Meeting Title: Planning: Honey Stinger-Readme-Eden-Insomnia Date: 2025-12-01 Meeting participants: Henry Zhao, Gabriel Lam, Rico Rejoso, Casie Aviles, Robert Tseng, Ashwini Sharma, Mustafa Raja, Amber Lin, Awaish Kumar, Demilade Agboola
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1 00:01:41.360 ⇒ 00:01:42.720 Robert Tseng: Hello, everyone.
2 00:01:43.820 ⇒ 00:01:44.410 Mustafa Raja: Hey.
3 00:01:55.770 ⇒ 00:02:02.490 Robert Tseng: Okay, I’m gonna jump into it. We’re gonna start with README, actually, because, Mustafo, there’s just, like.
4 00:02:02.930 ⇒ 00:02:11.410 Robert Tseng: They’re… they’re, they’re asking you about funnel verification again, and… They had, like, booked…
5 00:02:12.370 ⇒ 00:02:28.499 Robert Tseng: a time, if they really can’t do any other time, I might jump off this meeting and just go talk to them. But they really want an update, and we didn’t really say anything last week. Which is on me, because I didn’t really follow up on… by Friday. But yeah, I think I just need to catch up, like…
6 00:02:28.960 ⇒ 00:02:39.620 Robert Tseng: there was some back and forth. We… Mark had sent some recommendations on, like, what you could look into. I forwarded those messages to you, so where are we at now?
7 00:02:40.110 ⇒ 00:02:45.930 Mustafa Raja: So, work, with the filters that Mark suggested, we could only eliminate 400 more users.
8 00:02:46.180 ⇒ 00:02:50.270 Mustafa Raja: And we would still be about $5,000 off.
9 00:02:51.760 ⇒ 00:02:52.460 Robert Tseng: Okay.
10 00:02:57.220 ⇒ 00:03:02.149 Robert Tseng: Yeah, I mean, like, what are… what are our options? Like, is it…
11 00:03:02.150 ⇒ 00:03:02.840 Mustafa Raja: I mean…
12 00:03:03.120 ⇒ 00:03:03.770 Robert Tseng: Yeah.
13 00:03:03.920 ⇒ 00:03:06.239 Mustafa Raja: Yeah, so for, so for,
14 00:03:06.360 ⇒ 00:03:14.679 Mustafa Raja: what I said earlier is, I tried creating two accounts, and, I didn’t see the event fire, and.
15 00:03:14.680 ⇒ 00:03:20.730 Robert Tseng: I also went and did that, and I did not see it fire, so I agree with your assessment. Yeah.
16 00:03:20.900 ⇒ 00:03:22.970 Mustafa Raja: What it looks to me is…
17 00:03:23.630 ⇒ 00:03:29.299 Mustafa Raja: It doesn’t… it doesn’t always fire whenever a user signs up.
18 00:03:29.690 ⇒ 00:03:37.070 Mustafa Raja: the data in MongoDB about the users cannot be wrong, so there’s something with this event that needs to be
19 00:03:37.180 ⇒ 00:03:39.339 Mustafa Raja: Either clarified or fixed.
20 00:03:41.820 ⇒ 00:03:42.530 Robert Tseng: Okay.
21 00:03:47.240 ⇒ 00:03:54.069 Mustafa Raja: I mean, either we are not understanding how they have set up the event to trigger.
22 00:03:54.520 ⇒ 00:03:59.650 Mustafa Raja: Or… or there’s just something wrong with the trigger itself, you know? If that makes sense.
23 00:04:00.880 ⇒ 00:04:07.389 Robert Tseng: Yeah, but then why would Mongo be so much higher, right? Is it because… oh, you’re saying it’s because…
24 00:04:07.970 ⇒ 00:04:12.660 Robert Tseng: amplitude, we’re not capturing everything. Yeah, yeah, yeah.
25 00:04:12.660 ⇒ 00:04:16.649 Mustafa Raja: To me, it looks like Amplitude isn’t capturing that event.
26 00:04:16.779 ⇒ 00:04:17.570 Mustafa Raja: Properly.
27 00:04:17.579 ⇒ 00:04:19.079 Robert Tseng: Okay. Alright.
28 00:04:21.760 ⇒ 00:04:32.469 Mustafa Raja: I mean, Mark said that, Mark said that, it’s triggering, but yeah, I didn’t see that, so, maybe… maybe we need some clarification on that?
29 00:04:32.820 ⇒ 00:04:36.490 Mustafa Raja: You know, something needs to be… needs to happen for that to trigger.
30 00:04:36.650 ⇒ 00:04:37.810 Mustafa Raja: We just don’t know.
31 00:04:44.520 ⇒ 00:04:45.360 Robert Tseng: Got it.
32 00:04:59.660 ⇒ 00:05:05.960 Robert Tseng: Okay, I mean, they’re… they’re just… we’re just gonna have to tell them how it is, so there’s nothing…
33 00:05:06.460 ⇒ 00:05:09.110 Robert Tseng: more to say there.
34 00:05:14.830 ⇒ 00:05:16.420 Robert Tseng: Okay…
35 00:05:21.170 ⇒ 00:05:23.100 Robert Tseng: Alright, let’s move to…
36 00:05:23.290 ⇒ 00:05:36.180 Robert Tseng: I mean, we’re really just blocked on the same thing, so, I mean, I’m gonna have to find a way to tell them what it is. Mark is out of office the rest of the week, so, like, I don’t really think they’re gonna make any progress, which…
37 00:05:36.320 ⇒ 00:05:46.439 Robert Tseng: It’s just… just not great. Like, I just feel like we’ve been stuck on something that’s just out of our… out of our hands, because we can’t, like, go and actually change the instrumentation ourselves.
38 00:05:46.900 ⇒ 00:05:48.439 Mustafa Raja: Yeah.
39 00:05:48.980 ⇒ 00:05:49.970 Robert Tseng: Yeah.
40 00:05:50.210 ⇒ 00:05:55.889 Robert Tseng: I don’t know what else to say. Like, they’re just… yeah, we’re just… we’re still blocking the same thing.
41 00:05:56.120 ⇒ 00:06:01.780 Robert Tseng: Okay, I mean, I’m gonna have to… I’m just gonna have to tell… tell PB. Yeah, I’m just gonna write a quick message,
42 00:06:04.970 ⇒ 00:06:06.729 Robert Tseng: Anything to work…
43 00:06:12.570 ⇒ 00:06:18.899 Robert Tseng: TLDR… Whatever you think is working.
44 00:06:20.290 ⇒ 00:06:21.519 Robert Tseng: First sign up.
45 00:06:22.090 ⇒ 00:06:27.530 Robert Tseng: events… in Mongo.
46 00:06:27.650 ⇒ 00:06:32.500 Robert Tseng: doesn’t actually… Fire the same way in amplitude.
47 00:06:33.120 ⇒ 00:06:37.129 Robert Tseng: I don’t care how you’re testing, but if we were to hop
48 00:06:37.500 ⇒ 00:06:40.950 Robert Tseng: on a call, I would tell you the same thing.
49 00:06:45.200 ⇒ 00:06:47.979 Robert Tseng: Amplitude is clearly under.
50 00:06:50.170 ⇒ 00:06:52.339 Robert Tseng: Under reporting signups.
51 00:07:04.400 ⇒ 00:07:14.779 Robert Tseng: Okay, alright, that’s… I’m okay, I can make peace with that. Alright, let’s just move on to Honey Singer, just because I don’t really think there’s anything else to share there until we get more direction.
52 00:07:17.040 ⇒ 00:07:29.890 Robert Tseng: Yeah, I guess, Amber, there was some review… I mean, just assumed that nothing was really pushed out by next, like, last week, so we’re just trying to close things out from last week, while also trying to do some planning for this week, so…
53 00:07:30.120 ⇒ 00:07:30.810 Amber Lin: Yeah.
54 00:07:30.940 ⇒ 00:07:40.960 Amber Lin: So there was two analysises last week. One was on the Amazon PO side, which I… I found pretty interesting. I do want to…
55 00:07:41.070 ⇒ 00:07:51.090 Amber Lin: tell them what I think about they should do for the Amazon channel strategy. And the other one is what we did on Shopify, and…
56 00:07:51.480 ⇒ 00:08:10.249 Amber Lin: I think that one’s also very interesting. I think the conclusion there is that their retention probably is pretty bad, and they have more opportunity to increase the top of funnel. Because it might be that,
57 00:08:10.730 ⇒ 00:08:17.779 Amber Lin: They’ve been targeting… let’s see… So their overall revenue is flat, with significant spikes.
58 00:08:17.940 ⇒ 00:08:24.030 Amber Lin: on seasonal spikes, and also promotional spikes, say, in the November.
59 00:08:24.380 ⇒ 00:08:26.780 Amber Lin: for, Black Friday.
60 00:08:27.260 ⇒ 00:08:29.230 Amber Lin: So,
61 00:08:29.380 ⇒ 00:08:39.569 Amber Lin: It could be that their customer base is very seasonal or very discount-led, which leads to their retention being very bad.
62 00:08:40.850 ⇒ 00:08:41.169 Robert Tseng: Yeah.
63 00:08:41.179 ⇒ 00:08:47.229 Amber Lin: Because for new customers, has been flat, so they get about the same new customers.
64 00:08:47.879 ⇒ 00:08:49.469 Amber Lin: Year over year.
65 00:08:49.819 ⇒ 00:08:57.179 Amber Lin: which, coupled with flat revenue, means that there’s just no growing retention.
66 00:08:57.589 ⇒ 00:09:05.439 Amber Lin: So I want to look at that. I don’t know if they have that customer-based data, but I think that would be interesting to see.
67 00:09:06.610 ⇒ 00:09:23.750 Robert Tseng: Okay. Yeah, I mean, I think retention is… I hear what you’re saying, but this is not a subscription, like, company, e-comp company, so… I mean, if I… I’m a honey singer purchaser, like, I just buy waffles twice a year, when the best deals are happening, so…
68 00:09:24.140 ⇒ 00:09:34.619 Robert Tseng: that’s Black Friday, and probably sometime in the middle of the year. I’d buy, like, a 3-month supply, and then, like, that’s about it. Like, I’m not really gonna bye-bye waffles every week, so…
69 00:09:35.020 ⇒ 00:09:41.309 Robert Tseng: I think, like, that’s… that seems to make sense to me, that that’s how their customer behavior works.
70 00:09:42.730 ⇒ 00:10:02.599 Robert Tseng: But yeah, I mean, as far as, like, not getting new customers or new customer acquisition is flat year over year, that’s, that’s an interesting problem. I think that’s… there’s a… there’s a top-of-funnel kind of issue there. But yeah, as far as, like, getting… driving repeat purchases, like, I’m… I’m not surprised that that’s what you’re.
71 00:10:02.600 ⇒ 00:10:15.259 Amber Lin: Yeah, their conversion rate is going up slightly, and their revenue per customer is going up, but their top-of-funnel traffic is declining. So, I think they did something with their targeting, and right now they’re just…
72 00:10:15.350 ⇒ 00:10:23.409 Amber Lin: They’re lim… like, they could spend more. They don’t have to have such high revenue per customer, if their traffic’s being so low.
73 00:10:24.300 ⇒ 00:10:24.910 Robert Tseng: Okay.
74 00:10:25.460 ⇒ 00:10:25.970 Amber Lin: Yeah.
75 00:10:25.970 ⇒ 00:10:34.279 Robert Tseng: Okay, yeah, I mean, I thank you for kind of just that overview. I’ll, I’ll do the review on the slides, and then hopefully we can send this out today.
76 00:10:34.380 ⇒ 00:10:35.660 Amber Lin: Okay, yeah.
77 00:10:35.660 ⇒ 00:10:36.230 Robert Tseng: Yeah.
78 00:10:36.600 ⇒ 00:10:53.370 Amber Lin: And on the Amazon PO side, their PO is concentrated in very few units, so the top 3 covers 50%, which means that they probably should think of optimizing and removing some SKUs, because,
79 00:10:53.690 ⇒ 00:11:01.940 Amber Lin: Amazon’s about efficiency, and if they have too many ASINs, it’s hard to plan Inventory, so…
80 00:11:02.300 ⇒ 00:11:07.179 Amber Lin: Also, the spikes in Amazon is… Pretty much.
81 00:11:07.290 ⇒ 00:11:26.299 Amber Lin: The data only starts this May, essentially, but it is about 1.5 to 2 months before the Amazon events. So, Prime Day in July, so they had a spike in May, and then Prime Big Deals Day in October, they had a spike around.
82 00:11:26.390 ⇒ 00:11:35.769 Amber Lin: July, late September, and then recently, this spike, it’s probably for Black Friday, Cyber Monday.
83 00:11:36.110 ⇒ 00:11:39.359 Amber Lin: So, I do think that patterns are…
84 00:11:39.540 ⇒ 00:11:46.910 Amber Lin: Relatively predictable on Amazon. It’s also… the warehouses, even, is also very concentrated.
85 00:11:47.200 ⇒ 00:11:52.319 Amber Lin: Especially Indiana takes up a… about 18%, and the top, I think…
86 00:11:52.800 ⇒ 00:11:56.920 Amber Lin: The top… how many warehouses take up about, like.
87 00:11:57.090 ⇒ 00:12:05.060 Amber Lin: 50% of their orders, so, based on that, my recommendation is that Amazon should be, like, a…
88 00:12:05.200 ⇒ 00:12:14.879 Amber Lin: more concentrated, channel focusing on replenishables, and they can move the trial novelty SKUs to Shopify.
89 00:12:15.690 ⇒ 00:12:18.280 Amber Lin: So that they can optimize on Amazon.
90 00:12:18.900 ⇒ 00:12:22.910 Amber Lin: Like, that’s the… That’s what I see there.
91 00:12:24.110 ⇒ 00:12:24.740 Robert Tseng: Okay.
92 00:12:25.270 ⇒ 00:12:31.280 Robert Tseng: Yeah, I guess what I owe you then is a review, so we can send it, and then…
93 00:12:31.550 ⇒ 00:12:37.059 Robert Tseng: I guess Henry, have you opened Acosta’s SharePoint yet?
94 00:12:38.010 ⇒ 00:12:42.779 Henry Zhao: No, I get 404 file not found. Were you guys able to get in?
95 00:12:43.690 ⇒ 00:12:49.070 Robert Tseng: No. Okay. Yeah, I mean, I feel like we’re in the same situation. So, okay, I’ll have to follow up on that.
96 00:12:49.170 ⇒ 00:12:50.840 Henry Zhao: Okay.
97 00:12:51.180 ⇒ 00:12:54.570 Robert Tseng: Yeah, I… it’s… I don’t think it’s working for me.
98 00:13:02.310 ⇒ 00:13:03.170 Robert Tseng: Okay.
99 00:13:03.310 ⇒ 00:13:08.230 Robert Tseng: And, if I not to do it…
100 00:13:11.020 ⇒ 00:13:18.950 Robert Tseng: Alright, well, that’ll be… once we get Acosta’s access, that’ll kind of inform the H1 demand plan.
101 00:13:19.140 ⇒ 00:13:22.129 Robert Tseng: That’ll get assigned then.
102 00:13:22.380 ⇒ 00:13:30.180 Robert Tseng: So… I guess some of these need to be in internal review, so… What needs?
103 00:13:30.180 ⇒ 00:13:39.480 Amber Lin: Yeah, 61 and 62 are in the same slides, so you can put them in review. And then…
104 00:13:44.550 ⇒ 00:13:55.900 Amber Lin: We didn’t do it for Walmart, we did it for Shopify, we just did a Shopify analysis, so, like, we can create a ticket to review that.
105 00:14:00.170 ⇒ 00:14:03.939 Robert Tseng: Alright, so we still haven’t done the Amazon to Shopify comparison, though, right?
106 00:14:04.550 ⇒ 00:14:06.640 Amber Lin: Nope.
107 00:14:07.840 ⇒ 00:14:08.540 Robert Tseng: Okay.
108 00:14:08.850 ⇒ 00:14:11.169 Robert Tseng: That could be for the end of this week.
109 00:14:11.720 ⇒ 00:14:16.039 Robert Tseng: So, now that we have it, like.
110 00:14:16.040 ⇒ 00:14:20.189 Henry Zhao: I feel like we’ve done most of this, actually, Amber, but let’s schedule some time to just go over it together.
111 00:14:22.210 ⇒ 00:14:24.359 Robert Tseng: Have we touched Walmart yet?
112 00:14:24.580 ⇒ 00:14:30.550 Amber Lin: Yeah, we looked at it together. It’s… the data’s just a little bit… more limited.
113 00:14:33.040 ⇒ 00:14:41.509 Amber Lin: So we’ll just do the Shopify, Amazon, Walmart together. We’ll do a traffic comparison, and we’ll do a sales comparison.
114 00:14:43.700 ⇒ 00:14:44.380 Robert Tseng: Okay.
115 00:14:48.290 ⇒ 00:14:55.249 Robert Tseng: Yeah, I’m… that’s fine. Not much of their business is on Walmart, so I’m not that worried about it.
116 00:14:56.390 ⇒ 00:15:00.610 Robert Tseng: But okay, seems like we’re gonna do that. Alright, that is… that should be enough for this.
117 00:15:00.610 ⇒ 00:15:05.300 Henry Zhao: Quick question is, like, what are we trying to accomplish with the Walmart data? Like, what is in their control?
118 00:15:05.400 ⇒ 00:15:07.809 Henry Zhao: to improve or want to improve with Walmart.
119 00:15:08.400 ⇒ 00:15:10.599 Robert Tseng: The same thing on the other channels, I think.
120 00:15:10.840 ⇒ 00:15:12.690 Robert Tseng: So,
121 00:15:13.620 ⇒ 00:15:21.100 Robert Tseng: you know, if they are selling different products on Walmart that are performing better than Shopify and Amazon, I think we can highlight that.
122 00:15:21.220 ⇒ 00:15:24.770 Robert Tseng: Yeah, if the… if… I mean, I don’t know if the tr… if the…
123 00:15:26.000 ⇒ 00:15:40.680 Robert Tseng: the customer behavior trend is any different between… across the three marketplaces, I think we should call that out as well. But I don’t think they have a Walmart… I don’t think they have a Walmart strategy, per se. I mean, they want to do more B2B, which is…
124 00:15:40.920 ⇒ 00:15:44.509 Robert Tseng: helpful, so… I mean, if anything, like.
125 00:15:44.740 ⇒ 00:15:47.079 Robert Tseng: I think Walmart is the newest of the three.
126 00:15:47.220 ⇒ 00:15:51.469 Robert Tseng: And it’s still early on, so being able to, like.
127 00:15:51.650 ⇒ 00:15:57.370 Robert Tseng: under… you can… you’re diagnosing Walmart traffic and sales.
128 00:15:57.820 ⇒ 00:16:11.649 Robert Tseng: you know, you could limit it to the first… I’m pretty sure it’s… they’re still in their first few months. But let’s say they want to… which I think they are expanding into Target, and, other… and other retail, then…
129 00:16:11.920 ⇒ 00:16:19.550 Robert Tseng: that then what we’re learning from Walmart can inform, kind of, how they should expect those launches to go as well.
130 00:16:23.750 ⇒ 00:16:30.070 Robert Tseng: Right, so you’re basically… to me, the goal, because the volume is so low, you’re trying to just understand
131 00:16:31.050 ⇒ 00:16:37.800 Robert Tseng: When they open a new… when they launch into a new channel, which products…
132 00:16:37.980 ⇒ 00:16:45.789 Robert Tseng: are… I mean, maybe they’re… it’s negotiated for each, so maybe the product isn’t the right one, but you’re trying to understand,
133 00:16:47.550 ⇒ 00:16:54.530 Robert Tseng: how… How quickly that channel gets established, I think…
134 00:16:54.640 ⇒ 00:17:02.420 Robert Tseng: I think it’s also very channel-specific, so I… once again, like, I don’t think there’s, like, a… there’s not a playbook for this, but, like, if I’m thinking about…
135 00:17:02.500 ⇒ 00:17:18.830 Robert Tseng: when I was, like, launching a product into Costco before, and, like, not sure how that launch was gonna go, I had to just use, like, another comparable, like, channel that we were in, which was… which was Walmart at the time, or not Walmart,
136 00:17:19.980 ⇒ 00:17:35.769 Robert Tseng: I forget which other channel I used as a comp for Costco, but whatever. The point is, like, I used another channel to benchmark what the launch for Costco was going to be. It was a good enough comp, it, like, gave us an idea of, like, how the Costco launch was gonna go.
137 00:17:35.770 ⇒ 00:17:40.340 Robert Tseng: And that, that, that helps, like, inform what, you know.
138 00:17:40.340 ⇒ 00:17:58.269 Robert Tseng: some demand planning on that side. So, I know we don’t own the forecast, we don’t own the supply chain either, so, like, it’s not like we’re actually going to be taking action off of these, but I think that’s… you know, we’re still early stages, like, we don’t really understand, like, how they’re selling across all these channels still.
139 00:17:59.810 ⇒ 00:18:00.480 Henry Zhao: Okay.
140 00:18:00.810 ⇒ 00:18:01.540 Robert Tseng: Yeah.
141 00:18:03.650 ⇒ 00:18:06.360 Robert Tseng: Okay.
142 00:18:06.570 ⇒ 00:18:13.610 Robert Tseng: And then… That’s fine. There were some comments from…
143 00:18:13.920 ⇒ 00:18:24.089 Robert Tseng: Byron, I’ll probably just surface them in Slack, and we’ll talk about them later, but I think that’s… that’s… that’s fine. He’s just kind of clarifying what’s inattentive and whatever.
144 00:18:25.230 ⇒ 00:18:30.029 Robert Tseng: So, yeah, that might help with the Klaviyo.
145 00:18:30.250 ⇒ 00:18:31.060 Robert Tseng: Stuff.
146 00:18:31.220 ⇒ 00:18:35.479 Robert Tseng: But, okay, anyway, I think that’s… yeah, that should be enough for this week.
147 00:18:35.670 ⇒ 00:18:39.230 Robert Tseng: Let’s move to insomnia.
148 00:18:39.720 ⇒ 00:18:51.169 Robert Tseng: So, I already spoke with Zoran earlier, so I’m not gonna kind of rehash that. I met with Seznim last week on the Daily Impact scorecard redesign, so kind of expecting her to finish that this week.
149 00:18:51.470 ⇒ 00:19:01.370 Robert Tseng: Yeah, I guess, like… How… how are we on follow-ups with Matt and, Bertie?
150 00:19:01.830 ⇒ 00:19:17.529 Amber Lin: Matt didn’t respond yet. I’ll follow up with him again. Okay. I’m trying to schedule a birdie today, and I did the segment, Opportunity Sizing, looks promising, would love review on that. It’s also in the slides.
151 00:19:17.670 ⇒ 00:19:20.020 Amber Lin: C.
152 00:19:21.830 ⇒ 00:19:24.009 Amber Lin: He met Solove on my side.
153 00:19:25.200 ⇒ 00:19:25.860 Robert Tseng: Okay.
154 00:19:36.000 ⇒ 00:19:39.730 Robert Tseng: Okay, yeah, I owe you reviews on that as well.
155 00:19:41.100 ⇒ 00:19:42.240 Robert Tseng: Great.
156 00:19:48.730 ⇒ 00:19:53.449 Robert Tseng: Yeah, I mean, I think… I think that’s… that’s pretty much all we have for this week, for now.
157 00:19:53.580 ⇒ 00:19:57.809 Robert Tseng: Okay, let’s move into Eden.
158 00:19:59.010 ⇒ 00:20:06.289 Robert Tseng: Yeah, want to… I mean, we have a lot of stuff in cycle right now, so I want to spend most of the time here.
159 00:20:06.450 ⇒ 00:20:16.670 Robert Tseng: let’s go through, kind of, maybe we’ll start just top-down. Ashwini, kind of, what are you working on? Are these still in progress? Like, what’s the status on these?
160 00:20:17.700 ⇒ 00:20:20.559 Ashwini Sharma: This is under review.
161 00:20:22.000 ⇒ 00:20:24.480 Ashwini Sharma: Can you open that once?
162 00:20:24.780 ⇒ 00:20:25.410 Robert Tseng: Yeah.
163 00:20:25.710 ⇒ 00:20:26.350 Ashwini Sharma: Oops.
164 00:20:29.930 ⇒ 00:20:31.950 Ashwini Sharma: This is,
165 00:20:34.730 ⇒ 00:20:43.440 Ashwini Sharma: This is a 14-day one, yeah, yeah, this has been reviewed by, Zoran already, so I’ll ask him to, you know, accept the PR request and close it.
166 00:20:44.370 ⇒ 00:20:44.780 Robert Tseng: Okay.
167 00:20:44.780 ⇒ 00:20:48.770 Ashwini Sharma: So this is sort of done, yeah. Let’s look into the other one.
168 00:20:56.390 ⇒ 00:20:56.910 Robert Tseng: Yep.
169 00:21:01.770 ⇒ 00:21:04.619 Ashwini Sharma: Okay, so this was the initial ticket which,
170 00:21:05.610 ⇒ 00:21:08.639 Ashwini Sharma: Which was changed in the, in the previous ticket.
171 00:21:12.560 ⇒ 00:21:14.369 Robert Tseng: Okay, so we can just cancel this one?
172 00:21:14.370 ⇒ 00:21:15.640 Ashwini Sharma: Y-yeah, yeah.
173 00:21:16.540 ⇒ 00:21:17.160 Robert Tseng: Okay.
174 00:21:18.860 ⇒ 00:21:21.339 Robert Tseng: How about this one?
175 00:21:21.940 ⇒ 00:21:23.810 Ashwini Sharma: Yeah, this is done.
176 00:21:25.700 ⇒ 00:21:29.590 Ashwini Sharma: Maybe Avish can take a look at the pipelines.
177 00:21:33.970 ⇒ 00:21:40.890 Robert Tseng: Great. And then, I know Metaplane is… yeah.
178 00:21:43.440 ⇒ 00:21:53.690 Ashwini Sharma: Sorry, yeah. This is, not exactly a task, basically, I’m just exploring Metaplane and what we can do on top of Metaplane. I have some findings, and
179 00:21:54.030 ⇒ 00:21:58.500 Ashwini Sharma: Maybe I’ll just document it in one of the… Notion documents.
180 00:22:00.660 ⇒ 00:22:04.240 Robert Tseng: Okay So…
181 00:22:05.640 ⇒ 00:22:13.569 Ashwini Sharma: Or maybe, like, if we can add more details, like, basically the output of this ticket should be a document that compares features of,
182 00:22:14.110 ⇒ 00:22:17.310 Ashwini Sharma: Multiple, data observability tools.
183 00:22:31.240 ⇒ 00:22:31.880 Robert Tseng: Okay.
184 00:22:50.000 ⇒ 00:22:55.330 Robert Tseng: Let’s move on to… I don’t think Awash is on this call, so I’ll skip him.
185 00:22:55.440 ⇒ 00:23:01.659 Robert Tseng: Yeah, Casey… so, I mean, like, there’s… let’s just talk… can we just go through everything Catalyst-related, so…
186 00:23:02.980 ⇒ 00:23:10.129 Robert Tseng: I mean, I know that this is really more in Zoran’s court, so him not having… being here is a bit tough, but…
187 00:23:10.260 ⇒ 00:23:12.050 Robert Tseng: Yeah, is this done?
188 00:23:13.910 ⇒ 00:23:18.939 Casie Aviles: This is in review, I pretty much put all my updates here.
189 00:23:19.360 ⇒ 00:23:20.420 Casie Aviles: Okay.
190 00:23:21.000 ⇒ 00:23:23.770 Casie Aviles: I think my only concern is that there’s still…
191 00:23:24.510 ⇒ 00:23:30.930 Casie Aviles: with whatever I tried, whichever queries I tried, there’s still just very few refunds. I keep getting few refunds.
192 00:23:31.150 ⇒ 00:23:31.970 Henry Zhao: I can double check it.
193 00:23:32.650 ⇒ 00:23:33.119 Henry Zhao: I’ll double check.
194 00:23:33.120 ⇒ 00:23:38.779 Casie Aviles: So… Yeah, and I’m also going to meet with Ashwini.
195 00:23:39.610 ⇒ 00:23:41.170 Casie Aviles: Do check, as well.
196 00:23:42.280 ⇒ 00:23:43.990 Casie Aviles: To investigate that part.
197 00:23:44.180 ⇒ 00:23:45.720 Casie Aviles: But yeah,
198 00:23:46.250 ⇒ 00:23:51.590 Casie Aviles: So far, that’s what I have. I did just create, like, a notebook for now as well, in order to
199 00:23:51.870 ⇒ 00:23:56.429 Casie Aviles: Once we have the data, it’s just going to run… I’m just going to run the notebook.
200 00:23:57.200 ⇒ 00:23:58.560 Casie Aviles: But yeah. Okay.
201 00:24:00.870 ⇒ 00:24:06.129 Robert Tseng: Let’s close this out today. Like, this has been kind of just sitting here for a couple weeks, so…
202 00:24:07.100 ⇒ 00:24:12.470 Robert Tseng: I… it’s like, at this point, it’s all… it’s kind of… I mean, between you and Henry to close this out, so…
203 00:24:20.740 ⇒ 00:24:23.560 Robert Tseng: I’m gonna escalate this one…
204 00:24:23.790 ⇒ 00:24:29.859 Henry Zhao: Yeah, this one’s been a while, but it’s not high prime, because obviously Catalyst was only implemented 2 months ago, so…
205 00:24:30.800 ⇒ 00:24:31.490 Robert Tseng: Okay.
206 00:24:32.970 ⇒ 00:24:38.720 Robert Tseng: Yeah, did we finish this?
207 00:24:39.370 ⇒ 00:24:45.480 Robert Tseng: like… I know we added some test results, like, did this actually happen?
208 00:24:47.320 ⇒ 00:24:54.630 Casie Aviles: For the test results, we just collected the questions from Eden, but I wasn’t able to test it yet. I can do that.
209 00:24:54.940 ⇒ 00:24:57.300 Casie Aviles: today, but I was just wondering, like.
210 00:24:58.210 ⇒ 00:25:02.539 Casie Aviles: What’s a good, like, hard stop to the spike for now? Because I think…
211 00:25:04.260 ⇒ 00:25:07.160 Casie Aviles: We can continue to add, like, more…
212 00:25:08.060 ⇒ 00:25:13.120 Casie Aviles: We can continue to spike on other stuff, but, like, I was just wondering what’s a good, like.
213 00:25:15.150 ⇒ 00:25:21.249 Casie Aviles: Yeah, what’s a good stop for this in order to pause this and have it completed?
214 00:25:22.320 ⇒ 00:25:29.990 Robert Tseng: Yeah, well, I think, to me, the spike is done when we’ve… I mean, I guess we’ve picked a model for you to… I mean…
215 00:25:30.180 ⇒ 00:25:34.690 Robert Tseng: Is there a demo of, like, we can answer certain questions?
216 00:25:34.950 ⇒ 00:25:40.040 Robert Tseng: Like… It needs to just run…
217 00:25:40.740 ⇒ 00:25:44.099 Robert Tseng: Accurately on, on, like, one set of use cases.
218 00:25:44.390 ⇒ 00:25:52.580 Robert Tseng: validated by, like, our… by our team manually. And then once it’s good, then we can actually just put it in front of them and be like, look.
219 00:25:52.710 ⇒ 00:25:59.549 Robert Tseng: Eden, anytime you need to ask questions around this, you can use this feature now, and, like, we can continue to expand it from there, so…
220 00:25:59.760 ⇒ 00:26:03.119 Robert Tseng: I guess that, to me, is, like, when this is done.
221 00:26:04.430 ⇒ 00:26:05.020 Casie Aviles: Okay.
222 00:26:05.150 ⇒ 00:26:13.779 Casie Aviles: Yeah, so there are just… there are test questions in the… in the spike, but I… I… I will add, like, these actual client questions.
223 00:26:14.470 ⇒ 00:26:15.100 Robert Tseng: Okay.
224 00:26:15.710 ⇒ 00:26:19.880 Robert Tseng: Yeah. I’ll keep that in there.
225 00:26:23.260 ⇒ 00:26:23.760 Casie Aviles: This…
226 00:26:23.760 ⇒ 00:26:30.209 Robert Tseng: Alright, I know the session replayed, you’re still blocked on, you’re not actually… did you guys meet with Danny Valdez?
227 00:26:30.970 ⇒ 00:26:33.839 Henry Zhao: Ryan is gonna help us implement it.
228 00:26:34.420 ⇒ 00:26:35.070 Robert Tseng: Okay.
229 00:26:35.520 ⇒ 00:26:38.000 Casie Aviles: We sent him instructions already.
230 00:26:38.130 ⇒ 00:26:39.580 Casie Aviles: Okay, so thank you.
231 00:26:43.100 ⇒ 00:26:49.380 Robert Tseng: Alright, let’s move on then. Demlade, there’s a few things that are blocked here, so I want to call it out. So…
232 00:26:49.570 ⇒ 00:26:56.509 Robert Tseng: This is the classic BASC hasn’t added things, right? Anything… anything else that’s knocked out.
233 00:26:56.510 ⇒ 00:26:56.970 Demilade Agboola: on.
234 00:26:56.970 ⇒ 00:27:00.340 Robert Tseng: I mean, it’s been sitting here for a while, I’m just gonna move it out of cycle.
235 00:27:01.100 ⇒ 00:27:08.479 Demilade Agboola: Yeah, so for the Basque, I know Basque is trying to work on the valve size. I know that…
236 00:27:08.670 ⇒ 00:27:11.789 Demilade Agboola: I know Harry sent a message that IFX last week.
237 00:27:12.370 ⇒ 00:27:16.670 Demilade Agboola: So that is potentially something that will come in very soon.
238 00:27:16.930 ⇒ 00:27:22.800 Demilade Agboola: The offluence data modeling is being blocked by… the API.
239 00:27:23.220 ⇒ 00:27:29.289 Demilade Agboola: Posomic is trying to connect to this right now. They had to connect to Uploence, and…
240 00:27:29.840 ⇒ 00:27:44.969 Demilade Agboola: Effectively, that was… was going on throughout the Thanksgiving weekend, but Nathan, our plugin, Polyatomic, says he should have this up and running today, and he’ll let us know when that is done, so once that data starts coming in, we can start the data modeling.
241 00:27:45.340 ⇒ 00:27:49.480 Demilade Agboola: So… Today, all things being equal.
242 00:27:49.480 ⇒ 00:27:50.130 Robert Tseng: Okay.
243 00:27:52.090 ⇒ 00:27:59.739 Robert Tseng: Alright, so it’s still blocked, but, I’m gonna adjust this, gonna say, okay, assuming that it’s done, we can probably adjust this to…
244 00:28:00.920 ⇒ 00:28:02.200 Robert Tseng: Modeling.
245 00:28:03.190 ⇒ 00:28:06.880 Robert Tseng: Great.
246 00:28:07.120 ⇒ 00:28:14.860 Robert Tseng: Alright, and then… what about this one? Is this related? Seems like we got deprioritized, like, what does this mean? Do I just take it out of cycle?
247 00:28:16.180 ⇒ 00:28:18.909 Henry Zhao: I think Camry will probably be the best presencer.
248 00:28:19.120 ⇒ 00:28:20.200 Henry Zhao: I think this is done.
249 00:28:20.890 ⇒ 00:28:21.540 Robert Tseng: Okay.
250 00:28:21.810 ⇒ 00:28:23.150 Henry Zhao: The data’s done, yeah.
251 00:28:23.780 ⇒ 00:28:24.400 Robert Tseng: Fixed.
252 00:28:24.810 ⇒ 00:28:32.350 Robert Tseng: Order journey goal tracker, what is… yeah.
253 00:28:32.960 ⇒ 00:28:36.350 Robert Tseng: Is this… is this… I mean, this is, like, from 3 months ago, like…
254 00:28:36.350 ⇒ 00:28:38.869 Demilade Agboola: Okay, yeah, we could probably cancel this.
255 00:28:38.870 ⇒ 00:28:40.460 Robert Tseng: Okay, we’re canceling that.
256 00:28:40.680 ⇒ 00:28:44.130 Robert Tseng: And…
257 00:28:47.660 ⇒ 00:28:51.650 Demilade Agboola: Yeah, so this is still the opens. Oh, so this is, like, reverse ETL.
258 00:28:51.980 ⇒ 00:28:57.620 Demilade Agboola: So once we get the data, and we have the logic, we want to be able to push some of this back.
259 00:28:57.970 ⇒ 00:29:00.179 Demilade Agboola: 2… a plus.
260 00:29:04.260 ⇒ 00:29:08.149 Robert Tseng: Push the version 3D back to upload once.
261 00:29:09.140 ⇒ 00:29:14.290 Robert Tseng: Okay, so this is still… Blocked.
262 00:29:15.730 ⇒ 00:29:17.910 Robert Tseng: Public director, sure.
263 00:29:20.620 ⇒ 00:29:21.370 Robert Tseng: Gosh.
264 00:29:27.870 ⇒ 00:29:33.810 Robert Tseng: Okay, and then, yeah, so that seems to be that.
265 00:29:35.440 ⇒ 00:29:42.189 Robert Tseng: Okay, I feel like we’re pretty light on the data modeling work.
266 00:29:44.170 ⇒ 00:29:50.189 Demilade Agboola: Yeah, I think… I think the request right now from Eden might be more stable, and, like.
267 00:29:50.190 ⇒ 00:29:50.580 Henry Zhao: Yeah.
268 00:29:50.580 ⇒ 00:29:57.350 Demilade Agboola: repetitive, so we’re tweaking the same data that we have. So there’s… there’s not a lot of, like, expansion going on right now.
269 00:30:00.890 ⇒ 00:30:01.870 Henry Zhao: Yeah, exactly.
270 00:30:03.850 ⇒ 00:30:04.600 Robert Tseng: Okay.
271 00:30:10.380 ⇒ 00:30:17.659 Robert Tseng: Well, we can… we can get to that. We can get… cover that more later, but yeah, Henry, let’s… let’s kind of go through yours.
272 00:30:17.660 ⇒ 00:30:21.099 Henry Zhao: Yeah, I already went through all of these and cleaned them up, so…
273 00:30:21.330 ⇒ 00:30:27.529 Henry Zhao: This is the up-to-date one. My focus this week is getting the pharmacy stuff done and some forecasting work done with SEZM.
274 00:30:28.260 ⇒ 00:30:28.930 Robert Tseng: Okay.
275 00:30:29.430 ⇒ 00:30:31.289 Henry Zhao: So that’s what pretty much all of these things are.
276 00:30:36.410 ⇒ 00:30:41.910 Robert Tseng: Yeah, but there are no… there are no deadlines on any of these, so I guess, like, I’m still needing to have to go in and…
277 00:30:42.100 ⇒ 00:30:43.859 Robert Tseng: admin, right? So…
278 00:30:44.930 ⇒ 00:30:45.959 Henry Zhao: This one is done.
279 00:30:46.450 ⇒ 00:30:47.130 Robert Tseng: Okay.
280 00:30:47.420 ⇒ 00:30:48.020 Henry Zhao: Yeah.
281 00:30:49.710 ⇒ 00:30:50.520 Robert Tseng: Stone…
282 00:30:50.520 ⇒ 00:30:57.139 Henry Zhao: Morning, okay. And then this next two, like, we’re just still waiting on in Rebecca to pay Pharmetica for the API access.
283 00:30:59.890 ⇒ 00:31:09.200 Henry Zhao: I’m gonna probably, while I wait for Michelle, I’m gonna talk to… while I wait for Rebecca, I’m gonna also talk to Michelle this morning, just see, like, what can I do in the meantime, like, whether in pharmac…
284 00:31:09.200 ⇒ 00:31:18.660 Robert Tseng: Why do we need it? Like, is it just so that we can move the data to BigQuery? Or, like, why is Rebecca so resistant to paperless?
285 00:31:19.750 ⇒ 00:31:21.890 Henry Zhao: I don’t think she’s resistant, I just think she hasn’t done it yet.
286 00:31:23.840 ⇒ 00:31:24.770 Robert Tseng: Okay.
287 00:31:26.790 ⇒ 00:31:33.650 Henry Zhao: And I think the super high-priced stuff she has, like, in Pharmetica, so she’s not, like, super worried about… that’s just my read on it.
288 00:31:33.930 ⇒ 00:31:37.670 Henry Zhao: About, like, actual urgency, yeah. But that’s what I’m gonna double-check today.
289 00:31:38.210 ⇒ 00:31:40.249 Henry Zhao: It’s just to make sure that…
290 00:31:41.420 ⇒ 00:31:46.079 Henry Zhao: Yeah, like, the real urgent stuff that Rebecca cares about, she can get within Pharmetica on her own.
291 00:31:46.930 ⇒ 00:31:47.600 Robert Tseng: Okay.
292 00:31:48.040 ⇒ 00:31:48.570 Henry Zhao: Yeah.
293 00:31:49.470 ⇒ 00:31:50.080 Henry Zhao: Sounds like they’re.
294 00:31:50.080 ⇒ 00:31:50.699 Robert Tseng: She’s like.
295 00:31:50.700 ⇒ 00:31:54.040 Henry Zhao: oh, I need some new revenue, like, that’s in Pharmetica, right? So…
296 00:31:54.180 ⇒ 00:31:57.889 Henry Zhao: Moving it to Tableau doesn’t really add additional value for her.
297 00:31:58.580 ⇒ 00:31:59.250 Robert Tseng: Okay.
298 00:32:02.710 ⇒ 00:32:06.580 Robert Tseng: So, this is still… Blocked.
299 00:32:06.770 ⇒ 00:32:07.460 Robert Tseng: And this is…
300 00:32:07.460 ⇒ 00:32:13.270 Henry Zhao: I would change urgent to high. I would change urgent to high now, because what the client is showing me is it’s not actually that urgent.
301 00:32:14.090 ⇒ 00:32:17.409 Robert Tseng: Yeah, I mean, to me, this is the same as the other one, so I’m gonna cancel this.
302 00:32:34.210 ⇒ 00:32:36.860 Robert Tseng: Okay, what is this?
303 00:32:37.440 ⇒ 00:32:42.970 Henry Zhao: Yeah, so this is, like I said, I’m gonna look at Brad’s sheet and your forecasting sheet and see what we can do.
304 00:32:43.150 ⇒ 00:32:47.749 Henry Zhao: Right now, for pharmacy without the data from BASC, which is basically vial size.
305 00:32:49.930 ⇒ 00:32:57.640 Henry Zhao: So I’m gonna look at, kind of, the data he has, his goals, and figure out what are some analyses that we can do already with the data that we have that would be of value to him by end of year.
306 00:32:58.190 ⇒ 00:33:01.230 Henry Zhao: And then maybe also propose some analyses for 2026.
307 00:33:04.130 ⇒ 00:33:11.040 Henry Zhao: Yeah, because again, like I said, the last few weeks we were focused on other things, now we can focus on analysis. So that’s my main focus this week, is to…
308 00:33:11.440 ⇒ 00:33:13.190 Henry Zhao: Look for analysis opportunities.
309 00:33:13.340 ⇒ 00:33:15.089 Henry Zhao: And make those appointments. Yep.
310 00:33:15.930 ⇒ 00:33:16.890 Robert Tseng: Okay.
311 00:33:20.350 ⇒ 00:33:23.139 Robert Tseng: And then…
312 00:33:23.810 ⇒ 00:33:27.430 Henry Zhao: Yeah, so this I’m gonna go with… talk with Zezim on tomorrow to, like.
313 00:33:27.620 ⇒ 00:33:30.630 Henry Zhao: Ash will figure out what we can do for forecasting for finance.
314 00:33:31.290 ⇒ 00:33:46.470 Henry Zhao: So, we’ll eventually want to make a dash where we can put in, like, hypothetical ad spend, and NCAC, and see, like, if we spend this much, this is how much new users, new customers are going to get, like, this is how the pharmacy demands would be, and things like that, so that the ELT can prepare for the future.
315 00:33:49.160 ⇒ 00:33:53.410 Robert Tseng: Yeah, I mean, they’ve definitely had a wish list of things that they wanted to add, so…
316 00:33:53.960 ⇒ 00:34:01.479 Robert Tseng: I don’t think these are everything here. So, I think, yeah, you guys would probably need to…
317 00:34:04.110 ⇒ 00:34:10.560 Robert Tseng: I mean, you might even need to work with Jonah, like, ask him, like, kind of make the doc with him,
318 00:34:10.830 ⇒ 00:34:11.489 Robert Tseng: whoop.
319 00:34:14.719 ⇒ 00:34:20.429 Henry Zhao: I think a few months ago, Annie or someone already did work with Jonah to get that, so I can meet with him and just see if it’s still up to date.
320 00:34:20.639 ⇒ 00:34:25.319 Henry Zhao: But we already have, like, a plan and an idea, so… But yeah, I can re-sync with Jonah.
321 00:34:26.500 ⇒ 00:34:27.100 Robert Tseng: Yeah.
322 00:34:28.350 ⇒ 00:34:31.089 Henry Zhao: We just pushed it off because it didn’t seem that high prime back in that time.
323 00:34:31.889 ⇒ 00:34:32.609 Robert Tseng: Yeah.
324 00:34:37.379 ⇒ 00:34:41.679 Robert Tseng: Okay, and then… What is this?
325 00:34:41.679 ⇒ 00:34:52.159 Henry Zhao: This one is just waiting on Zoran. So Zoran is changing transaction ID in all of the attribution stuff to session ID. Once we do that, I just need to change it in the code, so it should be very fast.
326 00:34:59.230 ⇒ 00:34:59.830 Robert Tseng: Okay?
327 00:35:00.620 ⇒ 00:35:04.810 Henry Zhao: that I have a meeting with Seism tomorrow, about Product Insights, yeah.
328 00:35:05.400 ⇒ 00:35:05.990 Robert Tseng: Yep.
329 00:35:08.260 ⇒ 00:35:12.460 Henry Zhao: Yeah, this one Rico created, I’m just gonna look into this desk, see what we need to do here.
330 00:35:13.870 ⇒ 00:35:14.560 Robert Tseng: Okay.
331 00:35:17.930 ⇒ 00:35:21.930 Henry Zhao: Again, this is just, like, looking at analysis opportunities, but for products.
332 00:35:26.390 ⇒ 00:35:33.120 Henry Zhao: Alright, the next one is once Ryan implements heatmaps and session replays, I’m just gonna create a quick proposal on, like, what…
333 00:35:33.470 ⇒ 00:35:40.220 Henry Zhao: This… what we can do to, get insights out of the heat maps and session replays, and what we can do to improve the intake, for example.
334 00:35:43.920 ⇒ 00:35:51.630 Henry Zhao: Whether it’s, like, improving the back button, or, making certain pages less confusing, like, this should also be a pretty quick analysis.
335 00:35:51.980 ⇒ 00:35:55.249 Henry Zhao: I can… I can eventually get Casey involved in this if… if we want.
336 00:35:55.860 ⇒ 00:35:57.410 Robert Tseng: Yeah, okay.
337 00:35:57.660 ⇒ 00:36:02.829 Robert Tseng: I think, yeah, once… once this is… this should actually be moved to KC.
338 00:36:03.370 ⇒ 00:36:15.479 Robert Tseng: So, use a mixed panel to… To look at, optimization opportunities.
339 00:36:17.400 ⇒ 00:36:18.740 Robert Tseng: Okay.
340 00:36:22.710 ⇒ 00:36:26.420 Robert Tseng: Analyze, drop off rates from anything.
341 00:36:27.500 ⇒ 00:36:34.140 Robert Tseng: So… And this will probably be 2… I mean, you’re still blocked.
342 00:36:34.960 ⇒ 00:36:39.869 Henry Zhao: Yeah, so Casey, we can go over this when you have some time. I already have some ideas that we can tell you about.
343 00:36:41.400 ⇒ 00:36:42.410 Casie Aviles: Okay, blocked.
344 00:36:42.410 ⇒ 00:36:45.179 Robert Tseng: by Ryan, implementation.
345 00:36:51.540 ⇒ 00:36:52.849 Henry Zhao: Okay.
346 00:36:57.710 ⇒ 00:36:59.280 Henry Zhao: And then the next one, yeah.
347 00:36:59.570 ⇒ 00:37:00.630 Henry Zhao: Is this what he talked about?
348 00:37:00.630 ⇒ 00:37:04.859 Robert Tseng: I did… yeah, I know, I just… there’s nothing assigned here, so…
349 00:37:07.460 ⇒ 00:37:10.060 Robert Tseng: I don’t really think this is, like…
350 00:37:14.620 ⇒ 00:37:15.950 Robert Tseng: Product…
351 00:37:21.040 ⇒ 00:37:25.599 Robert Tseng: So, I mean, to me, like, you kind of need to outline some of these things, because, like.
352 00:37:28.080 ⇒ 00:37:34.269 Robert Tseng: Yeah, I mean, these are a lot of domains. You’re, like, kind of doing pharmacy, finance, and just products, so…
353 00:37:35.130 ⇒ 00:37:42.600 Robert Tseng: I mean, you’re gonna go and look into all these things, and we’re gonna have to figure out, like, what are you actually gonna prioritize,
354 00:37:43.020 ⇒ 00:37:43.750 Robert Tseng: Yeah.
355 00:37:45.360 ⇒ 00:37:49.630 Robert Tseng: So, I mean, I don’t know, I’m just… I’m just telling you, are you… are you actually gonna be able to…
356 00:37:49.970 ⇒ 00:37:54.850 Robert Tseng: Just come up with a bunch of ideas and know how to, like, prioritize them.
357 00:37:54.850 ⇒ 00:37:57.410 Henry Zhao: Yeah, and I’ll run them through you, like, midweek.
358 00:37:57.990 ⇒ 00:37:58.710 Robert Tseng: Okay.
359 00:37:58.710 ⇒ 00:38:03.599 Henry Zhao: Or the team. Yeah, I’ll put it either incline Eden, like, my thoughts, or we’ll talk about our one-on-one.
360 00:38:03.900 ⇒ 00:38:14.970 Robert Tseng: Sure, yeah, I mean, there’s no rush to do a deck or anything, that’s… we’re not up for that until next week, but I think by that point, I would have… I mean, ideally, if we have the ideas, like, I could send them out this week.
361 00:38:15.020 ⇒ 00:38:18.619 Henry Zhao: We can… we don’t have to wait till next week to get approval on the…
362 00:38:19.400 ⇒ 00:38:32.339 Henry Zhao: Yeah, but I want to get a head start on this, right? Because we know how things get dragged out, so I want to at least have the ideas by tomorrow one-on-one, or end of day to get, client Eden chats some thoughts from the team.
363 00:38:32.840 ⇒ 00:38:33.420 Robert Tseng: Great.
364 00:38:33.820 ⇒ 00:38:35.290 Robert Tseng: Okay. And some of this might end up getting.
365 00:38:35.290 ⇒ 00:38:37.370 Henry Zhao: deprioritized, right? So, we’ll see.
366 00:38:38.090 ⇒ 00:38:38.850 Robert Tseng: Sure.
367 00:38:38.850 ⇒ 00:38:41.339 Henry Zhao: But at least it gets to give me guidance on what to work on this week.
368 00:38:41.730 ⇒ 00:38:48.190 Henry Zhao: So this one, is there anything additional on this one? So this one also Rico created, I’m not sure which meeting this came from,
369 00:38:48.540 ⇒ 00:38:53.209 Henry Zhao: But was this just starting to get insights to present on the bi-weekly deck for ELT?
370 00:38:53.210 ⇒ 00:38:55.640 Robert Tseng: Yes, yes, yeah, so…
371 00:38:55.640 ⇒ 00:38:58.169 Henry Zhao: It’s kind of like the overarching task for the other things that are in here, right?
372 00:38:58.170 ⇒ 00:38:59.559 Robert Tseng: Yeah, I’m gonna delete this.
373 00:38:59.980 ⇒ 00:39:02.750 Robert Tseng: Okay. And then…
374 00:39:02.750 ⇒ 00:39:19.179 Henry Zhao: This one Ryan wanted us to look at, which is, like, now that we have edge layer data, he wants a dash that combines, kind of, some of the health info, so we can figure out, how we can use this edge layer data along with, like, our… the health data that we’re getting to better target our… our customers.
375 00:39:20.540 ⇒ 00:39:21.390 Robert Tseng: I see.
376 00:39:21.670 ⇒ 00:39:26.749 Henry Zhao: Are people with a certain weight or BMI group, like, more likely to convert, and things like that.
377 00:39:27.190 ⇒ 00:39:29.260 Henry Zhao: So this one might also be good for Casey.
378 00:39:30.240 ⇒ 00:39:30.910 Robert Tseng: Okay.
379 00:39:37.290 ⇒ 00:39:41.650 Robert Tseng: This is the old Look for Studio report, he wants to build something like this in Tableau.
380 00:39:41.650 ⇒ 00:39:43.850 Henry Zhao: Yeah, you won’t have access to it, but yeah.
381 00:39:44.560 ⇒ 00:39:45.240 Robert Tseng: Yeah.
382 00:39:45.240 ⇒ 00:39:47.569 Henry Zhao: Not necessarily Tableau, but he wants to combine the edge layer data.
383 00:39:48.780 ⇒ 00:39:49.340 Robert Tseng: Yeah.
384 00:40:00.460 ⇒ 00:40:04.500 Robert Tseng: Great. Then the last one here…
385 00:40:04.500 ⇒ 00:40:10.260 Henry Zhao: No, there’s one here with Adam, 828, so this one is an old one, but this one requires some modeling.
386 00:40:10.790 ⇒ 00:40:15.890 Henry Zhao: I don’t know if we ever ended up getting to do this modeling demo at it. Do you remember if you ended up being able to do this modeling?
387 00:40:17.360 ⇒ 00:40:21.590 Henry Zhao: Should we cancel it, or since modeling work is light, do we want to work on that this week?
388 00:40:23.130 ⇒ 00:40:25.620 Demilade Agboola: What’s the priority on this?
389 00:40:26.560 ⇒ 00:40:30.869 Henry Zhao: Very low, because Adam hasn’t mentioned it since, like, 3 months ago.
390 00:40:33.170 ⇒ 00:40:34.020 Demilade Agboola: Hmm…
391 00:40:36.650 ⇒ 00:40:44.269 Demilade Agboola: I think we have done part of it, but I’ll have to check, because this has been out of my scope. I’ll have to check and see what has been done, what remains to be done, and I’ll let you know.
392 00:40:44.270 ⇒ 00:40:47.549 Henry Zhao: Yeah, Robert, if you want to give this to Demilade as, like, maybe extra credit, or, like…
393 00:40:49.970 ⇒ 00:40:55.110 Robert Tseng: No, I mean, I think it doesn’t look like we have that much in cycles, so we could probably work on it.
394 00:40:56.060 ⇒ 00:40:56.430 Henry Zhao: Yeah.
395 00:40:56.430 ⇒ 00:40:57.100 Robert Tseng: Okay.
396 00:40:58.240 ⇒ 00:40:58.900 Henry Zhao: Okay.
397 00:40:58.900 ⇒ 00:41:03.189 Robert Tseng: It’s gonna be added to the retention dashboard, right? These are just new metrics for the retention dashboard.
398 00:41:03.190 ⇒ 00:41:04.130 Henry Zhao: Okay.
399 00:41:07.030 ⇒ 00:41:24.509 Henry Zhao: And then the last one is, an AI-related task that was kind of, like, just if I have time, is we have a lot of refund data on, like, why people get asked for refunds. We wanted to use AI to just categorize them, so we can have a dash and say, like, this percentage of refunds were because of this cause, this percentage were for another cause.
400 00:41:24.640 ⇒ 00:41:33.730 Henry Zhao: So Utam sent me, like, this AI generate function that I was gonna look into. So this is just, like, if I have free time, or if I’m waiting on stuff, I can work on this.
401 00:41:34.390 ⇒ 00:41:40.369 Robert Tseng: Okay. I mean, this seems related to what Casey’s working on with the refund.
402 00:41:41.830 ⇒ 00:41:42.780 Robert Tseng: Ding.
403 00:41:43.140 ⇒ 00:41:50.939 Henry Zhao: Yeah, this one is more like a statistical analysis, the other one’s more like using AI to categorize qualitative, yeah, qualitative inputs.
404 00:41:53.120 ⇒ 00:41:56.130 Robert Tseng: I mean, we already have Zendesk, right? So…
405 00:41:56.490 ⇒ 00:42:00.600 Robert Tseng: like, why don’t we… like, we should just do some… I mean, you’re…
406 00:42:02.540 ⇒ 00:42:11.219 Robert Tseng: I don’t know what you’re reading on top of in order to categorize them, but Zendesk data seems to be, like, where this is typically done.
407 00:42:12.830 ⇒ 00:42:14.360 Henry Zhao: I think it is Zendesk data.
408 00:42:14.930 ⇒ 00:42:15.560 Robert Tseng: Okay.
409 00:42:17.240 ⇒ 00:42:20.559 Henry Zhao: Yeah, I think it’s like, use AI to categorize Zendesk, comments.
410 00:42:21.510 ⇒ 00:42:22.270 Robert Tseng: Okay.
411 00:42:27.450 ⇒ 00:42:34.789 Robert Tseng: Cool. I think we’re still a little high here, so actually, I’ll probably… I’ll probably kick this. This is not that important.
412 00:42:35.350 ⇒ 00:42:38.939 Robert Tseng: And also the forecasting is…
413 00:42:38.940 ⇒ 00:42:41.530 Henry Zhao: It’s 7, but it’s, like, gonna bleed into next week, probably.
414 00:42:42.790 ⇒ 00:42:43.220 Robert Tseng: Okay.
415 00:42:43.220 ⇒ 00:42:46.519 Henry Zhao: Like I said, I’ll lower it when I figure out how much hours I actually spent on it this week.
416 00:42:47.030 ⇒ 00:42:47.720 Robert Tseng: Okay.
417 00:42:51.040 ⇒ 00:42:56.219 Robert Tseng: Yeah, I mean, we’re still closing out some of these things from last week, so I think this will go down.
418 00:42:56.470 ⇒ 00:42:59.450 Henry Zhao: And I expect meetings and ad hoc stuff to be like this week as well.
419 00:43:01.550 ⇒ 00:43:02.360 Robert Tseng: Okay.
420 00:43:04.440 ⇒ 00:43:07.989 Robert Tseng: Cool. Yeah, I think this looks good.
421 00:43:12.690 ⇒ 00:43:21.419 Robert Tseng: I think, we already… I think the folks on the other calls have already kind of chatted through some of these other ones, but Element is kind of picking up this week.
422 00:43:21.800 ⇒ 00:43:25.080 Robert Tseng: Lilo is picking up this week,
423 00:43:26.050 ⇒ 00:43:29.039 Robert Tseng: Yeah, so I think maybe we’ll be adding some more of these
424 00:43:29.320 ⇒ 00:43:36.579 Robert Tseng: clients into this strategy and analysis meeting moving forward, but at least for today, I’m not going to talk about them.
425 00:43:41.770 ⇒ 00:43:45.310 Robert Tseng: Okay, cool. Any other questions?
426 00:43:50.860 ⇒ 00:43:55.730 Mustafa Raja: Yeah, for README, you suggested me to, look into a cohort.
427 00:43:55.840 ⇒ 00:43:56.600 Mustafa Raja: Right.
428 00:43:56.890 ⇒ 00:44:02.929 Mustafa Raja: So, I looked into it. It was more, more of a signal that would indicate that
429 00:44:03.030 ⇒ 00:44:06.789 Mustafa Raja: People might, turn on… what’s it called?
430 00:44:07.120 ⇒ 00:44:13.230 Mustafa Raja: The booster pack, but the other event for Booster Pack toggled
431 00:44:13.340 ⇒ 00:44:18.410 Mustafa Raja: Indicated that the people did go ahead and toggle it, right?
432 00:44:20.240 ⇒ 00:44:25.990 Mustafa Raja: So I built my cohort on that, but I got only 6 users, and they don’t have any…
433 00:44:26.770 ⇒ 00:44:30.119 Mustafa Raja: You know, usage at all.
434 00:44:31.100 ⇒ 00:44:32.870 Robert Tseng: For the booster pack? Only 6.
435 00:44:32.870 ⇒ 00:44:33.890 Mustafa Raja: Yeah…
436 00:44:34.720 ⇒ 00:44:35.360 Robert Tseng: Okay.
437 00:44:37.170 ⇒ 00:44:40.340 Robert Tseng: I mean, that’s not enough to really say anything, but okay.
438 00:44:40.340 ⇒ 00:44:45.100 Mustafa Raja: I could, I could record a quick loom on that, so I could explain it better.
439 00:44:45.320 ⇒ 00:44:47.110 Robert Tseng: Yeah. So you can take a proper look.
440 00:44:48.890 ⇒ 00:44:53.489 Robert Tseng: Is that tied to one of the tickets already, or is that just a thing I just said one-off and we need to create a ticket for it?
441 00:44:53.490 ⇒ 00:44:57.579 Mustafa Raja: It should be with the dashboard ticket.
442 00:44:58.280 ⇒ 00:45:02.570 Mustafa Raja: But the context isn’t going to be there, I didn’t put it.
443 00:45:03.100 ⇒ 00:45:04.060 Robert Tseng: Right, okay.
444 00:45:05.810 ⇒ 00:45:06.480 Mustafa Raja: Yeah.
445 00:45:06.870 ⇒ 00:45:13.929 Robert Tseng: Let’s see… This is still…
446 00:45:23.510 ⇒ 00:45:32.760 Robert Tseng: Okay, yeah, I’ll go in and groom that ticket. Yeah, I should… I mean, I’m gonna be talking to README shortly after this, so should be able to follow up on this.
447 00:45:52.200 ⇒ 00:45:58.069 Mustafa Raja: Would be nice if we could ask them if they could, you know, add the metadata for Haas Booster Pack, you know?
448 00:45:58.680 ⇒ 00:45:59.400 Robert Tseng: Yeah.
449 00:46:00.110 ⇒ 00:46:04.359 Robert Tseng: Do you actually want to come with me into the call? They just scheduled it. It’s in 10 minutes.
450 00:46:05.070 ⇒ 00:46:07.659 Mustafa Raja: Oh, yeah, I guess I could…
451 00:46:08.880 ⇒ 00:46:21.670 Robert Tseng: Okay, yeah, then once we wrap up, then I’ll just pull you into that call. It’d be good for you to just meet them anyway. So, yeah, you may not have to, like… no worries, you don’t have to prepare to say anything unless they ask.
452 00:46:21.670 ⇒ 00:46:23.590 Mustafa Raja: Something very specific, yeah.
453 00:46:24.180 ⇒ 00:46:24.900 Robert Tseng: Okay.
454 00:46:25.320 ⇒ 00:46:33.030 Robert Tseng: Cool. All right, well, if nothing else, then I will just, we can… we can end here today. Thanks, everyone.
455 00:46:34.560 ⇒ 00:46:36.020 Henry Zhao: Thank you, Ryan.