Meeting Title: Insomnia Segmentation Strategy Discussion Date: 2025-11-04 Meeting participants: Robert Tseng, Amber Lin
WEBVTT
1 00:00:38.410 ⇒ 00:00:39.539 Amber Lin: Hi, Robert.
2 00:00:41.070 ⇒ 00:00:41.580 Robert Tseng: Yay!
3 00:00:42.090 ⇒ 00:00:45.390 Amber Lin: Hey, thanks for taking time out of class!
4 00:00:45.390 ⇒ 00:00:46.860 Robert Tseng: Sure, no problem.
5 00:00:48.240 ⇒ 00:00:50.800 Robert Tseng: I’m in your Notion doc right now, I’m starting to leave.
6 00:00:50.800 ⇒ 00:00:51.209 Amber Lin: Oh, yeah.
7 00:00:51.210 ⇒ 00:00:56.310 Robert Tseng: But we can, we can, we can chat through whatever you feel like is helpful.
8 00:00:56.530 ⇒ 00:00:58.039 Amber Lin: Okay,
9 00:00:58.550 ⇒ 00:01:13.239 Amber Lin: Well, when I started, I knew what segmentation was, but I’d never done segmentation exercises, so I don’t know how things translate into actual, actual steps or experiments we should take.
10 00:01:13.240 ⇒ 00:01:18.829 Amber Lin: I also don’t know what the appetite of insomnia is like, I don’t know…
11 00:01:19.440 ⇒ 00:01:25.670 Amber Lin: I don’t even know if they’re using their current segmentation, or just not at all.
12 00:01:25.960 ⇒ 00:01:28.849 Amber Lin: like, there’s some open questions I have, and…
13 00:01:29.720 ⇒ 00:01:37.749 Robert Tseng: Yeah, they are. I think if you go on Braze, you look at every campaign, they should have every… they should have RFM segments labeled, not…
14 00:01:37.860 ⇒ 00:01:42.080 Robert Tseng: I mean, you’re… you looked at,
15 00:01:42.440 ⇒ 00:01:44.950 Robert Tseng: A lot of the broad,
16 00:01:45.560 ⇒ 00:01:51.299 Robert Tseng: Broad campaigns are not… they’re just blasted through their entire.
17 00:01:51.300 ⇒ 00:01:51.960 Amber Lin: Whoa.
18 00:01:51.960 ⇒ 00:02:02.750 Robert Tseng: customer base, but I think for most of the other smaller audiences, they are using some type of segmentation, and it’s probably by RFM segment.
19 00:02:07.830 ⇒ 00:02:11.160 Robert Tseng: So… There’s that.
20 00:02:11.780 ⇒ 00:02:17.340 Robert Tseng: There’s also, like, I think if you look in the…
21 00:02:22.500 ⇒ 00:02:25.850 Robert Tseng: Maybe it would be good to look at…
22 00:02:27.200 ⇒ 00:02:36.599 Robert Tseng: by campaign type, like, what are the different types of segmentation they use currently? Because you had shared an insight about how NSO conversion is, like, pretty…
23 00:02:36.750 ⇒ 00:02:39.609 Robert Tseng: high, but I think that’s…
24 00:02:39.770 ⇒ 00:02:47.870 Robert Tseng: I think we had some feedback there. I think it’s just because the volume’s low. Like, I think the audience size there is probably, like, under 10,000.
25 00:02:47.870 ⇒ 00:02:49.679 Amber Lin: Small geography, yeah.
26 00:02:49.760 ⇒ 00:02:58.790 Robert Tseng: Yeah, so I think that’s obviously geo-targeted, and that’s not using the RFM segment, so…
27 00:02:58.910 ⇒ 00:03:04.330 Robert Tseng: I don’t think that’s the only… yeah, RFM, GEO, I don’t know, there’s…
28 00:03:04.440 ⇒ 00:03:07.820 Robert Tseng: I don’t know what else they’re using, but I think that’s…
29 00:03:08.990 ⇒ 00:03:11.160 Robert Tseng: I don’t know, that’s… that’s a starting point.
30 00:03:14.190 ⇒ 00:03:26.789 Robert Tseng: I think our exercise is trying to build more, like, intent-based segments. I don’t… I don’t think we need to come up with a whole new taxonomy for segments. I think you should first, like, understand, like.
31 00:03:26.930 ⇒ 00:03:32.100 Robert Tseng: okay, this is… every campaign type is segmented this way.
32 00:03:32.580 ⇒ 00:03:38.200 Robert Tseng: it’s good or bad because of XYZ reasons. Like, you’re… I think you should probably understand that first.
33 00:03:39.250 ⇒ 00:03:43.630 Robert Tseng: Yeah.
34 00:03:44.150 ⇒ 00:03:48.340 Robert Tseng: after that, I think the metrics that you have here to kind of
35 00:03:48.450 ⇒ 00:03:55.010 Robert Tseng: analyze the segments off of revenue efficiency, conversion rate, lifetime value, I think all of those things are
36 00:03:55.560 ⇒ 00:04:00.050 Robert Tseng: Good. I don’t know how you would measure fatigue.
37 00:04:00.460 ⇒ 00:04:08.969 Robert Tseng: they’re not, like, unsubscribing… I mean, open rates are very misleading, so I would just avoid open rates. I would just be looking at clicks.
38 00:04:08.970 ⇒ 00:04:10.180 Amber Lin: Thrive rates.
39 00:04:12.860 ⇒ 00:04:13.419 Robert Tseng: We do.
40 00:04:13.420 ⇒ 00:04:15.309 Amber Lin: I think so, yeah.
41 00:04:15.630 ⇒ 00:04:16.350 Robert Tseng: Okay.
42 00:04:18.329 ⇒ 00:04:25.610 Robert Tseng: Yeah, that’s… I mean, yeah, I think it’s…
43 00:04:25.870 ⇒ 00:04:33.460 Robert Tseng: interesting, but probably not a priority. Like, I don’t really think they have a problem with
44 00:04:34.620 ⇒ 00:04:37.780 Robert Tseng: Not having a loyal audience.
45 00:04:38.090 ⇒ 00:04:42.709 Robert Tseng: And, like, they have, like, a… they have a loyal customer base.
46 00:04:43.320 ⇒ 00:04:49.090 Robert Tseng: as you identify, there is, like, a group of people that is considered to be loyal.
47 00:04:49.330 ⇒ 00:04:54.239 Robert Tseng: Is that the Champions RFM segment? Like, I don’t… I do not know, like, I don’t…
48 00:04:54.640 ⇒ 00:05:07.630 Robert Tseng: to me, the only thing that Champions tells me is that these people spend a lot of money, and they made multiple purchases recently. That’s how you get categorized as a quote-unquote champion. But… I think…
49 00:05:08.200 ⇒ 00:05:12.569 Robert Tseng: there’s, like, different degrees to this. Is it, like, how easy is it to be a champion?
50 00:05:12.730 ⇒ 00:05:21.740 Robert Tseng: like, it seems pretty easy if 40% of your customers, like, follow the segment. So, I think that that’s… those are the types of pressure testing that, like.
51 00:05:22.220 ⇒ 00:05:28.679 Robert Tseng: I’d be, like, pushing on for the segmentation. It’s like… It’s not helpful if…
52 00:05:29.100 ⇒ 00:05:32.510 Robert Tseng: We’re calling 40% of the customer base a champion, right?
53 00:05:32.790 ⇒ 00:05:41.739 Robert Tseng: like, I don’t think you need to invent new language, you just have to, like… you have to, like, define what those def… you have to bring some clarity into what those definitions are.
54 00:05:42.440 ⇒ 00:05:54.210 Amber Lin: I see. On that, do we have their previous documentation on how they did these champions, and then those type of segmentations? That would be really helpful.
55 00:05:56.110 ⇒ 00:06:02.529 Robert Tseng: I don’t think there’s much of a art or science to it, like, I think he just, like, looked up,
56 00:06:02.940 ⇒ 00:06:04.640 Robert Tseng: RFM segments.
57 00:06:06.690 ⇒ 00:06:23.120 Amber Lin: They do have some sort of a combination, because there’s, some sort of a high… high valley, because there’s high valley and then lapsing, or who’s dormant, so there’s, like… I guess it’s…
58 00:06:23.330 ⇒ 00:06:36.989 Amber Lin: based on purchase behavior, so I was thinking of getting something that’s engagement behavior-based, but I think overall, I’m a bit… I want to understand, like, what the goal
59 00:06:37.480 ⇒ 00:06:40.740 Amber Lin: here is. Like, are we trying to…
60 00:06:41.120 ⇒ 00:06:53.089 Amber Lin: get more loyal customers? Are we trying to maximize each campaign’s returns? Are we trying to prevent churn?
61 00:06:53.210 ⇒ 00:06:57.970 Amber Lin: Like, what do you think… I should frame the gold.
62 00:06:59.620 ⇒ 00:07:00.390 Amber Lin: Excellent.
63 00:07:00.390 ⇒ 00:07:02.799 Robert Tseng: I just sent you the definitions.
64 00:07:02.800 ⇒ 00:07:06.540 Amber Lin: Okay. Oh, great.
65 00:07:08.720 ⇒ 00:07:09.550 Amber Lin: Thanks.
66 00:07:32.660 ⇒ 00:07:36.289 Robert Tseng: These numbers don’t mean anything specific, he’s just… it’s just like…
67 00:07:36.660 ⇒ 00:07:41.010 Robert Tseng: Everything is relative to the customer base, so he hasn’t…
68 00:07:46.600 ⇒ 00:07:57.890 Robert Tseng: There’s a range of… Customers… On all of these different dimensions, or just three dimensions of recency, frequency monitoring.
69 00:07:58.520 ⇒ 00:08:02.059 Robert Tseng: They’re assigned a score based on the quartile that they’re in.
70 00:08:02.980 ⇒ 00:08:08.300 Robert Tseng: Or is, like… in the top 25%. Of…
71 00:08:08.720 ⇒ 00:08:12.569 Robert Tseng: And so it’s just a relative scoring model.
72 00:08:12.570 ⇒ 00:08:13.100 Amber Lin: See?
73 00:08:15.870 ⇒ 00:08:19.509 Robert Tseng: Yeah, that’s… that’s all this is. To me, this is all very arbitrary.
74 00:08:19.970 ⇒ 00:08:39.029 Amber Lin: Yeah, there’s nothing that tells us, say, if I’m a new customer, doesn’t tell me what I need to do for this new customer. Or, say, if I’m a student, it doesn’t tell me, like, these people might purchase, or at different quantities, or different hours than other people. It doesn’t help them do any of their…
75 00:08:39.039 ⇒ 00:08:41.990 Amber Lin: campaigns. Like, there’s no direct relationship between
76 00:08:42.419 ⇒ 00:08:45.980 Amber Lin: Purchasing recently, and at high amounts to
77 00:08:46.530 ⇒ 00:08:56.769 Amber Lin: how they will react to a specific campaign. It just means that they’re more likely to… more likely to purchase overall. So, that’s my… that’s my take, but…
78 00:08:59.820 ⇒ 00:09:04.100 Robert Tseng: I’m not sure if I’m following, but let’s just pick one example.
79 00:09:06.360 ⇒ 00:09:15.130 Robert Tseng: hibernating is somebody who Has not purchased recently, is in the bottom 25%.
80 00:09:15.380 ⇒ 00:09:18.050 Robert Tseng: of… purchases, so…
81 00:09:18.050 ⇒ 00:09:20.650 Amber Lin: Probably someone who purchased more than a year ago.
82 00:09:20.960 ⇒ 00:09:26.409 Robert Tseng: who… So, on the recent… Frequency probably only made one purchase.
83 00:09:26.500 ⇒ 00:09:35.070 Amber Lin: And then, like, spent very little money. I understood this one. I was comparing this to other possible segmentation that I didn’t make that very clear.
84 00:09:35.450 ⇒ 00:09:36.130 Robert Tseng: Okay.
85 00:09:36.520 ⇒ 00:09:37.090 Amber Lin: Yeah.
86 00:09:41.700 ⇒ 00:09:43.980 Amber Lin: So…
87 00:09:44.960 ⇒ 00:10:01.160 Amber Lin: Based on this and what you just said, I think I’m gonna start with looking at how their current segmentation is comparing, because each campaign has that tag, and I will be able to compare, not only based on these users, but how
88 00:10:01.620 ⇒ 00:10:11.839 Amber Lin: like, the current segmentation targeting is doing. Like, that’s the first… first step I will do. And then the second one probably is to have a…
89 00:10:13.140 ⇒ 00:10:17.709 Amber Lin: Introduce a simple, engagement-based, or intent-based.
90 00:10:17.870 ⇒ 00:10:23.359 Amber Lin: segmentation? Do you think that’s the… that will be a good next step?
91 00:10:23.360 ⇒ 00:10:30.890 Robert Tseng: I think I sent you, like, some, screenshots before of, like, another subscription CBG company.
92 00:10:31.160 ⇒ 00:10:36.760 Robert Tseng: And, like, kind of how they started to, like,
93 00:10:39.540 ⇒ 00:10:46.259 Robert Tseng: Yeah, I think we don’t have to reinvent the wheel. Yeah, there’s, like, life cycle stages that we can kind of just…
94 00:10:46.260 ⇒ 00:10:46.980 Amber Lin: Bill?
95 00:10:46.980 ⇒ 00:10:52.160 Robert Tseng: from there, like, I think some adaptation of that is, like, a good baseline.
96 00:10:53.720 ⇒ 00:10:55.170 Amber Lin: Okay.
97 00:10:55.170 ⇒ 00:10:56.200 Robert Tseng: I think it’s…
98 00:10:58.770 ⇒ 00:11:16.180 Robert Tseng: new, reactivated, like, total… I mean, like, those are… those are the… those are, like, core… those are purely based off of transactions. It’s not really based on intent. I think then the set… there’s a second set of intent based… I mean, you do… you do need both, like, they tell you different stories. Like, one is…
99 00:11:16.520 ⇒ 00:11:24.699 Robert Tseng: Yeah, like, you know, the whole idea, like, for Eden, we care a lot about new versus returning customers. We haven’t even really broken out.
100 00:11:24.720 ⇒ 00:11:37.360 Robert Tseng: the segments beyond that. But, I mean, just having that is… is… is valuable. I don’t even think they’re… they’re looking at their business that way. New cookie customers versus returning cookie customers. Like, I… I think…
101 00:11:37.380 ⇒ 00:11:39.739 Robert Tseng: We don’t… yeah, like, I… so…
102 00:11:40.010 ⇒ 00:11:46.870 Robert Tseng: I think there are some very basic cuts that we can… that we can propose, that are… that are just kind of off of…
103 00:11:47.220 ⇒ 00:11:49.310 Robert Tseng: Kind of just a repackaging of this.
104 00:11:49.850 ⇒ 00:11:59.329 Amber Lin: Yeah, I wanted something very, very simple to start with, so I think life cycles are good.
105 00:12:04.220 ⇒ 00:12:06.219 Amber Lin: And then going back…
106 00:12:06.400 ⇒ 00:12:17.710 Amber Lin: What do you think their goal is? Like, is their goal to have more customers be returning, or just they’re purely looking at total revenue?
107 00:12:18.010 ⇒ 00:12:30.530 Amber Lin: Are they looking at customer lifetime now? Are they looking to make more people loyal… increase their very loyal customer base?
108 00:12:30.530 ⇒ 00:12:39.769 Robert Tseng: Yeah, well, I think the main goal is always, like, LTV maximization, but in order to do that, you need to know, like, who you’re going to actually influence in their customer base.
109 00:12:40.000 ⇒ 00:12:47.420 Robert Tseng: So that’s why it’s important to define, like, what even is, like, loyal, and then, you have to be able to
110 00:12:48.410 ⇒ 00:12:55.220 Robert Tseng: And if there even is a segment that you can… Influence to become more loyal.
111 00:12:56.470 ⇒ 00:13:00.939 Amber Lin: I don’t believe the RFM model tells you how you can do that.
112 00:13:01.940 ⇒ 00:13:03.170 Robert Tseng: Yeah, my good.
113 00:13:03.440 ⇒ 00:13:07.749 Robert Tseng: It’s… it’s an… it’s… it’s an… it just kind of explains, like.
114 00:13:08.420 ⇒ 00:13:18.389 Robert Tseng: who’s spending money with you, but, like, it doesn’t… it’s not really telling you how… how people are moving from one state to another. That’s why you need the… you need to tie it to lifecycle stages.
115 00:13:21.220 ⇒ 00:13:34.829 Amber Lin: I understand the lifecycle part, and then having transactions. When we say intent, do we mean, like, what the needs for specific… does it relate to people’s traffic? Does it relate to what they want?
116 00:13:35.130 ⇒ 00:13:53.649 Robert Tseng: Well, I think the intent here is very simple. It’s just, like, buying cookies. So, like, it’s not like a… it’s not like a SaaS product where they’re, there’s, like, a bunch of features you can use, and you have to score the features based on, like, how closely they… they… they, like, are… they… they tie to revenue, like…
117 00:13:53.650 ⇒ 00:14:06.620 Robert Tseng: stuff that I’m doing on README is basically, like, telling them which features, kind of lead to higher, conversion or kind of revenue impact. Like, there’s not… there’s none of that here. The action is… is just…
118 00:14:06.740 ⇒ 00:14:23.330 Robert Tseng: I mean, we look at clicks, visits, I mean, there’s, like, some responsiveness to own channel communication. You’re not even bringing in, like, foot traffic and other signals, like, from the rest of the business. Like, we’re… it’s, like, pretty limited, limited,
119 00:14:23.790 ⇒ 00:14:25.970 Robert Tseng: There’s a pretty limited set here.
120 00:14:25.970 ⇒ 00:14:31.400 Amber Lin: So, I think… I do think that frequency, like, I do think that RFM are, like.
121 00:14:31.400 ⇒ 00:14:38.210 Robert Tseng: Those are, like, the classic like, variable levers to kind of, like, look at.
122 00:14:38.210 ⇒ 00:14:38.599 Amber Lin: soft care.
123 00:14:38.600 ⇒ 00:14:41.190 Robert Tseng: And you can do LTV prediction off of that.
124 00:14:42.660 ⇒ 00:14:56.250 Robert Tseng: Yeah, it’s like… like, I… yeah, I think you’re not gonna be able to see much about customer behavior with just those three things. And, yeah, we don’t need to, like, overblow it by, like.
125 00:14:56.430 ⇒ 00:15:03.659 Robert Tseng: saying, like, what are all the different things we need to track? Like, I feel like you’re conflating, like, business models and kind of the way you’re talking to me about segmentation.
126 00:15:04.670 ⇒ 00:15:21.979 Amber Lin: Yeah, I… I have very limited experience in this, because I was thinking, oh, maybe people… certain people buy for gifts, and certain people like to have more rewards, but maybe that’s too far down before we even do basic, like…
127 00:15:22.920 ⇒ 00:15:25.490 Robert Tseng: Yeah, I mean, we should do that, like, I think, like.
128 00:15:25.940 ⇒ 00:15:39.589 Robert Tseng: punches their loyalty platform that gives you a sense of, like, those particular offers that they’re responding to. If it’s, like, Father’s Day, and people are purchasing a bunch of cookies, then, yeah, you could… you could triangulate that, like.
129 00:15:39.690 ⇒ 00:15:53.860 Robert Tseng: these purchases are for someone else. Like, I think that’s an interesting take. But, like, yeah, this just kind of requires you being able to, like, layer in more, more, like, more, more data.
130 00:15:54.000 ⇒ 00:15:56.760 Robert Tseng: I mean, there is POS data, there’s…
131 00:15:57.060 ⇒ 00:16:03.420 Robert Tseng: I mean, we’re not really looking at campaign, like, paid campaigns, like, I guess we’re only…
132 00:16:03.620 ⇒ 00:16:16.370 Robert Tseng: Yeah, I mean, you’re kind of limited by your starting point, so I think it’s more important to do the explanation of, like, this is how things are currently set up, and the limitations, and then you can
133 00:16:16.490 ⇒ 00:16:19.239 Robert Tseng: Then we can just talk about, like, what you would bring in.
134 00:16:19.910 ⇒ 00:16:20.580 Amber Lin: Oh, okay.
135 00:16:20.970 ⇒ 00:16:21.510 Robert Tseng: Yeah.
136 00:16:25.400 ⇒ 00:16:27.450 Amber Lin: Gotcha. So…
137 00:16:28.050 ⇒ 00:16:35.530 Amber Lin: I’ll do current set of limitations, and I’ll dive a little bit more into how I would bring in lifecycle-based
138 00:16:35.630 ⇒ 00:16:46.370 Amber Lin: And then… I’ll see… I think I can have…
139 00:16:46.530 ⇒ 00:16:49.569 Amber Lin: I can share findings, at least for the first one.
140 00:16:50.920 ⇒ 00:16:55.310 Amber Lin: This week, Is there a timeline that we’re aiming for?
141 00:16:58.050 ⇒ 00:17:07.019 Robert Tseng: I think that I would like you to be in touch with the client directly, like, I feel like you shouldn’t be building this out in a silo.
142 00:17:07.020 ⇒ 00:17:08.070 Amber Lin: I agree.
143 00:17:08.079 ⇒ 00:17:12.469 Robert Tseng: Yeah, so I think if you can have Utam intro you to Birdie.
144 00:17:12.609 ⇒ 00:17:14.839 Robert Tseng: And you start just kind of, like.
145 00:17:15.179 ⇒ 00:17:19.499 Robert Tseng: I mean, Birdie is pretty sharp, like, I think she will…
146 00:17:19.629 ⇒ 00:17:24.379 Robert Tseng: But, like, she… I mean, yeah, like, I think you’ll just need to… But I…
147 00:17:25.389 ⇒ 00:17:34.879 Robert Tseng: kind of just spend time with her, and understand, like, pick her brain on, like, how she’s… how she’s doing these things. But,
148 00:17:36.459 ⇒ 00:17:47.349 Robert Tseng: Yeah, I mean, as far as timeline, like I said, like, when I did customer segmentation, it took me 3 months. Like, I built out a whole survey, took 80… like, 80 questions, sent it out to 10,000 people.
149 00:17:47.409 ⇒ 00:18:06.119 Robert Tseng: Like, and I, like, emailed… I mean, I surveyed, like, existing… existing customers, I paid everybody, like, $20 in order to fill out the survey, and then I… I kind of, like, built a lot of different types of things out of that. Like, this is not, like, a one-week exercise, so I think…
150 00:18:06.299 ⇒ 00:18:09.019 Robert Tseng: Just, like, having, like, a…
151 00:18:10.199 ⇒ 00:18:17.349 Robert Tseng: Like, yeah, like, the first step is just trying to wrap your head around the existing definitions, and…
152 00:18:17.569 ⇒ 00:18:29.429 Robert Tseng: What they do tell you, what they don’t tell you, and, like, why we need to do, like, why we need more, runway in order to go bring in other types of data, like,
153 00:18:29.639 ⇒ 00:18:31.709 Robert Tseng: Yeah, I, I think that’s… that’s…
154 00:18:32.039 ⇒ 00:18:34.389 Robert Tseng: That’s what we need at this point.
155 00:18:34.390 ⇒ 00:18:42.350 Amber Lin: Gotcha, yeah. And that will help me talk to Bertie, because I don’t feel… I feel like I’m wasting her time if I talk to her right now.
156 00:18:42.350 ⇒ 00:18:44.880 Robert Tseng: Yeah. And I also need…
157 00:18:44.880 ⇒ 00:18:51.560 Amber Lin: To hear from her what… what she wants, like, what level of experimentation, or surveys, or whatever she wants to do.
158 00:18:52.290 ⇒ 00:18:58.689 Robert Tseng: Yeah, I mean, she’s not gonna do any of that. She doesn’t know how to run any of that. She just, like, kind of executes her campaigns.
159 00:18:59.040 ⇒ 00:19:05.179 Robert Tseng: She doesn’t know, like, she won’t… she won’t know what segment she wants, which is kind of why we need to tell her.
160 00:19:05.310 ⇒ 00:19:12.340 Robert Tseng: She just uses what she’s given. Like, she’s, you know, that’s… she’s just purely execution. She’s not gonna be really, like…
161 00:19:12.530 ⇒ 00:19:20.829 Robert Tseng: Telling you what the strategy should be, but, like, you can ask her questions about why she’s doing… why she’s executing a particular way.
162 00:19:21.220 ⇒ 00:19:30.779 Amber Lin: I see. Would she be able to make the call on, okay, we can send out surveys, or okay, we can test this A to B testing, like, would she be able to…
163 00:19:31.080 ⇒ 00:19:32.460 Amber Lin: Make the call on that.
164 00:19:32.460 ⇒ 00:19:48.220 Robert Tseng: I mean, she can be a good thought partner on the type of, like, experiments you want to run, like, I think that’s fair. She won’t run surveys, like, she doesn’t know how to do that, because she does not… I mean, yeah, like, that kind of moves more into, like, consumer insights, that’s not her…
165 00:19:48.630 ⇒ 00:19:55.509 Robert Tseng: She’s just a lifecycle marketer, so, like, I don’t really think that’s within her range. There’s nobody in Insomnia that does that.
166 00:19:55.680 ⇒ 00:19:57.600 Robert Tseng: So… .
167 00:19:57.730 ⇒ 00:19:59.340 Amber Lin: Okay, that’s why they have us.
168 00:20:00.030 ⇒ 00:20:00.600 Robert Tseng: Yeah.
169 00:20:01.340 ⇒ 00:20:20.279 Robert Tseng: Yeah, so I think… yes, yes, we’re limited to Braze, and that’s kind of where you’ve been playing. I do think that your curiosity in the structure of your thinking should bring you outside of Braze. I do think that intent is captured better in the customers that tell us the most, which are the ones who are in our loyalty program, which is in Punch.
170 00:20:20.480 ⇒ 00:20:25.140 Robert Tseng: Beyond that, it’s all transactional data, which is kind of just…
171 00:20:25.430 ⇒ 00:20:39.640 Robert Tseng: kind of everywhere. There’s, I mean, we have it in holistics, but you’ll just be spending too much time in there. I don’t really think that that’s helpful. So, we’re not really wanting, like, a holistic survey of everything, we just want to be able to explain
172 00:20:39.640 ⇒ 00:20:46.010 Robert Tseng: These are your loyal customers, this is what they look like, this is how they behave, and, like.
173 00:20:46.280 ⇒ 00:20:57.600 Robert Tseng: you know, this is how you can get someone to become more like that. Like, those are the meta questions that we’re trying to answer. We will not be able to within this week, but, like, that’s… that’s what you’re driving towards.
174 00:20:58.660 ⇒ 00:21:02.419 Amber Lin: Sure, okay. That helps… that makes it a lot more clear.
175 00:21:03.050 ⇒ 00:21:07.539 Amber Lin: And then I have to first define loyal customers, which I will need her input as well.
176 00:21:08.040 ⇒ 00:21:08.880 Robert Tseng: Yes.
177 00:21:08.880 ⇒ 00:21:09.930 Amber Lin: Okay.
178 00:21:16.320 ⇒ 00:21:21.869 Amber Lin: I have enough to do the first part, but I will draft the outline either
179 00:21:22.230 ⇒ 00:21:34.820 Amber Lin: this afternoon or tomorrow morning, I’ll try to get it for you to review tomorrow, and then I’ll try to pull… because it’s available right now, so I’ll try to do all the campaign
180 00:21:34.950 ⇒ 00:21:41.919 Amber Lin: analysis this week, so… and then next week, maybe I get introduced to Bertie.
181 00:21:42.320 ⇒ 00:21:43.719 Robert Tseng: Okay, that sounds good.
182 00:21:43.720 ⇒ 00:21:44.650 Amber Lin: Yeah, okay.
183 00:21:44.770 ⇒ 00:21:46.250 Amber Lin: Thank you for taking time.
184 00:21:46.610 ⇒ 00:21:48.600 Amber Lin: Yep, talk to you later. Bye. Bye.