Meeting Title: Brainforge Wholesale Dashboard Review Date: 2026-04-16 Meeting participants: Jasmin Multani, Advait Nandakumar Menon, Shivani Amar
WEBVTT
1 00:00:18.500 ⇒ 00:00:19.580 Advait Nandakumar Menon: Hey, again.
2 00:00:19.810 ⇒ 00:00:20.730 Jasmin Multani: Yay!
3 00:00:45.860 ⇒ 00:00:47.530 Jasmin Multani: She’s accepted.
4 00:00:52.360 ⇒ 00:00:54.080 Jasmin Multani: sit mute.
5 00:02:47.670 ⇒ 00:02:48.790 Shivani Amar: Hello.
6 00:02:49.810 ⇒ 00:02:52.210 Jasmin Multani: Oh, hey, hello! How’s it going?
7 00:02:52.430 ⇒ 00:02:53.620 Shivani Amar: doin’.
8 00:02:54.820 ⇒ 00:03:04.300 Jasmin Multani: Good, good, good. Kayla and Amber are thankfully giving… getting me lunch, so, like, very, very thankful.
9 00:03:04.590 ⇒ 00:03:08.790 Jasmin Multani: Okay, let me pull up the right records.
10 00:03:10.160 ⇒ 00:03:12.570 Shivani Amar: Which dashboards should we be looking at together?
11 00:03:12.770 ⇒ 00:03:22.090 Jasmin Multani: We’re gonna go over the wholesale spe- wholesale dashboard first, and then the retail. Let me pull up the Omni.
12 00:03:29.630 ⇒ 00:03:36.710 Shivani Amar: I think, like, I know that you tried to split it by, like, let’s do numbers one, and then visuals another, but, like, I feel like it’s gonna…
13 00:03:36.890 ⇒ 00:03:42.250 Shivani Amar: They’re gonna be blended, probably. So let’s just… it’s, like, hard for my brain to not…
14 00:03:42.730 ⇒ 00:03:44.769 Shivani Amar: Give feedback on both.
15 00:03:44.770 ⇒ 00:03:45.979 Jasmin Multani: At the same time. Sure.
16 00:03:45.980 ⇒ 00:03:46.620 Shivani Amar: Yeah.
17 00:03:47.440 ⇒ 00:03:48.649 Shivani Amar: Let’s see how it goes.
18 00:03:48.870 ⇒ 00:04:06.239 Jasmin Multani: Yeah. So, Advith and I, what we did was we went through your notes from the Slack messages and the spreadsheet, and also through the notes that I provided, and we’ve basically created a
19 00:04:06.400 ⇒ 00:04:15.939 Jasmin Multani: review list, and this review list can be found at, the bottom of the specs for each retail and wholesale.
20 00:04:17.170 ⇒ 00:04:26.090 Jasmin Multani: We reviewed things together, and we wanted to go through some, immediate questions, that we wanted to clear by you before,
21 00:04:27.170 ⇒ 00:04:40.619 Jasmin Multani: before saying that we’re finished out on things. So let’s go… I’m planning on running this by going through dashboard by dashboard, asking you the core questions, and then also getting a pulse check of,
22 00:04:40.780 ⇒ 00:04:43.079 Jasmin Multani: what you think Finnish looks like.
23 00:04:43.460 ⇒ 00:04:46.679 Shivani Amar: Okay, let’s see if this structure works.
24 00:04:48.070 ⇒ 00:04:48.660 Jasmin Multani: Yep.
25 00:04:49.340 ⇒ 00:04:58.099 Jasmin Multani: And if you have feedback, happy to have that feedback, on how the meeting is being run, so that we can redo tomorrow.
26 00:04:58.330 ⇒ 00:04:59.200 Shivani Amar: Okay.
27 00:04:59.350 ⇒ 00:05:01.729 Shivani Amar: Right off the bat on this one.
28 00:05:01.870 ⇒ 00:05:16.270 Shivani Amar: you have, like, a wholesale revenue number at the top, and it’s, like, wholesale revenue in the last 6 months. And I’m like, why is that… why would that be the first number that anybody cares about? I think you should just delete that entirely. Nobody would ever say, what’s the total revenue been in the last 6 months?
29 00:05:16.490 ⇒ 00:05:18.360 Shivani Amar: Like, that’s not a thing.
30 00:05:18.800 ⇒ 00:05:19.450 Jasmin Multani: Okay.
31 00:05:19.450 ⇒ 00:05:25.639 Shivani Amar: would just be like, what has it been month over month, or what has it been over a period of time? So I would, like, just delete that.
32 00:05:26.470 ⇒ 00:05:30.930 Jasmin Multani: Just delete it, not even do sales. Okay. And not even do orders?
33 00:05:31.170 ⇒ 00:05:43.160 Shivani Amar: Like, why… if you’re an executive of wholesales… wholesale, why are you coming in and saying, how many orders did we have over the last 6 months as a total? 25,000. What does that number mean to you?
34 00:05:44.490 ⇒ 00:05:46.999 Jasmin Multani: Personally, I…
35 00:05:47.170 ⇒ 00:05:53.519 Jasmin Multani: in the past, you end up tracking it, just to see how, percent contributions look like, but…
36 00:05:53.950 ⇒ 00:05:58.229 Jasmin Multani: It wouldn’t be relevant at the top, it would be relevant at the tabular level.
37 00:05:58.230 ⇒ 00:06:01.369 Shivani Amar: Yeah, so I think just delete those two things from the top.
38 00:06:05.230 ⇒ 00:06:06.959 Shivani Amar: We can just edit this live.
39 00:06:07.510 ⇒ 00:06:12.740 Shivani Amar: Like, why do we have to type it in? Like, is it possible for us to just do it together?
40 00:06:13.130 ⇒ 00:06:14.599 Jasmin Multani: We can do it together.
41 00:06:14.600 ⇒ 00:06:19.060 Shivani Amar: Okay, I’m like, let’s just do it, because then otherwise, there’s no reason for a rework.
42 00:06:19.350 ⇒ 00:06:27.340 Jasmin Multani: some things will be done together live, and then we would have to hit publish. Some things, odd bit will have to work on the back end. Yeah.
43 00:06:28.860 ⇒ 00:06:30.770 Jasmin Multani: So…
44 00:06:31.770 ⇒ 00:06:33.630 Advait Nandakumar Menon: You can just click on High Chart.
45 00:06:34.150 ⇒ 00:06:34.910 Advait Nandakumar Menon: Adjustment.
46 00:06:34.910 ⇒ 00:06:36.009 Jasmin Multani: You just hide chart.
47 00:06:36.520 ⇒ 00:06:37.100 Advait Nandakumar Menon: Yeah.
48 00:06:37.670 ⇒ 00:06:39.110 Advait Nandakumar Menon: Yep, that one.
49 00:06:48.860 ⇒ 00:06:50.539 Shivani Amar: And this can be way smaller.
50 00:06:52.460 ⇒ 00:06:53.630 Shivani Amar: It can be, like.
51 00:07:00.320 ⇒ 00:07:02.879 Shivani Amar: There’s, like, a little status button at the top.
52 00:07:03.620 ⇒ 00:07:04.680 Jasmin Multani: Let’s go with.
53 00:07:06.320 ⇒ 00:07:08.360 Advait Nandakumar Menon: Yeah, just moved to the… yeah.
54 00:07:08.360 ⇒ 00:07:18.290 Shivani Amar: Yeah, like, make it… just scrunch it to be, like, yeah, like, vertically smaller, not necessarily width smaller, and then the font sizes can be smaller.
55 00:07:19.270 ⇒ 00:07:20.490 Shivani Amar: But it’s just, like.
56 00:07:28.750 ⇒ 00:07:29.080 Jasmin Multani: Okay.
57 00:07:29.080 ⇒ 00:07:31.179 Advait Nandakumar Menon: You can’t… yeah.
58 00:07:33.300 ⇒ 00:07:34.640 Jasmin Multani: And this overlap?
59 00:07:36.050 ⇒ 00:07:38.050 Advait Nandakumar Menon: And no, we won’t be able to overlap.
60 00:07:41.860 ⇒ 00:07:42.650 Jasmin Multani: I know.
61 00:07:44.000 ⇒ 00:07:46.250 Jasmin Multani: We can just keep it like this for now.
62 00:07:47.290 ⇒ 00:07:55.189 Jasmin Multani: Okay, and then your feedback here was scrap the bar and add in the funnel, right?
63 00:07:56.190 ⇒ 00:08:02.099 Shivani Amar: Okay, hold on. So… Sorry, where are you now?
64 00:08:03.250 ⇒ 00:08:05.029 Jasmin Multani: Wholesale executive.
65 00:08:05.030 ⇒ 00:08:08.440 Shivani Amar: Yeah, no, no, when you say scrap the bar, what are you talking about?
66 00:08:08.700 ⇒ 00:08:09.999 Jasmin Multani: On these bar charts.
67 00:08:10.000 ⇒ 00:08:19.520 Shivani Amar: No, I actually changed that into a bar chart, because it was just a line chart, which I didn’t understand. So I changed into a bar chart, and then I said, you can actually have the segments be
68 00:08:19.690 ⇒ 00:08:21.650 Shivani Amar: The way that they report out on it.
69 00:08:21.830 ⇒ 00:08:32.520 Shivani Amar: in, in, so it’s… online resale, drink mix, like, basically, if you open the Brainforge wholesale…
70 00:08:33.600 ⇒ 00:08:36.500 Shivani Amar: document that Amber worked on? Do you know what I’m talking about?
71 00:08:38.789 ⇒ 00:08:41.549 Jasmin Multani: It’s just a document, right? Not…
72 00:08:41.549 ⇒ 00:08:42.859 Shivani Amar: Yeah, the spreadsheet?
73 00:08:43.690 ⇒ 00:08:45.409 Jasmin Multani: I think… yeah, one second.
74 00:08:46.910 ⇒ 00:08:48.420 Jasmin Multani: Boom.
75 00:08:56.670 ⇒ 00:08:58.350 Advait Nandakumar Menon: I dropped the link in the chat.
76 00:08:58.350 ⇒ 00:08:58.830 Jasmin Multani: Okay.
77 00:09:01.000 ⇒ 00:09:02.630 Shivani Amar: So if you go there…
78 00:09:03.320 ⇒ 00:09:09.699 Shivani Amar: you go to Hotel… Wholesale Summary Report, and this will be very informative, because this is, like, what I wanted.
79 00:09:09.810 ⇒ 00:09:12.469 Shivani Amar: So go to Wholesale Summary Report, and you’ll see.
80 00:09:12.650 ⇒ 00:09:25.160 Shivani Amar: You start with the funnel, right? Like, let’s just go slow down. So it’s like, how many applicants, how many accounts, how many are… how many active, how many are at risk, how many newly churned in that period? That’s, like, your funnel.
81 00:09:25.450 ⇒ 00:09:31.889 Shivani Amar: And then the nice thing about this Google Spreadsheet is that then you can click on the left side and uncollapse those things.
82 00:09:32.450 ⇒ 00:09:34.220 Shivani Amar: and then see by segment.
83 00:09:34.480 ⇒ 00:09:39.919 Shivani Amar: So it’s, like, it’s very neat, like, it’s just, like, tidy way of seeing what the funnel is.
84 00:09:40.340 ⇒ 00:09:44.230 Shivani Amar: Then, when you go down, like, a little bit further to…
85 00:09:45.000 ⇒ 00:09:50.700 Shivani Amar: The actual sales, right, gross sales, Sales by partner segment, etc.
86 00:09:50.830 ⇒ 00:09:52.420 Shivani Amar: If you scroll to the right.
87 00:09:54.510 ⇒ 00:09:58.010 Shivani Amar: This would be, like, rows 46 through 50.
88 00:09:58.260 ⇒ 00:10:01.169 Shivani Amar: are how they report out on this in their OKRs.
89 00:10:01.350 ⇒ 00:10:03.300 Shivani Amar: So, if you’re looking at, like.
90 00:10:03.430 ⇒ 00:10:05.970 Shivani Amar: The monthly values, which are to the right.
91 00:10:07.850 ⇒ 00:10:10.700 Jasmin Multani: Yep. So it grows by the right, okay.
92 00:10:10.700 ⇒ 00:10:15.699 Shivani Amar: Yeah, the monthly values are to the right, and this would say…
93 00:10:15.850 ⇒ 00:10:19.770 Shivani Amar: And, like, there’s a formula here, like, it’s, like, international resellers actually, like.
94 00:10:20.210 ⇒ 00:10:39.569 Shivani Amar: reduction from the sparkling number, like, you would have to see how they did it, but this is, like, gross sales across… and, like, this is how they’re currently reporting on stuff in the business. So it could be a stacked bar chart where it shows you sparkling, drink mix, international reseller, and U.S. reseller as the sales across each month.
95 00:10:39.810 ⇒ 00:10:48.089 Shivani Amar: That’s actually, like, what do they care about? It’s that. And so it’s, like, getting that into a visual is fine, or a table, but, like.
96 00:10:48.250 ⇒ 00:10:50.759 Shivani Amar: That would be, like, where you’re trying to get to.
97 00:10:52.030 ⇒ 00:10:55.449 Shivani Amar: The other thing that I would say is,
98 00:11:01.080 ⇒ 00:11:17.130 Shivani Amar: the… the definitions that I was asking with them in a wish about earlier today were, in this table, it says gross sales. In your thing on Omni, it says revenue. And I just never know, like, are you guys doing net revenue and taking out refunds? Or is this…
99 00:11:18.240 ⇒ 00:11:23.330 Shivani Amar: like, what’s the difference between the two categories? And so, like, that feels nebulous to me.
100 00:11:23.530 ⇒ 00:11:25.650 Shivani Amar: And it’s something I want clearly defined.
101 00:11:25.930 ⇒ 00:11:32.349 Shivani Amar: So when you say revenue, I want you to be able to back up what revenue means. When you say gross sales, I want you to be able to back up what gross sales means.
102 00:11:33.230 ⇒ 00:11:40.990 Jasmin Multani: Okay, so we’ll break down… breakdown… Okay, breakdown or vitamin.
103 00:11:41.450 ⇒ 00:11:47.899 Shivani Amar: It’s just like, if you’re saying a word, like sales or revenue, you just need to be so clear on what it actually is.
104 00:11:52.710 ⇒ 00:11:53.610 Jasmin Multani: I think it did.
105 00:11:54.490 ⇒ 00:12:02.210 Jasmin Multani: Would it be helpful for us to label the data columns, or is that overkill?
106 00:12:02.780 ⇒ 00:12:03.720 Shivani Amar: What do you mean?
107 00:12:03.980 ⇒ 00:12:12.660 Jasmin Multani: Like, are you actually going into, queries and the actual data tables and looking at the data columns that we source from?
108 00:12:15.050 ⇒ 00:12:15.660 Jasmin Multani: I think the.
109 00:12:15.660 ⇒ 00:12:24.549 Shivani Amar: I am not, but, like, yes, the taxonomy of sales versus revenue needs to be very clear in all levels of everything we do.
110 00:12:26.050 ⇒ 00:12:29.920 Shivani Amar: And I’ve made that abundantly clear to everybody on this team.
111 00:12:30.420 ⇒ 00:12:33.579 Shivani Amar: To Utam, to Greg.
112 00:12:34.140 ⇒ 00:12:40.659 Shivani Amar: now to you guys, and I’m like, I just need to feel, like, when I see a word like revenue, it’s…
113 00:12:40.910 ⇒ 00:12:42.469 Shivani Amar: Very clearly defined.
114 00:12:43.970 ⇒ 00:12:45.280 Jasmin Multani: I just want to…
115 00:12:52.560 ⇒ 00:12:56.730 Jasmin Multani: I think we can do that, or we will be able to do that, it’s a quick turnaround.
116 00:12:56.730 ⇒ 00:13:01.190 Shivani Amar: Why did we say for adding up to 100%? What is that one?
117 00:13:01.370 ⇒ 00:13:08.400 Shivani Amar: Oh, okay, gotcha, that’s for a different… okay, that’s for the wholesale… I’ll… I know what you’re talking about for that one.
118 00:13:08.900 ⇒ 00:13:16.790 Shivani Amar: So, like, this… if you scroll down, you say percent of total revenue on top 20 wholesale partners, and it says adds up to 100%.
119 00:13:17.050 ⇒ 00:13:19.469 Shivani Amar: Of… well, it’s only your top 20.
120 00:13:19.660 ⇒ 00:13:28.719 Shivani Amar: So it shouldn’t add up to 100% revenue, so I think just deleting percent of total revenue makes sense, because otherwise it’s just, like, that doesn’t…
121 00:13:29.230 ⇒ 00:13:32.799 Shivani Amar: The denominator just being the total for the 20 doesn’t make any sense.
122 00:13:34.260 ⇒ 00:13:36.470 Jasmin Multani: Okay,
123 00:13:37.600 ⇒ 00:13:42.389 Jasmin Multani: And you just want to delete this whole column, not even if we update the name to, like.
124 00:13:42.780 ⇒ 00:13:45.440 Jasmin Multani: Percent of top 20 revenue.
125 00:13:45.440 ⇒ 00:14:04.679 Shivani Amar: Well, is it the percent of top 20 revenue, or is it the percent of total revenue? Because then, if it’s, like, 9%, 6%, that’s at 15, then we’re at 20, 24, 27, like, does… that’s not gonna take me to 100. But then it says the total is 100. So maybe the total should be what you’re actually seeing in the cells, which is more like 28%.
126 00:14:04.720 ⇒ 00:14:12.229 Shivani Amar: Which is 28% of your revenue comes from the top 20 partners, but, like, seeing 100% there is very confusing.
127 00:14:22.480 ⇒ 00:14:24.800 Jasmin Multani: Uplo limiting to…
128 00:14:39.990 ⇒ 00:14:50.600 Jasmin Multani: So, if we were to do this… so, we could either delete this whole column, but would you want to see only… at this total level, would you want to see only
129 00:14:51.210 ⇒ 00:14:55.340 Jasmin Multani: The top 20 revenue, or would it be helpful to see the total total revenue?
130 00:14:58.520 ⇒ 00:15:03.380 Shivani Amar: Like, you’re saying for the third column?
131 00:15:04.740 ⇒ 00:15:06.880 Jasmin Multani: For this value.
132 00:15:07.470 ⇒ 00:15:09.109 Jasmin Multani: this entire.
133 00:15:09.110 ⇒ 00:15:09.960 Shivani Amar: Whoa.
134 00:15:10.180 ⇒ 00:15:10.840 Jasmin Multani: Yeah.
135 00:15:11.430 ⇒ 00:15:28.829 Shivani Amar: Like, I don’t really… like, if you’re just trying to be like, yo, these are your top partners, then the total… total line in and of itself might be the thing that you can remove, because it’s like, it doesn’t do that much for me to know. Unless you’re trying to tell me, of… your top 20 contribute to 28% of your…
136 00:15:28.840 ⇒ 00:15:31.440 Shivani Amar: revenue. I’m like, okay, that’s interesting, I guess.
137 00:15:31.800 ⇒ 00:15:33.410 Shivani Amar: Like, maybe?
138 00:15:33.640 ⇒ 00:15:34.260 Shivani Amar: Right?
139 00:15:36.540 ⇒ 00:15:38.260 Jasmin Multani: So, the total…
140 00:15:44.100 ⇒ 00:15:45.300 Jasmin Multani: Oopside there.
141 00:15:45.710 ⇒ 00:15:50.630 Jasmin Multani: Is there feedback?
142 00:15:51.530 ⇒ 00:15:52.560 Shivani Amar: On which one?
143 00:15:52.800 ⇒ 00:15:59.059 Jasmin Multani: Or, as in, like, are you re-ready to move on to the next tile?
144 00:16:01.840 ⇒ 00:16:09.919 Jasmin Multani: So, the next, set of feedback was basically adding the tabular view of
145 00:16:10.130 ⇒ 00:16:15.759 Jasmin Multani: The funnel, which was found in the, previous dashboards.
146 00:16:16.520 ⇒ 00:16:21.720 Jasmin Multani: So, the nice thing is that these are available, we just have to migrate it over.
147 00:16:23.000 ⇒ 00:16:34.750 Shivani Amar: Yeah, and I think just, like, labeling it as the funnel, so it doesn’t need to be, like, separate… it’s just how many applications, how many accounts created. Applications comes before accounts created, because it’s a funnel.
148 00:16:34.940 ⇒ 00:16:48.639 Shivani Amar: So, how many applications, how many accounts created? How many placed their first order? How many placed their second order? How many placed their third order? And then it’s like, how many are active, how many churned?
149 00:16:49.050 ⇒ 00:16:55.100 Shivani Amar: and whatever. Like, or how many are at risk, or something. So it’s just, like, putting things in a logical…
150 00:16:55.660 ⇒ 00:16:56.470 Shivani Amar: Order.
151 00:16:56.740 ⇒ 00:16:58.009 Jasmin Multani: Okay, okay, good.
152 00:16:58.380 ⇒ 00:17:01.999 Jasmin Multani: I’m trying to see how much we can… we should be mirroring.
153 00:17:02.610 ⇒ 00:17:06.340 Jasmin Multani: this to an exact T, and how much we should…
154 00:17:06.349 ⇒ 00:17:11.939 Shivani Amar: This was very… like, I… I really, like, built this out very much with my…
155 00:17:12.159 ⇒ 00:17:17.099 Shivani Amar: like, what I wanted, so this is a very good indicator of, like, how my brain works.
156 00:17:18.260 ⇒ 00:17:18.800 Jasmin Multani: Got it.
157 00:17:20.460 ⇒ 00:17:21.180 Jasmin Multani: Okay.
158 00:17:22.280 ⇒ 00:17:26.160 Shivani Amar: It’s just like, if I’m an operator, I’m kind of like, am I growing?
159 00:17:26.290 ⇒ 00:17:30.069 Shivani Amar: my wholesale partner pool? Am I shrinking?
160 00:17:30.680 ⇒ 00:17:45.949 Shivani Amar: And then I might want to drill down, like, where is the shrink coming from? Which types of partners have been churning more? That’s where, like, Omni can be useful from an AI standpoint, right? But, like, the first thing I would want to know is, how many partners do I have in wholesale?
161 00:17:46.110 ⇒ 00:17:49.889 Shivani Amar: How is that… How’s that growing or shrinking over time?
162 00:17:51.220 ⇒ 00:17:53.090 Shivani Amar: How is their order cadence?
163 00:17:53.770 ⇒ 00:17:57.430 Shivani Amar: How’s their order volume? Is that growing over time?
164 00:17:58.470 ⇒ 00:18:02.140 Shivani Amar: Like, if I see a big dip somewhere, I want to ask myself why.
165 00:18:16.930 ⇒ 00:18:18.350 Jasmin Multani: That is helpful.
166 00:18:19.180 ⇒ 00:18:36.139 Shivani Amar: And, like, what I was saying is this feels really busy, so it’s like, you have the segments, right? But, like, it’s just too busy, so what I want to see is, what’s my total churn in a week, or my… a month? And it’s like, oh, we had a thousand churn. Okay, then I might say, which… which segments did they come from? And you can
167 00:18:36.500 ⇒ 00:18:45.739 Shivani Amar: collapse that, but, like, this table is just, like, nobody’s gonna be able to under… nobody’s gonna be able to say, like, oh, the number I have to pay attention to is row 7.
168 00:18:50.760 ⇒ 00:18:58.459 Shivani Amar: Right? Like, like, I’m saying, as an example, I’m saying, like, nobody’s gonna be able to say which of these many numbers should I be paying attention to? It’s too many numbers.
169 00:19:01.790 ⇒ 00:19:09.400 Jasmin Multani: Eventually, we could do, And that’s why you liked the dropouts, too.
170 00:19:09.400 ⇒ 00:19:10.320 Shivani Amar: Yes.
171 00:19:11.480 ⇒ 00:19:15.139 Jasmin Multani: it was, like, dropout. Does that make sense of it?
172 00:19:15.850 ⇒ 00:19:17.210 Advait Nandakumar Menon: Yeah, yeah.
173 00:19:17.920 ⇒ 00:19:18.650 Jasmin Multani: Okay.
174 00:19:18.840 ⇒ 00:19:26.230 Jasmin Multani: Do you think we can make that happen visually, or, like, this drop-down?
175 00:19:27.750 ⇒ 00:19:38.529 Advait Nandakumar Menon: I think, Shivani, what you’re essentially asking for is whatever we have in a tabular structure in the summary report is what you want to see in Omni as well.
176 00:19:38.630 ⇒ 00:19:39.990 Advait Nandakumar Menon: Is that correct?
177 00:19:41.590 ⇒ 00:19:48.890 Shivani Amar: Yeah, it’s like, I think because I put so much effort into that dashboard, it’s actually a very good view, and then it’s like.
178 00:19:49.260 ⇒ 00:20:04.070 Shivani Amar: shifting to Omni being the source of truth, great, but, like, that has my imprint all over it in terms of, like, how I like to see data. I like to see funnels laid out clearly. I like to think about, what does somebody want to know? They want to understand the funnel of their customers and how the behaviors are.
179 00:20:04.070 ⇒ 00:20:12.579 Shivani Amar: They want to understand how sales are going over a period of time across which segments do they care about. Do they want sales by segment? Do they want sales by product type?
180 00:20:12.600 ⇒ 00:20:14.849 Shivani Amar: Those are gonna be the different cuts that people want.
181 00:20:15.110 ⇒ 00:20:28.099 Shivani Amar: Right? So you could imagine having, like, 2 graphs, honestly, side by side, that are just, like, 6 months trailing sales for revenue, or sales by segment, and then the same thing on the right, which is by product type.
182 00:20:28.490 ⇒ 00:20:43.800 Shivani Amar: And then, like, then you might want a crossover of them, but, like, people are just like, okay, is sparkling starting to grow amongst our wholesale partners? Is sparkling flat? Is, like, trusted health starting to increase in revenue? Or it’s shrinking? Those are the questions those operators are going to want to know.
183 00:20:43.980 ⇒ 00:20:45.180 Shivani Amar: How to answer.
184 00:20:46.600 ⇒ 00:20:47.400 Jasmin Multani: Okay.
185 00:20:47.610 ⇒ 00:20:51.830 Shivani Amar: Not just what was revenue over the last 6 months, which is kind of just so random.
186 00:20:58.900 ⇒ 00:21:04.389 Shivani Amar: It’s like, oh, revenue was flatter… or, like, reduced in March, why?
187 00:21:04.620 ⇒ 00:21:13.420 Shivani Amar: okay, well, Trusted Health suddenly had a huge drop-off, or like, I don’t know, right? Like, that’s, like, the type of questioning you can imagine somebody wanting to understand.
188 00:21:17.250 ⇒ 00:21:22.540 Jasmin Multani: There, and then… Also saw this graph.
189 00:21:22.540 ⇒ 00:21:29.730 Shivani Amar: Yeah, so this is, like, a standalone dashboard that I think should exist for every part of the business, like, every function, revenue…
190 00:21:29.980 ⇒ 00:21:40.660 Shivani Amar: part of the business. So if you have a wholesale version, you can imagine it’s daily sales, right? Like, and that’s not… that’s daily sales,
191 00:21:40.810 ⇒ 00:21:47.509 Shivani Amar: And… it’s, like, across each segment, or something like that, right? And then.
192 00:21:47.930 ⇒ 00:21:56.090 Shivani Amar: I like that they have, like, a ranking of the days. Now, the grain would be something that would be nice. If this was a standalone dashboard, I would want to be able to adjust the time grain.
193 00:21:56.570 ⇒ 00:22:04.989 Shivani Amar: I want to say I actually want to look at the best week. I want to look at all this, like, I want to look at the last 52 weeks of data and understand which week was the best week.
194 00:22:05.970 ⇒ 00:22:09.609 Shivani Amar: I want to look at the last several months of data and understand which month was our peak.
195 00:22:09.750 ⇒ 00:22:16.940 Shivani Amar: So it’s like, I want to be able to pick the time grain, and then say, what were sales across Trusted Health, da-da-da, and what was my total?
196 00:22:16.980 ⇒ 00:22:31.269 Shivani Amar: and then be able to, like, easily see when my spikes were. You can imagine a trend line sitting below it, that’s fine, but, like, but, like, I think there’s something cool about being able to say, like, what was your best day that you’ve had in the last year, and why?
197 00:22:33.770 ⇒ 00:22:34.560 Jasmin Multani: Okay.
198 00:22:34.800 ⇒ 00:22:42.960 Shivani Amar: So that’s, like, that table, just for context, is what they were using to say, what do we think is gonna happen when we introduce pink lemonade in e-commerce?
199 00:22:43.130 ⇒ 00:22:43.900 Jasmin Multani: Hmm.
200 00:22:43.900 ⇒ 00:22:53.780 Shivani Amar: And so, like, they’re just like, is it gonna hit 2 million in a day? Is it gonna be 1.5 million in a day? So, imagine an operator, like, immediately wakes up and is like, how much did we hit yesterday?
201 00:22:58.100 ⇒ 00:23:02.579 Advait Nandakumar Menon: Yeah, so I think it makes sense, Jasmine, like, what we discussed, like, to have it on a separate tab.
202 00:23:02.770 ⇒ 00:23:03.530 Jasmin Multani: Yeah.
203 00:23:03.530 ⇒ 00:23:12.679 Shivani Amar: It should be a separate tab for each revenue channel, right? So for e-commerce, it’ll look exactly like this. It’ll be Amazon, Shopify, Walmart.com.
204 00:23:13.040 ⇒ 00:23:29.139 Shivani Amar: For wholesale, it’ll be Trusted Health, da-da-da-da-da, your segments, and then you’ll also have it, you can also have a sparkling and drink mix, you can have those columns as well. And then it has the total. And then for retail, eventually it’s gonna have the same thing for Walmart, Target.
205 00:23:29.440 ⇒ 00:23:39.159 Shivani Amar: you know, vitamin shop, da-da-da-da-da, and then I could even say, I want to filter to just Vitamin Shop’s best day ever. I want to filter for what Costco’s best week ever was.
206 00:23:42.080 ⇒ 00:23:43.550 Jasmin Multani: Okay, okay, okay.
207 00:23:44.090 ⇒ 00:23:51.020 Jasmin Multani: Others, I think we need to keep it to one tab. That’s what my gut says.
208 00:23:51.270 ⇒ 00:23:54.089 Jasmin Multani: additional tab, on top of the
209 00:23:54.330 ⇒ 00:23:56.999 Jasmin Multani: Like, to the right of this. And then.
210 00:23:57.380 ⇒ 00:24:03.779 Jasmin Multani: have all the week labels and the month labels in the same size… same view. That way.
211 00:24:03.780 ⇒ 00:24:04.130 Advait Nandakumar Menon: Hmm.
212 00:24:04.130 ⇒ 00:24:06.279 Jasmin Multani: Keep, keep, aggregating.
213 00:24:07.120 ⇒ 00:24:13.580 Shivani Amar: So you mean, like, it’s a standalone file, right? Like, it’s not a… to the side of something? I don’t… I’m not quite sure what you’re following. Yeah.
214 00:24:13.580 ⇒ 00:24:21.049 Jasmin Multani: Literally, this view is gonna have, like, now a tab, just like the same way there are tabs over here.
215 00:24:21.890 ⇒ 00:24:40.280 Jasmin Multani: I would imagine it would be less busy, if we kept this as a singular… this view as a singular tab, and to the right of it, you see that huge table, dropdown, with just drilling down at the granular date level.
216 00:24:40.280 ⇒ 00:24:43.769 Shivani Amar: Why wouldn’t you just have that be a standalone dashboard?
217 00:24:47.090 ⇒ 00:24:49.200 Shivani Amar: Versus a tab in this one.
218 00:24:49.900 ⇒ 00:24:53.199 Jasmin Multani: I think as a user.
219 00:24:54.360 ⇒ 00:25:01.540 Jasmin Multani: It’s always helped me to flip back between, the actual total numbers and then the root causing.
220 00:25:02.600 ⇒ 00:25:04.159 Jasmin Multani: But, if you.
221 00:25:04.160 ⇒ 00:25:19.180 Shivani Amar: Why don’t we just play with it? It seems like you can make it a tab later, so just make it a standalone thing, because we’re gonna have that standalone thing for, like, I think every part of the business, and eventually we’ll have one that’s omnichannel. You can imagine the same thing where it says e-commerce at the top.
222 00:25:19.310 ⇒ 00:25:24.870 Shivani Amar: Wholesale… retail, and then you’re like, what was my best day ever at Element?
223 00:25:28.940 ⇒ 00:25:40.959 Shivani Amar: So I think it’s, like, a view that people will get used to, and they want to be… you want to be able to have them be able to manipulate, am I looking at monthly, am I looking at daily, am I looking at weekly, and that they’re in full control of setting those filters.
224 00:25:58.300 ⇒ 00:26:02.720 Jasmin Multani: And we can figure out how to… Prioritize building this.
225 00:26:02.880 ⇒ 00:26:16.289 Jasmin Multani: At this, but I’d say, like, we need to, like, we’ll clean up the lower hanging fruits to close out individual dashboards before, talking about which net new things we need to create.
226 00:26:16.840 ⇒ 00:26:26.610 Jasmin Multani: Okay. Okay, we talked about this. We talked about this. We went through this.
227 00:26:27.250 ⇒ 00:26:33.069 Jasmin Multani: This feedback has to mirror what’s in the spreadsheet. Feel good about that.
228 00:26:33.600 ⇒ 00:26:36.649 Jasmin Multani: And the funnel flu flow, okay, okay.
229 00:26:37.340 ⇒ 00:26:42.910 Jasmin Multani: I know we have 3 minutes, but I want to see if we can shift over to the reorder rate.
230 00:26:51.810 ⇒ 00:26:55.320 Jasmin Multani: Mainly have questions.
231 00:27:02.180 ⇒ 00:27:07.450 Jasmin Multani: Do you want to see that similar, funneling in here.
232 00:27:08.450 ⇒ 00:27:12.169 Shivani Amar: Yeah, I honestly think the, like, bar graph is not that helpful.
233 00:27:12.170 ⇒ 00:27:13.040 Jasmin Multani: Okay, okay.
234 00:27:13.040 ⇒ 00:27:13.680 Shivani Amar: Yeah.
235 00:27:13.910 ⇒ 00:27:15.290 Jasmin Multani: So, we’re okay with.
236 00:27:15.290 ⇒ 00:27:20.830 Shivani Amar: But if the funnel exists there, then you don’t need to have it in two places, right? So, I’m like…
237 00:27:21.170 ⇒ 00:27:25.329 Shivani Amar: I, I, that’s why I was like, I’m not quite sure what this is for.
238 00:27:26.840 ⇒ 00:27:29.209 Jasmin Multani: This entire dashboard, or just the…
239 00:27:29.210 ⇒ 00:27:34.369 Shivani Amar: Yeah, like, the top section, I’m like, I like the funnel being in the exact dashboard, like.
240 00:27:34.560 ⇒ 00:27:37.959 Shivani Amar: And then I’m not quite sure what’s… what we’re going for here.
241 00:27:38.720 ⇒ 00:27:44.439 Jasmin Multani: It’s mainly tracking, which…
242 00:27:44.930 ⇒ 00:27:49.650 Jasmin Multani: actual stores end up being power players for Element.
243 00:27:50.150 ⇒ 00:28:06.629 Jasmin Multani: So this will also… I think we… yesterday, Dan kind of also talked about how there’s, like, a huge amount of stock that he gets, and then he starts allocating, hey, where do we want to send it to? Where are we,
244 00:28:07.190 ⇒ 00:28:12.269 Jasmin Multani: where do we need to stock up more on? This also allows us to understand, like, which
245 00:28:12.470 ⇒ 00:28:20.050 Jasmin Multani: Stores already have an appetite, and what is their, current rate of They’re sell-through.
246 00:28:20.050 ⇒ 00:28:33.129 Shivani Amar: This feels like a customer behavior. That’s fine, like, it’s like, one is just, like, exact… I get what you’re going for. One is maybe just sales, like a standalone sales thing, then the other is, like, here’s your funnel, here’s some basic stuff about your revenue.
247 00:28:33.130 ⇒ 00:28:40.419 Shivani Amar: Then this one, if you’re trying to make it about customer behavior more, then we can figure out what that looks like. But I think the why behind this dashboard
248 00:28:40.420 ⇒ 00:28:47.329 Shivani Amar: Coverage and recency don’t feel like clear terms to me, so I think we’ve got some more work to do on this one.
249 00:28:49.550 ⇒ 00:28:56.850 Jasmin Multani: Quick question, we were able to go through these questions, right?
250 00:29:01.920 ⇒ 00:29:18.559 Shivani Amar: which partners are in wholesale? Sorry, sure? Yeah, what is the running total of orders and revenue? Yep. So this is just, like, the behavior of the customers, which is kind of like when you go back to the Excel tab, we have it in, like, if you go to…
251 00:29:21.850 ⇒ 00:29:22.780 Shivani Amar: That one?
252 00:29:23.630 ⇒ 00:29:29.989 Shivani Amar: Like, this is awesome, because then Madison can, like, look and say, okay, like, what’s going on with my wholesale customers? If you scroll to the right.
253 00:29:31.410 ⇒ 00:29:49.430 Shivani Amar: it has, like, their total orders, their average order value, their first order date, their last order date, active status, at-risk status, and so then that way, if she’s, like, ever trying to pull anything that is, like, I want to just look at a list of, like, at-risk wholesale partners who have been
254 00:29:50.480 ⇒ 00:30:06.469 Shivani Amar: sales over, like, total sales over a million dollars that, like, I need to target and do some initiative with, then she can pull that. And I’m like, Omni should be able to do that, but, like, the base table of this, being able to say, like, here’s just, like, all the behavior of your customers is awesome.
255 00:30:12.470 ⇒ 00:30:17.140 Jasmin Multani: And you don’t feel like the information found in this table.
256 00:30:17.260 ⇒ 00:30:23.389 Shivani Amar: Well, this doesn’t have zip code, which people need zip code. That’s been, like, a consistent theme that people are asking for zip code.
257 00:30:23.550 ⇒ 00:30:28.190 Shivani Amar: Not just Citi. So I’m like, no, it has some of it, it doesn’t have…
258 00:30:28.450 ⇒ 00:30:31.550 Shivani Amar: Like, it doesn’t have everything we would want.
259 00:30:31.740 ⇒ 00:30:35.920 Shivani Amar: Zip code is gonna be, like, a consistent thing that we’re gonna look for across all of our data.
260 00:30:37.310 ⇒ 00:30:39.160 Jasmin Multani: He thought I was mandatory.
261 00:30:39.500 ⇒ 00:30:39.880 Jasmin Multani: E.
262 00:30:39.880 ⇒ 00:30:42.200 Shivani Amar: I’m gonna start the next meeting.
263 00:30:42.380 ⇒ 00:30:45.469 Shivani Amar: And then we could set… we have more time tomorrow, right?
264 00:30:45.700 ⇒ 00:30:50.139 Jasmin Multani: 45 minutes, and then we can go through the 3 retail dashboards there.
265 00:30:50.140 ⇒ 00:30:51.459 Shivani Amar: Cool. Okay, thank you.
266 00:30:51.460 ⇒ 00:30:53.310 Jasmin Multani: Alright, take care, bye.