Meeting Title: Grain Group Project Recap and Planning Date: 2025-12-19 Meeting participants: Dan Buri, Byron Pittam, Robert Tseng
WEBVTT
1 00:00:47.270 ⇒ 00:00:48.630 Robert Tseng: Hey, guys.
2 00:00:49.220 ⇒ 00:00:49.720 Byron Pittam: Hey, Robert.
3 00:00:49.720 ⇒ 00:00:50.530 Dan Buri: Whoa!
4 00:00:51.090 ⇒ 00:00:52.240 Robert Tseng: Happy Friday!
5 00:00:52.440 ⇒ 00:00:53.580 Byron Pittam: Yeah, he was well, man.
6 00:00:53.870 ⇒ 00:00:55.200 Dan Buri: Sure is.
7 00:00:56.310 ⇒ 00:00:59.140 Robert Tseng: Now I’m… I’m back on the West Coast myself, so…
8 00:00:59.140 ⇒ 00:00:59.800 Byron Pittam: I’m nice!
9 00:01:00.240 ⇒ 00:01:01.040 Robert Tseng: Yeah.
10 00:01:02.970 ⇒ 00:01:03.670 Robert Tseng: Hold the people.
11 00:01:03.970 ⇒ 00:01:08.370 Robert Tseng: Yeah, I’m visiting my family in the Bay Area for Christmas.
12 00:01:08.540 ⇒ 00:01:08.950 Byron Pittam: Nice.
13 00:01:08.950 ⇒ 00:01:09.480 Dan Buri: Nice.
14 00:01:09.480 ⇒ 00:01:10.030 Robert Tseng: Yeah.
15 00:01:11.430 ⇒ 00:01:17.590 Byron Pittam: Hopefully, yeah, it doesn’t rain the whole time. I’m not sure what’s gonna happen right now. It’s just, it’s pouring on the.
16 00:01:17.590 ⇒ 00:01:20.770 Robert Tseng: Oh, over there? Oh, okay, well…
17 00:01:20.770 ⇒ 00:01:24.069 Dan Buri: Oh, I was hearing about one of those atmospheric rivers.
18 00:01:24.070 ⇒ 00:01:25.949 Byron Pittam: Yeah, it’s a very exciting time.
19 00:01:25.950 ⇒ 00:01:26.730 Robert Tseng: Wow.
20 00:01:28.150 ⇒ 00:01:28.720 Byron Pittam: Yeah.
21 00:01:28.910 ⇒ 00:01:34.650 Byron Pittam: We should have had 3 feet of snow here in Bend, but instead we had 3 inches or 5 inches of rain.
22 00:01:34.910 ⇒ 00:01:35.610 Robert Tseng: Wow.
23 00:01:35.610 ⇒ 00:01:36.210 Byron Pittam: Yeah.
24 00:01:37.150 ⇒ 00:01:47.220 Robert Tseng: Yeah, well, it was cold and snowy in New York, so either way, I don’t mind it being a little warmer and rainy here, if it ends up being that way.
25 00:01:47.690 ⇒ 00:01:48.240 Byron Pittam: Yep.
26 00:01:48.830 ⇒ 00:01:49.430 Robert Tseng: Yeah.
27 00:01:50.510 ⇒ 00:02:00.549 Robert Tseng: Cool. Well, it’ll just be me today. Amber… Amber’s out, and then Utam is out as well. He’s traveling. We’re having a little get-together in the Bay, over the weekend, so…
28 00:02:00.930 ⇒ 00:02:08.189 Robert Tseng: People are probably traveling on and about today. I just got… You’re making… you’re making people party on the weekend, Robert? Come on!
29 00:02:08.190 ⇒ 00:02:08.770 Byron Pittam: The bar?
30 00:02:08.770 ⇒ 00:02:11.319 Robert Tseng: We’re gonna have a good time, yeah.
31 00:02:11.320 ⇒ 00:02:12.790 Byron Pittam: story fun, I like it, yeah.
32 00:02:13.280 ⇒ 00:02:14.090 Robert Tseng: But yeah.
33 00:02:17.070 ⇒ 00:02:22.910 Byron Pittam: Cool, yeah, let’s pop in then, whatever, what we can… I’ve got all the decks up, too, I don’t know if they’ve been…
34 00:02:24.310 ⇒ 00:02:39.330 Robert Tseng: Yeah, we created a couple more, actually, so I haven’t shared these out with you, but sorry, we keep creating new links, just wanna… don’t wanna get things lost. I think where I’d like to start today is just kind of doing a recap of kind of how things have gone, up to this point, and then
35 00:02:39.330 ⇒ 00:02:44.459 Robert Tseng: you know, obviously, Amber had a couple follow-ups that she had from last week, so I’ll just kind of read those out.
36 00:02:44.500 ⇒ 00:02:57.799 Robert Tseng: And then, you know, we have a couple weeks left, so I just want to make sure that we’re using our time the most effectively, also recognizing that people are in and out. So, yeah, I think that would be… that’s kind of what I had in mind in terms of agenda.
37 00:02:58.200 ⇒ 00:03:09.600 Byron Pittam: And real quick as well, just so, you know, full disclosure, like, Megan was, like, they were, you know, not pushing back, but they were saying, like, if we added anything to the Looker dashboard, it’d be, like.
38 00:03:09.600 ⇒ 00:03:18.259 Byron Pittam: they’d want to implement it and have a fee, but I think we could push on that, if you think there’s anything we could put in the Looker dashboard that you guys could, you know, squeeze in there and connect.
39 00:03:18.760 ⇒ 00:03:19.610 Robert Tseng: Yeah, yeah.
40 00:03:19.610 ⇒ 00:03:30.730 Byron Pittam: So, if you have any thoughts on platforms that you’d like to put in there, I can go back to Megan and just say, hey, like, are you okay with Robert and team, like, going in there and adding X, Y, and Z, to the dashboard? Knowing that…
41 00:03:30.730 ⇒ 00:03:31.090 Robert Tseng: Yeah.
42 00:03:31.090 ⇒ 00:03:34.850 Byron Pittam: If it breaks, you don’t have to do anything with it, Green.
43 00:03:34.850 ⇒ 00:03:35.310 Robert Tseng: Yeah.
44 00:03:35.310 ⇒ 00:03:36.130 Byron Pittam: Figure it out.
45 00:03:36.500 ⇒ 00:03:44.950 Robert Tseng: Yeah. No, I mean, I think… I mean, just on… just on that note, like, I think my… what I gathered from the Looker, I’ve already clicked through it as well. Yeah, I mean, if they’re just…
46 00:03:45.000 ⇒ 00:03:59.170 Robert Tseng: kind of hooking up a bunch of these data sources, kind of similar to what we would do, putting it into BigQuery, and then they’re, like, kind of just plugging that into Looker Studio. So, if they’re charging you a fee just to add more sources, I think that’s kind of silly, to be honest, because it’s.
47 00:03:59.170 ⇒ 00:04:01.829 Byron Pittam: And I can… I can… I’m sure I can push on it.
48 00:04:01.830 ⇒ 00:04:13.450 Robert Tseng: Yeah, okay. Yeah, I mean, I’ve also looked at the historical data they sent over. It’s… it’s pretty clean, like, we’d be able to easily get into a format so that it can also show up in the looker report. So it’s just… but I understand.
49 00:04:13.450 ⇒ 00:04:19.069 Byron Pittam: And maybe… maybe that is, like, the bare bones, like, let’s just get the historical data in there.
50 00:04:19.390 ⇒ 00:04:26.289 Robert Tseng: Yeah, yeah, so I think that’s… that’s definitely, like, a quick, quick thing we could do. Yeah, like, that wouldn’t… that wouldn’t take us very long.
51 00:04:28.120 ⇒ 00:04:42.580 Robert Tseng: But yeah, I mean, I’ll get to that in a bit more detail in terms of, like, what I think it… what I think it does for you, and then what I think it doesn’t do for you, and we can kind of spend a little bit of time talking about, like, you know, like, what you want to do about that.
52 00:04:43.530 ⇒ 00:04:44.320 Robert Tseng: Okay.
53 00:04:45.890 ⇒ 00:04:56.290 Robert Tseng: So yeah, I think, like, original, kind of just to center us on, like, kind of original scope. This was before Dan started, so, you know, gonna just rehash a little bit of things, just so you can get caught up to speed.
54 00:04:56.290 ⇒ 00:05:08.709 Robert Tseng: So we kind of came in thinking that we were gonna do a little bit more on the lifecycle side, actually. So, obviously, like, Klaviyo, wasn’t… was not kind of ready for the in-depth, like, behavioral segmentation
55 00:05:08.720 ⇒ 00:05:11.779 Robert Tseng: You know, just the lifecycle work that we typically do.
56 00:05:12.110 ⇒ 00:05:14.990 Byron Pittam: I’ll be honest, Robert, it was a shitshow. It’s fine. You can…
57 00:05:16.270 ⇒ 00:05:32.920 Robert Tseng: Yeah, no, I mean, it’s just that, like, like you said, it was pretty early in maturity, so there wasn’t really that much, like, we could squeeze out of it, to be honest. So, we kind of were like, okay, well, we were parallel… in parallel, we were like, okay, let’s go and get all the marketplace data and see what we could do in terms of stitching.
58 00:05:32.920 ⇒ 00:05:51.730 Robert Tseng: Turns out, like, with the way that Amazon… what data we got off Amazon was less than what we typically see, so we weren’t able to, like, do the problemistic matching that I originally kind of was, like, excited to tell Byron that we could do. So, yeah, I mean, other than that, we were able to capture some interesting demand signals on the Amazon side.
59 00:05:51.730 ⇒ 00:06:05.560 Robert Tseng: Amazon, Shopify, Walmart, we’ve looked into all of those. And so it’s not necessarily about cross-channel, like, customer matching, but more just, like, kind of detecting customer behavior trends on each of the platforms. So we did some more analysis around there.
60 00:06:05.760 ⇒ 00:06:20.819 Robert Tseng: And then we were kind of expecting, maybe at some point, we would be working with kind of… there would be some handoff where, you know, once the… you know, I know going to BFCM, you kind of retweet the… the flows, and we thought we would maybe kind of pop back in there afterwards to
61 00:06:20.820 ⇒ 00:06:33.950 Robert Tseng: kind of help optimize them and, like, kind of analyze the triggers. We could still do that. I think there’s still time for that. We could just basically do a retro on the past few weeks on kind of how things were pre and post, like, the new implementation, so I think that’s a pretty low-hang.
62 00:06:33.950 ⇒ 00:06:41.890 Byron Pittam: Who would be the direct contact for that? Because Dan could just book that, and he’s got a couple of days in the office for the rest of the year. Okay. Would that be directly with you, or would that.
63 00:06:41.890 ⇒ 00:06:49.069 Robert Tseng: Yeah, yeah, just book that with me. Like, I’ll just go and, like, I’ll be able to get everything I need quickly from one or two calls. Yeah.
64 00:06:49.700 ⇒ 00:06:53.080 Dan Buri: Okay, yeah, let’s find some time, maybe at the end we can talk availability.
65 00:06:53.400 ⇒ 00:06:58.480 Robert Tseng: Okay, yeah, let’s do that. So I think that’s still something that we could… we could run with.
66 00:06:58.720 ⇒ 00:07:01.690 Robert Tseng: But where we ended up spending our time, yeah, I think.
67 00:07:01.690 ⇒ 00:07:05.439 Byron Pittam: Welcome to my world, Robert. Yeah, we…
68 00:07:05.440 ⇒ 00:07:05.790 Robert Tseng: Yeah.
69 00:07:05.790 ⇒ 00:07:07.690 Byron Pittam: Nothing, nothing is a straight line.
70 00:07:07.690 ⇒ 00:07:23.949 Robert Tseng: Yeah, oh no, it’s all good. I appreciate you guys for watching this. I just hope that this is, you know, I mean, I’m glad you guys are laughing about it, but obviously tell me if you’re just like, yeah, you know, like, this… we kind of… I mean, I know we kind of… we went… petered off in a couple different directions, so I just want to kind of get back on the same page.
71 00:07:24.060 ⇒ 00:07:32.789 Robert Tseng: So yeah, I mean, as far as, like, kind of things we learned about the business, you know, a lot of the time when we’re doing lifecycle work, it’s also to just kind of
72 00:07:33.030 ⇒ 00:07:37.239 Robert Tseng: There’s this whole, like, churn analysis, driving repeat purchases, etc.
73 00:07:37.240 ⇒ 00:07:59.250 Robert Tseng: but you’re not really, like, a monthly subscription business. We saw that, like, actually your demand, your customer kind of life cycle is pretty lumpy. Like, it’s, you know, maybe a biannual kind of batch purchases. Obviously, you have, your ambassadors that are purchasing a bit more frequently than that, but no one’s really doing, like, more than, like, you know, five, five orders a year kind of thing. And so, yeah, I think that’s… so that’s, like…
74 00:07:59.250 ⇒ 00:08:03.689 Byron Pittam: But maybe on B2B, Robert. I don’t know how much you got into that data, right?
75 00:08:03.690 ⇒ 00:08:04.300 Robert Tseng: So, I think that’.
76 00:08:04.300 ⇒ 00:08:05.480 Byron Pittam: Outstanding, yeah.
77 00:08:06.050 ⇒ 00:08:30.990 Robert Tseng: Yeah, like, the whole, okay, well, what if, you know, like, digital to wholesale retail? Like, that, we didn’t really have, you know, the time to really go into, and so I think there’s probably still more to the story there, right? And I think we’re asking questions around that. And then, you know, around, like, discount analysis, and as we were cutting the data here and there, I think, obviously, there were some inconsistencies of, like, hey, you know, actually.
78 00:08:30.990 ⇒ 00:08:55.050 Robert Tseng: like, our discount codes, they change a lot. They’re not, like, really… this is kind of what Dan was, like, talking about last week, right? Like, we want to really serialize them, you know, moving forward, and so, like, you know, you’re able to really, you know, better attribute back to these cohorts of customers that are receiving this particular code, right? And, you know, I think that’s obviously… that’s obviously really good data, you know, sanitization that we need in order to be able to do that cohort level
79 00:08:55.050 ⇒ 00:09:10.719 Robert Tseng: like, analysis, when you’re running the same type of campaign on, like, you know, different types, you know, in different… in different parts of the year. So, like, you know, I think that… that’s kind of what I, you know, would call out is kind of where, we… we got… we kind of ran into on… on that front.
80 00:09:10.720 ⇒ 00:09:25.759 Robert Tseng: But then, at, like, the marketplace, maybe this is, like, marketplace level… marketplace cohort segmentation, yeah, I think we were able to do some interesting analysis, figuring out, like, kind of drilling into high-value customer LTV segments.
81 00:09:26.020 ⇒ 00:09:43.369 Robert Tseng: And then, yeah, we’re able to kind of look at, you know, trends between discounted versus non-discounted, discount-affected customers, and we, like, have a better understanding of, like, subscribe and save versus Shopify subscriptions. So I think some of these, like, marketplace dynamics, like, we’ve been able to kind of share these insights with you, and
82 00:09:43.370 ⇒ 00:09:56.000 Robert Tseng: I think, like, if you were to kind of take that and you operationalize it, what you would do is, you know, if we liked the way that we kind of helped you to segment the customers, we would basically, like, turn those into, you know, things that you could actually
83 00:09:56.000 ⇒ 00:10:08.629 Robert Tseng: you know, be measuring, like, you know, over, over time on a weekly, weekly, monthly, quarterly business review or something, or even in your, like, whether it’s Klaviyo or if you’re moving to a different platform, like.
84 00:10:08.630 ⇒ 00:10:24.430 Robert Tseng: we would set up… yeah, we would basically encourage you to set up segments that are kind of focused on, based off… on those customer segments. So, I think that’s kind of, like, the next step that we haven’t gotten to with the kind of ad hoc analysis that we’ve done.
85 00:10:24.460 ⇒ 00:10:30.320 Robert Tseng: And then, like, lastly, like, we understand the limits of, like… Alright, Robert, is 2C in this… in this deck?
86 00:10:31.700 ⇒ 00:10:36.950 Byron Pittam: a slide for, for the compare, the, the Amazon and Shopify compare?
87 00:10:36.950 ⇒ 00:10:41.840 Robert Tseng: It’s not in this deck, this is more high level, but it’s probably one of, like, the, ad hoc decks that.
88 00:10:41.840 ⇒ 00:10:45.239 Byron Pittam: I just want to make sure I have that one, cause I…
89 00:10:45.370 ⇒ 00:10:50.880 Byron Pittam: I can look… I’m looking at the… the Shopify analysis deck, and I… yeah. Okay.
90 00:10:51.130 ⇒ 00:10:53.990 Byron Pittam: I want to make sure I have whatever slide you have for that.
91 00:10:54.340 ⇒ 00:10:56.590 Robert Tseng: Okay, okay, yeah, no, I’ll…
92 00:10:56.590 ⇒ 00:11:00.949 Byron Pittam: I don’t remember… I don’t recall seeing them side by side, which is great, I want to.
93 00:11:01.110 ⇒ 00:11:03.500 Robert Tseng: Okay, yeah, that was something that we were working on, yeah.
94 00:11:03.720 ⇒ 00:11:07.529 Dan Buri: Maybe it could be good just as a summary to, like, send an email with all of the decks, you know, just.
95 00:11:07.530 ⇒ 00:11:08.600 Robert Tseng: Yes, we will.
96 00:11:08.600 ⇒ 00:11:09.040 Dan Buri: Yeah, yeah, yeah.
97 00:11:09.410 ⇒ 00:11:14.130 Robert Tseng: Yeah, I know, I know there’s a… they’ve created a new one every week, so I will, I will send you one.
98 00:11:15.150 ⇒ 00:11:33.579 Robert Tseng: Yeah, and then the last piece is just kind of, like, I think we understand the limits of, like, what tools you have set up, what you don’t, and kind of, like, what we would need to move forward there. So, that’s pretty much just, like, an overview of kind of where I feel like our time, like, went these, you know, up to, like, five… five weeks so far. And so…
99 00:11:33.720 ⇒ 00:11:38.030 Robert Tseng: Yeah, I think, you know, question… you know, really the question is, like.
100 00:11:39.130 ⇒ 00:11:56.860 Robert Tseng: like, we’re… I mean, I’m just thinking, you know, beyond these next couple weeks, like, we’re, you know, something to start keeping in mind… I want us to think about is, like, you know, what does this next phase of, kind of, partnership look like? You know, do we want… do we want to stay on? And, like, do we want to actually do… like, yeah, right now, we’re kind of…
101 00:11:57.370 ⇒ 00:12:09.480 Robert Tseng: dabbling in both. We started off with doing some engineering lift to kind of land all the data and give you a sense of what that was like, but if we’re not going to invest more in the data foundations, like, is it helpful to stay in this kind of mode of just
102 00:12:09.480 ⇒ 00:12:19.849 Robert Tseng: doing more, like, analysis and advisory, I think that’s, like, something I’d like to kind of flush out, you know, if that’s something, like, over… you know, it doesn’t have to be today, but something I want… I would like to kind of…
103 00:12:19.850 ⇒ 00:12:21.809 Robert Tseng: be thinking about leading up to…
104 00:12:21.810 ⇒ 00:12:25.540 Byron Pittam: Invite us to your team party, Robert, and we can, you know, we can make it happen.
105 00:12:26.800 ⇒ 00:12:28.200 Robert Tseng: Yeah, I mean…
106 00:12:28.200 ⇒ 00:12:47.869 Byron Pittam: I still push… my main question here is, you know, on our side, who’s going to look at it, right? Like, so I think there’s something to be said for, like, we’re… I’m interviewing for… or, you know, Tim, who you haven’t met, I don’t think, is interviewing for an assistant brand manager position. Okay. He’d be much more equipped to leverage a lot of these… these pieces. Yeah.
107 00:12:47.870 ⇒ 00:12:53.850 Byron Pittam: So I can also bring that up in the infie process today, of like, you know, how would you… how would you use, kind of, a…
108 00:12:53.970 ⇒ 00:13:05.380 Byron Pittam: a data warehouse to analyze and produce, you know, even better insights. Yeah. So, yeah, I mean, once again, it’s that management piece of it all, and analysis piece of it all. If we do
109 00:13:05.500 ⇒ 00:13:09.090 Byron Pittam: Put a bunch of data in a warehouse, like, what’s gonna… who’s gonna look at it?
110 00:13:09.940 ⇒ 00:13:10.550 Robert Tseng: Yeah.
111 00:13:10.630 ⇒ 00:13:24.909 Byron Pittam: Or you show me how easy it is to kind of get to a dashboard level, and look at the dashboard, connect all the pipes, and if it breaks, like, you know, we can have it fixed once or twice a year, knowing that we can kind of backfill it, too.
112 00:13:25.270 ⇒ 00:13:41.330 Robert Tseng: Yeah, yeah. Yeah, no, I think it does sound like you guys don’t really need, like, heavy lift on the business intelligence side. I wouldn’t be pushing any sort of BI tool towards you. If you like the way that Looker Studio is set up, and you just want, like, kind of new tabs and that views, I think that’s pretty lightweight, it’s easy to do.
113 00:13:41.350 ⇒ 00:13:46.130 Robert Tseng: I think there’s just something about, you know, obviously being in control of your data, being able to, like.
114 00:13:46.280 ⇒ 00:13:54.730 Robert Tseng: kind of iterate on the metrics that you want to see, like, kind of the limits of, like, what Grain Group is able to do for you right now, and, like, I’ll share about that when we get to that slide.
115 00:13:55.080 ⇒ 00:14:01.440 Robert Tseng: Actually, no, I’ll just jump to it now. So, yeah, I mean, this is a pretty, pretty loaded slide.
116 00:14:01.730 ⇒ 00:14:08.629 Robert Tseng: Okay, come on. Spacing. People… I give my decks to my team and have them leave feedback.
117 00:14:08.810 ⇒ 00:14:11.690 Robert Tseng: But, like, anyway, spacing is not.
118 00:14:11.910 ⇒ 00:14:14.830 Byron Pittam: Your arrows are too wide, Robert.
119 00:14:15.150 ⇒ 00:14:18.910 Robert Tseng: Oh, I had a lot going on here, so… .
120 00:14:19.310 ⇒ 00:14:21.040 Byron Pittam: Chubby arrows, I like them, you know?
121 00:14:21.040 ⇒ 00:14:21.670 Robert Tseng: Yeah.
122 00:14:21.860 ⇒ 00:14:36.220 Robert Tseng: Yeah, so I mean, I just kind of used this sequence as, like, an example of, like, this is kind of the influencer performance kind of dash, like, you can… you can zoom into it a bit more. I just… it’s nothing really that look like. It’s just, like, a screenshot of, like, what you had, here.
123 00:14:36.610 ⇒ 00:14:49.389 Robert Tseng: You know, this is kind of, like, at the… at the channel level, you can drill down to, like, at the creative or campaigns, you can… you can look at these different… yeah, you can look at these different performance metrics, you can compare these, like, campaigns side by side.
124 00:14:49.400 ⇒ 00:15:02.319 Robert Tseng: But then you don’t really get to roll that up into, like, a channel-to-channel kind of comparison across all the different kind of influencers. And then, you know, as far as, like, how you’re able to iterate on these.
125 00:15:02.320 ⇒ 00:15:10.100 Robert Tseng: These metrics. I mean, some of these are helpful for you, because this is top of funnel, you want to know, like, the impressions you’re driving, clicks, etc.
126 00:15:10.150 ⇒ 00:15:23.129 Robert Tseng: But, you know, otherwise, you know, the only real monetary metrics I’m seeing, obviously, cost per click, ROAS, like, I don’t even know if you feel confident with, like, the ROAS metric here. And so typically what we see is with teams, like, you know, this is a little bit more…
127 00:15:23.360 ⇒ 00:15:36.750 Robert Tseng: bloated, but, like, you know, we even start… sometimes we start on a Google Sheet, and we just, like, kind of list out all the partners, like, on… you know, I was just kind of doing an apples-to-apples comparison when we’re doing kind of, like, a partnerships dashboard for… for another brand.
128 00:15:36.750 ⇒ 00:15:50.330 Robert Tseng: And we’re, like, kind of just, like, working through all these different, like, layers to the metrics. So, taking something like ROAS. You want to look at ROAS against CAC with LTV, and then you also want to be, you know, not just looking at clicks, but you want to be measuring
129 00:15:50.330 ⇒ 00:16:03.240 Robert Tseng: kind of sessions, add to carts, like, all these different things. And so, it’s this iterative process of, like, kind of mapping out all the different metrics that you would need to tell the story you want to see when you’re comparing partners against each other.
130 00:16:03.240 ⇒ 00:16:22.409 Robert Tseng: And then, you know, this gives you some, like, framework for how you want to… how you want to scale it, because you get to set benchmarks off of, like, you know, CAC LTV or OAS or whatever. And then, you know, I think that’s… that’s more of, like, what I think is, you know, at your level, as a director of digital, a director of e-com.
131 00:16:22.430 ⇒ 00:16:27.669 Robert Tseng: Like, you would want to be able to see, across all of your, kind of, like, influencers.
132 00:16:27.670 ⇒ 00:16:42.879 Robert Tseng: But, you know, obviously, this example is, like, they had about 200, they scaled up to, like, about 5,000 over the past year, so they just needed, like, a… like, a framework that could help them to, like, make decisions as they were… they were scaling… scaling that to that point.
133 00:16:42.880 ⇒ 00:16:47.339 Robert Tseng: So that’s kind of that middle stage, where even that is still not, like, you know.
134 00:16:47.430 ⇒ 00:17:10.009 Robert Tseng: there’s no fancy BI tool or whatever, it’s still just Google Sheets, but, like, this is all warehouse data now, and when we’re actually testing and building, iterating on these metrics, it’s very easy for us to… to… to change them, to basically upload into the warehouse, and then it populates quickly across all the reporting. So, that’s where, like, the warehouse data becomes more effective, because it just speeds up
135 00:17:10.010 ⇒ 00:17:11.809 Robert Tseng: Kind of, you know, the…
136 00:17:12.109 ⇒ 00:17:17.929 Robert Tseng: It speeds up your, like, how you’re, how you’re, like, working with the metrics.
137 00:17:18.300 ⇒ 00:17:37.049 Robert Tseng: And then maybe, like, a final form, which is, like, once things are pretty stabilized, and, like, you know, this is a little bit more zoomed out to, like, a CMO-level perspective, he literally just, you know, another brand of ours, separate one, they only… they only care about, like, marketing efficiency ratio. And so, like, they’ll go in there, and they’ll check off all the different channels, so…
138 00:17:37.050 ⇒ 00:17:48.729 Robert Tseng: how does the merr change if we turn off, like, a couple channels? You know, what’s the incremental lift? And, like, those… that’s the kind of, like, stuff that he’s looking at. And so, a truly, like, cross-channel, blended metrics.
139 00:17:48.730 ⇒ 00:18:05.700 Robert Tseng: And then it kind of gets distilled into, like, a simple, like, kind of set of charts, and this is just sitting in a tableau. Like, this to me is, like, kind of final stage for, like, what a, like, a C-level marketing executive would want to be able to see from, like, their performance marketing data. So, anyway, I just…
140 00:18:05.700 ⇒ 00:18:15.990 Byron Pittam: This dashboard, like, that marketing efficiency ratio can’t be piped back into, like, a Looker. That needs to be… Looker doesn’t have this kind of capability to consolidate.
141 00:18:15.990 ⇒ 00:18:29.270 Robert Tseng: Yeah, there’s not, yeah. Yeah, like, I think Looker is good for, like, channel-level, like, kind of analysis, like, kind of, like, what you’ve been able to see. But yeah, to be able to…
142 00:18:29.320 ⇒ 00:18:48.559 Robert Tseng: I mean, there’s a lot of stuff that’s, like, hidden behind the scenes here, right? Like, in terms of, like, how do you actually measure ROI on, like, a channel like Customer I.O, the similar… like, similarly to, like, ads, right? Ads… ads payback period, maybe you’re limiting your campaigns to 7-day or 14… 14-day, whereas, like, a Customer I.O.
143 00:18:48.560 ⇒ 00:18:55.620 Robert Tseng: our customer I.O. campaign may be 30 days. So there’s, like, certain, like, nuances to business logic there, that, like.
144 00:18:55.620 ⇒ 00:19:11.450 Robert Tseng: you know, even if in Looker, you would see them separately, but you would never be able to put them side by side. You would need to, like, kind of abstract it, a little, like, behind… behind the scenes so that, like, you’re actually kind of… you… you feel, like, you feel like you could actually compare, like.
145 00:19:11.950 ⇒ 00:19:14.319 Byron Pittam: Like, the Merida side.
146 00:19:14.740 ⇒ 00:19:23.959 Byron Pittam: Does Sky fall into, like, the Tableau capabilities? Is that kind of… or is Sky just too much, like, commerce forward and less, like, media?
147 00:19:24.580 ⇒ 00:19:39.700 Robert Tseng: Oh, no, I think, I think you can as well. I’m not… I’m not, like, a big Tableau advocate, honestly. Like, you know, we actually, you know, our favorite tool is, like, it’s a tool called Omni. I think, I think Sky is kind of, like, a little bit more lightweight than Tableau. Tableau is very hard to maintain,
148 00:19:40.020 ⇒ 00:19:50.739 Robert Tseng: like, yeah, yeah, it’s just… Salesforce products are just like that. You have to… you would not… you would not be able to go in and just, like, click a couple buttons to fix the report like you can with Looker.
149 00:19:50.870 ⇒ 00:19:52.140 Robert Tseng: Yeah, so…
150 00:19:52.180 ⇒ 00:19:56.789 Byron Pittam: What was the Omni… Omni software you were talking about? Omni, what’s it?
151 00:19:57.300 ⇒ 00:20:01.869 Robert Tseng: Oh, I think it’s just Omni.co, yeah.
152 00:20:03.650 ⇒ 00:20:17.460 Robert Tseng: It’s actually made by former Looker developers, so it kind of feels and looks like Looker, but it’s actually just… it’s warehouse native, you can run queries directly out of it, so it’s just… I mean, we like it a lot. It’s typically what we recommend.
153 00:20:17.460 ⇒ 00:20:23.790 Robert Tseng: Because it helps you to go from spreadsheet to dashboard very easily, and that’s typically, like, the speed that we want to work with.
154 00:20:23.790 ⇒ 00:20:28.210 Robert Tseng: Whereas, like, Tableau, you have to convert spreadsheets into their their Tableau.
155 00:20:28.210 ⇒ 00:20:28.600 Byron Pittam: Yeah, specifically.
156 00:20:28.600 ⇒ 00:20:38.069 Robert Tseng: like, model or whatever. I forgot what it’s even called. Yeah, I mean, I have Tableau developers on my team, like, I’m not really going in there myself. So…
157 00:20:38.510 ⇒ 00:20:38.990 Byron Pittam: the expert.
158 00:20:38.990 ⇒ 00:20:39.540 Robert Tseng: Yeah.
159 00:20:39.690 ⇒ 00:20:40.390 Byron Pittam: Okay.
160 00:20:40.710 ⇒ 00:20:51.240 Robert Tseng: Yeah, and it’s… and they’re… they’re expensive for doing stuff that would be very simple to do in Excel, to be honest. Yeah. Anyways, yeah, that’s… that said…
161 00:20:51.320 ⇒ 00:21:11.110 Robert Tseng: Yeah, so that to me is, like, kind of the different stages of, like, marketing performance reporting, and I think that’s just to give you, like, a sense of where I think, kind of, what you have with grain is sitting. And so you’re not able to do blended, like, tech LTV across all paid media. You’re not able to do a marketing efficiency ratio.
162 00:21:11.110 ⇒ 00:21:19.270 Robert Tseng: And then even kind of what we were saying about, like, online, offline, like, yes, we’ve told you the story of, like, the digital, kind of
163 00:21:19.760 ⇒ 00:21:31.500 Robert Tseng: customer journey, but, like, someone comes in on Meta, makes a purchase on .com, and then goes to Amazon. Oh, I guess, sorry, these are both… these are both digital. I had meant to include something that was more, like, offline.
164 00:21:31.850 ⇒ 00:21:44.089 Robert Tseng: But, like, yeah, like, I think… right now, we’re not able to tell the story, you know, obviously, through the local reporting of, like, how that works. So, yeah, I think that’s…
165 00:21:44.330 ⇒ 00:21:46.599 Robert Tseng: That, that to me is, like.
166 00:21:46.760 ⇒ 00:21:56.429 Robert Tseng: those are future capabilities that, you know, I’m sure maybe today is not the time for you to go ahead and do that, but just wanted to kind of put the…
167 00:21:56.750 ⇒ 00:22:01.210 Robert Tseng: you know, put the vision out there, like, I think that’s… that’s where… that’s where it could go.
168 00:22:04.670 ⇒ 00:22:23.840 Robert Tseng: Yeah, and then a couple other things that I’ll call out here. I mean, this is just more in-depth on, like, some of the stuff that I’ve mentioned in terms of, like, the wins that we’ve gotten. The risks are kind of the same things that I’ve… just more detail on what I’ve already listed above. Couple other things that came in that were… you guys had asked, and I want to acknowledge, but we didn’t actually get to.
169 00:22:24.000 ⇒ 00:22:42.620 Robert Tseng: You know, one is kind of like, yeah, something around Northbeam, like, wanting to… you want us to go and take a look at, you know, your paid media performance data there, and do some… do some validation from, like, what you’re seeing in Northbeam, and like, you know, basically get to, you know, let you know, like, do you feel like… do we feel like it’s reliable or not? We didn’t actually get to that, so…
170 00:22:42.680 ⇒ 00:22:44.300 Robert Tseng: Yeah, I mean…
171 00:22:44.300 ⇒ 00:22:48.490 Byron Pittam: We’re shutting North Beam down on December 31st anyway, once again, just nobody.
172 00:22:48.490 ⇒ 00:22:49.360 Robert Tseng: Oh, really? Okay.
173 00:22:49.360 ⇒ 00:23:01.029 Byron Pittam: leveraging it anyway. Okay. But yeah, I mean, I think we’ll do a data download of that. I don’t know if it’s worth kind of modeling anywhere else, you know, to pipe in, but yeah, I mean, I think…
174 00:23:01.430 ⇒ 00:23:23.860 Byron Pittam: Yeah, back to kind of your previous slide, like, if, you know, simplifying it to a certain degree, if we’re able to, like, you know, pipe in 8451 data and target marketplace, you know, information, or, you know, Roundel stuff, like, that’s sort of painting that bigger picture, and it’s Acosta. I don’t know why she wouldn’t harvest. She’s very… Megan’s very good about with their names, but it’s Acosta group that it’s… it’s not… not Harvest.
175 00:23:24.160 ⇒ 00:23:24.560 Robert Tseng: Yeah.
176 00:23:24.560 ⇒ 00:23:36.530 Byron Pittam: But but yeah, so, you know, that kind of level of stuff, like, we own those platforms, which is… which is good. Like, we’ve had them set up, you know, inside of our ad groups, as opposed to where we were at with XVaris before, where they…
177 00:23:36.880 ⇒ 00:23:51.439 Byron Pittam: played in their own ad areas, and gave us the data when we wanted it. You know, generally had to beg for it, but, you know, we’ve come a long way in that way, too, where the data is ours, it’s clean. It’s a matter of how…
178 00:23:51.610 ⇒ 00:23:58.549 Byron Pittam: I pull each of those every month, from each of those locations, Walmart Connect, etc. Like, if there’s one.
179 00:23:58.550 ⇒ 00:23:58.940 Robert Tseng: Hmm.
180 00:23:58.940 ⇒ 00:24:03.130 Byron Pittam: Pull it all from, then that saves me, you know, 3 hours a month.
181 00:24:03.800 ⇒ 00:24:04.370 Robert Tseng: Yeah.
182 00:24:04.690 ⇒ 00:24:06.139 Robert Tseng: Bah. Okay.
183 00:24:06.450 ⇒ 00:24:07.680 Robert Tseng: Oh, yeah, I think.
184 00:24:07.680 ⇒ 00:24:23.630 Byron Pittam: It’s nice to go into the platforms. I mean, our, you know, Cam, our new ad guy now, our new sponsored search guy, like, he, you know, he’s in there every day, right? So I like to go in there every once in a while just to make sure it’s good, and there aren’t any little, you know, red flags at the top. Target is notorious for that, like…
185 00:24:23.630 ⇒ 00:24:24.150 Robert Tseng: Yeah.
186 00:24:24.150 ⇒ 00:24:27.170 Byron Pittam: We stopped paying you 2 months ago, and you’re like… What?
187 00:24:28.130 ⇒ 00:24:29.730 Byron Pittam: Oh, really? Castle?
188 00:24:29.730 ⇒ 00:24:30.200 Robert Tseng: Yeah.
189 00:24:30.200 ⇒ 00:24:35.060 Byron Pittam: Yeah, the, but yeah, I mean, I think, once again, anything… yeah.
190 00:24:35.230 ⇒ 00:24:40.179 Byron Pittam: we can get to that again, too, but, like, if there’s any way to pipe that stuff into Looker, that’d be huge.
191 00:24:40.620 ⇒ 00:24:41.210 Robert Tseng: Okay.
192 00:24:41.590 ⇒ 00:24:51.280 Robert Tseng: Yeah, I mean, it sounds like, you know, just being able to get all the stuff into one place is, like, helpful for you. I mean, and we want to do… so, I guess if,
193 00:24:52.290 ⇒ 00:24:57.549 Robert Tseng: So, I guess there are a couple of solutions there. So, obviously, we can, we can talk to,
194 00:24:57.900 ⇒ 00:25:07.610 Robert Tseng: to grain and see, like, what actually… like, can we just do the modeling, and then they just, like, kind of… they just… they just would just store it in their warehouse, and they plug it in? If not, and, like.
195 00:25:08.030 ⇒ 00:25:13.789 Robert Tseng: I don’t know, like, they just… like, I don’t know what… how… how they… how they work, but…
196 00:25:13.900 ⇒ 00:25:21.269 Robert Tseng: I mean, all the platforms that you name, they have connectors out there. Like, we’re not building anything net new, unless you’re using some, like, obscure, like.
197 00:25:21.270 ⇒ 00:25:40.540 Robert Tseng: affiliate channel or something. Like, yeah, so I… I think it’s… it’s all pretty quick to do, so we just have to define, like, what are the last… what are the ones that we want to… we want to bring into the reporting. Like, I could tell you exactly how we would… how to do it, and, like, it’s, you know, it’s just a matter of, like, whether or not the
198 00:25:40.700 ⇒ 00:25:46.870 Robert Tseng: since they maintain the warehouse of BigQuery, like, you know, if they’re gonna let us just dump it in there or not.
199 00:25:47.380 ⇒ 00:25:47.920 Byron Pittam: Yup.
200 00:25:48.480 ⇒ 00:25:49.000 Robert Tseng: Okay.
201 00:25:49.000 ⇒ 00:25:54.319 Byron Pittam: Once again, if it’s a one-time fee to make the connection, then it’s worth it, you know?
202 00:25:54.320 ⇒ 00:26:03.519 Robert Tseng: Yeah, sure. Yeah, they’ve never been ticky-tacky with us in the past. Okay. I just think it’s out of Megan’s… as soon as it leaves and goes into the data.
203 00:26:03.520 ⇒ 00:26:06.690 Byron Pittam: the data realm in… in… in grain, like Megan.
204 00:26:06.690 ⇒ 00:26:07.190 Robert Tseng: Yeah.
205 00:26:07.190 ⇒ 00:26:14.610 Byron Pittam: can’t help us out. And I’ve… I’ve asked for a lot of things that I know aren’t in our scope of work, but what’s the harm in asking? Yeah.
206 00:26:15.730 ⇒ 00:26:16.280 Robert Tseng: Okay.
207 00:26:16.750 ⇒ 00:26:31.499 Robert Tseng: Yeah, I mean, I think one, like, pricing nuance would just be, like, I think sometimes with… I mean, obviously, we’ve run into this situation before, so sometimes they bill by connector, and it’s like, okay, like, they’ll… every source that you connect, they want to charge you something for it.
208 00:26:31.500 ⇒ 00:26:32.080 Byron Pittam: Yep.
209 00:26:32.570 ⇒ 00:26:49.899 Robert Tseng: Otherwise, like, you just… if they… if they just set up one connector to, like, a warehouse that we maintain, like, obviously, like, what we’re… I think we haven’t… I don’t think we showed you the bill, but, like, you know, your… your warehousing fees are, like, you know, under $100 or whatever a month, so it’s… it’s… warehouse is, like, very, very cheap. It’s…
210 00:26:49.900 ⇒ 00:26:52.650 Robert Tseng: relatively cheap, so, like, that’s, like, a way to…
211 00:26:52.650 ⇒ 00:26:58.370 Byron Pittam: Like, I’d rather give grain 50 bucks a month for a warehouse they’re already maintaining, right?
212 00:26:58.370 ⇒ 00:26:58.980 Robert Tseng: Yeah.
213 00:26:58.980 ⇒ 00:27:02.040 Byron Pittam: As opposed to having data in two different places all of a sudden.
214 00:27:02.040 ⇒ 00:27:06.819 Robert Tseng: Okay, yeah, well, so I’m just… yeah, I’m selling, like, that’s how cheap it should be, so, like, I don’t know how much they’re gonna.
215 00:27:06.820 ⇒ 00:27:08.050 Byron Pittam: Totally, totally, totally.
216 00:27:08.780 ⇒ 00:27:09.510 Robert Tseng: Yeah.
217 00:27:10.280 ⇒ 00:27:12.530 Robert Tseng: Okay. Yeah, like, even dig…
218 00:27:12.530 ⇒ 00:27:14.260 Byron Pittam: Excel spreadsheets aren’t, aren’t heavy.
219 00:27:14.760 ⇒ 00:27:16.100 Robert Tseng: Yeah, exactly.
220 00:27:16.990 ⇒ 00:27:21.380 Robert Tseng: It only gets heavy when you start having a bunch of text data, so, like.
221 00:27:21.900 ⇒ 00:27:26.739 Robert Tseng: Phone transcripts, customer service centers, like, when we’re doing stuff with those types of
222 00:27:26.880 ⇒ 00:27:31.690 Robert Tseng: kind of teams, then… then the bill gets up pretty high. Yeah. Yeah. Yeah.
223 00:27:31.850 ⇒ 00:27:35.149 Robert Tseng: But otherwise, structured transactional data is very, very cheap to store.
224 00:27:35.410 ⇒ 00:27:37.090 Robert Tseng: Okay.
225 00:27:37.150 ⇒ 00:27:40.200 Robert Tseng: I know I’m just kind of breezing through some of this stuff,
226 00:27:40.250 ⇒ 00:27:51.009 Robert Tseng: Yeah, and then, like, we had… you had asked about, like, wholesale strategy before, so, like, I didn’t… I didn’t, like, put together one specifically for… for your team, because, like, I didn’t actually meet with your wholesale guy.
227 00:27:51.010 ⇒ 00:28:15.260 Robert Tseng: But I thought it could be helpful to just share, like, another kind of just, like, way that we’ve thought about wholesale with another… with another client. So, this is just, like, a cut and paste of, like, a part of a slide that I had made for… for another client. So, you can kind of say, I mean, I tried to pick one that was, like, somewhat in your camp. They’re mostly Shopify native, but then, they invest a lot in wholesale in a similar segment as well, you know, going after, like.
228 00:28:15.420 ⇒ 00:28:35.080 Robert Tseng: you know, these health nuts, or kind of gyms and stuff as well. So, yeah, I mean, they, over the past two years, scaled from 200 to 13,000 partners, and, you know, our main… they brought us on to really build, like, a five-year channel growth plan for them in wholesale, because they basically felt like their wholesale growth kind of, like, capped out.
229 00:28:35.080 ⇒ 00:28:42.179 Robert Tseng: And their team’s feeling overwhelmed, they didn’t really know, like, what they needed to do, in order to, like, like, you know.
230 00:28:42.180 ⇒ 00:28:45.220 Robert Tseng: How many people do they hire? Like, is wholesale a channel that’s…
231 00:28:45.220 ⇒ 00:29:07.099 Robert Tseng: are the unit economics just gonna keep dropping because, like, I don’t know, maybe they’re already oversaturated in that channel. What’s the relationship between wholesale and… is it cannibalizing on, like, other types… on the other channels? Kind of similar questions that you were asking… you were asking us. And so, we’ve gone into the nitty-gritty with them, and basically, like, you know, what they’ve… well, over the past two years, because wholesale kind of blew up so much.
232 00:29:07.100 ⇒ 00:29:21.890 Robert Tseng: like, they realized that they weren’t able to trace, kind of, like, their wholesale partners across, like, different accounts, even as people kind of moved to different accounts, and even in their own labeling, like, because they were using Shopify tags to do all this labeling, and they basically couldn’t match, like, you know.
233 00:29:22.130 ⇒ 00:29:29.209 Robert Tseng: close to 90% of their, of their, of their partners. So, like, just a lot of guesswork, two people, like.
234 00:29:29.210 ⇒ 00:29:43.520 Robert Tseng: every day just keying in a bunch of stuff into Google… in spreadsheets to try to, like, stitch together the data. So this was just spending hours… hours for them, kind of maintaining, like, a really bloated Google Sheet to maintain, to manage all of their partners.
235 00:29:43.950 ⇒ 00:29:51.929 Robert Tseng: And so, you know, we’re kind of in this phase with them now, where, like, you know, we’ve landed everything to a data warehouse, we know all the data sources.
236 00:29:51.970 ⇒ 00:30:03.449 Robert Tseng: Yeah, a lot of the same stuff that we were telling you, but really, like, I think what they wanted is, like, a way to have flexible logic so that they could easily reclassify historical orders to the right partners.
237 00:30:03.470 ⇒ 00:30:12.490 Robert Tseng: For example, like, they started off with 3 segments only, like, health, buyer, like, specialty retail, bulk, or actually, they weren’t even in specialty retail before.
238 00:30:12.490 ⇒ 00:30:31.120 Robert Tseng: They were just, like, in health and bulk buyers. Then they opened up specialty retail, and they need to migrate a bunch of accounts from Trusted Health into specialty retail, create different incentives around there. And so, like, the cutover from, like, one segment to a new segment that they were spinning up, like, that was not… that was a very messy process for them.
239 00:30:31.180 ⇒ 00:30:46.880 Robert Tseng: And they imagine that they’re gonna keep splitting these more and more. And so, like, I think now they’re up to, like, about 5 distinct segments now, other than the 3, and so, like, that’s… that’s been something that they had a hard time keeping up with. So, we kind of were… we’re basically working on that problem for them right now.
240 00:30:47.120 ⇒ 00:30:55.429 Robert Tseng: And then, like, the future state that I see is kind of like, okay, look, they’re, like, doing all these interesting, like, co-bundling things now that you’re in the wholesale world.
241 00:30:55.470 ⇒ 00:31:08.399 Robert Tseng: you know, your wholesale partners will start to bundle your products with other things to try to, like, you know, if they try to send packages. And so, yeah, they’re just trying to, you know, they have a… that’s… that’s more kind of, like, of a strategic, kind of.
242 00:31:08.400 ⇒ 00:31:22.720 Robert Tseng: analysis that they want to know, like, what are the best pairings to really unlock more revenue for them, within their wholesale network. And then also, like, yeah, they just want to look at reorder cycles, like.
243 00:31:22.730 ⇒ 00:31:41.109 Robert Tseng: you know, be able to better forecast demand better, like, you know, obviously, because you’re buying, selling a bunch of product all at once, you don’t really have the clearest, like, visibility into the sell-through of your wholesale partner, and… but they do have, like, you know, a bunch of disparate data points everywhere, so being able to collate all of that together, so…
244 00:31:41.110 ⇒ 00:31:46.449 Robert Tseng: And then obviously, like, the… the hiring plan for them over the next… the next 5 years. So…
245 00:31:46.450 ⇒ 00:32:01.350 Robert Tseng: Yeah, I mean, this is kind of, like, you know, more of, like, a hefty project that we’re working on. Like, I have basically… I’m spending a good chunk of my time on this project, and I have two other people on it with me. So anyway, like, this is, you know, you had asked, like.
246 00:32:01.350 ⇒ 00:32:12.880 Robert Tseng: a couple times… a couple weeks ago about kind of, like, what we could do with you on wholesale. And so, like, I think this is kind of, like, a good, like, you know, intro to, like, what I… what I think we could… we could bring to the table.
247 00:32:13.610 ⇒ 00:32:30.780 Byron Pittam: Yeah, Dan, with your knowledge of NetSuite, would you be able to kind of pull some of those, like, you know, the customer classes that we have in there that we think make the most sense to go through? You know, maybe orders under 5,000, or something like that, where we can kind of
248 00:32:30.780 ⇒ 00:32:42.760 Byron Pittam: be like, hey, these, these, you know, 10,000 accounts make a lot of sense to put on B2B. We could cross-reference who’s already in there, the, you know, we have a similar number, 1,300 or 2,000 accounts we have already in there. Yeah.
249 00:32:42.900 ⇒ 00:32:51.870 Byron Pittam: And then, yeah, kind of push… push that way. I mean, Robert, to your point, too, like, we have… we started the opposite way, and I think we have, like, 15 or 16 tags of type of customer.
250 00:32:51.870 ⇒ 00:32:54.230 Robert Tseng: Oh, I know you’re just trying to…
251 00:32:54.230 ⇒ 00:33:01.860 Byron Pittam: I think it makes a lot of sense to go the other way. We can kind of push them into 5 or 6 categories, because that’s how we report up at a top line to.
252 00:33:01.860 ⇒ 00:33:02.440 Robert Tseng: Yeah.
253 00:33:02.620 ⇒ 00:33:05.269 Byron Pittam: To, you know, to our leadership team.
254 00:33:05.570 ⇒ 00:33:20.570 Byron Pittam: But yeah, I mean, inside of specialty, distinctly, you mentioned that too, like, you know, there is run, there is bike, there is, you know, swimming, stuff like that, too. So, you know, do we need that level of differentiation? Probably not. They’re gonna eat waffles, or chews.
255 00:33:22.630 ⇒ 00:33:28.759 Byron Pittam: It’s not like we’re giving them different packaging based on what, you know, different type of goggle. Yeah.
256 00:33:28.900 ⇒ 00:33:34.590 Byron Pittam: But yeah, no, I think, you know, Dan, as you get closer with Cody, too, we can talk… we can talk with him about what that…
257 00:33:34.630 ⇒ 00:33:52.610 Byron Pittam: how we can help him better, just to optimize all this stuff, because it is, yeah, just an underserved channel, and, you know, as you and I were talking about yesterday, it’s like, I really want… you know, we’re spending a lot, Robert, on a bunch of different apps and stuff like that, too, in the wholesale channel, and I’m like, if we’re not using it, like, turn it off. Like, it’s like.
258 00:33:52.610 ⇒ 00:33:53.030 Robert Tseng: Yeah.
259 00:33:53.030 ⇒ 00:33:55.390 Byron Pittam: We don’t… yeah, so there’s… there’s…
260 00:33:55.520 ⇒ 00:34:05.339 Byron Pittam: still some optimizations from the, yeah, from an easy level before we even get into the final outcome here, the steps. But, yeah. Yeah.
261 00:34:05.430 ⇒ 00:34:17.040 Byron Pittam: let us continue to have that conversation internally, and yeah, Dan, I think this might be a good time after, kind of, Nut Butter Waffle launch, just to be like, hey, how do we get some of these new customers through the, you know, through the portal?
262 00:34:17.280 ⇒ 00:34:29.170 Dan Buri: Yeah, and I talked with Cody a little bit about that yesterday, and about kind of how we can work together to target those customers a little bit differently and more effectively, and yeah, in terms of the NetSuite piece, if you wanted to…
263 00:34:29.510 ⇒ 00:34:35.769 Dan Buri: If we wanted to kind of, you know, put together some parameters, I can pull whatever we need from NetSuite, yeah.
264 00:34:36.380 ⇒ 00:34:37.060 Byron Pittam: Cool.
265 00:34:38.230 ⇒ 00:34:45.189 Robert Tseng: Yeah, I mean, if you… I mean, whatever you’re willing to send over, I can… I can take a look at, and, yeah, like, I… we can at least…
266 00:34:45.570 ⇒ 00:34:52.219 Robert Tseng: kind of whiteboard some of this… some of this out. But yeah, I do think this is, you know.
267 00:34:52.310 ⇒ 00:35:10.509 Robert Tseng: But hopefully this good picture. And then, like, on the partnership side, I kind of did a… this is more kind of this example, more fleshed out with a separate client as well. So, you know, tried to, like, make this a little bit clearer of, like, how people move through these different stages, but I won’t kind of belabor that point.
268 00:35:10.510 ⇒ 00:35:15.280 Robert Tseng: Yeah, so I’ll shoot this deck over to you. I don’t…
269 00:35:15.930 ⇒ 00:35:22.649 Robert Tseng: see if anybody else on my team wants to give a couple reviews before I brush that over, so I’ll just do it after the call.
270 00:35:22.650 ⇒ 00:35:28.660 Byron Pittam: Make sure, Robert, use that banana at the bottom to beautify the slide as much as possible. I just, you know, that’s…
271 00:35:28.660 ⇒ 00:35:30.739 Robert Tseng: I actually never click this button, I don’t know what it does.
272 00:35:30.740 ⇒ 00:35:34.309 Byron Pittam: Oh my god, no, we are in for it.
273 00:35:34.970 ⇒ 00:35:36.640 Byron Pittam: Oh man, banana.
274 00:35:38.610 ⇒ 00:35:44.489 Byron Pittam: I’m not really sure what that’s supposed to be. I think it’s, like, probably confused on what to do with everything that I have.
275 00:35:44.800 ⇒ 00:35:47.159 Byron Pittam: You just broke, you broke the system too much.
276 00:35:47.760 ⇒ 00:35:48.140 Robert Tseng: Yeah.
277 00:35:48.140 ⇒ 00:35:52.129 Byron Pittam: It’s gonna say, it’s gonna say delete and restart.
278 00:35:52.130 ⇒ 00:35:54.880 Robert Tseng: Okay, well, while that one’s loading, I’ll send you.
279 00:35:54.880 ⇒ 00:35:55.690 Byron Pittam: No, I’ll be…
280 00:35:55.690 ⇒ 00:36:01.909 Robert Tseng: that, yeah, I guess, like, a couple of the follow-ups that Amber wanted me to go through.
281 00:36:02.160 ⇒ 00:36:11.460 Robert Tseng: So yeah, I think we dug into some of these specific segments, so, I think the most interesting takeaway to me is, like, once we split out ambassador and non-ambassador.
282 00:36:11.510 ⇒ 00:36:22.270 Robert Tseng: Yeah, I mean, obviously, Ambassadors are purchasing more, but actually the LTV is, like, more… is… is more compressed. And so, she had a couple questions here. I think this could be interesting on, like.
283 00:36:22.530 ⇒ 00:36:34.849 Robert Tseng: you know, I’m… yeah, I guess, you know, 70… they’re about 8% of your customers, driving 70% of total orders, but yeah, like, I guess what’s not captured here is, like, how does…
284 00:36:35.210 ⇒ 00:36:50.169 Robert Tseng: Yeah, I mean, you’re… we’re comparing ambassador to non-ambassadors, but, like, are ambassadors kind of a growth driver for, like, your customers as well, and, like, what does that look like? Having ambassadors, does it, you know, how many… how many more? Yeah, anyway, so, like, I…
285 00:36:50.170 ⇒ 00:37:13.300 Byron Pittam: They definitely drive trial, but yeah, it’s a squishy number, right? Like, it’s like… it’s marketing 101, like, how do you… how do you back into that? But yeah, I think that our ambassador team, this is a good stat, Dan, to take to Sean as well. Absolutely. Like, we have what we think is 12,000 to 15,000 people on the ambassador team.
286 00:37:13.300 ⇒ 00:37:30.549 Byron Pittam: if only 7,000 are ordering, like, we got a little bit of a problem there, figuring out where, you know, where the bloat is, and what those other people are doing for us, right? I mean, it’s a reciprocal relationship, hopefully both sides are winning, but it seems like, you know, we’re… I’m unclear about what
287 00:37:30.550 ⇒ 00:37:33.439 Byron Pittam: 5 to 6K of the ambassadors are doing for us.
288 00:37:34.380 ⇒ 00:37:46.089 Dan Buri: Yeah, yeah, and I think that those questions right there are super relevant questions, right? Those are kind of the things that I want to get at as well, and this is the kind of information that’ll help us answer that. So, so yeah, this is awesome takeaway.
289 00:37:47.490 ⇒ 00:37:53.340 Robert Tseng: Great. And then on this one, we were also looking… we kind of rebuilt these cohorts a bit, I think, so…
290 00:37:53.410 ⇒ 00:38:11.209 Robert Tseng: I think Dan had asked specifically for discount acquired, had fully priced reorders, like, I think we just split this multi-purchase thing out a little bit more. So, by 20.2% of always buyers were ambassadors, so that’s, like, you know, that’s almost half of them.
291 00:38:11.270 ⇒ 00:38:18.860 Robert Tseng: And… yeah, well, that still means that, like, yeah, like, you know, half…
292 00:38:19.250 ⇒ 00:38:25.059 Robert Tseng: Yeah. Are you saying that that… so, 22% of that 14.6K, or 22% of the total?
293 00:38:25.190 ⇒ 00:38:28.239 Dan Buri: We’re ambassadors, because, yeah.
294 00:38:28.240 ⇒ 00:38:32.409 Robert Tseng: of the total, yeah. Of that 14, okay, great. Yeah. Yeah.
295 00:38:32.790 ⇒ 00:38:33.900 Dan Buri: No, that makes sense.
296 00:38:34.350 ⇒ 00:38:34.950 Robert Tseng: Yeah.
297 00:38:35.080 ⇒ 00:38:37.640 Robert Tseng: And then,
298 00:38:39.970 ⇒ 00:38:57.619 Robert Tseng: Yeah, I think, yeah, this is… this is the subscription that… yeah, 20… 20… yeah, what we’re saying, okay, well, people who are always paying full price, like, are they… are they subscribed? Well, it’s, yeah, it’s, like, more than 20% of them are… are, are, are subs… they’re… these are… these are all mostly subscription… subscription customers, so,
299 00:38:58.600 ⇒ 00:39:00.519 Robert Tseng: Yeah. Whereas, like…
300 00:39:01.120 ⇒ 00:39:16.549 Robert Tseng: of the ambassador… the ambassadors are only really… I mean, they’re all obviously discount-driven, you know, the ones that are paying full price, they’re not ambassadors, but yeah, whoever this is, great. I mean, they’re just… they’re subscribed, they’re paying full price, like, I mean, that… that sounds… that sounds like a good…
301 00:39:16.550 ⇒ 00:39:19.350 Byron Pittam: They’re getting their 15-ish percent off, and free shipping.
302 00:39:19.350 ⇒ 00:39:19.750 Robert Tseng: Yeah, individually.
303 00:39:19.750 ⇒ 00:39:22.350 Byron Pittam: They’re getting… they’re getting a perk in there, yeah.
304 00:39:22.510 ⇒ 00:39:35.119 Byron Pittam: But Dan, I mean, that’s a good, good potential, you know, movement, too. It’s like, do we give ambassadors a bigger, you know, incentive to… to subscribe? Just to keep them consistently getting a box and… and doing that stuff, like…
305 00:39:35.170 ⇒ 00:39:39.190 Dan Buri: Yeah, kind of flatten out that, that, you know, calendar in terms of sales, right?
306 00:39:39.190 ⇒ 00:39:51.800 Byron Pittam: But give them just… they know the quarterly code’s coming, and then instead of, like, having them actually have to click through and use the quarterly code, it’s like, hey, here’s your quarterly subscription box, you know, code. And have it stack well with Recharge.
307 00:39:52.400 ⇒ 00:39:54.040 Dan Buri: Yeah. Yep.
308 00:39:55.310 ⇒ 00:40:13.230 Robert Tseng: Yeah, so, I mean, obviously the naming for these cohorts could be refined, but, like, to me, this is, like, once we kind of keep iterating, and we’re good with these different cohorts, then, yeah, this would go into, you know, your Klaviyo, and you’d be able to do some specific, like, targeting for them, or, yeah, I mean, like, it’s just like a…
309 00:40:13.230 ⇒ 00:40:23.859 Robert Tseng: I mean, I would like to see how we can bring this level of customer segmentation into the way that you… you’re… you’re targeting your customers, right?
310 00:40:24.630 ⇒ 00:40:25.980 Dan Buri: Yeah, absolutely.
311 00:40:27.000 ⇒ 00:40:34.740 Robert Tseng: Okay, cool. Well, I think, actually, Byron probably has this lane, because I see him hovering around here, so I think she just continued on this deck.
312 00:40:34.740 ⇒ 00:40:39.879 Byron Pittam: I just want to make sure we have the Amazon, wherever that Amazon and subscription combo.
313 00:40:40.230 ⇒ 00:40:50.520 Robert Tseng: Yeah, I think that might have just been, like, a one-off thing on a separate deck, so I’ll go… I’ll go find that for you. It’s… I don’t really… I think this is purely Shopify, so… and we had one that was purely…
314 00:40:50.520 ⇒ 00:40:58.620 Byron Pittam: Amazon numbers are just nuts. They just don’t… they don’t make sense, right? Like, the number of subscribers and revenue we’re getting is… is bonkers.
315 00:40:58.830 ⇒ 00:40:59.450 Robert Tseng: Yeah.
316 00:41:01.180 ⇒ 00:41:10.270 Robert Tseng: Okay, great. Well, yeah, I mean, you guys have this. If you have any other questions on this, especially as you’re… if you’re sharing this around internally, you just want a kind of quick check on anything, just, like, let us know. We can…
317 00:41:10.420 ⇒ 00:41:15.020 Robert Tseng: Yeah, I mean, we can clarify anything here.
318 00:41:16.160 ⇒ 00:41:22.010 Robert Tseng: Yeah, otherwise, like, yeah, I guess, Dan, why maybe we set up… set up some time, to chat through…
319 00:41:23.060 ⇒ 00:41:25.499 Robert Tseng: What we were discussing earlier in the call.
320 00:41:25.960 ⇒ 00:41:26.760 Byron Pittam: The flows.
321 00:41:28.330 ⇒ 00:41:35.469 Dan Buri: No, that sounds good, I’d be happy to walk you through that. So, yeah, I’ll be… I don’t know, what does your schedule look like? Because, I’m going to be…
322 00:41:35.710 ⇒ 00:41:41.500 Dan Buri: out a good chunk of the next 2 weeks, but, I will be in on the 24th, if you’re around.
323 00:41:41.500 ⇒ 00:41:42.470 Robert Tseng: January 24th, yeah.
324 00:41:42.470 ⇒ 00:41:46.900 Dan Buri: Let’s do that. Yeah, I’m pretty wide open, I believe, on the 24th, so, yeah.
325 00:41:46.900 ⇒ 00:41:50.669 Robert Tseng: Okay, then let’s do…
326 00:41:56.610 ⇒ 00:42:03.380 Robert Tseng: Can you do, like, 9… AM, Pacific.
327 00:42:04.570 ⇒ 00:42:09.869 Dan Buri: Okay, yeah, I believe so. 9am… yeah, that should work.
328 00:42:09.870 ⇒ 00:42:11.610 Robert Tseng: That would be, like, a year 11, right?
329 00:42:12.030 ⇒ 00:42:15.250 Robert Tseng: That’d be 10 for me, but… Okay, okay. Is that okay? Alright.
330 00:42:15.920 ⇒ 00:42:18.350 Dan Buri: Sounds good, yeah, send an invite and we’ll make it happen.
331 00:42:18.900 ⇒ 00:42:21.159 Robert Tseng: Yeah, I’ll just do that now.
332 00:42:21.390 ⇒ 00:42:27.080 Robert Tseng: And… Doop, doot, oh, I don’t have your email saved.
333 00:42:29.970 ⇒ 00:42:30.760 Robert Tseng: It’s just…
334 00:42:30.760 ⇒ 00:42:32.730 Dan Buri: It’s D-B-U-R-I.
335 00:42:33.600 ⇒ 00:42:36.170 Robert Tseng: D-B-U-R-I.
336 00:42:36.170 ⇒ 00:42:41.139 Dan Buri: Correct. Oh, there we go. I know, I love how that doesn’t pop up until you get most of the way through, and it’s…
337 00:42:43.590 ⇒ 00:42:44.300 Robert Tseng: Okay.
338 00:42:44.520 ⇒ 00:42:45.300 Robert Tseng: Whoa.
339 00:42:45.960 ⇒ 00:42:49.000 Robert Tseng: That is very about right.
340 00:42:51.260 ⇒ 00:42:53.580 Robert Tseng: Bicycle closed.
341 00:43:06.610 ⇒ 00:43:07.600 Robert Tseng: Alright.
342 00:43:08.520 ⇒ 00:43:13.320 Robert Tseng: Okay, so that’s, that’s all I got. Anything else, from you guys?
343 00:43:15.310 ⇒ 00:43:16.340 Byron Pittam: No? Yeah, I mean…
344 00:43:16.340 ⇒ 00:43:16.710 Dan Buri: ridiculous.
345 00:43:16.710 ⇒ 00:43:20.129 Byron Pittam: Anything else, yeah, you need direction from us, let us know too.
346 00:43:20.450 ⇒ 00:43:21.920 Robert Tseng: Okay, sounds good.
347 00:43:22.330 ⇒ 00:43:23.100 Byron Pittam: Thanks, dude.
348 00:43:23.470 ⇒ 00:43:24.470 Robert Tseng: Have a good weekend.
349 00:43:24.470 ⇒ 00:43:25.399 Byron Pittam: You too. Bye.
350 00:43:25.400 ⇒ 00:43:25.930 Robert Tseng: Right.
351 00:43:26.130 ⇒ 00:43:26.830 Dan Buri: Yep.