speaker 1: real time information and analytics and say, look, here's here's 553 00:29:22,480 --> 00:29:25,080 Speaker 1: how we're doing, here's what we're doing, here's what's working, 554 00:29:25,120 --> 00:29:27,520 Speaker 1: and this is why you should be working with us. 555 00:29:28,200 --> 00:29:31,280 Speaker 1: So uh, you know, again, not a company that's going 556 00:29:31,360 --> 00:29:34,200 Speaker 1: to be providing anything that you and I as average 557 00:29:34,200 --> 00:29:37,320 Speaker 1: consumers are going to see, but maybe the company you 558 00:29:37,360 --> 00:29:41,520 Speaker 1: work for would be. Yeah. Um. They were founded in 559 00:29:41,560 --> 00:29:44,800 Speaker 1: two thousand five from a group of people from people Soft, 560 00:29:45,040 --> 00:29:48,720 Speaker 1: which had been been hostily taken over by Oracle. Yeah. Now, 561 00:29:48,760 --> 00:29:52,680 Speaker 1: the people from Oracle came in pitchforks waving torches blazing 562 00:29:52,800 --> 00:29:56,200 Speaker 1: and said this is ours now. Uh, and a group 563 00:29:56,440 --> 00:29:59,800 Speaker 1: of folks from People's Soft said you know what and 564 00:30:00,120 --> 00:30:05,520 Speaker 1: left to found this company. So uh that actually was well, 565 00:30:05,560 --> 00:30:08,120 Speaker 1: it will become a bit of a thorn in a 566 00:30:08,360 --> 00:30:11,160 Speaker 1: in some employees sides, according to one of the comments. 567 00:30:11,200 --> 00:30:14,480 Speaker 1: But uh. They They also held an I P O 568 00:30:14,560 --> 00:30:16,760 Speaker 1: in October two thousand twelve, so it is a publicly 569 00:30:16,800 --> 00:30:19,960 Speaker 1: traded company in its own right, um, and has done 570 00:30:20,120 --> 00:30:23,800 Speaker 1: quite well for itself. So this one also rated pretty high. 571 00:30:24,400 --> 00:30:28,000 Speaker 1: Uh yeah, they are a four point two and um 572 00:30:28,040 --> 00:30:32,840 Speaker 1: CEO approval rating of Mr and Neil Mercy, although we 573 00:30:32,840 --> 00:30:35,760 Speaker 1: should point out he is a co CEO and a 574 00:30:35,840 --> 00:30:39,280 Speaker 1: co founder. Okay, yeah, it's it's not on the list there. 575 00:30:39,320 --> 00:30:42,000 Speaker 1: But yeah, did you notice that the list had a 576 00:30:42,000 --> 00:30:44,959 Speaker 1: couple of percentages that had a little asterisk next to him? 577 00:30:45,160 --> 00:30:48,479 Speaker 1: Did you find what the asterisk meant? As far as 578 00:30:48,480 --> 00:30:51,080 Speaker 1: I could tell, it was an asterisk to nowhere. Yeah. See, 579 00:30:51,080 --> 00:30:52,760 Speaker 1: that's what I thought too. And then when I actually 580 00:30:52,760 --> 00:30:56,160 Speaker 1: looked at work days organization chart, I saw that it 581 00:30:56,200 --> 00:30:58,880 Speaker 1: was a co CEO. So that's a potential answer to 582 00:30:58,920 --> 00:31:02,880 Speaker 1: that question. Well okay, and so so employees say that 583 00:31:03,080 --> 00:31:05,680 Speaker 1: there are lots of incredibly smart people working there and 584 00:31:06,000 --> 00:31:09,240 Speaker 1: that you know, for for all of the hard work 585 00:31:09,280 --> 00:31:11,640 Speaker 1: that those smart people are doing, their their voices are 586 00:31:11,680 --> 00:31:14,720 Speaker 1: appreciated and heard. Yes, yeah, they actually say that the 587 00:31:15,080 --> 00:31:18,160 Speaker 1: organization there is very flat. In other words, you don't 588 00:31:18,200 --> 00:31:21,880 Speaker 1: have this level of mid managers in between you and 589 00:31:21,960 --> 00:31:25,800 Speaker 1: the people who are actually making the decision. So your 590 00:31:25,920 --> 00:31:29,560 Speaker 1: your voice is very important to everyone. However, like we 591 00:31:29,560 --> 00:31:31,920 Speaker 1: were saying, some of the complaints going on are are 592 00:31:32,000 --> 00:31:36,240 Speaker 1: just that if you weren't part of that people Soft transfer, 593 00:31:36,760 --> 00:31:39,520 Speaker 1: that there's a little bit of a clicky sort of problem, 594 00:31:39,600 --> 00:31:41,960 Speaker 1: like people like the people who came over from people 595 00:31:42,000 --> 00:31:45,720 Speaker 1: Soft are in a slightly different echelon than everybody else, 596 00:31:45,760 --> 00:31:50,480 Speaker 1: and that your your prospects for getting promoted or getting 597 00:31:50,480 --> 00:31:52,880 Speaker 1: a raise maybe affected by whether or not you happen 598 00:31:52,880 --> 00:31:55,200 Speaker 1: to be one of the people Soft elite. So even 599 00:31:55,240 --> 00:31:58,360 Speaker 1: though the organization is pretty flat, it can be difficult 600 00:31:58,400 --> 00:32:02,000 Speaker 1: if you weren't in that ground floor exactly. And as 601 00:32:02,040 --> 00:32:05,560 Speaker 1: for recent news, there's some interesting recent news. The other 602 00:32:05,720 --> 00:32:08,480 Speaker 1: co CEO, Dave Duffield, who was another one of the 603 00:32:08,520 --> 00:32:12,120 Speaker 1: founders of this company of work Day, sold off most 604 00:32:12,160 --> 00:32:16,920 Speaker 1: of his stock in the company back in November. Specifically, 605 00:32:16,920 --> 00:32:20,360 Speaker 1: he sold three hundred forty eight thousand, one twenty six shares. 606 00:32:20,720 --> 00:32:24,120 Speaker 1: He still retains more than fifty nine thousand shares, but 607 00:32:24,200 --> 00:32:27,320 Speaker 1: obviously he sold most of them and that was worth 608 00:32:27,360 --> 00:32:31,840 Speaker 1: a cool twenty seven point eight million dollars, so not 609 00:32:31,960 --> 00:32:36,080 Speaker 1: a bad haul there. Yeah, And that same day, Yeah, 610 00:32:36,240 --> 00:32:38,680 Speaker 1: CEO ce all right, you gutta say the name, because 611 00:32:38,680 --> 00:32:42,680 Speaker 1: I'm going to giggle if I say Michael Stankley. No, No, 612 00:32:42,720 --> 00:32:47,000 Speaker 1: there's no L there. It's stank I just imagined the 613 00:32:47,040 --> 00:32:49,640 Speaker 1: whole L. Now, that's fine, I mean I would do no. 614 00:32:49,840 --> 00:32:55,360 Speaker 1: Michael Stanky also CEO, sold forty four shares but retains 615 00:32:55,360 --> 00:32:58,440 Speaker 1: more than one hundred thousand shares. So that's nonetheless, that's 616 00:32:58,480 --> 00:33:02,360 Speaker 1: a decently big upset of share trading. Yeah, it was 617 00:33:02,400 --> 00:33:05,040 Speaker 1: a lot of there's a lot of shares that were unloaded. Um, 618 00:33:05,320 --> 00:33:08,320 Speaker 1: and and it doesn't mean that the company is doing poorly. 619 00:33:08,320 --> 00:33:11,840 Speaker 1: In fact, the uh, the amount that they unloaded it, 620 00:33:11,880 --> 00:33:14,280 Speaker 1: I think it was like somewhere around the mid seventies, 621 00:33:14,720 --> 00:33:17,120 Speaker 1: like around seventy five dollars something like that at the 622 00:33:17,120 --> 00:33:20,040 Speaker 1: share price that they sold their shares off of. But 623 00:33:20,280 --> 00:33:23,479 Speaker 1: they had done that just before there had been talks 624 00:33:23,520 --> 00:33:27,280 Speaker 1: about the share price rising up to be between seventy 625 00:33:27,400 --> 00:33:30,560 Speaker 1: nine and eighty five dollars per share, So in reality, 626 00:33:30,560 --> 00:33:35,200 Speaker 1: it's not like they were Yeah. So I and obviously 627 00:33:35,240 --> 00:33:38,320 Speaker 1: I can't speak to what their motives were or you know, 628 00:33:38,360 --> 00:33:40,720 Speaker 1: if they were trying to do this to get new 629 00:33:41,360 --> 00:33:44,120 Speaker 1: investment in the company. I don't know. I I honestly 630 00:33:44,120 --> 00:33:47,280 Speaker 1: don't know. Uh, they clearly have done quite a lot 631 00:33:47,320 --> 00:33:49,600 Speaker 1: of work to get the company valued at what it 632 00:33:49,680 --> 00:33:52,960 Speaker 1: is now. So, um, we'll see how this plays out 633 00:33:53,600 --> 00:33:56,600 Speaker 1: and an interesting thing to watch. Um. The next one 634 00:33:56,640 --> 00:34:00,000 Speaker 1: on our list, number six is a SAS Institute. Yeah, 635 00:34:00,600 --> 00:34:02,800 Speaker 1: is a little bit more familiar. Yeah, s a s 636 00:34:02,880 --> 00:34:05,000 Speaker 1: is what we've called it in a previous podcast, But 637 00:34:05,080 --> 00:34:07,440 Speaker 1: turns out you're supposed to call it SASS. I did 638 00:34:07,440 --> 00:34:10,160 Speaker 1: not know that until I happened to read it on 639 00:34:10,239 --> 00:34:13,680 Speaker 1: the website. We we've mentioned SAS once before, not just 640 00:34:13,760 --> 00:34:17,360 Speaker 1: as a company, but as a way of life. Well 641 00:34:17,400 --> 00:34:20,640 Speaker 1: obviously both Jonathan and I lived the sas. Yeah, we're 642 00:34:20,680 --> 00:34:23,560 Speaker 1: a little sassy, But no sas we talked about because 643 00:34:24,000 --> 00:34:28,160 Speaker 1: I remember specifically because we loved the CEO's name, right, 644 00:34:28,320 --> 00:34:31,879 Speaker 1: James Goodnight Goodnight. Yeah, this is the company we talked 645 00:34:31,920 --> 00:34:35,120 Speaker 1: about when we were talking about the richest tech billionaires 646 00:34:35,840 --> 00:34:38,200 Speaker 1: we were we mentioned James Goodnight. I think he was 647 00:34:38,320 --> 00:34:41,760 Speaker 1: number of fifteen or number fourteen on Forbes list last year. Yeah, 648 00:34:42,000 --> 00:34:44,200 Speaker 1: he's one of the co founders of the Company's still 649 00:34:44,239 --> 00:34:47,520 Speaker 1: the CEO. Yep. And this is a company that, according 650 00:34:47,560 --> 00:34:50,719 Speaker 1: to the website, has turned a profit every single year 651 00:34:50,719 --> 00:34:54,800 Speaker 1: of his thirty five year existence, and that has incredibly 652 00:34:54,800 --> 00:34:57,319 Speaker 1: low employee turnover. As for what does this is a 653 00:34:57,480 --> 00:35:01,840 Speaker 1: business analytics software company. And if you remember our discussion 654 00:35:01,920 --> 00:35:05,960 Speaker 1: from the the The Tech Executive episode we did months 655 00:35:05,960 --> 00:35:09,759 Speaker 1: and months ago, they started off by creating software that 656 00:35:09,840 --> 00:35:14,120 Speaker 1: helped agricultural companies analyze huge amounts of data. The thing 657 00:35:14,200 --> 00:35:17,200 Speaker 1: was that the agricultural industry in the United States had 658 00:35:17,200 --> 00:35:21,600 Speaker 1: amassed huge, huge amounts of information, but it was really 659 00:35:21,640 --> 00:35:24,640 Speaker 1: hard to organize it, or to format it, or to 660 00:35:24,640 --> 00:35:28,200 Speaker 1: to make any real use of it. And what happened 661 00:35:28,239 --> 00:35:31,040 Speaker 1: was you had some engineers who came up with this 662 00:35:31,120 --> 00:35:34,640 Speaker 1: way of creating a software that would very effectively go 663 00:35:34,719 --> 00:35:38,560 Speaker 1: through all this and make it meaningful. So the data 664 00:35:38,600 --> 00:35:40,680 Speaker 1: that you had was actually useful. It wasn't just that 665 00:35:40,719 --> 00:35:42,640 Speaker 1: you had lots of it, but you could do things 666 00:35:42,640 --> 00:35:46,440 Speaker 1: with it. And that was just the very first major 667 00:35:46,600 --> 00:35:49,440 Speaker 1: customer that SAS had, and after that they started to 668 00:35:49,480 --> 00:35:53,640 Speaker 1: branch out into doing analytics software for various industries and 669 00:35:53,680 --> 00:35:57,200 Speaker 1: businesses and for lots of different applications. So again yet 670 00:35:57,200 --> 00:36:01,000 Speaker 1: another company that works with other companies, not with right, right, 671 00:36:01,040 --> 00:36:02,960 Speaker 1: but yeah, it's it's a lot of really smart and 672 00:36:03,000 --> 00:36:06,520 Speaker 1: scalable stuff that can help companies of basically any size, 673 00:36:06,680 --> 00:36:09,120 Speaker 1: you know, look at look at look at an analyze 674 00:36:09,160 --> 00:36:12,120 Speaker 1: their statistics and visualize that data and all of that 675 00:36:12,200 --> 00:36:16,080 Speaker 1: important stuff that, right, I mean, give you meaning to 676 00:36:16,160 --> 00:36:19,600 Speaker 1: the information that you're gathering. Right, I mean again, I 677 00:36:19,640 --> 00:36:21,480 Speaker 1: know we keep saying this over and over, but you 678 00:36:21,600 --> 00:36:24,040 Speaker 1: just think about the amount of information that your typical 679 00:36:24,200 --> 00:36:31,480 Speaker 1: large businesses is generating, whether it's sales figures, customer loyalty, uh, 680 00:36:31,880 --> 00:36:36,000 Speaker 1: you know, the company value. These are concepts that are 681 00:36:36,040 --> 00:36:38,560 Speaker 1: are really important and sometimes they're a little difficult to 682 00:36:38,560 --> 00:36:40,400 Speaker 1: get a grasp on. So if you have a company 683 00:36:40,400 --> 00:36:43,080 Speaker 1: that can analyze that data may make it meaningful, create 684 00:36:43,160 --> 00:36:46,160 Speaker 1: data visualization where you can actually see what it means. 685 00:36:46,680 --> 00:36:50,160 Speaker 1: That can be a huge benefit. And and apparently, according 686 00:36:50,200 --> 00:36:53,000 Speaker 1: to Sas themselves, it is a very large benefit. They 687 00:36:53,040 --> 00:36:56,320 Speaker 1: say that their customers represent ninety of the top companies 688 00:36:56,320 --> 00:37:01,000 Speaker 1: on Fortune's Global Yeah, so n scent of the top 689 00:37:01,120 --> 00:37:05,680 Speaker 1: one companies listed by Fortune in that global list. That's 690 00:37:05,920 --> 00:37:09,440 Speaker 1: I mean, that's a great resume. Yeah, so, I mean, 691 00:37:09,480 --> 00:37:13,040 Speaker 1: that's that's important there. Uh And yeah, apparently working there 692 00:37:13,160 --> 00:37:17,040 Speaker 1: is is, at least for some employees, kind of awesome. 693 00:37:17,080 --> 00:37:19,160 Speaker 1: Now now they have offices all over the place. But 694 00:37:19,200 --> 00:37:23,480 Speaker 1: their main campus looks pretty amazing. Is I mean a 695 00:37:23,560 --> 00:37:25,879 Speaker 1: huge campus. It's kind of I mean it's the sort 696 00:37:25,920 --> 00:37:29,840 Speaker 1: of like food and recreation and bringing your your work 697 00:37:29,920 --> 00:37:33,120 Speaker 1: life and your life life together into one giant, happy 698 00:37:33,239 --> 00:37:35,759 Speaker 1: college like maths. Yes. The idea being that if you 699 00:37:35,800 --> 00:37:39,479 Speaker 1: can make the experience of going to work pleasant and 700 00:37:39,640 --> 00:37:42,359 Speaker 1: uh and uh and and be able to offset some 701 00:37:42,440 --> 00:37:44,120 Speaker 1: of the things that a lot of people have to 702 00:37:44,200 --> 00:37:47,200 Speaker 1: sacrifice when they go to work full time. You know 703 00:37:47,239 --> 00:37:50,560 Speaker 1: that things like daycare or even having a gym on site, 704 00:37:51,040 --> 00:37:53,480 Speaker 1: these are things that can make a big difference in 705 00:37:53,480 --> 00:37:56,080 Speaker 1: a person's life. I mean, my excuse for not going 706 00:37:56,120 --> 00:37:58,160 Speaker 1: to the gym is that we don't have one in 707 00:37:58,200 --> 00:38:01,840 Speaker 1: this building today. That's a very convenient excuse, and I 708 00:38:01,880 --> 00:38:04,960 Speaker 1: mean I'm sticking with it. Look, just because there's one 709 00:38:05,080 --> 00:38:08,600 Speaker 1: a whole two like like like half a mile dout 710 00:38:09,040 --> 00:38:13,320 Speaker 1: raining outside Lauren, it's raining, I'd get I'd get wet 711 00:38:13,360 --> 00:38:15,799 Speaker 1: on the way to the gym. Anyway, Do we have 712 00:38:15,800 --> 00:38:21,120 Speaker 1: any news about about that? So SAS Institute has, like 713 00:38:21,160 --> 00:38:23,359 Speaker 1: we said, it has a global reach. It's it's not 714 00:38:23,520 --> 00:38:26,280 Speaker 1: just in the United States. Uh. They held a survey 715 00:38:26,280 --> 00:38:29,200 Speaker 1: in the u K and it was a survey where 716 00:38:29,200 --> 00:38:32,359 Speaker 1: they ended up the findings said that they it's really 717 00:38:32,400 --> 00:38:36,520 Speaker 1: important that we find ways to educate people about big 718 00:38:36,600 --> 00:38:39,080 Speaker 1: data and how to handle it, how to analyze it, 719 00:38:39,320 --> 00:38:41,440 Speaker 1: and finding new ways to do that. I mean, this 720 00:38:41,520 --> 00:38:44,160 Speaker 1: is the business that SAS is involved with. But they're 721 00:38:44,200 --> 00:38:46,960 Speaker 1: saying not just don't it's not just come to us 722 00:38:47,000 --> 00:38:49,320 Speaker 1: so that we can fix your problem. It's we need 723 00:38:49,360 --> 00:38:52,000 Speaker 1: to make sure that this is something that we stress 724 00:38:52,080 --> 00:38:56,680 Speaker 1: in curriculum, in school curriculums, curriculum, I guess I should say, um, 725 00:38:57,080 --> 00:38:59,319 Speaker 1: so that we can make sure we're raising the next 726 00:38:59,360 --> 00:39:03,040 Speaker 1: generation of analysts so that we can take advantage of 727 00:39:03,080 --> 00:39:06,880 Speaker 1: this huge opportunity. And so SAS was actually saying that 728 00:39:06,920 --> 00:39:09,960 Speaker 1: the UK is poised to potentially being a leader in 729 00:39:09,960 --> 00:39:13,360 Speaker 1: this space. That if they were able to encourage this 730 00:39:13,440 --> 00:39:16,200 Speaker 1: kind of thing and maybe develop these kind of curricula, 731 00:39:16,320 --> 00:39:20,000 Speaker 1: then students would be able to really become experts in 732 00:39:20,040 --> 00:39:23,120 Speaker 1: this field that's an emerging field, and thus you have 733 00:39:23,800 --> 00:39:27,920 Speaker 1: a new generation of analysts that can really take advantage 734 00:39:27,960 --> 00:39:31,640 Speaker 1: of this incredible amount of information his big data. We've 735 00:39:31,640 --> 00:39:34,319 Speaker 1: been talking about that a lot too. It's it's got 736 00:39:34,360 --> 00:39:36,600 Speaker 1: a huge amount of potential, but it's also comes with, 737 00:39:36,680 --> 00:39:39,560 Speaker 1: you know, enormous challenges because you're just generating so much 738 00:39:39,640 --> 00:39:41,560 Speaker 1: every single day. How do you manage it? How do 739 00:39:41,640 --> 00:39:44,600 Speaker 1: you make me have anything to make sense of it? Right? Yeah? 740 00:39:44,719 --> 00:39:46,600 Speaker 1: I mean you know, it's like it's like throwing someone 741 00:39:46,680 --> 00:39:50,560 Speaker 1: into a library that's completely unorganized and saying, bring me 742 00:39:50,719 --> 00:39:52,960 Speaker 1: a book about such and such, and it was just 743 00:39:53,040 --> 00:39:55,160 Speaker 1: like I'm just I don't even know how to sort 744 00:39:55,200 --> 00:39:59,640 Speaker 1: through all this, right. Um. They also are engaged in 745 00:40:00,400 --> 00:40:03,600 Speaker 1: an effort in Nigeria along with a company called Resourcery, 746 00:40:03,760 --> 00:40:07,640 Speaker 1: to help fight fraud, which you know in that particular 747 00:40:07,680 --> 00:40:11,319 Speaker 1: country is a big issue. So um, they're you know, 748 00:40:11,320 --> 00:40:14,799 Speaker 1: they're looking at opportunities to not just do business but 749 00:40:14,840 --> 00:40:18,720 Speaker 1: to help people. Um. And and actually we totally forgot 750 00:40:18,760 --> 00:40:21,520 Speaker 1: to give the company rating. Um oh yeah, so that 751 00:40:21,680 --> 00:40:24,120 Speaker 1: they are at a four point three and their CEO 752 00:40:24,239 --> 00:40:29,360 Speaker 1: approval of Mr Goodnight is so um. You know again, 753 00:40:29,400 --> 00:40:31,880 Speaker 1: it's one of those things where people say, like, there 754 00:40:31,880 --> 00:40:35,440 Speaker 1: are a lot of interesting benefits, including one of the 755 00:40:35,440 --> 00:40:39,040 Speaker 1: ones I saw was food. Food. Food. There's food everywhere. 756 00:40:39,920 --> 00:40:44,319 Speaker 1: Food is awesome in general. Just if you give people food, 757 00:40:44,400 --> 00:40:46,960 Speaker 1: they'll love you. Forever. I think. Yeah, that's that's why 758 00:40:47,000 --> 00:40:49,640 Speaker 1: occasionally I will go across the street and buy a 759 00:40:49,680 --> 00:40:51,920 Speaker 1: dozen cupcakes and bring them back to the office. And 760 00:40:51,920 --> 00:40:54,239 Speaker 1: that is a true story. Yep, that that is that 761 00:40:54,280 --> 00:40:56,800 Speaker 1: has happened. I can tell you Jonathan is not lying 762 00:40:56,880 --> 00:40:59,840 Speaker 1: right now. Well, we've got five more companies to talk about. 763 00:41:00,000 --> 00:41:02,360 Speaker 1: In our next episode, you'll get to hear what the 764 00:41:02,400 --> 00:41:06,359 Speaker 1: top five are. And if you have any requests, like 765 00:41:06,400 --> 00:41:09,280 Speaker 1: there's some topic that you think we should cover, maybe 766 00:41:09,280 --> 00:41:11,080 Speaker 1: there's a company on this list you would like to 767 00:41:11,080 --> 00:41:14,040 Speaker 1: know more about, or maybe there's another company entirely different 768 00:41:14,080 --> 00:41:16,520 Speaker 1: company that you just are dying to have us cover, 769 00:41:17,560 --> 00:41:20,959 Speaker 1: or technology concept, whatever you like, let us know, write 770 00:41:21,000 --> 00:41:24,799 Speaker 1: us our email addresses, text stuff at Discovery dot com. 771 00:41:24,840 --> 00:41:28,680 Speaker 1: And hey, here's another thing. We're social people. We're on 772 00:41:28,760 --> 00:41:31,319 Speaker 1: some social networks. I wouldn't call us social, but yeah, 773 00:41:31,360 --> 00:41:34,480 Speaker 1: we are on Twitter, Facebook, and Tumbler. Our handle at 774 00:41:34,520 --> 00:41:37,759 Speaker 1: all three of those is text HSW. Yeah, so get 775 00:41:37,800 --> 00:41:40,560 Speaker 1: in touch with us because uh, you know, we'll we'll 776 00:41:40,560 --> 00:41:42,719 Speaker 1: read it, and we'll we'll enjoy it. And then once 777 00:41:42,760 --> 00:41:45,160 Speaker 1: we crawl out of our corners, uh, in which we 778 00:41:45,200 --> 00:41:47,759 Speaker 1: call our safe zone, we'll be happy to respond to 779 00:41:47,800 --> 00:41:52,040 Speaker 1: you as a social person. I'm the only anyway, So 780 00:41:52,120 --> 00:41:53,520 Speaker 1: get in touch with us. Guys. We want to hear 781 00:41:53,560 --> 00:41:56,319 Speaker 1: from you, and we will talk to you again really soon. 782 00:42:01,040 --> 00:42:03,600 Speaker 1: For more on this and thousands of other topics, visit 783 00:42:03,640 --> 00:42:10,400 Speaker 1: how staff works dot com.