Meeting Title: Customer Journey Data Review Sync Date: 2025-11-17 Meeting participants: Robert Tseng, birdiejackson, Amrita D
WEBVTT
1 00:01:46.510 ⇒ 00:01:47.750 birdiejackson: Hey, Robert.
2 00:01:50.360 ⇒ 00:01:51.140 Robert Tseng: Hey, birdie.
3 00:01:51.530 ⇒ 00:01:52.520 birdiejackson: How are you?
4 00:01:53.100 ⇒ 00:01:54.890 Robert Tseng: How are you? Long time, no see.
5 00:01:55.280 ⇒ 00:02:01.180 birdiejackson: I know, it’s been so long. I had a call with… how does he pronounce his name? Is it Utem, or…
6 00:02:01.360 ⇒ 00:02:03.199 birdiejackson: Ur… how do you… how do you say his name?
7 00:02:03.200 ⇒ 00:02:05.990 Robert Tseng: I… I don’t… I think I still butcher it.
8 00:02:05.990 ⇒ 00:02:06.460 birdiejackson: Okay.
9 00:02:06.460 ⇒ 00:02:15.589 Robert Tseng: I think what I’ve heard is Utem. UTM, okay. I had a call with Utem, last week, and… Yeah.
10 00:02:15.589 ⇒ 00:02:17.779 birdiejackson: somebody else, who I can’t remember, but…
11 00:02:17.780 ⇒ 00:02:18.540 Robert Tseng: Yeah, Amber.
12 00:02:18.540 ⇒ 00:02:20.900 birdiejackson: Oh my gosh, I haven’t seen… I haven’t seen you guys.
13 00:02:23.310 ⇒ 00:02:25.930 birdiejackson: So yeah, it looks like Amrita’s joining.
14 00:02:26.930 ⇒ 00:02:32.880 Robert Tseng: Yeah, sorry, I use Zoom if I… when I can, so I can get transcripts, because I never get them when we use tapes.
15 00:02:33.010 ⇒ 00:02:34.920 birdiejackson: No worries, I totally understand.
16 00:02:34.920 ⇒ 00:02:35.470 Robert Tseng: Oh, yeah.
17 00:02:35.850 ⇒ 00:02:37.270 birdiejackson: Hello!
18 00:02:38.360 ⇒ 00:02:39.340 Robert Tseng: Hey, Marita.
19 00:02:41.130 ⇒ 00:02:42.230 Amrita D: Hurry, guys.
20 00:02:42.990 ⇒ 00:02:44.439 Robert Tseng: Doing well, how are you?
21 00:02:44.910 ⇒ 00:02:45.710 Amrita D: Okay.
22 00:02:47.940 ⇒ 00:02:48.570 Robert Tseng: Yeah.
23 00:02:50.310 ⇒ 00:03:02.720 Robert Tseng: Well, I guess, I know we haven’t checked in, all three of us, on a call in a couple weeks, so, I mean, since then, we’ve shared a couple decks out. I think maybe we’ll just do the review for the most recent one, and then if we have time, we’ll kind of…
24 00:03:02.840 ⇒ 00:03:09.460 Robert Tseng: step backwards, that’s helpful, so I’m just gonna share my screen.
25 00:03:10.130 ⇒ 00:03:23.009 Robert Tseng: Yeah, so this is the one we sent out on Friday. I guess, like, the question here, you know, we’re still kind of in lifecycle land, kind of trying to better understand, okay, from the data that we do have access to, like, what can we tell about the customer journey?
26 00:03:23.010 ⇒ 00:03:32.259 Robert Tseng: maybe some of these things you already know, maybe just confirming intuition. But I’m assuming that you’ve kind of looked through the deck, so I’m not going to go through it line by line.
27 00:03:32.270 ⇒ 00:03:34.109 Robert Tseng: You know, there’s this…
28 00:03:34.300 ⇒ 00:03:48.670 Robert Tseng: especially as we’re thinking… and I’m not trying to reinvent customer segments right now, that’s not the goal of this, but obviously RFM kind of is a little bit nebulous, and so just thinking through, okay, well, you know, when you’re looking at, like, repeat purchases, like.
29 00:03:48.670 ⇒ 00:04:02.829 Robert Tseng: how, you know, when customers make that first order, only 20% of them come back to make that second purchase. Then after that, that seems to, you know, there’s a huge jump there, and it kind of flattens out afterwards. So, seems like after the fourth… the fourth cookie, like.
30 00:04:02.830 ⇒ 00:04:22.679 Robert Tseng: you know, more than half your customers are continuing to purchase more and more cookies, or more orders. So, it seems like that second… that second cookie and that fourth… I could call it cookie… second order and fourth order, kind of, stages are… are significant, and probably worth, kind of, like, drilling into more.
31 00:04:22.680 ⇒ 00:04:33.899 Robert Tseng: In terms of, like, how we can specifically target those people to get, like, the first-time customer into the second… second-time purchaser, and then also, like, at that fourth… that fourth order milestone.
32 00:04:33.900 ⇒ 00:04:38.790 birdiejackson: Saying that the… from the first order, To the second order.
33 00:04:39.600 ⇒ 00:04:43.250 birdiejackson: You’re… we’re only having 20… how many per… what’s the percentage of people.
34 00:04:43.250 ⇒ 00:04:45.100 Robert Tseng: 28%, yeah.
35 00:04:47.310 ⇒ 00:04:51.329 Amrita D: That’s consistent with some things that, do I have a weird filter on?
36 00:04:51.740 ⇒ 00:04:52.919 Robert Tseng: It’s a blur.
37 00:04:52.920 ⇒ 00:05:03.410 Amrita D: Okay. But that’s consistent with what, Rob, our finance VP, has told me before. Not the exact percentage, but getting 1 to 2 is the hardest.
38 00:05:04.200 ⇒ 00:05:08.970 Robert Tseng: Right. Yeah, so that seems like that’s the most useless lease in that 1 to 2.
39 00:05:09.170 ⇒ 00:05:22.539 Robert Tseng: And then there’s also kind of, like, that jump after four orders, you know, that, that, you know, more than half of them are continuing to come back. So, like, that seems like another milestone moment, if we’re kind of thinking through milestones in the customer journey.
40 00:05:23.450 ⇒ 00:05:29.670 birdiejackson: And then also 2 to 3, like, the second to third order, that seems to be a significant jump, if I’m looking at this correctly.
41 00:05:29.950 ⇒ 00:05:38.070 Robert Tseng: Yeah, well, I guess to me, yeah, I mean, that’s right. So 2, 3, and 4 are probably these big, big jumps. I mean, the 2 to 3 makes sense to me, it’s like…
42 00:05:38.520 ⇒ 00:05:53.110 Robert Tseng: all those who, like, pretty much just buy at one time, they never come back again, are not really gonna be… they’re kind of excluded, so that… that completely changes the… the dynamic, but yeah, I guess 2, 3, 4, kind of these… these milestones, if you want to think about it that way.
43 00:05:53.380 ⇒ 00:05:59.530 Amrita D: And the data you looked at was the praise data only, so really about purchases on e-comm?
44 00:06:00.630 ⇒ 00:06:16.249 Robert Tseng: Yes, just e-com purchases. We cross-referenced with transaction data, which is in aggregate, it’s not at the customer level, but we did check it, against what we… some stuff that we have in Holistics as well.
45 00:06:16.800 ⇒ 00:06:21.869 Robert Tseng: Yeah, just to see if it was directionally kind of the same, and I think it’s… it is, so…
46 00:06:21.870 ⇒ 00:06:36.029 birdiejackson: So what does that say about… like, I’m trying to understand specifically the first to second order. Like, to me, that’s an experience issue. Like, that’s someone saying, like, wow, that was… that was not worth… that cookie was not worth the…
47 00:06:36.310 ⇒ 00:06:45.689 birdiejackson: the experience of having to purchase through the app or the website. Is that… are you guys also thinking, seeing that? Or, like.
48 00:06:46.020 ⇒ 00:07:00.600 birdiejackson: Is there any customer behavior that’s, like, sort of indicating why first to second order, and then second to third order, and then maybe they get more comfortable with understanding how the app works, or, like, they know where to go for the promos, they know to look at the email.
49 00:07:00.650 ⇒ 00:07:08.209 birdiejackson: Like, that sort of thing, to then, like, you know, just a higher acceleration of purchasing and repeat customers.
50 00:07:08.690 ⇒ 00:07:20.339 Robert Tseng: Yeah, I guess, you know, that’s obviously a really great and loaded question. We could do a lot more digging into that. I think some of the other slides kind of poke at that, and, like, I think, yeah, as Amrita mentioned, I should just minimize this.
51 00:07:20.490 ⇒ 00:07:24.899 Robert Tseng: Sorry, like, the Zoom window’s blocking my brows.
52 00:07:25.020 ⇒ 00:07:41.789 Robert Tseng: we’re… yeah, we’re excluding FDA, no foot traffic orders, like, we’re not really doing POS systems here, so just purely off the e-comm. So yeah, I think… I do think there’s something about that e-comm experience, but we could look at, like, what are they actually purchasing in that first order versus the second order, right? So…
53 00:07:41.790 ⇒ 00:07:47.389 Robert Tseng: I think… I mean, this is… okay, this is more of, like, kind of, how long does it take them to place that second order?
54 00:07:47.520 ⇒ 00:07:52.300 Robert Tseng: Median time is, like, about a month, a little over a month, so…
55 00:07:52.350 ⇒ 00:08:09.510 Robert Tseng: I mean, I think there’s, you know, maybe there’s something that we can do to… knowing that it’s taking, you know, on average, like, over a month for them to go get that second order, what are some things that we can do to shorten that, right? And so, these are just, like, some really light recommendations. Obviously, you probably have the better ideas here.
56 00:08:09.580 ⇒ 00:08:12.630 Robert Tseng: Of, like, that… what that… that kind of…
57 00:08:12.700 ⇒ 00:08:17.730 Robert Tseng: that sequence looks like between the first and second order. So…
58 00:08:18.280 ⇒ 00:08:19.560 birdiejackson: Whether it’s, like.
59 00:08:19.560 ⇒ 00:08:26.980 Robert Tseng: Remind… if you want to do a top-down perspective, like, kind of reminders based off of the best sellers, you know, and then
60 00:08:27.110 ⇒ 00:08:37.290 Robert Tseng: kind of, you know, keeping it broad, or if we want to do a bottoms-up approach by kind of going after specific segments, of, like, really targeted, offers at… towards
61 00:08:37.320 ⇒ 00:08:45.180 Robert Tseng: customers based on what they ordered in their first purchase, which we can get to that later. So, like, if somebody ordered chocolate chunk cookie, I could tell you, like, what are… what
62 00:08:45.180 ⇒ 00:09:03.819 Robert Tseng: based off of your historical data, like, what the second order typically is, and so you can specifically send out a message to those who purchased the chocolate chunk from their first order to basically be like, oh, you know, maybe these three options are, like, kind of the next one. So that’s what I mean by bottoms up, where we’re really, like, taking what we know about them from their first order, and
63 00:09:03.830 ⇒ 00:09:13.830 Robert Tseng: And, trying to give them a targeted offer, versus the top-down approach, which is just, like, we just look at broadly across the portfolio, we know what the best sellers are.
64 00:09:13.870 ⇒ 00:09:16.370 Robert Tseng: Obviously we have these different, like.
65 00:09:16.530 ⇒ 00:09:29.589 Robert Tseng: holiday or kind of new store opening kind of promotion, like, general promotions that kind of impact all customers. And maybe it’s a mix of both kind of approaches that continues to shorten that.
66 00:09:29.970 ⇒ 00:09:33.419 Robert Tseng: That… that, cycle from the first to the second order.
67 00:09:33.900 ⇒ 00:09:35.160 birdiejackson: Does that make sense?
68 00:09:35.350 ⇒ 00:09:35.960 birdiejackson: Yeah.
69 00:09:36.070 ⇒ 00:09:36.690 birdiejackson: Okay.
70 00:09:36.690 ⇒ 00:09:41.039 Amrita D: Bertie, what are the automations we currently have? It’s just…
71 00:09:41.530 ⇒ 00:09:52.319 Amrita D: getting them to join our loyalty. Like, I know some of the transactional ones, like Abandoned Cart, if we have them at all, do not exist in Braze, because… I asked David about that, he said it was because…
72 00:09:52.820 ⇒ 00:09:58.720 Amrita D: like, the volume of it, like, it… you know how braise we have, what is it, credits or whatever?
73 00:09:58.720 ⇒ 00:10:00.029 birdiejackson: Consumption report, yeah.
74 00:10:00.030 ⇒ 00:10:02.450 Amrita D: consumption. It eats into that, so that’s why…
75 00:10:02.450 ⇒ 00:10:03.080 birdiejackson: Don’t do that.
76 00:10:03.080 ⇒ 00:10:03.730 Amrita D: that way.
77 00:10:03.730 ⇒ 00:10:16.699 birdiejackson: Yeah, so we have retention, basically, like, RFM canvases for, lapsed users, and for…
78 00:10:17.170 ⇒ 00:10:24.769 birdiejackson: Hibernating users, and then we’ve got, like, a welcome series, and then a birthday email to people whose birthday it is.
79 00:10:24.770 ⇒ 00:10:29.909 Amrita D: So the welcome series means they have already bought once, so maybe we need to take a look at that.
80 00:10:29.910 ⇒ 00:10:37.720 birdiejackson: Well, actually, not necessarily. So, pop-up series, it could, if you buy… if you sign up and you buy a cookie, like, the same…
81 00:10:38.150 ⇒ 00:10:39.470 birdiejackson: Within, like, the same.
82 00:10:39.470 ⇒ 00:10:41.680 Amrita D: So it’s welcome to loyalty.
83 00:10:44.250 ⇒ 00:10:55.639 birdiejackson: It would be, yeah, because we don’t have another way for you to, like, per… like, there’s not a capture, and that’s what the acquisition pop-up is for, is, like, to be able to capture a lead to then convert quickly.
84 00:10:55.850 ⇒ 00:10:56.690 birdiejackson: Yeah.
85 00:10:58.110 ⇒ 00:11:05.009 Amrita D: Okay, but they could buy online, having never bought before, and not sign up for loyalty.
86 00:11:05.990 ⇒ 00:11:07.090 birdiejackson: I don’t lie.
87 00:11:07.580 ⇒ 00:11:18.900 birdiejackson: Yes, I believe so. I think the customer… and I can double check, but I believe the customer journey does not require you to create an account to purchase. Like, you can check out as a guest.
88 00:11:19.060 ⇒ 00:11:27.730 birdiejackson: But you would still need to include some form of email to get information about, like, hey, your order’s ready, or your order’s on the way, your order is.
89 00:11:27.730 ⇒ 00:11:28.110 Amrita D: bail.
90 00:11:28.110 ⇒ 00:11:37.820 birdiejackson: here’s your receipt. Is how I understand the purchasing process, at least from the website experience, not app.
91 00:11:39.150 ⇒ 00:11:39.680 Amrita D: Okay.
92 00:11:40.090 ⇒ 00:11:51.890 Robert Tseng: We have a call booked with Matt tomorrow to ask him some loyalty-specific questions, because I was going to ask the same question, and just, like, try to understand, like, what are the different ways that customers can become a loyalty member.
93 00:11:52.910 ⇒ 00:12:05.700 Robert Tseng: Yeah, because I think I had some… I mean, not every analysis makes it into the slides. I think some of them are kind of questionable, so I kind of leave them in our bank until we kind of figure out these details. But, you know, I… you know.
94 00:12:06.040 ⇒ 00:12:08.520 Robert Tseng: I’m hoping he’ll be able to answer that tomorrow.
95 00:12:08.520 ⇒ 00:12:15.830 birdiejackson: It’s actually interesting to me, the… the time between cookie order 1 and 2 and 2 and 3.
96 00:12:16.270 ⇒ 00:12:34.019 birdiejackson: and honestly, 3 and 4, like, this is consistent with the LTO launches that we’ve had, at least in the past year, where it’s like, we have a month that the LTOs are live for, and we’re actually reducing that down to a lifetime of, like, 2 max 3 weeks versus 4 weeks.
97 00:12:34.480 ⇒ 00:12:48.410 birdiejackson: basically, like, a lot of waste at the end of the fourth week, because people lose interest. And we’re also talking… then talking about other things at that point. So I wonder if we will see a shortening of time frame here.
98 00:12:49.010 ⇒ 00:12:52.820 Robert Tseng: That’s interesting. LTO is about…
99 00:12:52.820 ⇒ 00:12:53.990 birdiejackson: Yeah, that’s you.
100 00:12:53.990 ⇒ 00:12:56.680 Robert Tseng: 10% of campaigns, okay.
101 00:12:57.360 ⇒ 00:12:58.260 Robert Tseng: Yeah.
102 00:12:58.830 ⇒ 00:12:59.600 Robert Tseng: Okay.
103 00:13:01.090 ⇒ 00:13:13.509 birdiejackson: And if you think about it outside of own channels, like, for example, for influencers, like, we have influencers, every time there’s an LTO drop, make a video about tasting the cookies, and so, like, that wouldn’t then immediately attribute back to, like.
104 00:13:13.560 ⇒ 00:13:24.920 birdiejackson: an email, like, how we’ve… like, what success looks like in e-com, because maybe they’re going in store, but, like, there are… there are things that are happening outside of just own channels for LTOs as well.
105 00:13:25.450 ⇒ 00:13:26.170 Robert Tseng: Okay.
106 00:13:26.350 ⇒ 00:13:29.370 Robert Tseng: Has that changed for LTOs?
107 00:13:29.480 ⇒ 00:13:32.250 Robert Tseng: Changed? Or been, has that already happened?
108 00:13:33.390 ⇒ 00:13:44.260 birdiejackson: I don’t believe so. Amrita, do you know if Seth’s moved up timeframe? I told Hands Free that it would be a 2026 initiative, because we’ve already had…
109 00:13:45.260 ⇒ 00:13:48.009 Amrita D: Move it to do what? Move them closer together?
110 00:13:48.820 ⇒ 00:13:52.719 birdiejackson: Ltos only living for 2 weeks versus a month.
111 00:13:53.820 ⇒ 00:14:10.369 Robert Tseng: Yeah, because, like, you know, an analysis that we could run is, like, okay, let’s take that LTO example. If we were to compress the timeline, so instead of 4-week campaign, it’s a two-week one, we could model out, like, what does that… how does that impact us? Obviously, we’d have to make some assumptions, but that gives you, like, a…
112 00:14:10.400 ⇒ 00:14:16.990 Robert Tseng: kind of a leading indicator on, like, is that really going to make a difference on this particular view?
113 00:14:18.030 ⇒ 00:14:18.990 Robert Tseng: Yeah, I mean…
114 00:14:18.990 ⇒ 00:14:29.119 birdiejackson: Because I just have a hunch every minute that, like, between order 1, 2, and 3, this is, like, about a month time frame for each of those. 3 and 4 is, like.
115 00:14:29.120 ⇒ 00:14:33.800 Robert Tseng: Yeah, it’s like 3 months before they place their fourth order, is almost, is kind of what I’m reading there.
116 00:14:33.800 ⇒ 00:14:49.799 birdiejackson: So I wonder if that they’re like, oh, there’s a new cookie, like, I want to go try it, because it’s, like, all about the new freshness that we have, like, the new cool flavor. So I’m just… and then after that fourth one, they’re like, oh wait, I actually really… like, insomnia’s, like, my go-to, I’m gonna get…
117 00:14:49.980 ⇒ 00:15:00.150 birdiejackson: if I’m craving a chocolate chip cookie, I’m gonna go and get it from Insomnia, or, you know, they just like our cookies at that point, because that’s what we’re seeing here, was that consistent reorder.
118 00:15:01.740 ⇒ 00:15:02.350 Robert Tseng: Yeah.
119 00:15:02.780 ⇒ 00:15:14.070 Robert Tseng: To also kind of, like, to kind of qualify this a bit more, this is another view we should look at in terms of once we started pushing boxes, that definitely changed, like.
120 00:15:14.370 ⇒ 00:15:24.400 Robert Tseng: proportion of the purchase behavior here. So, I mean, it looks like boxes were actively pushed, kind of like, you know, Q1 of this year.
121 00:15:24.520 ⇒ 00:15:29.120 Robert Tseng: So, as far as, like, the classic
122 00:15:29.670 ⇒ 00:15:42.500 Robert Tseng: Yeah, that didn’t really impact classic cookie purchases, like, I mean, slight dip, but it’s still mostly stable. But once boxes are pushed out, then we see deluxe cookies drop, significantly, and then…
123 00:15:43.260 ⇒ 00:15:44.890 Robert Tseng: Let me change this.
124 00:15:45.310 ⇒ 00:15:47.149 Amrita D: And what is the vertical axis?
125 00:15:47.150 ⇒ 00:15:47.850 birdiejackson: Yeah.
126 00:15:49.270 ⇒ 00:15:58.170 Robert Tseng: Yeah, vertical assets is share of purchases, so… I mean, I think this would have looked better as, like, a bar chart, so apologies if it’s a bit hard to read, but this is, like.
127 00:15:58.300 ⇒ 00:16:14.000 Robert Tseng: Of the purchases per month, 60% in the past 3 months, maybe 3 or 4 months, has been box purchases, versus, like, individual classics, individual, deluxes.
128 00:16:14.300 ⇒ 00:16:17.079 Robert Tseng: And, I’m sorry, I don’t know what type 6 is, I don’t exist.
129 00:16:17.080 ⇒ 00:16:18.370 birdiejackson: I bet it’s ice cream.
130 00:16:19.010 ⇒ 00:16:20.069 Robert Tseng: Yeah, maybe that’s ice cream.
131 00:16:21.420 ⇒ 00:16:28.119 Robert Tseng: Yeah. So, I wonder if we… which I already kind of have this as a follow-on, just to check.
132 00:16:30.550 ⇒ 00:16:38.449 Robert Tseng: Yeah, like, I want to know what this looks like before, boxes versus after boxes, because this might actually…
133 00:16:38.660 ⇒ 00:16:42.770 Robert Tseng: Like, I wonder… yeah, I’m not really sure how.
134 00:16:43.630 ⇒ 00:16:44.670 birdiejackson: There’s also…
135 00:16:44.670 ⇒ 00:16:45.950 Robert Tseng: Not as impacted, yeah.
136 00:16:45.950 ⇒ 00:16:58.060 birdiejackson: Yeah, like, I don’t know if this is the… maybe I’m just not looking at it right, so I want to ask you, too. Like, knowing that box… inside boxes, we actually want somebody to buy a box, because it’s more expensive than buying, like, one or two cookies.
137 00:16:58.060 ⇒ 00:17:19.909 birdiejackson: So, to me, it’s like, it’s okay that the boxes spike, and then the sales of individual deluxe or individual classics go down. Like, what I… because the AOV is higher, right? So it’s, like, the volume of those single purchases. It’s an interesting graph, but I’m not… like, I’m not sure… I don’t know what that means, like, in terms of…
138 00:17:19.910 ⇒ 00:17:27.300 birdiejackson: are we doing something wrong? Like, are we talking about boxes too much? Like, does it make more sense to talk, like, to talk about them less? Like, I don’t know if I’m seeing that right.
139 00:17:27.920 ⇒ 00:17:42.840 Robert Tseng: Yeah, no, I think… so I think this one kind of answered… leads into the response, which is, yeah, you know, 55% of customers are purchasing boxes in their first, in their first purchase. I mean, this is from data that’s after this inflection point.
140 00:17:43.060 ⇒ 00:17:48.050 Robert Tseng: And then with every subsequent purchase, you can see that people, like.
141 00:17:48.140 ⇒ 00:18:07.049 Robert Tseng: it seems like customers are… after they get the box, you know, maybe they just figure out that they just like specific cookies, and so they could… they would go back to purchasing just individual cookies, and you can see that this proportion kind of shifts. It starts at, like, around 55%, and then this kind of shrinks to about, like.
142 00:18:07.320 ⇒ 00:18:11.700 Robert Tseng: you know, we’re just eyeballing, but this is, like, about 30%, so…
143 00:18:11.700 ⇒ 00:18:17.190 birdiejackson: They’re no longer trying to, like, find… they’re not, like, trying a bunch of cookies. Maybe they’re gonna get a 4-pack of…
144 00:18:17.310 ⇒ 00:18:23.830 birdiejackson: Sugar, because they know that those are their favorite, versus, like, a 12-pack of various different flavors to kind of, like, taste test which one they want.
145 00:18:24.180 ⇒ 00:18:32.509 Robert Tseng: Right. Yeah, so your most loyal customers are not the ones that are buying up all the boxes, right? They pretty much found what they like, and they just keep going back to it.
146 00:18:32.770 ⇒ 00:18:34.580 birdiejackson: Interesting.
147 00:18:34.580 ⇒ 00:18:35.300 Robert Tseng: Yeah.
148 00:18:36.080 ⇒ 00:18:40.840 Amrita D: So, 54% of first-time customers buy boxes, so…
149 00:18:41.260 ⇒ 00:18:45.320 Amrita D: For us to know that they have opted into email and not purchased.
150 00:18:45.910 ⇒ 00:18:46.830 Amrita D: Right?
151 00:18:47.220 ⇒ 00:18:47.780 Robert Tseng: Yeah.
152 00:18:50.570 ⇒ 00:18:55.530 Amrita D: So people are already opting into email without making a purchase.
153 00:18:55.920 ⇒ 00:18:56.909 Amrita D: Or is this, like…
154 00:18:56.910 ⇒ 00:19:11.639 Robert Tseng: So this is inclusive of everyone who’s opted in to email that we have, like, yeah, that we have embrace. So that includes people who have… yeah, that… yeah, that includes whether or not they’ve made a purchase, whether they made a purchase after they opted in, or before.
155 00:19:13.920 ⇒ 00:19:14.800 Amrita D: Okay.
156 00:19:18.340 ⇒ 00:19:24.829 Robert Tseng: No, I’m not following. So, they had to have opted in for us to have this data on them, right? Yeah.
157 00:19:25.580 ⇒ 00:19:35.909 Amrita D: And then, once they opt-in, their first purchase is a box. So it actually goes opt-in and then box, or it could be simultaneous. They opted in to buy that first box, right?
158 00:19:36.490 ⇒ 00:19:48.630 Robert Tseng: Yeah, but let’s say, like, they purchase and they don’t opt-in until later. As soon as they opt in, we can back… we can back… we’re basically backfilling them, because then we can actually match that data to what we have in Warehouse, and say.
159 00:19:48.630 ⇒ 00:19:58.259 Robert Tseng: they actually did buy something before, and we can guess based on the product name, it’s a box or whatever. So that’s why I’m trying to say we tried to capture whether or not it was
160 00:19:58.370 ⇒ 00:19:59.130 Robert Tseng: when they…
161 00:19:59.130 ⇒ 00:19:59.800 Amrita D: Hold on.
162 00:19:59.800 ⇒ 00:20:07.780 Robert Tseng: Yeah, it’s like, regardless of when they put… they locked it in for email, like, yes, that’s the criteria, but, it’ll always go back to their first order.
163 00:20:08.830 ⇒ 00:20:14.669 Amrita D: So, we have done, some six-pack boxes, probably in the last couple of months, promos, but…
164 00:20:15.950 ⇒ 00:20:21.159 Amrita D: our CEO’s very hesitant to do 6-pack promos, which is why they’ve mostly all been 12-packs.
165 00:20:21.430 ⇒ 00:20:27.179 Amrita D: And then today, I think you were still on the call, Bertie, when he said last week we had a 12-pack offer, and this week we…
166 00:20:27.410 ⇒ 00:20:32.809 Amrita D: Or whatever, 2 weeks ago we had a 12-pack, last week we didn’t, and it did the same, whether we had an offer or not.
167 00:20:33.300 ⇒ 00:20:35.320 Amrita D: So, I don’t know, like…
168 00:20:35.520 ⇒ 00:20:41.970 Amrita D: And finance has kind of mentioned this to me, too. There’s an analysis I haven’t personally seen yet, where it’s essentially, like.
169 00:20:42.210 ⇒ 00:20:48.730 Amrita D: all of our promos do nothing, but they all do the same thing. So, like, really doesn’t matter what the promo is. So, just trying to triangulate
170 00:20:49.270 ⇒ 00:20:57.300 Amrita D: some of that information with this as well. But again, knowing that you pulled specifically from, like, Braze data, that’s why I keep asking about it.
171 00:20:57.540 ⇒ 00:20:58.060 Robert Tseng: Yeah.
172 00:20:58.060 ⇒ 00:20:58.760 Amrita D: Okay.
173 00:21:01.300 ⇒ 00:21:08.289 Robert Tseng: They’re pretty much selling the same thing. It’s like, as they make more orders, they just, you know, they’re going for smaller baskets.
174 00:21:08.950 ⇒ 00:21:12.510 Robert Tseng: Or basically, you know, fewer cookies per box, or whatever.
175 00:21:12.630 ⇒ 00:21:19.519 Robert Tseng: Yeah, I mean, this is… I mean, seems to contradict what you’re saying in terms of…
176 00:21:19.670 ⇒ 00:21:21.640 Robert Tseng: 12-pack impact or whatever, but…
177 00:21:21.640 ⇒ 00:21:23.330 Amrita D: Well, I was talking about promos.
178 00:21:23.840 ⇒ 00:21:27.049 Amrita D: Okay, oh, I see. I don’t think you can buy a 6-pack without a promo.
179 00:21:27.270 ⇒ 00:21:27.640 Robert Tseng: Okay.
180 00:21:28.290 ⇒ 00:21:28.750 birdiejackson: Yeah, I thought…
181 00:21:28.750 ⇒ 00:21:29.440 Robert Tseng: In that case.
182 00:21:29.440 ⇒ 00:21:35.909 birdiejackson: It’s a little confusing. It’s hard to… it’s not, like, a one-to-one, I think, to this graph, because of the emotional aspect of it.
183 00:21:35.910 ⇒ 00:21:43.350 Robert Tseng: Well then, yeah, I guess this is basically saying 6-pack is the most popular of the packs.
184 00:21:43.350 ⇒ 00:21:43.970 birdiejackson: Right.
185 00:21:45.110 ⇒ 00:21:58.279 Robert Tseng: Although, it seems like returning customers, you know, the favoritism shifts, like, it ends up being the 12-pack becomes the biggest segment, like, with… as… as the orders number increases. So,
186 00:22:01.000 ⇒ 00:22:13.020 Robert Tseng: yeah, it seems like it’s not that returning customers don’t want to buy more boxes, it seems like they are buying boxes. For those that are buying boxes, they are purchasing larger boxes. So,
187 00:22:13.310 ⇒ 00:22:19.419 Robert Tseng: Even though, kind of, in this view, You see that,
188 00:22:19.670 ⇒ 00:22:25.320 Robert Tseng: Returning customers are favoring, kind of, the individual cookies or, like, the non-box options.
189 00:22:25.530 ⇒ 00:22:33.620 Robert Tseng: But those that do end up continuing to purchase boxes, they are upgrading to bigger boxes. That’s how I…
190 00:22:33.620 ⇒ 00:22:42.260 birdiejackson: Is the yellow, or the orange is a 6-pack, green is a 9-pack, and blue is the 12-pack? I mean, I don’t really see a ton of movement within the…
191 00:22:42.410 ⇒ 00:22:43.670 birdiejackson: 12-pack here.
192 00:22:45.550 ⇒ 00:23:02.089 Robert Tseng: Yeah, well, so the 12th is pretty stable. It still stays around 40%. This starts at 40%, and then it shrinks, so… but, like, you know, maybe the 9-pack seems to grow a bit. But it doesn’t dilute the 12-pack, so, I mean, that also has to be increasing to some…
193 00:23:02.090 ⇒ 00:23:09.220 Robert Tseng: like, relative proportion in order for it to stay, the same, so… Yeah.
194 00:23:10.550 ⇒ 00:23:21.789 Amrita D: And do the colors correspond to all the slides? Because there’s, you know, the one we looked at at the beginning, and other ones that say type, and, probably, like, in a day from now, I won’t remember what’s what.
195 00:23:21.790 ⇒ 00:23:23.030 Robert Tseng: Yeah, we can, we can.
196 00:23:23.030 ⇒ 00:23:27.329 Amrita D: Can you, like, make sure the labels, yeah, are accurate? Yeah. To the pack? Okay.
197 00:23:27.330 ⇒ 00:23:32.340 Robert Tseng: Make sure the colors are consistent.
198 00:23:33.010 ⇒ 00:23:34.160 Robert Tseng: Response…
199 00:23:34.770 ⇒ 00:23:37.320 Amrita D: A couple of them say, like, type 1, type 2, yeah.
200 00:23:37.320 ⇒ 00:23:43.980 Robert Tseng: Yeah, and we’re also gonna change that off. Okay.
201 00:23:44.130 ⇒ 00:23:45.320 Robert Tseng: tight.
202 00:23:46.170 ⇒ 00:23:46.980 Robert Tseng: Mr.
203 00:23:48.730 ⇒ 00:24:08.390 Robert Tseng: But yeah, I guess, Bertie, to your point, like, maybe 12-pack’s not, like, expanding, it’s not… it’s not shrinking, 6-pack is shrinking. 9-pack seems to be the one that’s, like, kind of growing. So… but that’s still kind of, like, the same… the same story that, like, they’re… for those that are coming back to buy boxes, they’re buying bigger boxes.
204 00:24:15.940 ⇒ 00:24:27.459 Robert Tseng: So, I mean, this is more of, like, a CRO takeaway, but something I was sharing with the team was like, well, just for returning customers, especially in e-com experience, just automatically give them the pre-selected, like.
205 00:24:27.540 ⇒ 00:24:38.369 Robert Tseng: just show them, like, 9 or 12-pack options, like, earlier without showing them the 6-pack options, so they’ll just default to buying bigger ones. I wonder if that’s.
206 00:24:38.370 ⇒ 00:24:41.819 birdiejackson: something, Amrita, that we can do in the For You section?
207 00:24:41.960 ⇒ 00:24:52.319 birdiejackson: So, Robert, just for transparency, we’re really limited on, like, the turnaround for site changes and app changes. Our dev team is pretty strapped, I see.
208 00:24:52.440 ⇒ 00:25:00.420 birdiejackson: I think… I don’t know if you know this, but our email… but our site and our app are both homegrown builds, like, they’re not leveraging.
209 00:25:00.420 ⇒ 00:25:01.230 Robert Tseng: I knew that.
210 00:25:01.230 ⇒ 00:25:03.130 birdiejackson: Yeah, so they…
211 00:25:03.880 ⇒ 00:25:08.280 birdiejackson: Something like this maybe wouldn’t be something that, like, we would be able to show them, like.
212 00:25:08.430 ⇒ 00:25:13.489 birdiejackson: you know, up at the top, they get a personalized banner or something, but maybe in the For You section.
213 00:25:13.710 ⇒ 00:25:28.369 birdiejackson: which, actually, I don’t know, I think it… we’d have to talk to Matt about, like, what capabilities we have for targeting, because I think that that would make sense. Like, in the for you section, we have the 9-pack or the 12-pack pre-selected for someone who’s ordered more than 3 times, or…
214 00:25:28.790 ⇒ 00:25:39.029 birdiejackson: the six-pack for just somebody who is ordering for the first time. I don’t know what sort of lift we’re going to see there, because I don’t know what the interaction is on that section of the pay… of the website versus, like, the rest of the website, but…
215 00:25:39.830 ⇒ 00:25:40.680 birdiejackson: Yeah.
216 00:25:41.090 ⇒ 00:25:45.090 birdiejackson: We might want to just, like, move past any sort of website suggestions.
217 00:25:45.310 ⇒ 00:25:45.920 Robert Tseng: Okay.
218 00:25:46.470 ⇒ 00:25:47.250 birdiejackson: Yep.
219 00:25:47.460 ⇒ 00:25:48.409 Robert Tseng: I’ll make a note of that.
220 00:25:48.410 ⇒ 00:25:49.479 Amrita D: You can leave them, but…
221 00:25:49.480 ⇒ 00:25:52.140 birdiejackson: Yeah, you can leave them, but I don’t know that they’ll be implemented.
222 00:25:52.430 ⇒ 00:25:53.600 birdiejackson: Unfortunately.
223 00:25:53.800 ⇒ 00:25:54.420 Robert Tseng: Yeah.
224 00:25:54.420 ⇒ 00:25:55.229 birdiejackson: It’s a good idea.
225 00:25:56.370 ⇒ 00:26:02.539 Robert Tseng: That’s interesting. I mean, I kind of figured, like, it would be your… it would be, like, within Braze, that you’d be able to…
226 00:26:02.700 ⇒ 00:26:04.570 Robert Tseng: Especially when you’re targeting…
227 00:26:04.570 ⇒ 00:26:07.640 birdiejackson: The only thing you can reactivate
228 00:26:07.840 ⇒ 00:26:15.889 birdiejackson: within Braze, or the only thing that you can… that we on the site can change within Braze are the content cards, and I don’t know what.
229 00:26:15.890 ⇒ 00:26:16.440 Robert Tseng: Right.
230 00:26:16.440 ⇒ 00:26:18.619 birdiejackson: Imagmentation we can have for that.
231 00:26:18.980 ⇒ 00:26:22.099 birdiejackson: To your point, maybe that means that we have…
232 00:26:22.230 ⇒ 00:26:24.950 birdiejackson: a content card that Matt segments.
233 00:26:25.080 ⇒ 00:26:28.060 birdiejackson: to just… Okay, I see what you mean.
234 00:26:28.630 ⇒ 00:26:38.659 Robert Tseng: Yeah, yeah. I mean, maybe that’s where, kind of, we run into the limitations of the current segmentation and why we need to be able to segment off of, like, milestones or whatever, so that.
235 00:26:38.660 ⇒ 00:26:44.839 birdiejackson: I mean, we can segment based off of, purchase times, like, volume, so… or frequency. Purchase volumes.
236 00:26:44.840 ⇒ 00:27:02.209 Robert Tseng: Okay. Yeah, well, yeah. Well, at least the way that I saw the RFM kind of code that Rob Hanthrop sent over, you can’t actually select the… you can’t say… you can’t add the cutoff. You can’t say 4 orders, or past 7 days. Like, it’s all, like, relative to itself.
237 00:27:02.210 ⇒ 00:27:03.359 Amrita D: Exactly right.
238 00:27:03.840 ⇒ 00:27:07.820 birdiejackson: Interesting. Within Braids, that’s how the segmentations are… that’s how the segments are built.
239 00:27:08.810 ⇒ 00:27:10.029 birdiejackson: are, like… But they’re all.
240 00:27:10.030 ⇒ 00:27:11.120 Amrita D: is changing?
241 00:27:11.510 ⇒ 00:27:13.030 birdiejackson: Well, yeah, because it’s a dynamic…
242 00:27:13.030 ⇒ 00:27:13.470 Amrita D: Yeah.
243 00:27:13.470 ⇒ 00:27:14.370 birdiejackson: invitation.
244 00:27:14.370 ⇒ 00:27:20.650 Robert Tseng: Yeah, but, like, the point is, you can’t, like, you can’t definitively say, like, send it to…
245 00:27:20.880 ⇒ 00:27:28.690 Robert Tseng: fourth-time purchasers in the past, like, 7 days, or 30 days, or something, like,
246 00:27:28.850 ⇒ 00:27:31.040 Robert Tseng: Yeah, it’s… you would just be selecting.
247 00:27:31.040 ⇒ 00:27:31.430 birdiejackson: Thank you.
248 00:27:31.430 ⇒ 00:27:34.479 Robert Tseng: On a scale of, like, frequency, or whatever.
249 00:27:34.480 ⇒ 00:27:40.580 birdiejackson: Interesting, yeah, because, I mean, I can do… I can target an email to someone who’s purchased more than twice.
250 00:27:42.020 ⇒ 00:27:46.189 Amrita D: So that’s based on purchase history, that’s different than the RFM stuff that Kantor has done.
251 00:27:46.310 ⇒ 00:27:46.870 birdiejackson: Right.
252 00:27:46.870 ⇒ 00:27:51.900 Amrita D: I’m just saying for Matt, like, if he’s talking about content card segmentation for, like.
253 00:27:51.900 ⇒ 00:27:53.109 birdiejackson: For this specific.
254 00:27:53.110 ⇒ 00:27:53.550 Robert Tseng: Yes.
255 00:27:53.550 ⇒ 00:27:54.429 birdiejackson: don’t like that.
256 00:27:54.430 ⇒ 00:27:55.110 Robert Tseng: Could do that, yeah.
257 00:27:55.110 ⇒ 00:28:01.349 birdiejackson: We could do that. It’s just not within the segments that are in Graze. It’s something that we would have to just select within.
258 00:28:01.630 ⇒ 00:28:02.130 Robert Tseng: Yeah.
259 00:28:02.130 ⇒ 00:28:10.029 birdiejackson: Yep. So maybe change your note of hard to action to We’ll test actionability.
260 00:28:10.030 ⇒ 00:28:11.400 Robert Tseng: Haha, okay.
261 00:28:11.610 ⇒ 00:28:14.770 Robert Tseng: With Matt.
262 00:28:15.330 ⇒ 00:28:18.539 Robert Tseng: Let’s get exposed.
263 00:28:21.710 ⇒ 00:28:30.389 Robert Tseng: Yeah, I mean, the other stuff is kind of up for… up for grabs. I don’t really need to spend too much time on it. Just, like, different ways of, like, kind of…
264 00:28:30.860 ⇒ 00:28:41.220 Robert Tseng: It’s… same thing. Applying the same segmentation, not just varying the content cards, also changing the copy, maybe there’s some incentive to kind of push them into higher,
265 00:28:41.490 ⇒ 00:28:52.620 Robert Tseng: you know, packed as well. I don’t know if we want… if we really have the… the agency to, like, manipulate shipping or anything like that, so I won’t spend too much time there. But just trying to give ideas of how we can, like.
266 00:28:52.970 ⇒ 00:28:55.990 Robert Tseng: Actually, like, target them differently.
267 00:28:56.400 ⇒ 00:28:58.200 Robert Tseng: Last point to cover…
268 00:28:58.200 ⇒ 00:28:59.950 Amrita D: Definitely lacking around here.
269 00:29:01.760 ⇒ 00:29:13.159 Robert Tseng: Last thing to point out here, I also asked for this to kind of shrink down, there’s too many options there. I wanted to just show the top 10. Okay, but basically, it’s…
270 00:29:14.190 ⇒ 00:29:19.069 Robert Tseng: This is… the chocolate chunk is the number one first, it’s the highest
271 00:29:19.550 ⇒ 00:29:33.119 Robert Tseng: like, the most popular choice, but then over time, you can see that that shifts. Like, the V6 cream becomes a big, big, a big chunk, a big caramel apple also grows. So, at least to me, it’s like, okay, well.
272 00:29:33.950 ⇒ 00:29:51.099 Robert Tseng: maybe people start off, like, choosing the classic flavors, and then returning customers, they end up kind of finding their niche cookie that they like, and then they keep coming back, and then that… and that becomes something that they keep going… going towards. So, it’s kind of in…
273 00:29:51.100 ⇒ 00:30:00.539 Amrita D: was interesting, because it was an LTO. You’re mentioning LTOs, but, and then now we brought it back permanently in August, and I know it
274 00:30:00.880 ⇒ 00:30:05.389 Amrita D: I don’t know, Snickerdoodle is number 3 or something. Mel was telling me the other day.
275 00:30:05.570 ⇒ 00:30:09.899 Amrita D: So, I gotta go, because people will keep staring at me, because they want the room, but this is…
276 00:30:09.900 ⇒ 00:30:10.430 Robert Tseng: Okay.
277 00:30:10.430 ⇒ 00:30:13.489 Amrita D: helpful, maybe? Let me, like, digest some more, and we might…
278 00:30:13.630 ⇒ 00:30:18.060 Amrita D: Need to find a little bit more time, but yeah, thank you for that, for sure.
279 00:30:18.060 ⇒ 00:30:22.859 Robert Tseng: Okay, great, yeah, I mean, based on your questions, we have a couple other things to kind of follow up on, so this is… this is good.
280 00:30:22.860 ⇒ 00:30:25.120 Amrita D: Okay, great. Thank you. Bye.
281 00:30:25.120 ⇒ 00:30:25.819 Robert Tseng: Thanks. Bye.