Meeting Title: [Eden] Daily Standup Date: 2025-04-02 Meeting participants: Aakash Tandel, Robert Tseng, Josh, Rob, Nick G, Sahana Asokan, Michael Minter


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1 00:01:21.060 00:01:22.180 Nick G: Hey! Morning!

2 00:01:23.900 00:01:24.910 rob: Morning guys

3 00:01:50.870 00:01:52.269 Aakash Tandel: Hello! How’s it going

4 00:01:52.270 00:01:53.050 Robert Tseng: Hey, Kasha.

5 00:01:59.360 00:02:10.469 Robert Tseng: yeah. So for Rob and Nick, this, we’re not doing a traditional stand up today. We’re trying to like, do some roadmap planning with, I guess, really with Josh. But having you guys here, be helpful.

6 00:02:11.030 00:02:13.109 Robert Tseng: So it’ll just be us on the call

7 00:02:13.720 00:02:14.350 Aakash Tandel: Yep.

8 00:02:14.730 00:02:15.260 Nick G: Okay, cool.

9 00:02:15.620 00:02:18.120 Nick G: We’ll get sorry when when Josh pops in. Then

10 00:02:19.840 00:02:20.330 Aakash Tandel: Yep.

11 00:02:23.150 00:02:25.210 Robert Tseng: Yeah. So, Hana, you don’t need to be on this call.

12 00:02:25.630 00:02:26.760 Sahana Asokan: Oh, okay.

13 00:02:26.860 00:02:27.440 Aakash Tandel: Unless

14 00:02:28.670 00:02:32.539 Robert Tseng: Yeah, no, no, I can’t. Don’t. Yeah.

15 00:02:34.420 00:02:40.349 rob: Hey, Robert? I just wanna let you know that those new web hooks are all live, and they’re in bigquery. So

16 00:02:40.460 00:02:45.970 rob: if you don’t need me, I’ll jump. But Cutter has a bunch of stuff for me to do. But yeah, I just wanna let you know

17 00:02:45.970 00:02:46.660 Robert Tseng: Okay.

18 00:02:46.790 00:02:56.000 Robert Tseng: is there any I know? Cutter’s been kind of chatting, and the incremental thing keeps popping up. Is there anything that you need or like you want to chat through or from us on that

19 00:02:56.930 00:02:59.759 rob: Oh, no! Is Cutter been asking about incremental

20 00:03:01.474 00:03:05.319 Robert Tseng: I mean, is it Cutter? Who’s who is that here

21 00:03:05.320 00:03:05.729 rob: Doubt it.

22 00:03:06.260 00:03:09.970 rob: It’s probably Stuart. Yeah. Stuart or Sam, or Josh?

23 00:03:10.530 00:03:18.650 rob: No, I don’t know. They haven’t asked me to do anything on it, but if they do, I’ll I’ll do it. I I gave them report at the beginning, but

24 00:03:19.640 00:03:20.360 Robert Tseng: Okay. Cool.

25 00:03:20.360 00:03:24.779 rob: You can assign me anything you want to do like you can assign me tickets. It’s okay.

26 00:03:25.350 00:03:31.280 Robert Tseng: Okay, yeah. I mean, the only thing we really had was the web book thing. So I think if that’s clear, then yeah.

27 00:03:32.360 00:03:34.060 rob: Okay. Then I’m gonna bounce

28 00:03:34.260 00:03:35.659 Robert Tseng: Yep, alright! See you

29 00:03:35.660 00:03:36.629 rob: Guys see ya

30 00:03:37.460 00:03:38.170 Aakash Tandel: Yeah.

31 00:03:42.630 00:03:43.919 Aakash Tandel: yeah, I’m I’m not.

32 00:03:43.920 00:03:50.814 Nick G: I’m not sure how helpful I’ll be. I can. I can stay in if you think that there’s some that might be relevant to me. But

33 00:03:51.080 00:04:01.280 Robert Tseng: Maybe, Nick, I have one question for you. I think, like the intake stuff is coming up again. So Cutter is asking like, oh, like, where do I find reporting on intake data? So

34 00:04:01.390 00:04:02.610 Robert Tseng: I

35 00:04:02.970 00:04:08.930 Robert Tseng: kind of don’t really have a good answer for him like I that that works good pause for us at this point. But like.

36 00:04:09.230 00:04:16.390 Robert Tseng: yeah, I don’t know if you have any more like kind of updates on the Embeddables thing. And like

37 00:04:17.120 00:04:22.370 Nick G: I I don’t know the current status of the Embeddables thing. I had thought that

38 00:04:22.960 00:04:32.459 Nick G: I thought that we were getting close to the launch. I’m actually kind of surprised that I haven’t heard any updates on that recently. But I can. I can ask a couple people to

39 00:04:32.980 00:04:39.407 Nick G: check if they have any information I don’t on embeddables. I haven’t really been a part of a lot of those calls.

40 00:04:39.700 00:04:40.360 Robert Tseng: Okay.

41 00:04:40.520 00:04:46.405 Nick G: And then in terms of intake data. That’s something that I

42 00:04:47.340 00:04:55.100 Nick G: don’t really have too much insight into right now, however, I am like setting up a meeting with Sebastian

43 00:04:55.240 00:04:58.549 Nick G: for to like look into this exact topic

44 00:04:58.780 00:05:16.860 Nick G: so so hopefully, I’ll have some more news on that front soon. What’s your current visibility into like our intake data? Is it the case that, like you, you’ve got the data for people who are like completing our intakes only? But you don’t have any like kind of partial completion data. Do you have

45 00:05:17.190 00:05:21.050 Nick G: it? It? Could you say, like, Go ahead, go ahead.

46 00:05:21.050 00:05:38.210 Robert Tseng: We actually do I think for the longest time, like people thought we didn’t have partial completion data. But Akash, like kind of did this like side quest where he kind of showed where we could actually track a lot of that with Google tags. Like, we know where people drop off. So

47 00:05:38.680 00:05:45.940 Robert Tseng: like we were able to pretty much look at. Yeah, we know what stage they drop off at. Which was the main concern.

48 00:05:46.810 00:05:47.969 Robert Tseng: Yeah, so, but

49 00:05:47.970 00:05:53.619 Nick G: What’s the what’s like the delta between where you are and where you want to be with regards to intake data

50 00:05:54.810 00:06:10.320 Robert Tseng: Well, I mean, it’s it was just like a matter of like, okay, we have this method that like doesn’t require any new tech to like, actually show intake, drop off. We didn’t actually deploy it and turn it into reporting, because we kind of

51 00:06:10.320 00:06:29.009 Robert Tseng: got halted. And then I guess, before you started joining these stand ups, we had done a separate scope of work to go and bring in type form data. So we have the type form data as well. But I don’t think that’s being used for intakes anymore. So it was kind of like we were just being pointed towards in directions. And we just kept running into dead ends. And so we just

52 00:06:29.010 00:06:38.970 Robert Tseng: that just kind of they drop. They dropped off. And so it’s not a matter of we don’t have the capability to report on it. We just need to have like a clear like, green light on like, okay.

53 00:06:38.970 00:06:39.620 Nick G: Clean

54 00:06:40.960 00:06:47.640 Nick G: cool that that totally makes sense. Then that’s that’s honestly, I think that’s a good problem to have. We’ve got the data we just need to make use of it.

55 00:06:49.000 00:06:56.330 Nick G: I can get back to you. I’m gonna like, I’m gonna message Sebastian right now. He said, that he should be free to like. Meet with me about

56 00:06:56.520 00:06:59.689 Nick G: the like intake slash. Gtm, stuff.

57 00:06:59.860 00:07:03.059 Nick G: So yeah, so I think

58 00:07:03.310 00:07:12.349 Nick G: maybe I’ll message you after that, and to just like, catch up to my my new kind of state knowledge, and then we can figure out what we want to do with that

59 00:07:12.890 00:07:13.520 Robert Tseng: Got it.

60 00:07:13.850 00:07:25.781 Robert Tseng: Okay? And then, actually, one more thought came to mind as you were thinking, I mean, so I I feel like in my mind, you’re like the vast systems, Sme, kind of like we’re like that subject matter expert, supposedly.

61 00:07:26.530 00:07:37.730 Robert Tseng: I mean, now that we’re kind of doing like a full order. Sla like report, like reporting are you? How familiar are you with like fast order statuses and stuff

62 00:07:38.816 00:07:50.019 Nick G: Not probably as particular as not as familiar as either of us would want me to be. Unfortunately, I think that that’s that’s like one of the

63 00:07:50.140 00:07:53.230 Nick G: all these things are things that I want to like

64 00:07:53.580 00:07:59.150 Nick G: understand a bit better. But right now I just don’t have a lot of visibility into that data. Unfortunately.

65 00:07:59.900 00:08:00.410 Nick G: so

66 00:08:01.210 00:08:14.440 Robert Tseng: Then, like the Basque, I mean, kind of like, what’s your relationship with bass like? Kind of like, what? What do you own? And on the bask side, or I mean, just like what systems are. Do you do you like feel like you’re the go to person for that? I can kind of keep in mind

67 00:08:14.440 00:08:27.299 Nick G: Yeah. So right now, I’m definitely I’d say the go to person for actually managing the intakes. But in terms of the data, I’m just not really there yet, but I’d like to be hopefully.

68 00:08:27.520 00:08:28.030 Nick G: you know.

69 00:08:28.030 00:08:29.440 Nick G: Okay, pretty soon

70 00:08:29.440 00:08:34.120 Robert Tseng: So you’re like doing the intake design and all the stuff and the sigmas like we look through that for or

71 00:08:34.120 00:08:35.699 Nick G: A lot of that. Yeah, yeah, I’m not.

72 00:08:36.070 00:09:04.210 Nick G: That’s doing that. But any of the like, the more complex kind of things in bask that like require like significant customization kind of falls to me. But yeah, I I have, like, you know, the programming and kind of data background to be doing more. And like, I feel like I’m just like a little bit held up in that regard right now. So

73 00:09:05.120 00:09:05.830 Robert Tseng: Okay.

74 00:09:06.780 00:09:08.560 Nick G: But but yeah.

75 00:09:11.220 00:09:21.599 Robert Tseng: Alright. Well, I don’t know if he’s gonna respond. I mean, if you don’t have to stay on, I guess if you if you can just talk a bit more about screwing what we have now.

76 00:09:22.174 00:09:28.040 Robert Tseng: and then, like things that we can triage for the team today, but like I don’t know what. Why, Josh isn’t showing up today.

77 00:09:28.500 00:09:29.060 Aakash Tandel: Sure.

78 00:09:29.760 00:09:30.450 Robert Tseng: Okay.

79 00:09:30.450 00:09:32.630 Aakash Tandel: That sounds good. Yeah. Feel free to drop, Nick.

80 00:09:33.830 00:09:35.960 Aakash Tandel: unless you want to witness this

81 00:09:35.960 00:09:39.830 Nick G: Yeah, yeah, yeah, I’m gonna I’m gonna hop off and have a good one. Y’all

82 00:09:40.010 00:09:41.080 Robert Tseng: Alright! See you

83 00:09:41.080 00:09:41.390 Aakash Tandel: Bye.

84 00:09:45.580 00:10:00.800 Robert Tseng: Okay, I think, like the biggest or the most pressing thing that showed up in this past day since our last met, I just kinda the Ncaa marketing model change like I needed to push away from that like, I think that’s just throwing off some numbers. And people are freaking out again. So

85 00:10:02.030 00:10:05.850 Aakash Tandel: Yeah, yeah, this guy.

86 00:10:05.850 00:10:08.614 Robert Tseng: Yeah, I’m gonna move it to escalated. Then

87 00:10:11.890 00:10:21.200 Aakash Tandel: I closed out the I closed out the Basque thing because Rob finished this one. So I just read that. He finished it

88 00:10:21.750 00:10:23.449 Robert Tseng: Yeah. So now we have to.

89 00:10:23.910 00:10:32.070 Robert Tseng: Actually, well, that’s all he does. He sets up the connector. We have to actually go and see what data is coming in? And how do we actually bring that into the order thing

90 00:10:32.650 00:10:35.639 Aakash Tandel: Where and do we have a ticket for that? Probably not

91 00:10:35.840 00:10:52.340 Robert Tseng: Yeah, I can create one. So review new task orders. They’re also infant to order calls.

92 00:10:55.260 00:10:57.599 Robert Tseng: Do we want to put that on a wish, or didn’t want it.

93 00:10:59.644 00:11:01.710 Aakash Tandel: I think this is net new.

94 00:11:01.900 00:11:03.350 Aakash Tandel: We can put it in the lobby

95 00:11:14.690 00:11:17.409 Robert Tseng: I’m gonna consider that part of the

96 00:11:23.610 00:11:25.100 Robert Tseng: data.

97 00:11:31.340 00:11:35.809 Robert Tseng: not product data centers. Okay, it’s really just like part of like performance.

98 00:11:37.030 00:11:38.330 Aakash Tandel: The pharma stuff. Yeah.

99 00:11:38.750 00:11:39.340 Robert Tseng: Yeah.

100 00:12:01.780 00:12:04.879 Aakash Tandel: Oasis work on that

101 00:12:11.080 00:12:14.300 Aakash Tandel: is this, demo ades or

102 00:12:17.499 00:12:24.430 Robert Tseng: He already did that. So I think we’re good on that or, yeah, it would just put that into interview or something. I just had him take a look.

103 00:12:25.444 00:12:36.430 Robert Tseng: This was like the main thread that I was getting pinged in today on my data quality stuff. But I think it basically just redirected me to the Ncaa modeling issue

104 00:12:36.600 00:12:37.743 Aakash Tandel: Okay, that makes sense.

105 00:12:39.720 00:12:45.219 Aakash Tandel: Okay, yeah. Hopefully, he gets forward progress on these guys.

106 00:12:50.868 00:12:57.989 Aakash Tandel: I know we have a couple of meetings rescheduled for Friday and stuff. So that sounds fine.

107 00:12:59.740 00:13:02.110 Robert Tseng: Yeah, up.

108 00:13:03.700 00:13:07.250 Robert Tseng: Sit down. Yeah. I. Also.

109 00:13:07.380 00:13:10.619 Robert Tseng: I’m gonna review Sauna’s dashboards with

110 00:13:11.270 00:13:21.149 Robert Tseng: with with Danny, who’s their CEO today? Just because I do want to get feedback on it and then be able to make a couple of changes before Friday. But yeah.

111 00:13:32.110 00:13:41.520 Robert Tseng: okay, said he’ll join soon. So if you don’t, yeah, you know, if you can’t run over, here’s a

112 00:13:42.030 00:13:46.110 Aakash Tandel: Yeah, no worries. I have a 1130, but I can at least be yep.

113 00:13:47.810 00:13:48.690 josh: Oh!

114 00:13:49.530 00:13:50.450 Aakash Tandel: Hello!

115 00:13:50.450 00:13:51.050 josh: What up.

116 00:13:51.050 00:13:52.030 Robert Tseng: Hey, Josh.

117 00:13:52.030 00:13:53.649 josh: What’s going on

118 00:13:57.770 00:14:08.289 Robert Tseng: We are. Yeah, we’re just we’re just grooming some stuff. But yeah, I think, Josh, for I mean Akash has a hard stop at the 30. So I wanna at least jump right through it

119 00:14:08.520 00:14:10.150 josh: We got mentor invited.

120 00:14:11.330 00:14:12.859 Robert Tseng: No, I did not

121 00:14:14.310 00:14:16.300 josh: Okay, let me get him in here

122 00:14:17.500 00:14:19.790 Robert Tseng: I can. We can we like add him afterwards, like

123 00:14:19.790 00:14:21.630 josh: Oh, yeah, that’s fine. That’s fine. That’s fine.

124 00:14:21.630 00:14:27.919 Robert Tseng: Cause. I I think this is more of a roadmap planning session. And I don’t wanna just go around this Ltv rabbit hole.

125 00:14:28.910 00:14:29.710 Robert Tseng: Yeah.

126 00:14:30.290 00:14:31.690 josh: Okay. Cool.

127 00:14:31.985 00:14:34.939 Robert Tseng: Yeah, gotcha, why don’t? Why don’t you? Just you can

128 00:14:35.290 00:14:57.170 Aakash Tandel: Sure. Yeah. So this is the stuff that we kind of have in flight at the moment. So we have product standardization. So we’re working with the Basque data modeling and data quality thing. That’s actually moving along. Well, this product work stream is the Mattesh dashboard. So we have good feedback from Mattesh, and that’s going through some revisions right now.

129 00:14:57.745 00:15:08.909 Aakash Tandel: We have the data mart modeling. So that is also for Mattesh, but it’s using the data sources that they get from

130 00:15:09.100 00:15:12.089 Aakash Tandel: had to get from grin in parable.

131 00:15:12.650 00:15:14.599 Aakash Tandel: To get the influencer

132 00:15:14.600 00:15:18.879 Robert Tseng: Cross on that across. We’re not actually gonna do that in the cycle. That’s that’s why the backlog

133 00:15:19.050 00:15:21.110 Aakash Tandel: Yeah, but it’s also in the future. Yep.

134 00:15:21.110 00:15:22.092 Robert Tseng: Right? Right? Okay.

135 00:15:22.420 00:15:48.760 Aakash Tandel: That’s like to future stuff. And then the ship data ingestion modeling is should be done this week. That’s kind of the goal for that one. I know they’ve been working on that for a while. And then we have some tech deck cleanup, but that’s everything in flight or in progress at the moment. And then we can go into show you the stuff that’s in backlog that’s upcoming. But do you have any questions on kind of the stuff that’s currently in flight.

136 00:15:50.281 00:15:58.890 josh: It just sounds like a lot of cleanup and modeling behaviors which hopefully just means, hey, we’re laying the foundation to do all the other stuff

137 00:16:00.220 00:16:09.569 Robert Tseng: Yeah, I mean, I think at this point all the urgent reporting stuff has already been cleared out. So it’s just kind of this work that’s been chugging along in the background that we don’t talk about day to day, necessarily, with you.

138 00:16:09.970 00:16:13.149 josh: Okay, no, that makes sense.

139 00:16:14.000 00:16:22.290 josh: I I think that as long as we end up getting clean or data, and it’s consistent. And we have like rules in place to make sure that it stays clean, cool

140 00:16:25.700 00:16:26.260 Aakash Tandel: Cool.

141 00:16:27.340 00:16:35.939 Aakash Tandel: Okay? So the stuff that we have in backlog, you can see here that there’s a lot of stuff that’s kind of finishing up. And we’ll

142 00:16:35.940 00:16:44.020 josh: Also, I I am having let me put this very cleanly.

143 00:16:44.701 00:16:54.188 josh: We’re we’re Carlos is going in a different direction than we are in Eden. So we will be seeking a replacement.

144 00:16:54.740 00:16:56.280 josh: immediately. Okay,

145 00:16:58.130 00:17:03.020 josh: So for now I have Rebecca kind of like as the interim head over that.

146 00:17:03.210 00:17:10.419 josh: And so his need to get more data should also make it just cleaner. It’s just one person. So she’ll be doing a lot of pharmacy and

147 00:17:10.670 00:17:15.479 josh: care stuff. Probably also be leveraging Katie a little bit more, too.

148 00:17:17.430 00:17:18.930 Robert Tseng: Okay. Noted.

149 00:17:19.290 00:17:41.009 Aakash Tandel: Yep, that sounds good. Yeah, we’re meeting Rebecca, I think on Friday morning to talk through some of our stuff. So that makes sense. But yeah, so the the Zendesk stuff for agent performance is pretty much being closed out by the end of this week. So that’s an item. That’s kind of kind of stretched a little bit, but it should be done

150 00:17:41.010 00:17:45.879 josh: There is a lot of good data that we want to start gleaning out of Zendesk that you can tell you like.

151 00:17:46.000 00:17:55.239 josh: So right now, what we have in care is we have a ton of people that are firefighters, and what we want to start creating is smoke detectors.

152 00:17:56.420 00:18:02.830 josh: That’s like the goal that I have for that group. And so it’s like finding motifs and like being able to

153 00:18:03.020 00:18:25.549 josh: have the team organize tickets in certain ways with their tags, so that we understand like, Hey, this is a doctor issue, or it’s a pharmacy related issue, or it’s this or that or the other. And then like starting to drill down and double click into what is actually the root cause. So we can solve root causes as opposed to storing bodies at it. That’s that’s the reason why I want to go a different direction, because they don’t think it was going the right direction.

154 00:18:26.340 00:18:38.539 josh: So yeah, so that’s like the high level of Hey, great! We’re gonna have agent performance. This is awesome. But moving forward. What I really want to get out of Zendesk is exactly that I want to start having smoke detectors

155 00:18:39.300 00:18:43.879 Robert Tseng: Great. No, I think that’s good for me. I think the main reason why I was like we were.

156 00:18:44.020 00:18:46.170 Robert Tseng: I consider this unfinished with like.

157 00:18:46.520 00:18:55.479 Robert Tseng: Well, we, I think, with all the back and forth with Carlos it was hard to kind of push beyond, like, okay, well, we’re just recreating what you already see in Zendesk. And so.

158 00:18:56.010 00:19:15.400 Robert Tseng: anyway, like, I think the Asian performance dashboard to me is just v. 1. It’s just like monitoring status quo business as usual, and we’re not really taking advantage of all the data that we want to do, some of the more proactive signaling that you’re talking about. So I I think that’s that is kind of where we want to head with v. 2. So I I understand

159 00:19:15.640 00:19:16.190 josh: Cool.

160 00:19:18.150 00:19:38.229 josh: and then in terms of sla’s. It’s less about sla performance. It’s more about a ping. When certain amount of products go beyond an sla as opposed to just. Oh, the static report is just showing me that there’s this many like I think I sent you guys the imagery of the sla thing that before

161 00:19:38.750 00:19:39.770 josh: maybe not.

162 00:19:40.600 00:19:41.690 josh: Hold on

163 00:19:47.680 00:19:54.789 josh: Let me see here did I send? I sent you that whole dashboard that I built up before right

164 00:19:55.190 00:19:55.760 josh: right

165 00:19:55.760 00:20:00.599 Robert Tseng: That I mean, you sent me a Google Sheet. I didn’t actually see us. I saw a spreadsheet

166 00:20:02.360 00:20:06.139 josh: Like. Those are things that I I built all this stuff like level one

167 00:20:06.980 00:20:09.060 josh: the last time we built a huge one.

168 00:20:15.770 00:20:18.509 josh: and like these are all super important things.

169 00:20:19.000 00:20:22.639 josh: So if you’re looking for like more of a roadmap here, I’ll share this real quick

170 00:20:22.640 00:20:23.230 Aakash Tandel: Yep.

171 00:20:29.180 00:20:31.190 josh: You’re looking for like a roadmap

172 00:20:31.540 00:20:33.800 josh: like this is kind of where my head goes.

173 00:20:36.730 00:20:39.959 josh: It’s a huge thing.

174 00:20:41.040 00:20:43.840 josh: So it’s like, obviously, I got TV in retention

175 00:20:43.990 00:20:50.900 josh: and then check in data, getting all this stuff in retention.

176 00:20:53.430 00:20:55.270 josh: Nps, data

177 00:20:58.920 00:21:02.750 josh: doing some analysis on the data itself.

178 00:21:03.621 00:21:14.099 josh: getting some forecasting abilities, you know, based on like orders, like where we’re trending what we think is gonna happen like a general, just a basic forecast outline. For

179 00:21:14.300 00:21:18.360 josh: like the the care. Sorry the pharmacy team, so they can share that

180 00:21:18.710 00:21:19.270 Aakash Tandel: Yep.

181 00:21:20.800 00:21:28.863 josh: you know, like, being able to like incorporate a bunch of like our marketing tests and things like that into here.

182 00:21:29.720 00:21:42.880 josh: you know, like getting better processes from analytics to marketing to feedback. I think those are cheaper, like, you know, reducing this like the noise to signal ratio and getting it more to signal to noise.

183 00:21:43.500 00:21:53.510 josh: Kind of ratio. You know, and then leadership stuff.

184 00:21:53.710 00:21:58.119 josh: This is a big one. Mobile view. I’ve always been this way. Sorry

185 00:21:58.120 00:21:58.810 Robert Tseng: Yeah.

186 00:21:59.300 00:22:02.810 josh: Just run the other one

187 00:22:02.810 00:22:06.450 Robert Tseng: This is what you did in a different life, like what is, what is this

188 00:22:06.450 00:22:14.409 josh: Yeah, this is literally, I’ve built full organizations across all this shit before dude like. That’s what I’m saying all this shit before.

189 00:22:15.270 00:22:18.630 josh: So it’s not that I’m like, like some just random guy, you know what I mean.

190 00:22:19.080 00:22:26.799 josh: built like a whole data organization and built like a whole like commerce teams that built all these things before

191 00:22:27.490 00:22:30.010 Aakash Tandel: Yeah, if we get a copy of this spreadsheet, I think this would be super helpful

192 00:22:30.010 00:22:30.610 josh: I said this.

193 00:22:30.610 00:22:33.829 Robert Tseng: He did send it to me. He did send it to me. I haven’t shared it with you, Akash.

194 00:22:34.324 00:22:34.819 Aakash Tandel: Yeah.

195 00:22:35.560 00:22:45.990 josh: So essentially like all of this stuff, is like the stuff that I was working on, and then being able to like incorporate heat maps and descriptive stuff. And you know, deployment timings, and.

196 00:22:46.130 00:22:52.429 josh: you know, start to do way more audits. And, you know, like getting better comprehensive retention data

197 00:22:52.690 00:23:04.560 josh: better. You know, stuff across comp company health like, and then thinking about it from like all of our different functions. So again, like generalized company level things, you have like

198 00:23:04.680 00:23:10.190 josh: mission critical things. You have medical specific things. You have. Cx.

199 00:23:10.420 00:23:21.280 josh: you know, like message ratings by user. You know what I mean, like, who’s who’s doing well, who’s not like the All? This data is like the stuff that I built out previously. I did all this in 2023,

200 00:23:22.190 00:23:27.956 josh: and I just gotta redo it here, and then I was gonna tell you guys, also, we are

201 00:23:28.910 00:23:39.109 josh: we are. Keep this on the Dl, please don’t share this. I’m just entering. I just entered an agreement where we have our own Emr. Built out within the next, probably 12 weeks

202 00:23:40.100 00:23:40.820 Robert Tseng: Right.

203 00:23:41.190 00:23:43.790 josh: So we won’t have to fucking deal with bask, shitty ass.

204 00:23:44.455 00:23:45.120 josh: Yeah.

205 00:23:45.120 00:23:55.100 josh: we’ll have all of this data like all on our own. But yeah, please do not say anything, because, like, there’s a very delicate, obviously, you know what it’s like to work with the fucking guy. So

206 00:23:55.460 00:23:56.170 Robert Tseng: Yeah.

207 00:23:56.170 00:24:18.040 josh: Just keep that under wraps. But anyway, so all this stuff is all super important, like this is all like the same stuff, like being able to look across all reports, and like what is the 1st product sold, and then what is the most common? Second and then 3, rd and then like, what is the, you know, like looking at the timing between them, looking at what things are causing them to cross. So like all that stuff like really building up the e-commerce like

208 00:24:18.210 00:24:19.280 josh: IQ

209 00:24:19.798 00:24:42.341 josh: and then like starting to like incorporate, we’re gonna be adding a bunch more quizzes to the page like Bmr ratings, Tds, and like looking at that as like a lead Gen. Thing, and seeing what products are actually leading themselves into, based on those quizzes like, there’s a lot of shit coming down the pipe. So that’s when you said to me yesterday, like all the pipelines basically done, I’m like Bro, it’s not even close like we’re like, literally just getting started

210 00:24:42.880 00:24:57.510 Robert Tseng: Oh, no, understand, there’s a lot of stuff. So I mean, just like, this is like you, top down like kind of, you know, sharing your the, you know, a roadmap. Obviously, we have. We’ve built a roadmap kind of more bottom up. Working with the team leads to the other people, and so

211 00:24:57.510 00:24:57.950 josh: Yeah.

212 00:24:57.950 00:25:03.520 Robert Tseng: I think there’s a gap, obviously where you know what you what you see versus like, what we’ve gathered from them.

213 00:25:04.560 00:25:12.860 Robert Tseng: Yeah. So I think we just gotta like, maybe like we. I think that that to for us to show you what we what we have. And then

214 00:25:12.990 00:25:22.749 Robert Tseng: we can. We can go back and spend a I mean on our. We can spend a deeper session kind of studying kind of that that spreadsheet that you said, and we can kind of do some of the like kind of

215 00:25:23.250 00:25:30.229 Robert Tseng: matching on on our own. But I do want you to see like what the team came up with and what we’ve worked on for them. So

216 00:25:31.470 00:25:35.690 Robert Tseng: yeah, I think that’s that’s kind of where we need to like get some clarity on

217 00:25:36.170 00:25:40.889 Robert Tseng: at least be able to bring some of these projects back into the next cycle.

218 00:25:42.040 00:25:45.670 Robert Tseng: Yeah, yeah. So I guess

219 00:25:48.920 00:26:04.594 Robert Tseng: I’ll flash a couple of things, and then you can kinda just kind of take notes. So agent performance stash. Right? This is this is kind of what we built for Carlos at this point. This was what he wanted, which is basically just like, you know, tickets, assignments by agents, or whatever.

220 00:26:05.170 00:26:25.110 Robert Tseng: you know, different statuses, performance metrics. Yeah. So that’s and then that’s different types of escalations. But yeah, this is this is just reading the status quo, really. But this was the v 1 that he asked for. So if this, that to us was like what we did to support him. You know, this took a few weeks to get to get done, but that’s what we have for him.

221 00:26:27.150 00:26:28.650 Robert Tseng: Yeah, I think

222 00:26:28.820 00:26:43.540 Robert Tseng: so. What we could do is we could take. This is a v 1. We kind of go back and work with you more on like, what does that? V. 2 look like? How do we get towards more proactive signals like rather than just reading out kind of statuses of tickets, right?

223 00:26:43.540 00:26:44.110 josh: Yeah.

224 00:26:44.740 00:26:56.910 Robert Tseng: Okay. So. But anyway, like that’s, you know, for the purposes of like the the Kpis kind of like progress check in by the q. 1 like this is, you know, the work stream. This is the result of like what we ended up doing with him.

225 00:26:57.310 00:26:57.885 josh: Yeah.

226 00:26:59.040 00:26:59.970 Robert Tseng: I think.

227 00:27:00.290 00:27:06.054 Robert Tseng: Then on the what do you call this again?

228 00:27:08.590 00:27:13.880 Robert Tseng: So look at this. That’ll work here.

229 00:27:14.270 00:27:17.960 Robert Tseng: Have the desk agents product for Slt.

230 00:27:19.150 00:27:19.860 Aakash Tandel: What are you doing?

231 00:27:19.860 00:27:22.730 Robert Tseng: Oh, it’s still a draft. No, it’s this one. Yeah.

232 00:27:23.090 00:27:29.660 Robert Tseng: So and then this was kind of which I’m not happy with this, to be honest, but like I think this is, you know what we

233 00:27:30.470 00:27:38.249 Robert Tseng: we we had Carlos and Rebecca kind of tried to pass vision for, like what? Like a combined dash would look like.

234 00:27:41.040 00:27:42.480 Robert Tseng: Yeah. So

235 00:27:42.700 00:27:51.579 Robert Tseng: I’ll just show you like, you know, this, these, these were the the designs that we put together. And then this is what we actually built out. I’ll zoom in a bit more. So

236 00:27:51.750 00:27:58.199 Robert Tseng: yeah, I mean, I already gave some feedback internally. But you know, frankly, like my feedback to the team in general is just like.

237 00:27:58.470 00:28:14.820 Robert Tseng: I don’t really think this is that helpful? Like, yeah, we have, like some sense of like, okay, this. These are the all the active orders different statuses, just whether or not they can ship versus delivered. Sure. That gives us some idea like, right here early March. You see, there’s

238 00:28:14.920 00:28:15.960 Robert Tseng: a bunch of order

239 00:28:15.960 00:28:23.400 josh: Carlos is no longer here, so anyways, you don’t have to. You don’t have to belabor the point. I get it. I agree with you. I think that it was going the wrong direction

240 00:28:24.500 00:28:30.449 Robert Tseng: Oh, okay, I know I wasn’t. I wasn’t trying to like throw him under the rug at this point. This is just like, Okay, I think

241 00:28:30.450 00:28:33.800 josh: And they got rid of him because of your feedback. Don’t worry. You should feel

242 00:28:34.480 00:28:36.000 josh: possible for forgive the guy

243 00:28:36.000 00:28:39.510 Robert Tseng: No, no, I mean, I I’m not that kind of person. Yeah.

244 00:28:39.640 00:28:41.489 Robert Tseng: I I’m just okay. Well, I I do think

245 00:28:41.490 00:28:44.460 josh: Anyone else or anyone else that you want us to get rid of, for you

246 00:28:44.460 00:28:48.010 Robert Tseng: No, we. We need a new we need. I think.

247 00:28:48.290 00:28:59.120 Robert Tseng: I, yeah, I think we, this needs to go back to the drawing board. And so I I don’t know who the owner would be, for, like a full customer journey, or I mean, this isn’t really even a customer journey that so

248 00:28:59.120 00:29:00.990 josh: You and me can work through this

249 00:29:01.220 00:29:26.810 Robert Tseng: Okay. So what I’m gonna do, really, with this effort like this was supposed to be like a full end to end like order like tracking like like an order. Order dashboard! So you could see from the top of the funnel all the way to delivery like kind of what that looks like. So I do think this needs to be redesigned. But this was what we work, what we what we what we built out with them up to this point. So I would, yeah.

250 00:29:26.980 00:29:29.430 Robert Tseng: so that’s that’s something that.

251 00:29:29.590 00:29:34.280 Robert Tseng: Yeah, I don’t even really want to publish this live. I think maybe we could just kind of

252 00:29:34.420 00:29:37.225 Robert Tseng: I want to bring. Put this back on the backlog. But

253 00:29:38.040 00:29:43.420 Robert Tseng: yeah, because the vision that I had casted for vision or for for Carlos and Rebecca was like, Hey, like

254 00:29:44.250 00:30:01.000 Robert Tseng: Cx and Px. Obviously, you’re looking at 2 different sides of the order lifecycle. One is like everything before, or like everything, post a delivery, and then one is like more, everything pre delivery. And so we needed to kind of like, consolidate and get a single like, customer 3, like, order 360 view.

255 00:30:01.770 00:30:05.750 Robert Tseng: Yeah, I guess that that didn’t happen. And then we yeah, we’re kind of where we are now.

256 00:30:06.516 00:30:19.509 Robert Tseng: So I feel like that’s still something that we didn’t deliver on in this quarter that I would like to work on. Because we have all the necessary data. Now we have. We have order statuses from beginning to end.

257 00:30:19.510 00:30:36.580 Robert Tseng: And I think that would be a you know. That’s that’s that’s a capability that I would like to show at this point. But I I so I would just if I were to make a bet on like what would be a valuable like project to tee up like. That’s I do want to bring this this vision to completion.

258 00:30:37.400 00:30:44.330 Robert Tseng: But yeah, I think it’s all kind of detailed out in the different projects that we have in in in the in linear. So

259 00:30:45.040 00:30:50.719 Robert Tseng: yeah, that’s that’s that’s just my piece on on this particular work stream.

260 00:30:51.660 00:30:52.900 josh: No makes sense.

261 00:30:53.620 00:31:07.659 Robert Tseng: Okay, Akash, I’m gonna just transition it back over to you just to kind of yeah, go through what we’ve already kind of talked about, and then, hopefully, if Josh agrees with the priorities that we do, then we can bring their the high, the high ones into the next cycle.

262 00:31:07.660 00:31:10.769 Robert Tseng: I actually have to drop for another meeting is there?

263 00:31:10.770 00:31:13.350 Robert Tseng: Oh, right. Okay. Sorry. I didn’t realize it was time.

264 00:31:14.331 00:31:15.519 Robert Tseng: I’ll take it

265 00:31:15.520 00:31:16.870 Aakash Tandel: Exactly. Okay.

266 00:31:17.200 00:31:18.110 Aakash Tandel: Thanks. Josh.

267 00:31:19.065 00:31:19.500 josh: Thanks.

268 00:31:23.540 00:31:26.699 Robert Tseng: Okay? So yeah, I mean, I

269 00:31:27.540 00:31:33.451 Robert Tseng: Asian performance, that’s done. This is what I just walked you through is really kind of like, maybe more sla performance reporting

270 00:31:34.740 00:31:43.529 Robert Tseng: I guess we could call that. Call it that. So that’s kind of something that I want to tee up for the next next cycle margins, and escalate

271 00:31:43.790 00:31:44.440 josh: Is, the

272 00:31:44.440 00:31:44.920 Robert Tseng: Correct.

273 00:31:44.920 00:31:49.399 josh: Is the is the agent performance. One published

274 00:31:50.280 00:31:51.369 Robert Tseng: It is published.

275 00:31:53.090 00:32:00.590 Robert Tseng: Yeah, yeah, it’s kind of back and backlog, because, oh, anyway. Well.

276 00:32:01.978 00:32:05.921 Robert Tseng: yeah, so it yeah, it is. It is possible.

277 00:32:15.580 00:32:22.609 Robert Tseng: and then we have this margins and escalation thing. This was like kind of coming out of the the figma there. So this is really

278 00:32:25.140 00:32:32.197 Robert Tseng: yeah, to me, this is a bit unclear. To be honest. We had originally envisioned that this would be.

279 00:32:35.210 00:32:38.907 Robert Tseng: I guess Rebecca specifically has like this spreadsheet.

280 00:32:39.790 00:32:44.820 Robert Tseng: that’s just looking at margins across across products. And then.

281 00:32:45.670 00:32:57.989 Robert Tseng: yeah, I guess to to me, that’s it’s more of like a spreadsheet exercise to to get that to get that done. That seems pretty lightweight to handle. So we just kind of thought, I just, I just kind of bundled them together because they’re pretty, they’re pretty similar.

282 00:32:58.690 00:33:10.750 Robert Tseng: So yeah, that was, this would kind of shift our focus from just supporting kind of Natasha’s priorities to like, really kind of digging in more with Rebecca and making sure that she has all these like sub things, kind of fleshed out.

283 00:33:11.139 00:33:24.599 Robert Tseng: Obviously the intake is still being adjusted. You just showed us like a list of new things that you want to test but we talked to Nick daily pretty much, and so I know everything that he’s he’s working on on in in terms of like for management.

284 00:33:25.330 00:33:32.230 Robert Tseng: we we are able to track all this data. It’s just a matter of like when we want to make the reporting the priority and like

285 00:33:32.560 00:33:46.229 Robert Tseng: which which? Yeah, like, then then we can actually go and and build the dash. So it’s just in in backlog because we haven’t. We don’t have anything on the roadmap right now to like build a specific intake level report

286 00:33:46.470 00:33:49.549 josh: We’re not need to get this stuff from Embeddables to somehow.

287 00:33:50.040 00:33:54.170 josh: But give me give me one second. Give me one second. I’ll be right back in 2 min. 2 min. Okay.

288 00:33:54.510 00:33:55.180 Robert Tseng: Okay.

289 00:33:55.380 00:33:56.040 josh: Excellent

290 00:37:12.790 00:37:15.720 josh: aiden bye, an internal

291 00:37:15.720 00:37:16.154 Robert Tseng: Hey!

292 00:37:16.950 00:37:18.440 josh: Alright! Hey? Sorry about that.

293 00:37:18.910 00:37:19.580 Robert Tseng: No worries.

294 00:37:22.520 00:37:38.599 Robert Tseng: okay, fewer words, more kind of like putting it in your in your in your port, because we already kind of walk through this? So yeah, this is just kind of our our, we ranked kind of what’s been planned out in this priorities. I kind of made it to the push I advocated for the couple of things that I think for the highest priority.

295 00:37:39.096 00:37:47.709 Robert Tseng: But wondering how the rest of this kind of ranks for you. I can just let you look at it. And if you want more detail, like I can click, double, click, and talk about any of these

296 00:37:49.916 00:37:57.680 josh: I think that retention, like those changes we talked about in the retention, or hopefully, really quick

297 00:37:58.350 00:38:06.029 Robert Tseng: Yeah, that’s in progress. That’s- that’s that’s-. That’s that that’s done or should be done today. Like I, yes.

298 00:38:06.460 00:38:08.087 josh: Cool. And then,

299 00:38:11.880 00:38:16.770 josh: sure to think, think if we start going through

300 00:38:19.290 00:38:23.790 josh: probably integrating some of that data that we’re going to be getting from the check ins

301 00:38:24.380 00:38:26.519 josh: needs to fit on here somewhere. So

302 00:38:26.916 00:38:28.500 Robert Tseng: Does it notie stuff

303 00:38:28.500 00:38:32.289 josh: No, no, no, no, it’s from right now. It’s from type form.

304 00:38:32.720 00:38:37.660 josh: but it’s going to be interim while we’re waiting to build out all of the stuff on the Mr.

305 00:38:40.210 00:38:44.030 Robert Tseng: Oh, the check in is not from the embeddables, or from okay, or from Bath

306 00:38:44.030 00:38:49.379 josh: Yeah, it can. It can be from Basque. It can be from Beddables. We do have both.

307 00:38:49.640 00:38:55.120 josh: but we also have a 3rd one right now. It’s like just way faster and easier to get, which is through type

308 00:38:57.280 00:39:07.180 Robert Tseng: Yeah, I mean, we have the type form integration set up. I think it’s a matter of like adding it to the creating the tables we want. So this, this should be a fast project

309 00:39:08.750 00:39:09.590 josh: Cool

310 00:39:10.720 00:39:17.960 josh: And then the other thing, like I said, is like forecasting, and like light forecasting work

311 00:39:21.320 00:39:27.395 Robert Tseng: Yeah. I did build like a demo. I did build a forecast for

312 00:39:27.990 00:39:30.271 Robert Tseng: Rebecca. I mean, it obviously can be tuned. But like

313 00:39:30.800 00:39:34.969 Robert Tseng: we, we have probably kick already. Kick started that before.

314 00:39:37.110 00:39:48.519 Robert Tseng: So maybe we need to connect on like what you think. Maybe we can review the current forecast together at some point, and then kind of what? What? Like particular views you want to see from that forecast

315 00:39:50.240 00:39:51.233 josh: Got it

316 00:39:52.120 00:40:01.669 Robert Tseng: Yeah, like, I kind of modeled out scenarios. And like, it’s at a product level. And like, I have, you know, actually use my product. And all this stuff like I already built this out for her

317 00:40:05.660 00:40:06.010 josh: No.

318 00:40:06.010 00:40:10.666 Robert Tseng: I mean, I haven’t touched it in like since February, but it was for March onwards. And

319 00:40:11.170 00:40:16.480 Robert Tseng: yeah, this is for her to report to the pharmacies like what she should expect. For each product

320 00:40:16.660 00:40:22.310 josh: I would also mention like quarter over quarter Ltv performance.

321 00:40:27.440 00:40:33.160 josh: So like, where like, imagine you’re taking a a cohort? Right? You have a q. 1.

322 00:40:33.510 00:40:40.290 josh: And then that thing gets all the way like q. 1 of 2024. Right? And then you’re comparing that against

323 00:40:40.480 00:40:45.779 josh: the same timing of where Q, 2, 2024 is right.

324 00:40:46.040 00:40:47.609 josh: So it’s like, Hey.

325 00:40:47.910 00:40:56.399 josh: basically on day one, we should expect to see this, then this and this, and like one or the 2 will probably outperform the other. You see what I’m saying. So it actually becomes useful

326 00:40:58.890 00:41:04.289 Robert Tseng: So, okay, I think this is like the okay.

327 00:41:05.750 00:41:17.774 Robert Tseng: maybe we start like, I think this this ends up being like the whole monthly week, like weekly, monthly slash quarterly Business Review. Cycle where I think I flat before, like

328 00:41:19.760 00:41:23.750 Robert Tseng: I don’t know. Have this here, but oops.

329 00:41:34.420 00:41:39.549 Robert Tseng: Okay, I don’t know what I named it before. But okay, sure, just

330 00:41:39.740 00:41:42.890 Robert Tseng: I’m a mental. No, it’s my

331 00:42:00.000 00:42:05.413 Robert Tseng: okay. So that makes sense to me.

332 00:42:06.480 00:42:12.910 Robert Tseng: you still want to keep mixing panel like not on there

333 00:42:14.290 00:42:16.959 josh: Personally, yeah, cause I don’t think anyone’s using it

334 00:42:17.830 00:42:18.480 Robert Tseng: Okay.

335 00:42:18.480 00:42:23.480 josh: And then, if you were, you able to get me the emails for the people attached

336 00:42:24.820 00:42:28.180 josh: to those 9 to like those 81

337 00:42:28.620 00:42:40.780 Robert Tseng: Oh, yeah, I mean the thorough past Guy gave me some direction. It wasn’t as straightforward as he did so when I clicked into it. And when I followed his instructions I didn’t actually get the email. So I didn’t. I didn’t have anything to send to you.

338 00:42:41.000 00:42:44.529 Robert Tseng: It’ll have to go into

339 00:42:44.530 00:42:50.190 josh: Basically, if you can just literally give me a stupid simple, here’s an Excel file

340 00:42:50.540 00:42:56.020 josh: with all the fucking tools we have. And then here are the email addresses associated to each

341 00:42:56.960 00:43:00.539 josh: grams. I will be able to make really quick work of it.

342 00:43:01.000 00:43:01.960 Robert Tseng: Okay? Sure.

343 00:43:06.480 00:43:10.980 Robert Tseng: yeah. I I know where to grab it at this point. I I would. It wouldn’t be through thorough pass. It would.

344 00:43:11.130 00:43:18.330 Robert Tseng: Okay, the the tool throw path gives me the tools. But I need to go into our like Google admin to go and figure that out

345 00:43:18.560 00:43:19.290 josh: Got it

346 00:43:19.710 00:43:20.340 Robert Tseng: Yeah.

347 00:43:26.610 00:43:48.259 Robert Tseng: Okay, yeah. So I mean, as far as like, kind of maybe adjustments from my side. And like, kind of how I’m staffing the team on these projects. I mean, I think some learnings would just be like having one having one analyst do like 2 or 3 like spread across 2 or 3 like games just like doesn’t work. It’s not efficient. So I’ve rearranged the team. So we’re only doing

348 00:43:48.270 00:43:57.914 Robert Tseng: one analyst for function. So like you’ll notice now, like it’s only one person for everything. Farm Ops one person for everything marketing or whatever

349 00:43:58.570 00:44:01.909 Robert Tseng: And so that’s that’s kind of adjustment I’ve made on my side.

350 00:44:02.486 00:44:09.530 Robert Tseng: Yeah. And then I feel good about our data. Engineering work like things are, the layer of redundancy is is solid there. So.

351 00:44:10.110 00:44:15.619 Robert Tseng: yeah, you could expect, probably like, at any given moment, 4 people on our team working working on stuff.

352 00:44:16.031 00:44:18.119 Robert Tseng: If we want to do more than like

353 00:44:18.750 00:44:26.919 Robert Tseng: one. I mean, right now, we kind of basically do 2 functions at a time. So it’s in this cycle. It’s been marketing plus farm Ops.

354 00:44:27.340 00:44:37.760 Robert Tseng: I would say, that’s our capacity. If you want us to kind of tackle like 3 functions at a time, then, like I would need more budget to like Staff, a second, another analyst on, to be able to handle

355 00:44:37.760 00:44:44.079 josh: I think it’s too hard. I think it’s too hard to try to manage more than 2 right now. Anyways, I mean, once we get humming. And we get this more.

356 00:44:44.440 00:44:46.950 josh: you know, like streamline and get like a better

357 00:44:47.870 00:44:58.070 josh: process. And we keep letting this thing flush out. Then yeah, no problem like as of right now, like, I still want to get Rob involved another. You know, he’s like

358 00:44:58.570 00:45:02.090 josh: 12 or 15 KA month resource. Still.

359 00:45:03.910 00:45:04.520 Robert Tseng: Yeah.

360 00:45:06.010 00:45:08.660 josh: And so, until we can totally retire. That

361 00:45:09.250 00:45:10.989 josh: kind of my hands are tied. Dude

362 00:45:12.350 00:45:18.471 Robert Tseng: Okay, that’s fine. Then I mean, I at least I feel comfortable with the way that we’re kind of running things. Now.

363 00:45:24.870 00:45:28.280 Robert Tseng: yeah, I mean, you’ve as far as like.

364 00:45:29.820 00:45:32.580 Robert Tseng: I mean, Rob basically jumps at like the urgent.

365 00:45:33.130 00:45:48.399 Robert Tseng: I don’t know. He jumps up the noise, and he sets up like, you know, he sets up the Bandaid solution. And it’s like, I mean, I’m I’m okay with that, because that gives us time to like build things out the right way, I guess, because everything he he hands us. We have to basically like Redo at this point.

366 00:45:49.430 00:45:50.600 Robert Tseng: But

367 00:45:51.080 00:45:52.110 josh: Yeah, I mean there.

368 00:45:52.330 00:46:00.170 josh: because, like, I gotta get this, everyone on the marketing team is clamoring about this incremental thing. And like, I’m gonna be getting beat up about it all day today

369 00:46:00.590 00:46:11.790 Robert Tseng: But I mean I did check with Cutter. Cutter says, not asking for that urgently anymore. So I don’t know. I think there’s other stuff that kind of Rob’s kind of working on. But that seems to not be one of them.

370 00:46:11.790 00:46:17.740 josh: Or if you ask the drip team, and that’s why I also wanted Michael in here because he’s

371 00:46:18.760 00:46:24.240 josh: he’s like begging boy. He’s just begging, I mean, can we throw him in this call? Real quick?

372 00:46:24.240 00:46:29.319 Robert Tseng: Yeah, I mean have until the top of the hour. But yeah, can

373 00:46:30.920 00:46:32.740 josh: Meeting, info

374 00:46:36.770 00:46:41.910 josh: Texting sure

375 00:47:16.570 00:47:18.120 Michael Minter: Alright! What’s going on, guys?

376 00:47:19.540 00:47:20.610 josh: No.

377 00:47:20.610 00:47:22.389 Michael Minter: Yo-yo! How we doing

378 00:47:22.390 00:47:22.734 josh: Oh!

379 00:47:23.360 00:47:24.239 Robert Tseng: Good! How are you?

380 00:47:24.510 00:47:30.610 josh: I got a couple of questions for you, Homie, before you start berating everyone about Ltvs. And

381 00:47:30.871 00:47:34.009 josh: I just wanna make sure I’m looking at the right dash. Honestly.

382 00:47:34.010 00:47:40.370 josh: yeah, no, no, I know. So walk me through. Why incremental is so important

383 00:47:41.680 00:47:50.040 Michael Minter: Because we’re advertising on so many channels. Right now, we need to be able to attribute what’s driving that top of funnel value for us incrementally as we scale. You know, and

384 00:47:50.040 00:47:52.967 josh: Explain to me that like like talk to me like

385 00:47:53.570 00:47:57.950 josh: like I’m the dumb, the dumb business guy that I am.

386 00:47:57.950 00:47:59.220 Michael Minter: Cool so there’s

387 00:47:59.220 00:48:04.969 josh: And explain, like what their solution does, that we can’t normally do

388 00:48:04.970 00:48:05.610 Michael Minter: Yeah.

389 00:48:05.800 00:48:28.659 Michael Minter: So their solution is allowing us. So I guess, let me talk about. I’ll take a step back and dumb it down. So we have. There’s multiple ways to measure incremental scale. And typically the most easy rinse and repeat way that you’re gonna do. An incremental test is going to be a holdout test. Which means we’re gonna take like 50. For example, I wanted to measure Ctv effectiveness. I’m gonna take 50% of our Ctv budget. And I’m gonna completely kill it from like a set period of days.

390 00:48:28.990 00:48:40.309 Michael Minter: Like house, for example. That’s how they operate. You can do small holdout tests. They can tell you the incremental lift of the platform incremental. The reason that we went with them is, 1st of all, the cost is a fraction, but, secondly, they don’t require holdouts

391 00:48:40.786 00:48:51.950 Michael Minter: according to their platform, that they can just measure what changes were made to each individual platform. Report on the daily spend and daily revenue. And then they can measure the incrementality of each channel based on that. So

392 00:48:51.950 00:49:15.680 Michael Minter: the value that it’s going to provide to eaten is basically gonna tell us, okay, we’re advertising on 10 different channels right now, when we add a new channel, or if we add budget on a top of funnel channel. Or if we scale brand awareness like, what’s the impact? The overall revenue when we did that? And is that going to be a viable, scalable strategy for us long term. So like, if we added, you know, for example, on Facebook right now, this is like a great example. I wish we had this tool a while ago to measure this. But

393 00:49:15.680 00:49:23.930 Michael Minter: we’ve taken our daily spend from Facebook from like 15 KA day. Now to over 30 KA day matching Google’s daily spend. And our Cpas are coming down.

394 00:49:24.154 00:49:33.340 Michael Minter: A lot of that. What we’re doing on Facebook right now, that’s been different than what we’ve been doing in the past is we’re pushing really, really hard on top of funnel. So going after new audience, creating new demand.

395 00:49:33.697 00:49:51.260 Michael Minter: Now, previously. And if we just looked at the data in north Beam, you’re gonna see? Oh, my God, we’re scaling Facebook, and it has a thousand dollar cap right now. Why the hell are we doing that? But when you look at our overall dashboard, you’re saying we’re scaling on top of funnel significantly. And it’s actually driving our Cpa down. As we’re scaling on other channels, too. So

396 00:49:51.400 00:49:58.440 Michael Minter: what incremental is gonna basically do is tell us what was the impact of that new budget that we added to this strategy. And is that effective

397 00:50:02.370 00:50:10.580 josh: Okay. So, Robert, the question for you is, how does that plan against something like a build or slide

398 00:50:12.700 00:50:15.909 Robert Tseng: Yeah, I mean, I think, just my understanding of.

399 00:50:16.660 00:50:35.599 Robert Tseng: I guess what these tools do is, you know. Obviously, they have aggregated attribution data. And so it’d be like a similar North theme feature at that point. But basically just bring the same thing over there. So that’s do to me. That’s a duplication of what we already have. And then they have their own models running on my

400 00:50:35.800 00:50:45.660 Robert Tseng: kind of just time series, like, I don’t know, like predictive stuff. And I mean, I don’t know what they’re using under the hood. Maybe it’s like a Facebook profit model. I’m not really sure.

401 00:50:46.073 00:51:07.129 Robert Tseng: And then from there. They do. If they probably work with enough clients that they basically have their own benchmark and send you would send you the trend. So the difference between using that versus what we build in house is we would just be using and we could deploy this, we could figure out what model they’re using and deploy the same model. But we won’t have the same learned kind of like benchmark that they have from

402 00:51:07.570 00:51:11.259 Robert Tseng: you don’t know. They won’t tell you who they’re benchmarking you against.

403 00:51:12.103 00:51:15.330 Robert Tseng: At least, from what I’ve seen working with kind of other

404 00:51:15.520 00:51:23.430 Robert Tseng: things like do y or Yukon, Ml. Or whatever like have to me is kinda a bucket in the same same type of tools. So.

405 00:51:24.290 00:51:33.350 Robert Tseng: in in a sense, like I’m just saying it, it’ll still be a black box to me on like, why, why, they’re projecting it a certain way. So

406 00:51:33.920 00:51:46.350 Robert Tseng: at least, when I was doing leading data team in in house at ruggable like, yeah, we. We would test some of these tools here and there, but like we would still have our own model internally. And they ended up just being like A,

407 00:51:47.410 00:51:53.620 Robert Tseng: they’re. They’re more optimistic. Our own model is more conservative. And so when we’re doing scenario planning, we end up just

408 00:51:53.840 00:51:55.309 Robert Tseng: having multiple.

409 00:51:55.790 00:52:01.030 Robert Tseng: We just have multiple views. And then you just pick a blended perspective to to move forward. So

410 00:52:01.190 00:52:18.930 Robert Tseng: I I see a case for it. I think it’s just. It’s not as simple as a plugin, and we’d be able to report it because it’s a net new data source. There isn’t a connector for it like we would have to set up that work, too. But then we probably, you know, in the longer term we would still need to build internally, because we wouldn’t wanna

411 00:52:19.500 00:52:22.340 Robert Tseng: put our eggs all our eggs in in their in their model

412 00:52:22.640 00:52:25.020 josh: Are we still even leveraging?

413 00:52:25.360 00:52:30.100 josh: What’s their name? The other, the other attribution tool, rob.

414 00:52:30.100 00:52:30.850 Robert Tseng: North, beam.

415 00:52:31.040 00:52:31.780 josh: Yeah.

416 00:52:32.930 00:52:39.410 Robert Tseng: I mean, we just use them for ad spend aggregation, which I think is that’s not what they’re I mean, they’re good at. I mean.

417 00:52:39.760 00:52:42.160 Robert Tseng: they do. You know, mmm, and

418 00:52:42.380 00:52:57.569 Robert Tseng: I, yeah, I think they’re, you know best best in class tool for that. And you know that saves us a lot of time to build something like that in house. So I but I think for our current usage, like we’re not leveraging what our team is good at. So

419 00:52:57.570 00:53:11.420 Michael Minter: I. That’s that’s my problem with working right now, too. And and I don’t know how things have been set up. But this is I mean Zack, handle all this stuff a while ago. But I mean, we’re we’re when I look at north being data. This is my problem with it. It. Just it gives Meta 0 love.

420 00:53:11.420 00:53:28.950 Michael Minter: And when I’m when I’m actually judging, if Meta successful on Northeam, what I’m looking for is that it’s reporting on a Cpa of like less than 1,000 on Meta. That usually means I’m profitable on Meta actual performance. So it’s like it’s really up backwards. And then, when I see like 1,200 plus, I’m like, Hey, Meta is not working right now.

421 00:53:30.230 00:53:37.552 Michael Minter: but of course we’re at like 800. I know we’re doing well, but the fact that I’m looking at an $800 intact value north beam and saying that that’s successful, because we know that really means

422 00:53:37.890 00:53:45.490 Michael Minter: 4 50 to $500 Cpa. Then, you know, I just don’t know how things are running properly. That’s why I reached out to them initially, because

423 00:53:45.620 00:53:55.754 Michael Minter: our data is just wrong. Ctv. Spend isn’t pumping in. We have an Api set up for it. I got that created for Zach a while ago, and I guess it just wasn’t plugged in. Then when they tried to plug it in, they changed the

424 00:53:56.420 00:53:57.830 Michael Minter: the insertion

425 00:53:57.960 00:54:19.670 Michael Minter: set up in their pixels. So that cause an issue. But yeah, the way we’re using working right now is totally not the way it’s supposed to be is, it’s supposed we have the Mta set up right now, and we’re getting 0 Mta. Data. When I go through the orders, Tab, I see one touch, order one touch for every single 1st time. Customer. Now for recurring customers, you’ll see like 8 to 10 plus, but for the 1st time order. That’s the one I care about, and I’m seeing one touch.

426 00:54:22.970 00:54:24.210 Michael Minter: So it doesn’t really help much

427 00:54:24.210 00:54:28.099 josh: So should we be getting? Should we be focusing Robert on getting rid of

428 00:54:29.280 00:54:38.729 josh: North being and trying to roll out incremental at the same time, like, because I’m again like, I’m also like, I have every piece of software known to man.

429 00:54:39.010 00:54:40.969 josh: And I’m exhausted at this.

430 00:54:41.240 00:54:51.710 josh: I want to give everyone the best shot to do what they need to do. But it’s like, how the fuck can I keep having a million pieces? Software? And every single one is the Holy Grail, and none of them ever work

431 00:54:52.350 00:55:04.940 Robert Tseng: So I don’t know what incrementals like kind of causes. But like, I said, there’s a duplication of effort there where they will do their own admin aggregation through incremental everything that we do to hook up stuff into Michael’s team probably have to do again incremental.

432 00:55:05.240 00:55:21.589 Robert Tseng: And I think maybe you know I if we can kind of like time box and do like a like a we can cap the cost like I don’t know what incrementals contract is. But I know the cost that it would take for us to basically remove Northeas out of the picture, go direct with all the data. These data sources.

433 00:55:22.670 00:55:42.600 Robert Tseng: Like, yeah, I mean, it’s basically like a hundred to 500 a month in tooling costs or like, in setting up our own direct connect connections. And I’d be able to replicate that with, obviously, you know, some time and labor for my for my team to do that.

434 00:55:43.012 00:55:49.849 Robert Tseng: So that’s what it would be cost to that. That’s what it would cost for me to show you like a North Current North Beam replacement.

435 00:55:50.470 00:56:01.748 Robert Tseng: I don’t know on the incremental side, like they probably, even if we did that, they would probably still do the aggregation anyway. So like, I do think that we can parallelize these.

436 00:56:02.570 00:56:05.410 Robert Tseng: I think it’s just a call for you, Joshua Mike.

437 00:56:05.950 00:56:19.479 Robert Tseng: Yeah, there will be a period of time where we’re gonna have north theme. We’re gonna have direct kind of like ad spend aggregation. And we’re also gonna have incremental aspect aggregation. And that’s that could be confusing to have 3 things like kind of going at the same time

438 00:56:20.540 00:56:25.910 josh: It is, it is, gonna be it already is confusing, because no one actually knows what the real number is. Alright

439 00:56:27.500 00:56:32.280 Michael Minter: This is kind of why I push for house in the early stages because it just runs off a true holdout model, and

440 00:56:32.400 00:56:37.119 Michael Minter: that’s gonna be different than what we can run on any any other network that we have right now. There’s a little

441 00:56:37.120 00:56:40.699 josh: Well, I think what Robert saying is that we just build it correctly and out

442 00:56:40.700 00:56:42.819 Michael Minter: Yeah. And I’m I’m whatever

443 00:56:42.820 00:56:47.530 josh: I think is probably the right moves. But, Robert, I don’t know the timing like I don’t know

444 00:56:48.090 00:57:01.799 Robert Tseng: No. So the initial thing that I would, I wouldn’t build it straight from the ground like there, there are multiple platforms out there that basically just do direct connectors with these ad ad spend. So I would just push another partner that I’ve worked with before

445 00:57:02.566 00:57:09.960 Robert Tseng: and we would just plug into that, basically do what North Beam is doing. But like there’s more control over over it.

446 00:57:10.634 00:57:16.559 Robert Tseng: So that’s like the fastest way to get something up and running, and then, if we like it, then we would just build. Then we just build it ourselves.

447 00:57:21.110 00:57:27.899 josh: So like. What does it? What does that look like in terms of timing versus just having the incremental things stood up, shutting down

448 00:57:28.410 00:57:31.340 josh: North Union, etc.

449 00:57:31.340 00:57:34.040 Robert Tseng: Yeah, so I I could have something up and running within a week

450 00:57:35.200 00:57:36.660 josh: Does that work for you? Mentor?

451 00:57:37.050 00:57:39.930 Michael Minter: Yeah, I mean, it’s to re realistically, it’s gonna take

452 00:57:40.650 00:57:47.245 Michael Minter: 2 to 3 weeks for incremental to even start learning our historical data and start monitoring what we’re doing now. So

453 00:57:47.670 00:57:50.210 Michael Minter: I mean, I don’t think that’s gonna cause much of a delay. If any

454 00:57:50.740 00:58:11.969 Robert Tseng: It’s like a week demo we could. We can. We can compare what what it says, like, kind of the differences between that and work theme. Yeah, if there are any like kind of like other catch kind of gotchas that we’re not like anticipating from a particular ad source, like, I don’t know. Like, if Michael saying, like, Meta is specifically kind of not like that, that’s been like a red flag for him. Then we would just

455 00:58:12.460 00:58:21.059 Robert Tseng: yeah, we would just basically try to understand the discrepancies between the 2. And then if we once we feel good about it, then we can make the call on if we want to build it or not.

456 00:58:23.570 00:58:27.680 josh: Yeah, let’s do that. Let’s let’s add that one into this. Next.

457 00:58:28.600 00:58:31.460 josh: like, you know, spread cycle for this next week.

458 00:58:31.760 00:58:40.470 Robert Tseng: Okay. So then, what I would need is like which which sources exactly that we want to run this with like, I mean, I could show you. There’s a list of like 500

459 00:58:40.470 00:58:44.979 josh: Mentor mentor will send you the exact list that he wants

460 00:58:45.840 00:58:47.999 josh: basically end of day, I’m sure, today, cause he

461 00:58:48.000 00:58:50.450 Michael Minter: Yeah, I can. I can send it like 5 min.

462 00:58:50.450 00:58:50.790 Robert Tseng: Yeah.

463 00:58:50.790 00:58:55.660 Michael Minter: I guess my only question with you, Robert, is like

464 00:58:56.060 00:59:07.290 Michael Minter: offline channels, you know, like, let’s just say, for example, local ads in a in a gym, or affiliate and influencer marketing like, how are we gonna be able to attribute those kinds of things doing something like this?

465 00:59:07.790 00:59:19.239 Robert Tseng: Yeah. Well, I don’t know how big of that. What percentage of that is the budget right now. But I don’t think we’d be able to do that right away. So, yeah, this is really just all digital pay channels that we could do like super fast. Yeah.

466 00:59:19.240 00:59:25.490 Michael Minter: Cool. Okay? Well, I mean digital channels of the priority. So it’s fine. But that’d be something that I definitely wanna make sure we figure out, because

467 00:59:26.270 00:59:36.910 Michael Minter: influencer at least, is gonna be growing for sure, exponentially month over month over month. But I don’t think it’ll be like something that’s going to be a large enough lift to compare to what we’re doing on paid for another like 3 months, probably to be honest.

468 00:59:37.810 00:59:49.030 Robert Tseng: I mean paid offline channels like, I don’t know, like I don’t know if we do like QR. Codes or anything like there are like URL, kind of tracking methods that are pretty easy to kind of implement like I I know that like.

469 00:59:49.410 00:59:50.890 Robert Tseng: I mean, at least, that’s what I’ve

470 00:59:51.190 01:00:05.789 Robert Tseng: that’s what I’ve seen before in the office. We don’t. I don’t think we necessarily need another source like I don’t know how we’re setting up ads for these offline channels like it usually is just like A. You are like A, I think the QR. Code approaches

471 01:00:05.910 01:00:09.610 Robert Tseng: the most standard to me, so I don’t know I. But I

472 01:00:09.810 01:00:14.110 Robert Tseng: that’s that’s just me speaking as like, that’s, that’s clean data.

473 01:00:14.110 01:00:14.630 Robert Tseng: Okay.

474 01:00:15.325 01:00:24.409 Michael Minter: Just go search instead. It’s been weird, like, even with direct mailers. We saw like no activity on QR. Codes and track

475 01:00:24.410 01:00:27.719 josh: You got one other question I got to jump in a minute. What’s your

476 01:00:27.720 01:00:28.580 Robert Tseng: Yeah, for me, too.

477 01:00:30.810 01:00:31.879 Michael Minter: What was that? Josh? Sorry.

478 01:00:31.880 01:00:33.990 josh: We have an Ltv. Question before you have this, make it

479 01:00:33.990 01:00:44.959 Michael Minter: Oh, yeah, I sent some screenshots in the slide channel. So I’m just looking at. We got the product row as an Ltv dashboard and the mobile version of the product row as an Ltv dashboard. And I’m seeing different values for Ltv. On those

480 01:00:44.960 01:00:47.270 Robert Tseng: They say different things between those 2 dashes

481 01:00:47.270 01:01:05.170 Michael Minter: Yeah, between those 2, 1 of them. When I look at the 3 month average, I see the date range is off. So that’s probably part of it, but when I go back 15 months, so I can see March of 2024. In the Mobile version I see average Ltv. 1.8,000. So 1,800, and then the other dashboard. When I go back to March I see 1,700,

482 01:01:06.100 01:01:06.559 Michael Minter: not a few

483 01:01:06.805 01:01:17.100 Robert Tseng: Can look into that that should be, they should be. They should be the same. It really. They’re using the same models. But I don’t know what. Maybe we just displayed it. I don’t know. Yeah, I don’t know. Top, my head

484 01:01:17.100 01:01:18.690 Michael Minter: Didn’t display, too, because it doesn’t show as many.

485 01:01:19.010 01:01:21.080 Michael Minter: It’ll round up pretty big if it did

486 01:01:21.840 01:01:22.460 Robert Tseng: Okay.

487 01:01:22.830 01:01:29.830 Michael Minter: But that was pretty much it. I was just trying to get the Ltv. Stuff and make sure I have the right numbers. So otherwise all good. I just wanna make sure that the source of truth right

488 01:01:30.150 01:01:42.219 Robert Tseng: Okay, yeah. I mean, the Ltv, I feel like should be consistent. The Cac numbers will change today because we’re pushing a change based off of excluding the offer, so that will affect the ratio. But the Ltv. Number will not be

489 01:01:42.700 01:01:43.280 Michael Minter: Cool.

490 01:01:43.620 01:01:44.300 Robert Tseng: Okay.

491 01:01:44.790 01:01:46.550 josh: Cool. Awesome thanks. Guys.

492 01:01:46.550 01:01:47.240 Michael Minter: Thanks guys