WEBVTT - Ovation’s CEO on Addressing Customer Complaints 0:00:12.280 --> 0:00:13.440 Welcome to Chopping It Up. 0:00:13.520 --> 0:00:15.800 I'm your host, Mike Hallon, the senior Restaurant and Food 0:00:15.840 --> 0:00:19.560 Service analyst at Bloomberg Intelligence. Our research and that of 0:00:19.640 --> 0:00:22.000 bi's five hundred analysts around the globe can be found 0:00:22.040 --> 0:00:25.720 exclusively on the Bloomberg terminal. If you enjoy the pod, 0:00:25.920 --> 0:00:27.640 I'd love it if you could leave us a review 0:00:27.640 --> 0:00:30.920 on Apple or Spotify. Today we're joined by Zach Oates, 0:00:31.000 --> 0:00:34.120 founder and CEO of Ovation and hosts of the Given 0:00:34.120 --> 0:00:35.400 Ovation podcast. 0:00:35.520 --> 0:00:36.400 Zach, what's up? 0:00:36.440 --> 0:00:36.920 My man? 0:00:37.360 --> 0:00:38.920 Just living the dream here? 0:00:39.000 --> 0:00:42.479 Mike, Dude, I uh saw doing a little background on you. 0:00:42.920 --> 0:00:45.479 I dug up some interesting stuff. This is gonna be fun. 0:00:45.520 --> 0:00:47.800 I've been looking forward to this, But after what I 0:00:47.840 --> 0:00:50.239 dug up, this could go in different directions. 0:00:50.320 --> 0:00:50.479 Man. 0:00:50.520 --> 0:00:53.279 First of all, dude, First of all, you grew up 0:00:53.280 --> 0:00:53.800 in Jersey. 0:00:54.240 --> 0:00:55.640 Yeah, Man, I'm a Jersey boy. 0:00:55.760 --> 0:00:57.080 Where did you grow up in Jersey? 0:00:57.240 --> 0:01:01.880 Morristown, Motown. Just to be clear for those who aren't 0:01:01.880 --> 0:01:06.080 familiar with Jersey, I did say Morristown, which is different 0:01:06.080 --> 0:01:10.520 than Moorestown, which is different than Norristown. So all three 0:01:10.520 --> 0:01:14.479 of those places are like very different. And I grew 0:01:14.560 --> 0:01:17.399 up in Morristown, which is. When I say the city, 0:01:17.480 --> 0:01:19.280 I mean New York, I don't mean Philly. 0:01:20.959 --> 0:01:24.560 Yeah, for sure, Morristown's got a man it's got a 0:01:24.600 --> 0:01:26.400 good food scene too, man. 0:01:26.440 --> 0:01:29.360 Yeah, good food scene. I mean it was awesome, Like 0:01:29.400 --> 0:01:31.480 the town I grew up in. I grew up right 0:01:31.480 --> 0:01:34.560 outside of Morristown, and they had duck crossing signs, and 0:01:34.959 --> 0:01:36.800 I mean it's just in the middle of the forest, 0:01:36.920 --> 0:01:39.959 and yet I could drive five minutes away and be 0:01:40.280 --> 0:01:43.360 by a movie theater and be by you know, amazing 0:01:43.440 --> 0:01:46.119 restaurants and so anyway, it's an awesome place to grow up. 0:01:46.319 --> 0:01:47.680 Yeah, Morris County's phenomenal. 0:01:47.720 --> 0:01:50.280 What uh, That's actually where I got my That's where 0:01:50.280 --> 0:01:53.320 I got my like first foray into food. I was. 0:01:53.800 --> 0:01:56.280 I worked at Friendlies there in Morristown. 0:01:57.600 --> 0:01:59.040 How was that experience, dude? 0:01:59.040 --> 0:02:02.480 It was great and like full circle moment when they 0:02:02.960 --> 0:02:05.639 started working with us, and then super full circle moment 0:02:05.720 --> 0:02:09.799 when they we got awarded Vendor of the Year with them, 0:02:10.040 --> 0:02:12.120 and so it was just like super cool to have 0:02:12.160 --> 0:02:14.960 that experience of going from you know, that's where I 0:02:15.000 --> 0:02:17.960 got my start to like vendor of the Year of Friendlies, 0:02:18.200 --> 0:02:21.320 and I was. I was just so popped. I had 0:02:21.320 --> 0:02:24.160 no idea, So it was. It was quite the honor 0:02:24.760 --> 0:02:28.720 and loved working there and basically like where I cut 0:02:28.760 --> 0:02:31.200 my teeth in hospitality. 0:02:31.400 --> 0:02:32.480 That's very cool man. 0:02:32.919 --> 0:02:35.200 The chocolate almond chip ice cream is still one of 0:02:35.200 --> 0:02:36.160 my all time favorites. 0:02:36.280 --> 0:02:40.160 Oh Man, that that peanut butter sauce. Oh yeah, and 0:02:41.000 --> 0:02:41.480 so good. 0:02:41.720 --> 0:02:45.400 Yeah. That Reese's Pieces Sunday phenomenal. So where'd you go 0:02:45.400 --> 0:02:46.000 to high school? 0:02:46.680 --> 0:02:49.840 Newark Academy, right down the street from Friendlies in Morristown. 0:02:49.919 --> 0:02:53.280 Yeah, yeah, all right, very cool man. Yeah, I grew 0:02:53.320 --> 0:02:54.080 up in Ceedar Grove. 0:02:54.800 --> 0:02:56.120 Yeah, it was. 0:02:56.120 --> 0:02:58.120 After my time, but when my brother was. 0:02:58.080 --> 0:03:01.240 In high school, we were actually playing against NORC Academy 0:03:01.280 --> 0:03:01.880 and some sports. 0:03:01.919 --> 0:03:03.880 I think we might have played them in basketball when 0:03:03.880 --> 0:03:04.240 I was. 0:03:04.360 --> 0:03:06.679 Well, I was I'm I'm I'm older than you, Mike. 0:03:06.840 --> 0:03:11.040 So yeah, we probably didn't crossover in high school. 0:03:11.480 --> 0:03:12.160 I don't think so. 0:03:13.280 --> 0:03:16.839 Also, your dad is very well known in New York 0:03:16.880 --> 0:03:17.639 and New Jersey. 0:03:17.680 --> 0:03:17.960 Man. 0:03:18.600 --> 0:03:21.320 Yeah, he's very well known in very small circles. 0:03:21.400 --> 0:03:22.080 Yeah, he's. 0:03:23.680 --> 0:03:26.640 Well one, very big circle Giants fans. I mean he 0:03:26.720 --> 0:03:30.160 won a lot of games, including three Super Bowls, two 0:03:30.200 --> 0:03:33.680 with the Giants, two USFL championships. 0:03:33.680 --> 0:03:36.080 He won whatever he went, man, so you must have 0:03:36.160 --> 0:03:37.080 learned a lot from him. 0:03:37.640 --> 0:03:39.920 I did. It was like one of those things I 0:03:39.960 --> 0:03:43.080 tell people that my father was a professional athlete, my 0:03:43.120 --> 0:03:46.520 mother was a model, and unfortunately I got my dad's 0:03:46.560 --> 0:03:50.520 looks in mother's athletic ability, and so I was on 0:03:50.680 --> 0:03:52.880 the you know, I had to work hard for what 0:03:52.920 --> 0:03:55.920 I got. But no, it was it was really interesting 0:03:56.000 --> 0:04:00.440 growing up with your dad. Not only you know, three 0:04:00.480 --> 0:04:02.960 Super Bowls is great, but he also is a five 0:04:03.040 --> 0:04:07.240 time pro bowler, you know, and so being the best 0:04:07.280 --> 0:04:09.360 in the world at something and growing up with your 0:04:09.440 --> 0:04:12.000 dad who is the best in the world, and you know, 0:04:12.200 --> 0:04:14.520 we always talk about that in terms of like, oh, 0:04:14.600 --> 0:04:16.080 you got to be the best in the world at 0:04:16.120 --> 0:04:18.560 something and like, but growing up with a dad who 0:04:18.800 --> 0:04:22.719 was is just really inspiring because it's it makes it 0:04:22.880 --> 0:04:26.520 so much more real. And it's not like this you know, 0:04:26.680 --> 0:04:29.240 trite phrase that people use, but it's like, no, that's 0:04:29.240 --> 0:04:31.680 like the guy at the dinner table, you know, the 0:04:31.760 --> 0:04:34.440 one driving me to church on Sunday. Like I mean, 0:04:34.480 --> 0:04:37.880 like he's the best in the world at throwing a 0:04:37.880 --> 0:04:41.160 football upside down backwards between his legs, but hey, best 0:04:41.160 --> 0:04:42.120 in the world as something. 0:04:44.880 --> 0:04:48.040 Ah, that's very cool. Man. Yeah, I'm a Raider fan, 0:04:48.080 --> 0:04:50.680 but my whole family of Giants fans. And you know, I. 0:04:50.640 --> 0:04:54.120 Actually got to go to a few regular season games 0:04:54.600 --> 0:04:59.200 in nineteen eighty six, the first Super Bowl win. Yeah, 0:04:59.200 --> 0:05:01.160 I missed the old Giant Stadium. There wasn't a bad 0:05:01.200 --> 0:05:02.359 seat in the house, man. 0:05:02.400 --> 0:05:04.800 I mean yeah, I mean I also went to a 0:05:04.839 --> 0:05:08.920 few a few Giants games growing up. Actually, do you 0:05:09.000 --> 0:05:11.360 know my favorite part about the Giants games was on 0:05:11.400 --> 0:05:14.599 the way home there was a Red Robin that we 0:05:14.640 --> 0:05:18.920 would stop at, and I that's where I love Red 0:05:19.000 --> 0:05:21.480 Robin and that was that was the place that I 0:05:21.520 --> 0:05:23.880 would that was like my jam coming back from the games. 0:05:23.920 --> 0:05:26.359 And when I got older, they would bribe me to 0:05:26.400 --> 0:05:28.160 stay for the second half because I would always be like, 0:05:28.200 --> 0:05:30.839 all right, halftime, let's go, like I'm done. And then 0:05:30.920 --> 0:05:32.800 as I got older, they would bribe me and they say, Okay, 0:05:32.800 --> 0:05:35.240 if you stay the second half, then in the third 0:05:35.320 --> 0:05:38.599 quarter we can go and get nachos, and then after 0:05:38.680 --> 0:05:40.680 the game we'll go to Red Robin. So that's how 0:05:40.720 --> 0:05:45.159 they eventually uh bought me into staying at football games. 0:05:45.160 --> 0:05:47.600 But you'd be hard, Mike you'd be hard pressed to 0:05:47.640 --> 0:05:51.520 find me watching a football game nowadays. I'm not a 0:05:51.600 --> 0:05:52.120 huge fan. 0:05:52.720 --> 0:05:55.599 I love football, but uh yeah, takes up takes up 0:05:55.600 --> 0:05:57.960 a lot of time. All right, good stuff, man, And 0:05:58.040 --> 0:06:00.479 I love that red robin on your tower. 0:06:00.480 --> 0:06:03.320 It's fantastic too good. Yeah, all right. 0:06:03.480 --> 0:06:06.600 So, how many companies have you started and were any 0:06:06.600 --> 0:06:10.440 of them in or related to the restaurant industry before ovation? 0:06:11.480 --> 0:06:14.280 No. I started three companies and this is my third 0:06:14.279 --> 0:06:18.159 company i've started. But I also did international nonprofit. I 0:06:18.200 --> 0:06:21.200 lived in Ukraine for two years and I started and 0:06:21.320 --> 0:06:24.480 ran an organization for eight years and we worked with 0:06:25.240 --> 0:06:28.520 shelters in Ukraine for women and children, helping them with 0:06:28.760 --> 0:06:34.919 job training and computer literacy and it was and group therapy, amazing. 0:06:34.960 --> 0:06:38.359 The organization had a lot of incredible experiences there, but 0:06:38.680 --> 0:06:40.320 with the war and everything, we had to kind of 0:06:40.360 --> 0:06:42.320 put that on pause. So looking forward to picking that 0:06:42.600 --> 0:06:45.039 back up off the shelf. But Ukraine's a near and 0:06:45.080 --> 0:06:48.760 dear place to my heart. Love love that part of 0:06:48.839 --> 0:06:52.719 the world. And then my other companies. One was in AI, 0:06:53.080 --> 0:06:57.159 so before AI was really a thing. And what we 0:06:57.200 --> 0:07:00.360 actually did was I developed an algorithm to translate social 0:07:00.400 --> 0:07:03.840 media data into gift recommendations, and so we were featured 0:07:03.880 --> 0:07:07.359 in you know, all sorts of publications and I won't 0:07:07.360 --> 0:07:11.080 mention because someone might be competing, but uh, we were 0:07:11.440 --> 0:07:13.800 you know, all over the place. Had a great run there, 0:07:13.840 --> 0:07:16.880 sold the algorithms. The other one was a child safety wristband. 0:07:17.160 --> 0:07:20.280 So it was hardware tech for kids, which is if 0:07:20.320 --> 0:07:24.760 you want to do, like the hardest type of company 0:07:24.800 --> 0:07:27.560 to start in the world besides a restaurant, uh, get 0:07:27.600 --> 0:07:31.800 into hardware tech for kids, because that is just, I mean, 0:07:32.400 --> 0:07:36.360 unbelievably challenging. But it was great. And then we ended 0:07:36.440 --> 0:07:38.520 up selling the patents for that one. So the company 0:07:38.520 --> 0:07:42.560 didn't like do phenomenal, but the patents sold and uh, 0:07:42.800 --> 0:07:44.840 and so that was that was a great experience. And 0:07:44.840 --> 0:07:47.800 then and then started ovation. And you know, this is 0:07:47.800 --> 0:07:51.360 something where because I knew a lot about AI and 0:07:51.720 --> 0:07:55.760 what AI can do, and I knew a lot about uh, 0:07:56.120 --> 0:07:58.560 you know, growing up in the restaurant industry. It was 0:07:58.600 --> 0:08:00.440 just a passion of mine. I mean, my dad when 0:08:00.440 --> 0:08:03.640 he retired, he actually got a little bit into restaurants himself. 0:08:03.640 --> 0:08:07.520 He was an investor in a restaurant right by us. 0:08:07.560 --> 0:08:11.280 And we had some restaurant to our friends. Actually, the 0:08:11.320 --> 0:08:13.920 guy that owned the Red Robin, he to this day, 0:08:14.400 --> 0:08:18.080 every time I go home, he comes over and visits, 0:08:18.080 --> 0:08:20.400 like we're such good friends to this day, and he 0:08:20.440 --> 0:08:21.760 comes over to the house all the time for all 0:08:21.840 --> 0:08:26.360 the holidays and everything, and so we've got some you know, 0:08:26.440 --> 0:08:28.960 growing up with restaurants, it just was always a passion 0:08:29.000 --> 0:08:32.600 of mine and seeing what algorithms can do. And then 0:08:32.640 --> 0:08:35.760 I did some customer experience consulting for Fortune fifty companies 0:08:36.320 --> 0:08:41.640 and realizing that there's an opportunity to there's a huge 0:08:41.720 --> 0:08:48.000 dearth of information about the guests in restaurants and especially 0:08:48.000 --> 0:08:51.679 around the guest experience, and it just seemed like bananas 0:08:51.720 --> 0:08:55.640 to me that we're still doing fifty question surveys to 0:08:55.760 --> 0:08:59.559 try to understand how our restaurants are doing. Like this 0:08:59.640 --> 0:09:01.960 isn't this isn't the nineties. Like that's not how the 0:09:02.000 --> 0:09:05.439 world works. That's not how consumers work. If you're gonna 0:09:05.720 --> 0:09:07.719 if you're going to ask them to do you a 0:09:07.760 --> 0:09:11.360 favor and tell you how things are, they don't want 0:09:11.360 --> 0:09:13.640 to take twenty minutes to get a dollar off their taco, 0:09:13.920 --> 0:09:17.000 Like that's just that's that's not how it works. And 0:09:17.040 --> 0:09:20.800 if we're making business decisions based on what that demographic 0:09:20.880 --> 0:09:24.120 of people want. Like if you have twenty minutes to 0:09:24.120 --> 0:09:26.800 get a dollar off your next taco, I don't want 0:09:26.840 --> 0:09:30.520 your opinion because I want people's opinions that that they 0:09:30.600 --> 0:09:32.360 value their time a little bit more, you know what 0:09:32.440 --> 0:09:35.200 I mean. And so that's that's really what got me 0:09:35.240 --> 0:09:39.840 into starting Ovation. But having those other experiences starting those 0:09:39.840 --> 0:09:42.680 other companies was amazing. I learned so many things and 0:09:42.720 --> 0:09:46.680 it was great and from you know, the ups and 0:09:46.720 --> 0:09:51.160 the downs of all of that and realizing that, you know, 0:09:51.200 --> 0:09:53.760 I remember having one kid dm me on back in 0:09:53.800 --> 0:09:59.000 the day Twitter, and he was from India and he said, Hey, 0:09:59.040 --> 0:10:01.240 I just wanted to say thing, thank you for starting 0:10:01.240 --> 0:10:04.079 your company because I didn't know what gift to get 0:10:04.080 --> 0:10:07.040 from my girlfriend. I got onto your app, I used 0:10:07.040 --> 0:10:09.640 it and I got the perfect gift and she loved it, 0:10:09.720 --> 0:10:12.200 and I just wanted to say thank you. That was 0:10:12.280 --> 0:10:15.160 like one of the most wild moments for me to realize, 0:10:15.160 --> 0:10:18.280 Like here I was in this hotel at this conference 0:10:18.600 --> 0:10:21.120 and this guy in India's messaging me to say thank 0:10:21.160 --> 0:10:24.800 you for finding this gift, and I'm like, wow, like 0:10:25.120 --> 0:10:27.480 we can we can do something, Like we could make 0:10:27.520 --> 0:10:30.599 the world, even even like a little corner of the 0:10:30.679 --> 0:10:34.040 world a better place. And man, that's powerful. And I 0:10:34.040 --> 0:10:37.000 don't need to be like Steve Jobs or you know, 0:10:38.320 --> 0:10:41.079 I guess elon Musk prior to this year and and 0:10:42.559 --> 0:10:46.959 make all of these just like world shifting changes. I 0:10:47.000 --> 0:10:49.839 could change my corner of the world, and that's that's great. 0:10:50.000 --> 0:10:52.360 And if I could help the world move forward a 0:10:52.360 --> 0:10:54.880 little bit and help people find a little bit of joy, 0:10:54.920 --> 0:10:57.840 then I'm all about it. Let's build some value, baby. 0:10:58.960 --> 0:11:02.160 Yeah, that's that's fair, fantastic man that it's a great outlook. 0:11:02.960 --> 0:11:05.040 And that kind of leads part of that leads into 0:11:05.320 --> 0:11:09.280 my next question. You know, you talked about these long surveys, 0:11:09.559 --> 0:11:12.520 you know on LinkedIn. You're the self proclaimed anti survey 0:11:12.600 --> 0:11:15.960 survey or, so please talk a little bit more about that. 0:11:16.760 --> 0:11:19.199 Yeah. So, one of the things I always tell people 0:11:19.240 --> 0:11:22.439 is everything that we do in hospitality, from the ingredients 0:11:22.440 --> 0:11:24.440 to the training, to the ambiance, to the music, to 0:11:24.480 --> 0:11:29.480 the furniture to the plates, everything is about what creating 0:11:29.600 --> 0:11:35.720 a great guest experience hard stop right now. Obviously you 0:11:35.760 --> 0:11:38.160 got a P and L in there, because you got 0:11:38.160 --> 0:11:40.320 to make margins to create a great guest experience. I 0:11:40.320 --> 0:11:43.200 think that's like self evident, because if you don't, if 0:11:43.200 --> 0:11:46.600 you're not making money, then you can't create the experience anyway. 0:11:47.240 --> 0:11:49.320 But it's all about the guest experience, and so it's 0:11:49.360 --> 0:11:54.440 about how can I create the best guest experience with 0:11:54.600 --> 0:11:58.520 my P and L. And when I think about that, 0:11:58.760 --> 0:12:01.920 it's like then I said to myself, Okay, well, how 0:12:01.960 --> 0:12:04.080 are we measuring that experience? And again it's up to 0:12:04.360 --> 0:12:07.920 long surveys, which very few people do, or online reviews, 0:12:08.320 --> 0:12:11.679 which very skewed people do. Right, the experience has to 0:12:11.720 --> 0:12:14.840 be very skewed to leave an online review. And so 0:12:15.280 --> 0:12:18.520 what we found is that if you make a survey simple, 0:12:19.040 --> 0:12:22.520 and by simple I mean the ovation survey starts with 0:12:22.720 --> 0:12:27.240 two questions, no matter how much people have paid us 0:12:27.920 --> 0:12:31.960 to add questions to that survey, our answer is always 0:12:32.000 --> 0:12:36.959 and will always be no. That survey is sacred. And 0:12:37.240 --> 0:12:40.680 why we have done the studies. We have done the research. 0:12:40.760 --> 0:12:43.280 If you want to get the data, you start with 0:12:43.360 --> 0:12:46.560 that and you let us, with all the AI that 0:12:46.600 --> 0:12:49.080 we've been doing with the millions of points of data, 0:12:49.320 --> 0:12:52.640 let us tell you what that unstructured data means. And 0:12:52.679 --> 0:12:55.800 it's not just pulling in from the ovation feedback, but 0:12:55.880 --> 0:13:00.560 we pull in from Google, Yelp, Facebook, Door, dash up Hub. 0:13:00.960 --> 0:13:04.840 Why Because all of that unstructured data is also guest feedback. 0:13:04.880 --> 0:13:08.679 You can't treat it differently than your guests that are 0:13:08.720 --> 0:13:12.280 giving you private feedback. So we we have adapted our 0:13:12.400 --> 0:13:16.240 feedback to be in a similar context to what that 0:13:16.600 --> 0:13:20.880 other unstructured review data is. And by bringing that all together, 0:13:21.600 --> 0:13:26.280 you now have statistically significant data to make operational changes 0:13:26.400 --> 0:13:32.360 at location basis, at menu basis, at ease of ordering basis, 0:13:32.360 --> 0:13:34.800 Like you could know exactly what to fix where in 0:13:34.840 --> 0:13:39.160 your operations without harassing your guests with fifty questions. Now, Mike, 0:13:39.600 --> 0:13:42.520 I do want to have one like giant asterix here 0:13:44.200 --> 0:13:46.960 while I am the anti survey survey guy, and I 0:13:47.000 --> 0:13:51.280 think that that's like a very appropriate, very appropriate like title. 0:13:52.679 --> 0:13:56.080 I do believe that long surveys have a place I 0:13:56.120 --> 0:13:59.320 think of. I wrote a book about dating, and the 0:13:59.360 --> 0:14:02.880 way that I think about long surveys, long surveys are 0:14:03.600 --> 0:14:06.839 are like the first kiss, you know, like when you 0:14:06.880 --> 0:14:09.439 go to pick up a blind date. You don't open 0:14:09.520 --> 0:14:12.640 up the door and just kiss them on the doorstep 0:14:12.840 --> 0:14:16.080 right when you go to pick them up. No, maybe 0:14:16.200 --> 0:14:18.640 it was a really good first date. Maybe at the end, 0:14:18.720 --> 0:14:21.720 you know, and I think that like, but the concept 0:14:21.760 --> 0:14:24.680 is maybe later on, more more likely than not. But 0:14:24.720 --> 0:14:28.360 the concept is it has a place, but its place 0:14:28.480 --> 0:14:32.600 is not initially because when a guest wants to reach out, 0:14:32.640 --> 0:14:35.040 they want to reach out for a reason, Mike. They 0:14:35.080 --> 0:14:39.080 want to reach out because you forgot their sauce, you 0:14:39.240 --> 0:14:45.160 forgot their fries, that the server, the server was rude. 0:14:45.280 --> 0:14:48.080 There's something that is on their mind that is a 0:14:48.200 --> 0:14:51.280 very emotional thing, and that's what they want to tell you. 0:14:51.720 --> 0:14:54.360 And so I think that that's one of the very 0:14:54.440 --> 0:14:58.560 key things that's critical to remember is that a survey 0:14:58.640 --> 0:15:02.160 is not bad. It's just a survey upfront is And 0:15:02.520 --> 0:15:07.000 what we say is let the guest get the feeling 0:15:07.200 --> 0:15:10.680 off their chest, and then an hour later or the 0:15:10.720 --> 0:15:13.400 next day, you can get the data that you want 0:15:13.480 --> 0:15:16.360 that might not be structured in that in a in 0:15:16.440 --> 0:15:19.960 a might not be included in unstructured feedback. For example, 0:15:21.040 --> 0:15:24.480 we have customers right now that are asking about their ltos. 0:15:25.200 --> 0:15:28.000 All right, Mike, you come into zach Shack and we're 0:15:28.000 --> 0:15:31.480 doing a peanut butter and jelly hamburger, and I'll ask 0:15:31.520 --> 0:15:33.280 you Mike, did you enjoy the peanut butter and did 0:15:33.280 --> 0:15:35.400 you try the peanut butter and jelly hamburger. If you 0:15:35.480 --> 0:15:38.000 say yes, I say great, tell me more about it. 0:15:38.320 --> 0:15:40.840 If you say no, I say great, here's a here's 0:15:40.880 --> 0:15:44.680 a five dollars off coupon to come and get that 0:15:44.880 --> 0:15:50.080 lto So now we're driving you know, recency, and we're 0:15:50.160 --> 0:15:54.360 driving spend and we're doing it all while collecting data. 0:15:54.640 --> 0:15:58.040 And that's just like one example. Another example is if 0:15:58.080 --> 0:16:01.880 you're you have a restaurant in Vega, and you want 0:16:01.880 --> 0:16:04.000 to do text marketing, but you don't know who's local 0:16:04.000 --> 0:16:07.200 and who's not. Great, ask a follow up question, do 0:16:07.240 --> 0:16:10.240 you live in Vegas? And then you're not sending your 0:16:10.280 --> 0:16:12.520 text messages to people who live in sheboygan that we're 0:16:12.520 --> 0:16:16.840 there for a bachelorette party and so you know, or 0:16:16.920 --> 0:16:19.720 if you want to ask about you know, how did 0:16:19.760 --> 0:16:21.880 you hear about us? So you can measure the effectiveness 0:16:21.880 --> 0:16:24.840 of different forms of marketing. Great, and so all of 0:16:24.880 --> 0:16:27.680 these things are possible with long form surveys, and all 0:16:27.720 --> 0:16:33.120 of these things are unlikely to come up in unstructured data. 0:16:33.960 --> 0:16:37.120 But what we found is that if you ask the 0:16:37.160 --> 0:16:40.120 two question survey first, and you followed up with a 0:16:40.160 --> 0:16:44.360 long form survey, you actually will get more long surveys 0:16:44.400 --> 0:16:47.600 completed than if you start with a long form survey. 0:16:47.880 --> 0:16:51.960 And so that's the Ovation way is we make sure 0:16:51.960 --> 0:16:54.400 that the guest gets the emotion off. We make sure 0:16:54.400 --> 0:16:57.800 that the restaurant can have a really easy path to 0:16:58.320 --> 0:17:01.400 handle that guests and either through you know, if they 0:17:01.480 --> 0:17:03.720 loved it, let's get them to drive more revenue. If 0:17:03.760 --> 0:17:07.080 they didn't love it, let's have AI help us recover them. 0:17:07.480 --> 0:17:11.680 But then you need to separate what is a one 0:17:11.720 --> 0:17:15.280 off issue and what's a consistent problem. And so ovation 0:17:15.480 --> 0:17:18.720 helps to bifurcate that with our AI to say, hey, 0:17:18.800 --> 0:17:23.800 Mike had a problem with the service, and turns out 0:17:23.840 --> 0:17:27.119 that nobody else complained about service this month, and so 0:17:27.720 --> 0:17:30.840 let's apologize to Mike, but let's not beat up our 0:17:30.920 --> 0:17:35.439 staff over service because one person complained about it. But 0:17:36.040 --> 0:17:39.479 let's say that there's a specific location that has a 0:17:39.720 --> 0:17:43.400 five percent higher incident rate, which is, if you take 0:17:43.480 --> 0:17:47.800 the total number total pieces of feedback and you look 0:17:47.840 --> 0:17:50.920 at what percentage of those had an incident about service, 0:17:51.400 --> 0:17:54.000 if they are five percent higher than the average restaurant 0:17:54.040 --> 0:17:56.640 in your group. Then yeah, you need to go talk 0:17:56.680 --> 0:18:00.320 to that location about service and retrain them on the 0:18:00.400 --> 0:18:04.159 Zach Shack way of being friendly and treating customers. And 0:18:05.480 --> 0:18:09.720 then the final step to this piece here, Mike, is 0:18:09.760 --> 0:18:12.960 that all of that data is great and I love 0:18:13.040 --> 0:18:16.959 being able to share data with restaurants, but you gotta 0:18:17.080 --> 0:18:19.480 do something with it. And so what we do is 0:18:19.480 --> 0:18:23.640 we have this whole entire goals module that uses AI 0:18:24.000 --> 0:18:26.840 to tell that GM, here's exactly what you need to 0:18:26.880 --> 0:18:30.160 do to improve, here's what you should be focused on. 0:18:30.720 --> 0:18:34.280 And then with the guest feedback, we track how well 0:18:34.280 --> 0:18:36.919 that GM is doing, and we give the brands a 0:18:37.000 --> 0:18:41.359 dashboard to easily view every location in one spot and 0:18:41.400 --> 0:18:44.040 which ones are on track, off track, how are they doing, 0:18:44.080 --> 0:18:46.200 what are they working on, and if you want them 0:18:46.200 --> 0:18:48.960 to work on something different besides what the AI thinks 0:18:49.040 --> 0:18:51.280 is going to be best, great, click a button and 0:18:51.320 --> 0:18:55.359 override that. And so that's that's the power of collecting it, 0:18:55.560 --> 0:18:58.960 taking action in the moment, finding the trends and fixing 0:18:59.000 --> 0:19:03.520 those trends, and measuring that by collecting the feedback. Very cool, 0:19:03.560 --> 0:19:05.080 And what was the question. 0:19:07.200 --> 0:19:11.480 I forget? But a quick aside Zach's Dating book has 0:19:11.520 --> 0:19:13.120 phenomenal reviews on Amazon. 0:19:13.480 --> 0:19:17.480 Uh huh, talk to me a little bit about the 0:19:17.720 --> 0:19:20.800 quantity of responses versus severity. 0:19:21.080 --> 0:19:23.600 Yeah, so this is something where a lot of times 0:19:23.680 --> 0:19:26.919 people will get feedback, and especially when they're looking at 0:19:26.920 --> 0:19:31.040 their unstructured feedback. And guess what the majority of feedback 0:19:31.080 --> 0:19:33.320 is going to be about. Mike, we're in restaurants. What 0:19:33.359 --> 0:19:36.800 do you think the majority of feedback is about food? Food? 0:19:37.400 --> 0:19:41.760 And so people are sitting there in these offices just 0:19:42.000 --> 0:19:46.159 pouring over this feedback about food, trying to understand. Okay, 0:19:46.200 --> 0:19:47.800 Mike said it was too salty, but then somebody else 0:19:47.840 --> 0:19:50.000 said it wasn't salty enough. You know, someone said it 0:19:50.040 --> 0:19:52.080 was too spicy, someone said it wasn't spicy enough. Okay, 0:19:52.080 --> 0:19:57.520 how do we tw tweak? Tweak, tweak. There absolutely is 0:19:57.720 --> 0:20:00.919 a time and a place for that, and you've amazing. 0:20:00.960 --> 0:20:05.600 Food is now table stakes. The problem that we find 0:20:05.920 --> 0:20:10.520 is that food is not usually the reason that people 0:20:10.600 --> 0:20:15.119 get most angry, and that anger is gonna yield to 0:20:15.240 --> 0:20:18.120 negative reviews. That anger is gonna yield to I'm never 0:20:18.160 --> 0:20:21.400 trying them again. That anger is gonna yield to Hey, 0:20:21.520 --> 0:20:23.960 I'm telling fifteen of my friends not to go to 0:20:24.040 --> 0:20:29.040 zach Shack. It's not the food, because food is very 0:20:30.040 --> 0:20:34.520 it's very preferential based. The same exact food is gonna 0:20:34.520 --> 0:20:38.800 be you know, it's gonna be great to someone and 0:20:38.920 --> 0:20:43.399 terrible to somebody else. Right now, there are mistakes that 0:20:43.440 --> 0:20:47.040 are made. Something is burnt, something is you know, the 0:20:47.119 --> 0:20:50.000 rice is dry, like there may be some things like 0:20:50.040 --> 0:20:54.080 that that, yeah, you can improve operationally. But then you 0:20:54.160 --> 0:20:58.119 get to this middle ground of service, which is a 0:20:58.160 --> 0:21:02.440 little more on the black and white of hey, were 0:21:02.480 --> 0:21:05.639 you nice to me or not. Now, if I'm having 0:21:05.640 --> 0:21:07.520 a bad day and I go into a restaurant and 0:21:07.520 --> 0:21:09.680 somebody doesn't kind of go above and beyond, I may 0:21:09.720 --> 0:21:13.120 think they're being rude. If I go into a restaurant 0:21:13.119 --> 0:21:16.119 with four kids and I'm waiting for five minutes for 0:21:16.200 --> 0:21:20.000 my food, that may feel like twenty minutes, right if 0:21:20.000 --> 0:21:22.200 I'm by myself, or if I'm just like, if I'm 0:21:22.200 --> 0:21:23.879 on a date and they bring me my food in 0:21:23.920 --> 0:21:26.679 five minutes, I'm like, now, like, give me some more time, Like, 0:21:26.720 --> 0:21:30.479 you know, we're still breaking the ice here, you know, 0:21:30.600 --> 0:21:32.760 Or my wife and I were sitting down, we want 0:21:32.760 --> 0:21:35.280 more time to talk because we're finally you know, the kids, 0:21:35.520 --> 0:21:37.359 got a babysitter, so like, I'm not in a rush. 0:21:38.359 --> 0:21:41.679 A little more subjective, but that's going to get you 0:21:41.920 --> 0:21:46.600 angry reviews. If someone is believes that they were not 0:21:46.720 --> 0:21:51.520 treated well, if someone was told that they are, if 0:21:51.520 --> 0:21:54.320