Meeting Title: Product Sales Summary Query Review Date: 2025-09-23 Meeting participants: Awaish Kumar, Henry Zhao, Demilade Agboola
WEBVTT
1 00:00:02.370 ⇒ 00:00:03.250 Awaish Kumar: Hello?
2 00:00:10.650 ⇒ 00:00:11.610 Awaish Kumar: Hello?
3 00:00:13.940 ⇒ 00:00:15.289 Awaish Kumar: Can you hear me, guys?
4 00:00:15.570 ⇒ 00:00:16.070 Henry Zhao: Yeah.
5 00:00:16.079 ⇒ 00:00:16.889 Demilade Agboola: -Oh.
6 00:00:23.520 ⇒ 00:00:29.090 Henry Zhao: Real quick, Awash, can you just check if this query is correct for me? It should be very simple, actually.
7 00:00:33.360 ⇒ 00:00:34.290 Awaish Kumar: Sorry.
8 00:00:35.460 ⇒ 00:00:37.949 Henry Zhao: Let me put into a bunch of…
9 00:00:38.370 ⇒ 00:00:39.660 Awaish Kumar: Yeah.
10 00:00:50.990 ⇒ 00:00:52.300 Henry Zhao: Should be correct, right?
11 00:00:52.300 ⇒ 00:00:53.340 Awaish Kumar: Whoa.
12 00:00:53.670 ⇒ 00:00:54.679 Awaish Kumar: That’s correct.
13 00:00:55.110 ⇒ 00:00:57.100 Henry Zhao: Product sales summary by transaction.
14 00:00:57.210 ⇒ 00:01:05.230 Henry Zhao: I’m just summing your account, summing the ad spend, and then Demolade broke it out into new customer account excluding offer, and new customer account excluding offer.
15 00:01:05.670 ⇒ 00:01:09.239 Henry Zhao: Oh, shoot, this is not right. I need to do some ad spend plus offer spend.
16 00:01:12.180 ⇒ 00:01:14.620 Awaish Kumar: So, ad spend does not include offer span?
17 00:01:16.690 ⇒ 00:01:19.739 Demilade Agboola: No, it doesn’t include the first thing, but you have to use it, you have to use a comma.
18 00:01:20.200 ⇒ 00:01:24.280 Demilade Agboola: And also, it’s, Offer Affiliate Spend, that’s the new name, you know.
19 00:01:24.760 ⇒ 00:01:26.820 Henry Zhao: What does it offer affiliates then?
20 00:01:26.820 ⇒ 00:01:27.500 Demilade Agboola: Yes.
21 00:01:28.870 ⇒ 00:01:29.680 Henry Zhao: I need a comma.
22 00:01:30.180 ⇒ 00:01:31.019 Awaish Kumar: So my question is…
23 00:01:31.020 ⇒ 00:01:31.570 Demilade Agboola: Nicely.
24 00:01:31.570 ⇒ 00:01:37.780 Awaish Kumar: His ad spend doesn’t… Does ad spend not include, affiliate spend?
25 00:01:39.990 ⇒ 00:01:47.379 Demilade Agboola: No, that’s kind of why we’ve had to create two separate, columns for it.
26 00:01:47.840 ⇒ 00:01:53.190 Demilade Agboola: So that they can see the ad spend, and then the affiliate spend by upgrading does not include all of it.
27 00:01:54.270 ⇒ 00:01:55.100 Awaish Kumar: Okay.
28 00:01:55.350 ⇒ 00:01:58.540 Henry Zhao: So this should be correct, right? And then I just did marketing product name equals semaglutide.
29 00:01:58.540 ⇒ 00:02:01.589 Awaish Kumar: Okay, that… it might break, like…
30 00:02:02.210 ⇒ 00:02:06.619 Awaish Kumar: Will it will not break our dashboards? Because…
31 00:02:06.820 ⇒ 00:02:11.650 Awaish Kumar: For example, if I want to say MCAT, right, I will divide
32 00:02:12.690 ⇒ 00:02:17.430 Awaish Kumar: New… like, ad spend divided by customer… new customer loan.
33 00:02:17.770 ⇒ 00:02:22.579 Awaish Kumar: Right? And if… if we look up low, we just did a spend by one new customer car.
34 00:02:23.250 ⇒ 00:02:27.869 Awaish Kumar: That’s wrong, like, it does not account for the fluid stream.
35 00:02:27.870 ⇒ 00:02:32.209 Demilade Agboola: Yeah. Yeah, I agree, and that’s part of why I just did that PR now.
36 00:02:32.430 ⇒ 00:02:34.510 Demilade Agboola: So that we can have,
37 00:02:34.780 ⇒ 00:02:45.079 Demilade Agboola: It’s different affiliate spend, as well as the total affiliate spend, so that can now be added to the ad spend to make the total amount that can be used for things like NCAC and ROS,
38 00:02:45.210 ⇒ 00:02:46.870 Demilade Agboola: all the calculations.
39 00:02:49.550 ⇒ 00:02:53.889 Awaish Kumar: Okay, so… now you are making a PR for…
40 00:02:54.980 ⇒ 00:02:57.669 Demilade Agboola: We’ve made it already, it’s one of… it’s watched your merged today.
41 00:02:58.480 ⇒ 00:03:00.259 Awaish Kumar: But I already merged it.
42 00:03:00.960 ⇒ 00:03:05.970 Demilade Agboola: Yes, it’s available. It’s available, so we just need to modify the dashboard to reflect that.
43 00:03:09.170 ⇒ 00:03:16.479 Awaish Kumar: So, like, in your new changes, like, ad spend is just the ad spend without affiliate or with the affiliate?
44 00:03:17.410 ⇒ 00:03:22.799 Demilade Agboola: If ad spend is just ad spend by itself, then there’s total affiliate spend.
45 00:03:23.020 ⇒ 00:03:23.350 Awaish Kumar: Okay.
46 00:03:23.350 ⇒ 00:03:30.060 Demilade Agboola: As it’s… so now you can add ad spend and total affiliate spend to see what the total ad spend is.
47 00:03:30.190 ⇒ 00:03:35.240 Awaish Kumar: My point is that then you have to change the formulas in Tableau as well.
48 00:03:35.240 ⇒ 00:03:40.719 Demilade Agboola: Yes, yes, yes, yes, yes, that would be something we need to talk to, like, Henry will need to just do.
49 00:03:42.380 ⇒ 00:03:43.090 Awaish Kumar: Okay.
50 00:03:45.630 ⇒ 00:03:50.470 Henry Zhao: I would have thought it’s better to just include, affiliate spending ad spend, and then
51 00:03:50.580 ⇒ 00:03:55.020 Henry Zhao: Put the affiliate stuff the same way you’re doing now, so that if we want to exclude it, we can.
52 00:03:55.130 ⇒ 00:03:56.370 Henry Zhao: Might be easier to do it that way.
53 00:03:58.440 ⇒ 00:04:01.860 Demilade Agboola: Well, the… the reason why I didn’t add…
54 00:04:04.310 ⇒ 00:04:11.399 Demilade Agboola: if I add the total affiliate spend into ad spend, it might be harder to be able to filter
55 00:04:12.700 ⇒ 00:04:15.729 Demilade Agboola: certain things, like, for instance, if I see…
56 00:04:16.170 ⇒ 00:04:30.619 Demilade Agboola: The way I did it now is I’m giving you every single option. I’m giving you ad spend, I’m giving you offer spend, I’m giving you all the different channels, and then I’m giving you total affiliate spend. That way, it’s easy for you to play around with different things, add filters, remove filters.
57 00:04:31.050 ⇒ 00:04:35.250 Demilade Agboola: It’s basically, like, Easy for you to play around with things.
58 00:04:36.630 ⇒ 00:04:40.570 Henry Zhao: Wouldn’t it be easier to have a total ad spend, which is what it’s called ad spend right now, and then have
59 00:04:40.740 ⇒ 00:04:45.419 Henry Zhao: what was ad spend be a new column? Like, that way you still give us all the options, but then we don’t have to…
60 00:04:46.100 ⇒ 00:04:48.339 Henry Zhao: Like, when’s every dash and make sure it’s updated?
61 00:04:51.900 ⇒ 00:04:57.150 Demilade Agboola: If I make… if I change names, you have to stop breaking things. That’s… that’s always the worry.
62 00:04:58.930 ⇒ 00:05:02.519 Henry Zhao: You’re saying right now in Tableau, all of the ad spend already doesn’t have affiliate spend, right?
63 00:05:03.500 ⇒ 00:05:04.319 Henry Zhao: No, we need to go in.
64 00:05:04.320 ⇒ 00:05:09.870 Demilade Agboola: So you can… yeah, the… it would be including the…
65 00:05:10.350 ⇒ 00:05:15.580 Demilade Agboola: So there’s a total affiliate spend, so that can just be summed up to the ad spend.
66 00:05:16.870 ⇒ 00:05:27.170 Demilade Agboola: Or, what you can do, I know for one of the dashboards, what they just wanted was the ad spend as one column, and then the next column should be total affiliate spend.
67 00:05:27.800 ⇒ 00:05:32.080 Demilade Agboola: That way, they can see everything. They didn’t need it summed up.
68 00:05:32.350 ⇒ 00:05:42.459 Demilade Agboola: I mean, we summed up for the formula for NCAC and NRAS, but in terms of just… they wanted to see how much is being spent on affiliates versus how much is being spent on the other ads.
69 00:05:44.780 ⇒ 00:05:53.109 Demilade Agboola: It’s things like that that just… I’ve just said to, like, make it in a way that, like, you can play around with that, answer whatever questions they need.
70 00:05:53.270 ⇒ 00:05:53.800 Demilade Agboola: Yeah.
71 00:05:53.800 ⇒ 00:05:56.860 Henry Zhao: Yeah, we just have a lot of dashboards that we’ll probably need to go in and…
72 00:05:58.480 ⇒ 00:06:02.429 Henry Zhao: I don’t know, do they want us to include the offer ad spend on all of the Tableau dashes?
73 00:06:02.560 ⇒ 00:06:03.699 Henry Zhao: That have ad spend?
74 00:06:05.540 ⇒ 00:06:12.100 Demilade Agboola: I don’t know if it’s all of them, but I know it’s the major ones in terms of, like, product ROS, I know it’s in terms of
75 00:06:12.760 ⇒ 00:06:17.200 Demilade Agboola: the product to us, product LTV snapshot dashboard.
76 00:06:18.230 ⇒ 00:06:26.160 Demilade Agboola: those are the main ones. I don’t even think if… but we could also do it for Josh as well, but I don’t know if the… for Josh one, they made a request for.
77 00:06:27.870 ⇒ 00:06:31.560 Henry Zhao: Okay, I will double-check with them on that at my meeting tomorrow.
78 00:06:31.740 ⇒ 00:06:50.020 Awaish Kumar: Yeah, but the thing is that now they are spending a lot on these platforms, and also there are conversions from these platforms. We are getting the orders from, for example, the offer, and we are also spending a lot of money on the offer, so why not? It will be part of just an ad spend, right?
79 00:06:50.150 ⇒ 00:06:58.329 Awaish Kumar: So it will just come into… come into our calculations for CAC, NCAC, and LTV, and things like that.
80 00:07:01.580 ⇒ 00:07:06.240 Demilade Agboola: I agree. Definitely something we need to integrate into what we have right now.
81 00:07:06.760 ⇒ 00:07:15.060 Awaish Kumar: Similarly for customer count, like, I see your query, right, you wrote for Henry. It includes, like, new customer.
82 00:07:15.620 ⇒ 00:07:22.250 Awaish Kumar: Including the offer, excluding the offer, but previously in Tableau, we just have some of new customer count.
83 00:07:22.500 ⇒ 00:07:27.490 Awaish Kumar: So we need to account for these things, or, like, is it… is it…
84 00:07:28.260 ⇒ 00:07:35.499 Awaish Kumar: Like, compatible with the reports, or new changes you are making in product sales summary?
85 00:07:35.990 ⇒ 00:07:39.990 Awaish Kumar: Does that… can affect… the Tableau reports.
86 00:07:42.010 ⇒ 00:07:44.680 Henry Zhao: Either way, I need to do, like, probably an audit, so…
87 00:07:46.110 ⇒ 00:07:47.670 Awaish Kumar: There’s a question for Damilade.
88 00:07:49.810 ⇒ 00:07:51.089 Demilade Agboola: Perfect. What was the question?
89 00:07:51.740 ⇒ 00:08:00.860 Awaish Kumar: Question is that, I see in the query, you are saying new customer count, including the offer, and then you are saying, new customer count.
90 00:08:01.620 ⇒ 00:08:06.870 Awaish Kumar: Including and excluding the offer, and then sum it, and then call the new customer count.
91 00:08:07.100 ⇒ 00:08:12.060 Awaish Kumar: So this is a new definition of a new customer account. Previously, we just have one field.
92 00:08:12.500 ⇒ 00:08:14.660 Awaish Kumar: It was called Macau.
93 00:08:14.770 ⇒ 00:08:19.310 Awaish Kumar: So, how… did we make that adjustment in our Tableau reports?
94 00:08:20.590 ⇒ 00:08:25.049 Demilade Agboola: Yes, yes. So this was because they wanted to have the offer filter.
95 00:08:25.210 ⇒ 00:08:29.260 Demilade Agboola: So they wanted to be able to click and see… The offer alone.
96 00:08:29.640 ⇒ 00:08:33.949 Demilade Agboola: And so that’s why I added things like offer affiliate spend.
97 00:08:35.159 ⇒ 00:08:51.309 Demilade Agboola: The offer… new customer accounts, just… the offer, new customer account, excluding all that, so that way they can start to see if you just want to see the offers impact the loan, you can see the values directly without having to switch dashboards.
98 00:08:51.890 ⇒ 00:08:58.249 Henry Zhao: What about now that we’re switching to Catalyst? Are you still gonna be doing customer count excluding offer, and including offer, or…
99 00:08:58.710 ⇒ 00:08:59.639 Henry Zhao: Are you not gonna have, like.
100 00:08:59.640 ⇒ 00:09:00.010 Demilade Agboola: Okay.
101 00:09:00.010 ⇒ 00:09:00.520 Henry Zhao: regardless.
102 00:09:00.710 ⇒ 00:09:02.220 Demilade Agboola: Oh, but, but we…
103 00:09:02.420 ⇒ 00:09:07.459 Demilade Agboola: I don’t… I’m not sure… you’re not supposed to… it’s just supposed to be new customer account.
104 00:09:08.000 ⇒ 00:09:10.770 Demilade Agboola: Including offer. You don’t need to…
105 00:09:11.970 ⇒ 00:09:12.490 Henry Zhao: Oh.
106 00:09:12.490 ⇒ 00:09:17.229 Demilade Agboola: Yeah, it’s just the new customer count included in the offer. That’s the total new customer account.
107 00:09:17.700 ⇒ 00:09:23.469 Henry Zhao: So if I want the offer, new customer account, I just have to do new customer excluding offer minus new customer account excluding offer.
108 00:09:23.470 ⇒ 00:09:28.260 Awaish Kumar: Yeah, including offer meals, it includes everything and offer…
109 00:09:29.300 ⇒ 00:09:31.480 Demilade Agboola: Yes, give me one second.
110 00:09:32.420 ⇒ 00:09:33.500 Henry Zhao: That one’s a rough period.
111 00:09:38.600 ⇒ 00:09:40.609 Awaish Kumar: Why we are doing it like this?
112 00:09:41.050 ⇒ 00:09:43.039 Henry Zhao: Alright, so then…
113 00:09:43.440 ⇒ 00:09:44.980 Awaish Kumar: Can we think of something?
114 00:09:45.670 ⇒ 00:09:56.140 Demilade Agboola: So there are three, there are three… there are three… there are three columns. There’s customer count excluding offer, customer count including offer, and Customer Account Offer Only. There are three columns.
115 00:09:56.360 ⇒ 00:10:04.360 Demilade Agboola: The included offer is… including offer is all the single offers. Like, every single… every single, like, new customer.
116 00:10:04.520 ⇒ 00:10:18.710 Demilade Agboola: Excluding offer is we just want to see everything minus the offer. So if you want to create a filter and only see things minus the offer, you can do that. And if you now want to only view the offer alone, there’s a new customer account offer on income.
117 00:10:18.710 ⇒ 00:10:20.870 Awaish Kumar: My point… my point is that…
118 00:10:21.130 ⇒ 00:10:26.759 Awaish Kumar: Instead of using all these different columns, why not we add a
119 00:10:26.880 ⇒ 00:10:29.570 Awaish Kumar: Or, like, we use general field.
120 00:10:31.800 ⇒ 00:10:44.230 Awaish Kumar: for that, right? We have date, we have a product name, we have a channel, and we can say, on this day, for Semma, for the offer, new customer count is this, and Arisman is this.
121 00:10:45.570 ⇒ 00:10:50.839 Awaish Kumar: Like… Like, why can’t we restructure our table?
122 00:10:52.390 ⇒ 00:10:53.600 Henry Zhao: Yeah, I think I agree with that.
123 00:10:56.840 ⇒ 00:11:02.290 Demilade Agboola: This is in product sales… this is for product sales summary by transaction. This is where all this…
124 00:11:02.690 ⇒ 00:11:10.510 Awaish Kumar: No, that’s my question, like, We can bring in channel field in the product sale summary by transaction.
125 00:11:11.010 ⇒ 00:11:20.230 Awaish Kumar: Right? And that channel field will have all these different sources, like Google Ads, Meta, like the…
126 00:11:21.140 ⇒ 00:11:21.629 Henry Zhao: Yeah, I agree.
127 00:11:21.630 ⇒ 00:11:29.930 Awaish Kumar: offer, M&T and Vibe, everything. If we want to sum it all together, we can just sum it. Otherwise, we can show it separately as well.
128 00:11:30.460 ⇒ 00:11:38.630 Henry Zhao: Yeah, basically, Demolade, I think what she’s saying, which is what I’m thinking, is instead of having these by columns, it should be by rows. So, like, the offer should be a row.
129 00:11:39.830 ⇒ 00:11:41.100 Henry Zhao: Etc, you know what I mean?
130 00:11:42.140 ⇒ 00:11:47.220 Demilade Agboola: Yes, but then it doesn’t… the problem is it’s… spreading across.
131 00:11:47.660 ⇒ 00:11:51.039 Demilade Agboola: I’ll look into it, but, like, we also have things like gender.
132 00:11:51.420 ⇒ 00:11:57.270 Demilade Agboola: And I’m not sure we’ll be able to split it across By those metrics.
133 00:11:57.560 ⇒ 00:12:02.679 Demilade Agboola: By those, like, dimensions, basically. Not dimension measures, basically.
134 00:12:03.050 ⇒ 00:12:03.630 Henry Zhao: You’re kind of…
135 00:12:03.630 ⇒ 00:12:06.159 Awaish Kumar: We can, we can, like…
136 00:12:07.010 ⇒ 00:12:11.900 Demilade Agboola: If there’s no clean way to join it, Because then we’ll be…
137 00:12:12.140 ⇒ 00:12:16.310 Demilade Agboola: Either having to duplicate or remove certain measures.
138 00:12:17.920 ⇒ 00:12:27.449 Awaish Kumar: I don’t know what cities we are talking about right now, like, we do have a channel seat… if you can do it across, you can do it downwards.
139 00:12:28.650 ⇒ 00:12:29.449 Henry Zhao: You know what I’m saying?
140 00:12:29.450 ⇒ 00:12:33.260 Demilade Agboola: So, the way I’m doing it across is by saying, hey.
141 00:12:33.510 ⇒ 00:12:37.639 Demilade Agboola: it’s… I’m randomly assigning, so for every… can I share my screen?
142 00:12:38.250 ⇒ 00:12:38.810 Henry Zhao: Yeah.
143 00:12:42.440 ⇒ 00:12:45.359 Henry Zhao: What I’m saying, if you can do it across, you can do it downwards by just doing a cross join.
144 00:12:47.030 ⇒ 00:12:59.620 Demilade Agboola: But that will explode… that will explode the data. We would have duplicates. That’s what I’m trying to be cautious about. Like, and nothing cannot be done, but we’ll need to, like, make major modifications to the model. That’s all I’m just trying to say.
145 00:13:00.960 ⇒ 00:13:02.099 Demilade Agboola: Right now.
146 00:13:02.620 ⇒ 00:13:05.980 Demilade Agboola: These are the main measures that we were looking at.
147 00:13:06.570 ⇒ 00:13:13.950 Demilade Agboola: the date… This product… marketing product name, which is quite kind of similar, the membership plan, and the gender.
148 00:13:14.250 ⇒ 00:13:29.460 Demilade Agboola: Right? So these, for every… every day, should be unique. This is a combination that should be unique, and we’re getting the different values. If we add channel to this, because there isn’t a clear way to join this, we’re doing channel by product, we know what the product is.
149 00:13:29.650 ⇒ 00:13:32.630 Demilade Agboola: But we don’t necessarily know what the membership plan is.
150 00:13:34.610 ⇒ 00:13:36.690 Demilade Agboola: And in some cases, gender is.
151 00:13:36.800 ⇒ 00:13:55.240 Awaish Kumar: If you don’t always know. That’s what I’m saying, right? Similar to how we are joining for date and product name, we are going to join it for date, product name, and channel, and then for membership plan and gender, we use our regular logic, which is by
152 00:13:55.260 ⇒ 00:14:02.570 Awaish Kumar: counting the transactions, right? Percentage of transaction multiplied by… I’ll just spend whatever.
153 00:14:03.870 ⇒ 00:14:08.330 Demilade Agboola: And off agenda, actually, I believe it’s really included in…
154 00:14:08.740 ⇒ 00:14:20.690 Awaish Kumar: Membership plan, I’m doing that. I don’t know how you are doing it for gender, for membership plan. For example, for monthly membership plan, for SEMA products, if it is, like, the…
155 00:14:20.780 ⇒ 00:14:31.289 Awaish Kumar: number of… it depends on number of orders. Like, if we have a higher number of orders, then a highest percentage of ad spend is going to be assigned to SAMA. That’s…
156 00:14:32.120 ⇒ 00:14:33.899 Awaish Kumar: how I’m doing it.
157 00:14:37.190 ⇒ 00:14:39.959 Demilade Agboola: Sure… I will look into that.
158 00:14:40.400 ⇒ 00:14:48.480 Demilade Agboola: What’s… yes, so there’s a yes, there’s a ticket… sorry, there’s a… I’m guessing it from… the customers.
159 00:14:48.650 ⇒ 00:14:50.790 Demilade Agboola: same customer, so we know their agenda.
160 00:14:51.600 ⇒ 00:14:53.739 Awaish Kumar: And that’s how easy it is to propagate it.
161 00:14:54.630 ⇒ 00:15:07.150 Awaish Kumar: Yeah, but… but for genders, you know, from orders, what is the gender, but for… from ad spend, you are… we are… we are not… we don’t know what the gender is, right? So…
162 00:15:07.530 ⇒ 00:15:13.140 Awaish Kumar: You must be using some logic to split the ad span between Male and female.
163 00:15:14.470 ⇒ 00:15:21.789 Demilade Agboola: Yeah, so for that… Yes, I believe, yeah, yeah, I do the percentage, I believe.
164 00:15:28.270 ⇒ 00:15:29.179 Awaish Kumar: I’m not sure.
165 00:15:29.180 ⇒ 00:15:33.219 Demilade Agboola: Because… because… because gender has a tie to others.
166 00:15:34.000 ⇒ 00:15:37.669 Demilade Agboola: I… and these things are joined based off the order.
167 00:15:39.940 ⇒ 00:15:41.579 Demilade Agboola: I can just join it.
168 00:15:42.600 ⇒ 00:15:43.820 Demilade Agboola: Oh, come on, I would…
169 00:15:43.820 ⇒ 00:15:49.570 Awaish Kumar: Yeah, but just joining it with order is, like, will duplicate the span.
170 00:15:56.560 ⇒ 00:15:58.010 Demilade Agboola: You’re a lot of child’s been…
171 00:16:09.510 ⇒ 00:16:10.390 Awaish Kumar: -Oh.
172 00:16:10.490 ⇒ 00:16:11.370 Awaish Kumar: Like…
173 00:16:12.090 ⇒ 00:16:22.359 Awaish Kumar: Like, like, okay, so, like, let’s simplify this. For, like, for now, Demilare, let’s… let’s give Henry what, what he needs, and,
174 00:16:22.670 ⇒ 00:16:23.190 Awaish Kumar: Alright.
175 00:16:23.190 ⇒ 00:16:24.090 Henry Zhao: I don’t need a…
176 00:16:24.090 ⇒ 00:16:36.320 Awaish Kumar: The way it is set up, right? And we can discuss the PR right now. But for product sales summary, Demolari, we can sync between us, and we can come up with a solution together.
177 00:16:36.620 ⇒ 00:16:39.260 Demilade Agboola: Yeah, definitely. That’s no problem.
178 00:16:40.060 ⇒ 00:16:59.100 Awaish Kumar: Yeah, we can sync separately, and, like, that might be a bigger task, so I don’t want, like, anything gets blocked by our improvements. So that’s, like, internal improvement. We are going to work together to come to a conclusion and build the model. And in the meantime, Henry, you are going to use
179 00:16:59.230 ⇒ 00:17:02.949 Awaish Kumar: the… the fields as demo are they built right now.
180 00:17:03.500 ⇒ 00:17:04.099 Awaish Kumar: I’m good.
181 00:17:04.109 ⇒ 00:17:06.009 Henry Zhao: Right, Amalada? I can send this off to Jonah.
182 00:17:06.250 ⇒ 00:17:06.859 Awaish Kumar: Yep.
183 00:17:07.700 ⇒ 00:17:08.699 Awaish Kumar: It looks okay.
184 00:17:08.700 ⇒ 00:17:09.640 Demilade Agboola: Boom.
185 00:17:11.720 ⇒ 00:17:13.820 Demilade Agboola: Yes, it looks fine.
186 00:17:14.280 ⇒ 00:17:14.880 Henry Zhao: Okay.
187 00:17:15.109 ⇒ 00:17:19.890 Henry Zhao: But he also said, he said, can we add ad spend by day to the marketing dashboard on Tableau?
188 00:17:20.230 ⇒ 00:17:29.000 Henry Zhao: I mean, this looks nice, like, by month. I don’t want to add… I don’t want to keep adding, like, day breakdown dashes to everything to make things super messy, so I’m probably just gonna ask Jonah
189 00:17:29.210 ⇒ 00:17:32.689 Henry Zhao: If this spreadsheet is fine, I can just update it for him on a regular basis.
190 00:17:33.390 ⇒ 00:17:39.199 Awaish Kumar: maybe we can give… put a, like, at the bottom, like, a table view for him? I don’t know.
191 00:17:40.290 ⇒ 00:17:41.319 Henry Zhao: I can do that.
192 00:17:42.910 ⇒ 00:17:44.070 Awaish Kumar: Okay, I’ll ask about that.
193 00:17:44.610 ⇒ 00:17:47.110 Henry Zhao: Alright, so the… the pull request.
194 00:17:47.830 ⇒ 00:17:48.500 Awaish Kumar: Fair enough.
195 00:17:48.500 ⇒ 00:17:50.180 Henry Zhao: Basically, this is the…
196 00:17:50.180 ⇒ 00:18:10.050 Awaish Kumar: What I’m… sorry, let me just complete what I’m saying. So, like, there are… we are using a logic, in a standardized product name, which is a mix of a lot of different things. We are using the rejects, we are using direct, like, name, comparisons, and we are also using the product IDs.
197 00:18:10.360 ⇒ 00:18:29.229 Awaish Kumar: So, my point was just that, like, whatever you are doing, can we just bring that in this macro? So, if you are using some rejects matching, let’s move it here, if we can. So, it’s combined for all of our,
198 00:18:29.400 ⇒ 00:18:42.160 Awaish Kumar: Like, anywhere we are… we are… we need a standardized product name… mapping, we just use it, so it is, like, normalized across our… all of our models and dashboards.
199 00:18:42.450 ⇒ 00:18:44.660 Henry Zhao: Gonna mess up the dashboards, though.
200 00:18:45.680 ⇒ 00:18:51.289 Awaish Kumar: Yeah, that’s what I want to understand, like, if you can give me an example, that would be nice.
201 00:18:51.840 ⇒ 00:18:59.299 Henry Zhao: Yeah, absolutely. So, one, for example, is we have a breakdown in customer I.O. for SMRL and Sublingual.
202 00:18:59.470 ⇒ 00:19:04.120 Henry Zhao: But… here, everything is put into Summer Larin.
203 00:19:04.220 ⇒ 00:19:05.460 Awaish Kumar: Injection.
204 00:19:07.860 ⇒ 00:19:08.670 Henry Zhao: Okay.
205 00:19:08.670 ⇒ 00:19:15.810 Demilade Agboola: Do we have… Do we have a product name… do we have a product number that matches that?
206 00:19:17.850 ⇒ 00:19:18.610 Awaish Kumar: Oh.
207 00:19:19.160 ⇒ 00:19:20.140 Awaish Kumar: Okay, I…
208 00:19:20.140 ⇒ 00:19:29.480 Demilade Agboola: If you want… if you want to split it into, like, this, is there… because right now, Injectable summer is actually being gotten by the product ID.
209 00:19:29.870 ⇒ 00:19:37.199 Demilade Agboola: Which is also… Sorry, no, no, summer. Sarmaline is actually gotten by… yeah, so it’s gotten by the product.
210 00:19:38.080 ⇒ 00:19:42.150 Demilade Agboola: The ODT is what I got from the marketing team, that’s the product ID.
211 00:19:42.660 ⇒ 00:19:46.959 Demilade Agboola: And then if it doesn’t… if it doesn’t fall in, that’s when we use the…
212 00:19:48.300 ⇒ 00:19:54.290 Awaish Kumar: Like… So, like, the Henry, the product name you showed, it’s called, semolin What?
213 00:19:54.890 ⇒ 00:20:03.810 Awaish Kumar: Sublingual. So, is… is that different than… Ceramoline injection, and… ODT.
214 00:20:04.650 ⇒ 00:20:08.539 Henry Zhao: Yeah, it’s different than injectable, and it’s different than… I don’t know about… I don’t know what ODT is.
215 00:20:09.850 ⇒ 00:20:12.009 Demilade Agboola: That’s what I’m trying to say. I think…
216 00:20:12.430 ⇒ 00:20:17.060 Demilade Agboola: I don’t want to say, like, rename stuff if it’s just a naming convention.
217 00:20:17.670 ⇒ 00:20:22.409 Demilade Agboola: For some… some people refer to different things by different names across their company.
218 00:20:23.190 ⇒ 00:20:25.489 Demilade Agboola: Or it could still be the same thing.
219 00:20:26.240 ⇒ 00:20:30.879 Henry Zhao: Could we maybe add product ID and bundle ID into BASC Treatment Updated?
220 00:20:34.170 ⇒ 00:20:36.380 Demilade Agboola: experiment updated…
221 00:20:36.790 ⇒ 00:20:44.000 Demilade Agboola: Yes, we could. We have it, but not for every… not for all time. We have some treatment ID.
222 00:20:44.120 ⇒ 00:20:47.349 Demilade Agboola: In the order data.
223 00:20:48.050 ⇒ 00:20:59.690 Demilade Agboola: And the other data has that number, or those numbers, those IDs, so we can join and add it. But the treatment ID only got added in June 20… on June 25th, so before that, it would be hard to do that.
224 00:21:01.970 ⇒ 00:21:05.719 Henry Zhao: Yeah, let me look at what were the other, roadblocks.
225 00:21:07.090 ⇒ 00:21:10.640 Awaish Kumar: I… I, like… so, sublingual means…
226 00:21:10.770 ⇒ 00:21:14.619 Awaish Kumar: A medicine which can… you can put it,
227 00:21:14.770 ⇒ 00:21:22.740 Awaish Kumar: under your tongue, right? And it gets dissolved. Similarly, ODD means some,
228 00:21:22.930 ⇒ 00:21:32.569 Awaish Kumar: marital, which you can just put in your mouth, and you can take it without… without the need for water. So basically, these are the same things. We are… we just…
229 00:21:33.580 ⇒ 00:21:38.159 Awaish Kumar: We just need to understand which vocabulary is correct, all they need.
230 00:21:38.950 ⇒ 00:21:40.900 Awaish Kumar: But basically, it’s the same thing.
231 00:21:41.460 ⇒ 00:21:42.940 Demilade Agboola: Yeah, no, I think it’s…
232 00:21:44.240 ⇒ 00:21:47.200 Henry Zhao: Another thing is, Everyday Plus needs to be grouped together.
233 00:21:48.150 ⇒ 00:21:51.169 Henry Zhao: And you guys have Everyday Plus broken down by a lot.
234 00:21:51.400 ⇒ 00:21:55.700 Henry Zhao: I can group by in my… final query?
235 00:21:55.890 ⇒ 00:21:59.279 Henry Zhao: But I just feel like that, again, introduces, like.
236 00:21:59.280 ⇒ 00:22:00.310 Awaish Kumar: Complexity.
237 00:22:00.660 ⇒ 00:22:03.040 Henry Zhao: Either way, we’re gonna have complexity that we need to maintain.
238 00:22:03.270 ⇒ 00:22:09.060 Awaish Kumar: Oh, let me, like, yeah, open, one more… macro hills for you.
239 00:22:10.200 ⇒ 00:22:16.260 Henry Zhao: Because eventually my query is gonna be something like this, to… get…
240 00:22:23.190 ⇒ 00:22:26.659 Henry Zhao: is I need to, like, match treatment updated with treatment created.
241 00:22:27.630 ⇒ 00:22:29.330 Henry Zhao: Order completed.
242 00:22:29.740 ⇒ 00:22:33.749 Henry Zhao: to… to look at the changes, right? So…
243 00:22:33.750 ⇒ 00:22:39.089 Awaish Kumar: Yeah, like, we also have one more macro called Marketing Product Name.
244 00:22:40.700 ⇒ 00:22:41.660 Henry Zhao: Right.
245 00:22:41.660 ⇒ 00:22:44.839 Awaish Kumar: Maybe, if you open that.
246 00:22:48.650 ⇒ 00:22:52.980 Awaish Kumar: I can share the… thing. So, basically.
247 00:22:54.300 ⇒ 00:22:55.270 Henry Zhao: Shoot.
248 00:22:56.960 ⇒ 00:22:57.779 Henry Zhao: One second.
249 00:22:58.010 ⇒ 00:22:59.790 Awaish Kumar: Yeah, I sent the link in chat.
250 00:23:01.500 ⇒ 00:23:02.529 Henry Zhao: Is it a macro?
251 00:23:03.140 ⇒ 00:23:15.119 Awaish Kumar: Yeah, it’s called marketing product name. So, how it goes is, we have a string, you basically pass it as a parameter to standardized product name, and whatever comes from a standardized product name goes into
252 00:23:15.150 ⇒ 00:23:23.270 Awaish Kumar: this macro marketing product name, and you basically get the grouped version, which you are saying, like, instead of a granular
253 00:23:23.460 ⇒ 00:23:28.109 Awaish Kumar: Name of the product, you will just get a category, like, the top… top level.
254 00:23:28.110 ⇒ 00:23:33.779 Henry Zhao: Yeah, the problem is, semaglutide, they want combined, so it’s still, like, not the right level.
255 00:23:35.910 ⇒ 00:23:46.790 Henry Zhao: Like, they want all these to be compounded to my glue type. So I would either have to do this and then still group by here. Like, either way, I have to… like, there’s nothing out of these two that are exactly what Bobby wants in CustomerIO.
256 00:23:49.630 ⇒ 00:23:52.310 Awaish Kumar: So… That’s the thing.
257 00:23:52.700 ⇒ 00:23:53.530 Demilade Agboola: Hello?
258 00:23:54.030 ⇒ 00:23:55.809 Demilade Agboola: From what I’ve seen so far.
259 00:23:56.800 ⇒ 00:24:00.399 Demilade Agboola: Standardized products mean is us categorizing.
260 00:24:00.400 ⇒ 00:24:02.270 Awaish Kumar: Based off what’s coming in.
261 00:24:03.170 ⇒ 00:24:09.270 Demilade Agboola: I’m not seeing what the issue is with the categorization. It feels very much like a main thing.
262 00:24:09.720 ⇒ 00:24:14.559 Demilade Agboola: You want the name to rep… like, he wants the name to look a certain type of way, which is fine.
263 00:24:15.480 ⇒ 00:24:19.700 Demilade Agboola: But I don’t want us to be changing standardized product name, because
264 00:24:20.460 ⇒ 00:24:25.889 Demilade Agboola: Number one is kind of… it takes a while for… it’s taken us a while for us to get to this point.
265 00:24:26.260 ⇒ 00:24:28.529 Henry Zhao: And number two, it’s…
266 00:24:28.950 ⇒ 00:24:32.290 Demilade Agboola: If it’s a main thing, if, for instance, he, like.
267 00:24:33.080 ⇒ 00:24:36.739 Demilade Agboola: The issue is not that we’re categorizing a product wrongly.
268 00:24:36.880 ⇒ 00:24:39.950 Demilade Agboola: But that the name of the product is not
269 00:24:40.170 ⇒ 00:24:49.980 Demilade Agboola: we want it to be, or that instead of having so many types of everyday plus, we want to have one type, I think we can, like, do that in the marketing product name.
270 00:24:50.060 ⇒ 00:24:53.469 Awaish Kumar: We can put everything, so if it’s every day plus weight.
271 00:24:53.470 ⇒ 00:25:07.329 Demilade Agboola: Make it Everyday Plus. If it’s Everyday Plus, whatever, make it Everyday Plus. It’s all consistent in the way that Bobby can use, but it does not affect the actual categorization, because this drives things like revenue, and how, like, people are.
272 00:25:08.020 ⇒ 00:25:14.289 Awaish Kumar: Yeah. So, Damalade, we… we are not changing… Our macro standardized product name.
273 00:25:14.390 ⇒ 00:25:16.129 Awaish Kumar: Henry wants that.
274 00:25:16.280 ⇒ 00:25:24.180 Awaish Kumar: he wanna, like, add a new macro with his definitions to use it in the CIO.
275 00:25:24.610 ⇒ 00:25:28.270 Awaish Kumar: He will not be updating the macro V. Exactly.
276 00:25:29.230 ⇒ 00:25:30.670 Henry Zhao: Yours will stay the same.
277 00:25:31.110 ⇒ 00:25:41.479 Henry Zhao: The reason I need my own macro is because this is a different logic, basically. So I basically, if somebody changes from Everyday Plus to, like, a different Everyday Plus, they need to stay in the same treatment group.
278 00:25:41.930 ⇒ 00:25:49.840 Henry Zhao: Whereas if they change from compounded semaglutide to a different type of semaglutide, they need to… needs to flag that it’s now a different treatment group.
279 00:25:50.650 ⇒ 00:26:00.840 Henry Zhao: That’s all. Because how Judd sets up the campaigns in Customer I.O. is going to depend on whether or not they switched treatment groups, or whether or not they started a new treatment group.
280 00:26:02.090 ⇒ 00:26:03.050 Henry Zhao: In Basque.
281 00:26:03.550 ⇒ 00:26:04.459 Henry Zhao: Does that make sense?
282 00:26:05.310 ⇒ 00:26:06.530 Demilade Agboola: Yeah, that makes sense.
283 00:26:06.830 ⇒ 00:26:19.920 Henry Zhao: So it’s kind of like, if I’m, like, a car dealership, and you switch from, like, a red Kia to a blue Kia, like, I don’t need to change my marketing flow to you, because it’s still a Kia, but if you change to, like, an electric car, I might need to…
284 00:26:20.210 ⇒ 00:26:26.480 Henry Zhao: like, revenue-wise, that might be the same classification, but if I… I probably need to send you different, like, reminders, like, instead of
285 00:26:26.640 ⇒ 00:26:32.239 Henry Zhao: gas… fill up in gas, and it just send you, like, electric car maintenance. That’s, like, kind of the analogy of, like, why I need.
286 00:26:32.240 ⇒ 00:26:34.239 Awaish Kumar: I, I just want to understand now.
287 00:26:34.420 ⇒ 00:26:43.689 Awaish Kumar: So I understand your requirement, and Demilade also understands that. So my question is that your CIO work is related to marketing.
288 00:26:44.090 ⇒ 00:26:53.170 Awaish Kumar: And marketing, like the… Marketing product name, which we have built, is also for marketing team.
289 00:26:53.470 ⇒ 00:26:59.149 Awaish Kumar: So, do you think, Mark, that they both should be the… should align with each other, or…
290 00:26:59.740 ⇒ 00:27:17.560 Henry Zhao: No, so that I will still use for the dashboard for Judd. So the dashboard I have made for Judd is to look at, like, sales performance and things like that. So that, I’m going to use the standardized marketing table and the query that Demolade shared in the stand-up today, because that’s marketing-related. But this is specifically for Judd to be able to implement
291 00:27:17.700 ⇒ 00:27:24.389 Henry Zhao: The correct, marketing campaigns based on what treatment group they’re in, and if they changed or switched treatment groups.
292 00:27:28.800 ⇒ 00:27:32.619 Demilade Agboola: I think another question is, maintainability.
293 00:27:33.000 ⇒ 00:27:39.470 Demilade Agboola: It, like, is… Will they… do they change the name of the customer I.O, like, often?
294 00:27:40.900 ⇒ 00:27:45.219 Henry Zhao: That one can just be on me and Judd. If they do change, we can just make the change there.
295 00:27:45.380 ⇒ 00:27:50.560 Henry Zhao: But it shouldn’t be as often. Like, you’ll still maintain the marketing one the same way you do now.
296 00:27:50.670 ⇒ 00:27:53.350 Henry Zhao: I don’t think that’ll affect anything.
297 00:27:57.450 ⇒ 00:27:59.470 Demilade Agboola: Okay, sounds good. I mean…
298 00:27:59.470 ⇒ 00:28:01.600 Henry Zhao: Things have been very low, no amounts of change.
299 00:28:03.460 ⇒ 00:28:11.569 Henry Zhao: It’s only whenever they create a completely new product group, like, if instead of injectables, it’s not for the tongue, I just need to change that. But Bobby will let me know about those.
300 00:28:11.570 ⇒ 00:28:12.410 Awaish Kumar: Yeah, I’m
301 00:28:12.840 ⇒ 00:28:22.999 Awaish Kumar: why I was concerned is just that, like, whatever you are pushing to CIO, and then, yeah, they… they open up Tableau, and they see different things, okay, I don’t see this.
302 00:28:23.410 ⇒ 00:28:24.050 Henry Zhao: No.
303 00:28:24.050 ⇒ 00:28:24.710 Awaish Kumar: Or…
304 00:28:24.710 ⇒ 00:28:28.829 Henry Zhao: This thing I’m doing will not affect any reporting. It will not be client-facing at all.
305 00:28:28.830 ⇒ 00:28:32.469 Awaish Kumar: I understand that, but the person… for example, I’m the same person.
306 00:28:32.600 ⇒ 00:28:37.150 Awaish Kumar: working in CIO, right? And I want to compare a few things, right?
307 00:28:37.240 ⇒ 00:28:53.820 Awaish Kumar: and I open up Tableau. In Tableau, I see three in marketing product names, I see 3 versions of, Sermoline. But when I go into CIO, I just see one name called Sarmoline, Sibling, or whatever, and…
308 00:28:53.820 ⇒ 00:28:59.309 Henry Zhao: This is literally just my script to output something to Customer I.O.
309 00:29:00.820 ⇒ 00:29:03.170 Demilade Agboola: Yes, I think our wish’s point is that
310 00:29:03.410 ⇒ 00:29:09.589 Demilade Agboola: If people are comparing between both places, they will see a disparity.
311 00:29:09.750 ⇒ 00:29:16.240 Demilade Agboola: And we don’t, like, you don’t necessarily want to cause confusion. If someone sees Aye.
312 00:29:16.740 ⇒ 00:29:21.669 Demilade Agboola: like, if the number… because, for example, if we combine all everyday plus, that means the number will be larger.
313 00:29:21.900 ⇒ 00:29:27.519 Demilade Agboola: If that is… if that can cause confusion down the line, or if someone is expecting a certain name.
314 00:29:27.730 ⇒ 00:29:34.499 Demilade Agboola: They’re not seeing that, you know, potentially that could cause some issues if people are using… going between both of them.
315 00:29:35.750 ⇒ 00:29:37.450 Henry Zhao: Okay, I will just double check beyond that.
316 00:29:37.800 ⇒ 00:29:38.320 Henry Zhao: But that’s a.
317 00:29:38.320 ⇒ 00:29:44.009 Demilade Agboola: Yeah, unless we’re… yeah, unless we’re sure that the people using Customer I.O. are only using Customer I.O.
318 00:29:45.640 ⇒ 00:29:51.520 Henry Zhao: No, yeah, that’s a good point. I will just double-check with Bobby on that, but yeah. Either way, we should be good to go here.
319 00:29:51.820 ⇒ 00:29:54.429 Henry Zhao: And I’ll just check with Bobby on that, he’ll just say it’s not gonna be.
320 00:29:54.430 ⇒ 00:30:10.889 Awaish Kumar: Yeah, we are just mentioning it because we have been this before, right? We saw people comparing multiple dashboards, and they are seeing different things because we were keeping different definitions of things, and hence…
321 00:30:12.060 ⇒ 00:30:16.420 Henry Zhao: Okay, I’ll double-check with Bobby on that, that’s a good point, and then I will… I’ll get back to you ASAP.
322 00:30:17.060 ⇒ 00:30:18.200 Awaish Kumar: Okay, thank you.
323 00:30:18.200 ⇒ 00:30:21.059 Henry Zhao: Alright, thank you guys for your input, this is really, really appreciated.
324 00:30:21.700 ⇒ 00:30:22.300 Awaish Kumar: What?
325 00:30:23.960 ⇒ 00:30:24.620 Henry Zhao: Bye.