Meeting Title: Robert Tseng and Lexi Allen Date: 2025-06-17 Meeting participants: Robert Tseng, Lexi Allen (she/her)
WEBVTT
1 00:01:04.200 ⇒ 00:01:05.170 Lexi Allen (she/her): Hey!
2 00:01:06.260 ⇒ 00:01:07.210 Robert Tseng: Hey lexi.
3 00:01:07.210 ⇒ 00:01:08.570 Lexi Allen (she/her): What’s up? How you doing.
4 00:01:08.830 ⇒ 00:01:09.820 Robert Tseng: Good! How are you?
5 00:01:10.020 ⇒ 00:01:11.020 Lexi Allen (she/her): Good.
6 00:01:11.380 ⇒ 00:01:13.370 Robert Tseng: You’re in Boston for the week, you said.
7 00:01:13.560 ⇒ 00:01:20.110 Lexi Allen (she/her): Yeah. So you know, father’s day, I also had my like 10 year high school reunion. So
8 00:01:20.300 ⇒ 00:01:28.610 Lexi Allen (she/her): well, so funny. So those are 2 reasons to come. And then I was like, Okay, why not? I’ll I’ll stick around for a second. So
9 00:01:30.010 ⇒ 00:01:31.860 Lexi Allen (she/her): how are you? Are you.
10 00:01:31.860 ⇒ 00:01:32.640 Robert Tseng: And get.
11 00:01:32.640 ⇒ 00:01:34.360 Lexi Allen (she/her): Traveling a lot or.
12 00:01:34.580 ⇒ 00:01:46.939 Robert Tseng: Was I traveling a lot? Oh, I guess when I 1st connected with a spark plug I was. I was traveling. I was in Kenya for a couple of weeks. But yeah, I’m I’m usually based in New York. So I’m here now.
13 00:01:47.170 ⇒ 00:01:53.589 Lexi Allen (she/her): Okay, cool. And this is like your full time, like your full time, Con Freelancer, or like.
14 00:01:54.120 ⇒ 00:01:57.512 Robert Tseng: Oh, yeah. So I I run an agency.
15 00:01:58.210 ⇒ 00:02:02.120 Robert Tseng: yeah. So I mean, I guess it’s a full time contracting, freelancing.
16 00:02:02.120 ⇒ 00:02:04.899 Lexi Allen (she/her): Running an agency. Sorry I don’t know what the.
17 00:02:04.900 ⇒ 00:02:14.580 Robert Tseng: Yeah, yeah. Yeah. I mean, I guess with with this one, I just just got started myself. I haven’t brought anyone in my team but I don’t know. Maybe there’s opportunity in the future. Yeah.
18 00:02:14.580 ⇒ 00:02:16.009 Lexi Allen (she/her): Okay. Cool. Nice. Yeah.
19 00:02:16.970 ⇒ 00:02:23.070 Robert Tseng: And what? How long have you been with spark plug? And I guess your product, that’s all I know about you. Yeah.
20 00:02:23.070 ⇒ 00:02:37.186 Lexi Allen (she/her): Here for 2 years now. And yeah. So I’m the product manager. So there’s no other product manager just just me and 35 people. So yeah, so it’s still quite small.
21 00:02:38.920 ⇒ 00:02:46.769 Lexi Allen (she/her): yeah, okay, cool. So let’s see. And you said, you live. Where did you say you live again. Lincoln Square.
22 00:02:46.770 ⇒ 00:02:49.400 Robert Tseng: Yeah, I’m around Lincoln Square. I’m on 59.th
23 00:02:49.610 ⇒ 00:02:50.440 Lexi Allen (she/her): Okay. Nice.
24 00:02:50.440 ⇒ 00:02:50.900 Robert Tseng: Yeah.
25 00:02:51.020 ⇒ 00:02:54.979 Lexi Allen (she/her): Never go up there. Do you come to Brooklyn, or like.
26 00:02:55.206 ⇒ 00:03:02.689 Robert Tseng: I I don’t come enough, but I do like it down there. I mean, whenever friends visit, they always want to go. Do like the picture by the depot, bridge, or whatever so.
27 00:03:02.690 ⇒ 00:03:03.380 Lexi Allen (she/her): Of course.
28 00:03:03.380 ⇒ 00:03:05.137 Robert Tseng: That’s usually when I go down.
29 00:03:05.430 ⇒ 00:03:15.320 Lexi Allen (she/her): I know I feel like I’m only going to Dumbo. My Co. Working space was actually over there before. But now I only go there when, like someone is in town. And I’m like, Okay, let’s go see.
30 00:03:15.320 ⇒ 00:03:16.050 Robert Tseng: Yeah.
31 00:03:16.552 ⇒ 00:03:25.589 Lexi Allen (she/her): Views. So, okay, cool, cool. So yeah, let me give you a whole overview of like.
32 00:03:25.780 ⇒ 00:03:30.500 Lexi Allen (she/her): what this product is like, what are we doing here? And then.
33 00:03:30.500 ⇒ 00:03:39.920 Robert Tseng: I did watch the tutorial video that you had sent me before. So I have big contacts. Obviously, I flipped around to like, do all the tracking stuff. But yes, just. I’m all starting from 0. If that helps.
34 00:03:39.920 ⇒ 00:03:46.299 Lexi Allen (she/her): That’s good. That’s good. So yeah, so I feel like the main thing like the main, like.
35 00:03:46.680 ⇒ 00:03:48.729 Lexi Allen (she/her): I would say, the main takeaway is like.
36 00:03:49.360 ⇒ 00:03:56.469 Lexi Allen (she/her): just because people aren’t an app every day does not necessarily mean that they’re like, not like
37 00:03:56.640 ⇒ 00:04:02.387 Lexi Allen (she/her): the strongest users. So because of like ecosystem that we have right now.
38 00:04:03.260 ⇒ 00:04:19.290 Lexi Allen (she/her): people like when I would do Bud, tender interviews like, it’s it’s pretty common for people to think of it like, Okay, as long as I’m seeing it once a week, like I’m sorted because a lot of these campaigns like the sparks, the courses or events are
39 00:04:19.440 ⇒ 00:04:20.260 Lexi Allen (she/her): like
40 00:04:21.209 ⇒ 00:04:31.609 Lexi Allen (she/her): not. It’s not like a flash thing like they’re not flash. They’re like more like long or week long, or like 2 weeks long, etc. So
41 00:04:32.290 ⇒ 00:04:44.990 Lexi Allen (she/her): people might not be in the habit of checking every day unless they like really like the like they like get off on on seeing their numbers go up every day. Yeah, like, so know that.
42 00:04:45.240 ⇒ 00:04:49.676 Lexi Allen (she/her): So we’re also thinking about like access to
43 00:04:51.050 ⇒ 00:05:03.209 Lexi Allen (she/her): access to like campaigns. So I think that’s like a really big one that we’ve been talking about. And then we’re getting developer work to be able to identify that a little bit clearer because we want to know, like.
44 00:05:03.760 ⇒ 00:05:05.910 Lexi Allen (she/her): okay, on the vendor side.
45 00:05:06.580 ⇒ 00:05:10.629 Lexi Allen (she/her): We want people to be engaging with the campaigns
46 00:05:10.830 ⇒ 00:05:12.539 Lexi Allen (she/her): on the employee side. We want people.
47 00:05:12.540 ⇒ 00:05:15.560 Robert Tseng: And these campaigns are set by the brand retail athletes.
48 00:05:15.820 ⇒ 00:05:22.270 Lexi Allen (she/her): So these campaigns are set by the brand. Admins. So retail Admins sometimes.
49 00:05:22.270 ⇒ 00:05:22.589 Robert Tseng: Oh, okay.
50 00:05:22.590 ⇒ 00:05:39.349 Lexi Allen (she/her): If they have paid. Basically like the people that can run incentives are the paid retailers or the brands. Okay? So like, any brand can run an incentive, and then any paid retailer can run an incentive. So
51 00:05:39.500 ⇒ 00:05:46.770 Lexi Allen (she/her): you think about like, we have customers. Okay, on the brand side, we have customers that are like
52 00:05:46.960 ⇒ 00:05:50.910 Lexi Allen (she/her): big multi-state operators where they are like
53 00:05:51.030 ⇒ 00:05:57.829 Lexi Allen (she/her): kind of like. I don’t know if you’re like familiar with dispensaries at all like, how familiar are you with a dispensary before I like? Get into.
54 00:05:58.151 ⇒ 00:06:10.700 Robert Tseng: Kind of yeah. There’s actually like a dispensary in lower East Side that I’m familiar with, I know, like I don’t know. I, anyway? My, my, I have a friend that runs it. So it’s like, Yeah.
55 00:06:10.700 ⇒ 00:06:22.969 Lexi Allen (she/her): Awesome. So yeah, some people like, I don’t know. It’s always funny. If you’ve been in dispensaries, it’s we’re like, very weed friendly. So I’m like me. Personally, I’m always in the dispensary. So I know exactly what’s
56 00:06:25.100 ⇒ 00:06:28.040 Lexi Allen (she/her): now, some dispensaries
57 00:06:28.190 ⇒ 00:06:49.780 Lexi Allen (she/her): are like multiple big chain dispensaries, and then others are like, really, Mom Pop, so like New York is an interesting market as a right point, because of the fact that it’s like, still quite new. Still, quite baby like, you know, there’s like from the smoke shops to like. Now, it’s real dispensaries. It’s all very small. Whereas Michigan, for example, they have like
58 00:06:49.930 ⇒ 00:06:53.739 Lexi Allen (she/her): these multiple, like big chains of dispensaries. Okay.
59 00:06:53.740 ⇒ 00:06:54.160 Robert Tseng: Yeah.
60 00:06:54.160 ⇒ 00:06:56.410 Lexi Allen (she/her): So if you think of a retail admin.
61 00:06:57.390 ⇒ 00:07:09.420 Lexi Allen (she/her): our basically, our like retail admin could be like someone that is like in charge of like 50 or 10 stores, or it can be like this like store manager. That’s just like
62 00:07:09.810 ⇒ 00:07:16.769 Lexi Allen (she/her): trying to like stay afloat, you know. So we have pretty different personas there. And also then they have
63 00:07:17.080 ⇒ 00:07:23.020 Lexi Allen (she/her): different levels of time on their hands. So like, if it’s a retail manager that’s like
64 00:07:23.190 ⇒ 00:07:38.269 Lexi Allen (she/her): on one store, they’re usually like running around and like doing like 18 different things, whereas, like the regional one on like for 10 stores, is like more of a corporate person that’s like sitting up by their calendar and like taking zoom calls, you know, and like
65 00:07:38.450 ⇒ 00:08:05.789 Lexi Allen (she/her): being more aware of the data because it like, that’s their whole job versus the retail managers on the brand side, like same thing with the brands. So it’s like, if it’s a small brand. This person’s running around like a million times and like just trying to stay afloat, maybe looking at the phone, maybe opening spark plug on their computer in their car. Okay? Whereas other people are like very much like seated at a desk. And like, that’s their corporate job. Okay.
66 00:08:05.790 ⇒ 00:08:06.330 Robert Tseng: Yeah.
67 00:08:08.070 ⇒ 00:08:09.920 Lexi Allen (she/her): So yeah, just know that there’s like
68 00:08:10.040 ⇒ 00:08:13.899 Lexi Allen (she/her): a pretty big range in terms of like our our persona. That’s like
69 00:08:14.070 ⇒ 00:08:28.530 Lexi Allen (she/her): from the brand, like there could be like the ones that have, like all their pedigree behind them, is like an OP. Like that happens a lot. But then there’s people like, hey? Sorry. I’m just like coming from my car. And like, I don’t have time for this. And I’m really relaxed. So
70 00:08:29.970 ⇒ 00:08:44.379 Lexi Allen (she/her): okay, that’s all to say, lot of different personas, a lot of different availability to be on their computer. And then a lot of different availability to be like checking the data. So much. So we have customers that are like, really into the data
71 00:08:44.630 ⇒ 00:08:49.500 Lexi Allen (she/her): and frankly buy spark plug just for the data alone. Okay.
72 00:08:49.500 ⇒ 00:08:50.300 Robert Tseng: Oh, wow!
73 00:08:50.300 ⇒ 00:08:57.830 Lexi Allen (she/her): So like they’re not running incentives. 25% of our brands right now that are active have don’t have a single incentive running.
74 00:08:57.970 ⇒ 00:09:03.829 Lexi Allen (she/her): and then they pay like 500 bucks a month, but so we’re at 750 bucks a month, sometimes a thousand bucks a month.
75 00:09:04.301 ⇒ 00:09:08.639 Lexi Allen (she/her): Just to get access to the data for all their other stores.
76 00:09:08.640 ⇒ 00:09:09.260 Robert Tseng: Yeah.
77 00:09:10.720 ⇒ 00:09:35.519 Lexi Allen (she/her): and then on the employee side. There’s no like turning off spark plug. So it’s like once you’re enrolled, you’re just enrolled. So even if, like, there’s no more incentives that are coming through or like, you maybe don’t work at the dispensary anymore. And like, unless the retail admin, like actively on unenrolled you. You yourself can’t like unenroll yourself. Okay.
78 00:09:35.700 ⇒ 00:09:36.040 Robert Tseng: Yeah.
79 00:09:36.040 ⇒ 00:09:38.739 Lexi Allen (she/her): So there can be like a ton of
80 00:09:39.140 ⇒ 00:09:41.650 Lexi Allen (she/her): bud tenders that are just kind of like
81 00:09:42.180 ⇒ 00:09:44.529 Lexi Allen (she/her): on app without being on app.
82 00:09:44.810 ⇒ 00:09:45.350 Robert Tseng: Yeah.
83 00:09:48.110 ⇒ 00:10:00.289 Lexi Allen (she/her): okay, so those are like contextual things about it. What are you most interested in in seeing? Are you interested in like seeing more like product, demo wise or like
84 00:10:02.160 ⇒ 00:10:04.309 Lexi Allen (she/her): where are the main gaps for you?
85 00:10:05.686 ⇒ 00:10:12.820 Robert Tseng: Yeah, I think for me, like what I, my main goal from this call is really just to understand. Like
86 00:10:13.190 ⇒ 00:10:27.569 Robert Tseng: user flows differently across different Admins. I guess you maybe you’ve mentioned a few things like, I think what was interesting was like the difference between like a store manager versus like a 50 store admin like and kind of like how they use the app differently.
87 00:10:28.251 ⇒ 00:10:30.710 Robert Tseng: Obviously, that probably like like.
88 00:10:31.340 ⇒ 00:10:39.319 Robert Tseng: well, I guess I’m trying to better understand your highest value accounts, and like how we can, you know, use data to tell a story of like, are there
89 00:10:40.450 ⇒ 00:11:07.520 Robert Tseng: ways that we can kind of help. Your like kind of the middle of a crop kind of like grow into that, or like, you know, if there’s something that I could do also on like the go to market side to kind of help your team. I give them the data points they need to go after. More more of those folks that’d be interesting. And then, obviously, you’re launching a bunch of features all the time. The fact that 25% of your brands are like just paying you for the platform. That’s that’s pretty good to me. I’m I’m curious, like.
90 00:11:07.600 ⇒ 00:11:17.860 Robert Tseng: yeah, you know. Like, how do you get? You know more more brands to just use it just for that, because that’s pretty, that’s pretty great. So if there’s a way that I can help quantify
91 00:11:18.243 ⇒ 00:11:26.749 Robert Tseng: like from a data instrumentation perspective features that are widely adopted, that drive high value like, I’d love to be able to help tell that story as well.
92 00:11:27.180 ⇒ 00:11:28.700 Lexi Allen (she/her): Totally. So.
93 00:11:29.320 ⇒ 00:11:37.260 Lexi Allen (she/her): what’s most important right now like it? Because it’s like this 3 way marketplace like we need. So
94 00:11:37.520 ⇒ 00:11:40.599 Lexi Allen (she/her): it’s it’s an interesting case that 25% of our
95 00:11:40.750 ⇒ 00:11:50.320 Lexi Allen (she/her): brands are not like doing incentives, because actually, we like brand ourselves as like a bud, tender or like employee engagement.
96 00:11:50.390 ⇒ 00:11:51.850 Lexi Allen (she/her): tool.
97 00:11:51.870 ⇒ 00:12:12.700 Lexi Allen (she/her): and we need a lot of we need them to engage in the campaigns in order for the bud tenders to be as active as they are now. So we have, like 100,000 like a hundred 1,000, like Bud tenders on on platform, but like about like 12,000 to 13,000 weekly active users.
98 00:12:13.082 ⇒ 00:12:26.460 Lexi Allen (she/her): We need them to stay engaged and like, when there’s a drip when there’s a dip in sparks, we sometimes see a dip in engagement. So which makes sense, obviously but it’s not as
99 00:12:27.260 ⇒ 00:12:53.910 Lexi Allen (she/her): it’s not as direct, because it’s like, if you think about it like I go and see. I have certain apps that I’m like, Okay, what are the deals? What are the deals? It takes me a second. If I’m like, okay, it’s been like 3 months, and there hasn’t been a deal like I’m gonna stop using it. So if somebody see that like trailing effect a little bit later on, then, like actively like, Oh, there’s no incentives. I’m gonna like, immediately stop using it. It’s like, Okay, I return. And there’s not enough value consistently. So I’m gonna like, drop off.
100 00:12:54.350 ⇒ 00:12:55.000 Robert Tseng: Yeah.
101 00:12:56.330 ⇒ 00:12:57.989 Lexi Allen (she/her): Other things that
102 00:12:58.350 ⇒ 00:13:13.299 Lexi Allen (she/her): we need to know on the bud. Tender side is, even though they have, like sparks to engage with, or courses to engage with. Sometimes the sparks like they have sale incentives, but they don’t actually have the inventory to
103 00:13:14.010 ⇒ 00:13:25.590 Lexi Allen (she/her): act on it. So it’s like, Oh, I can get a commission. If I sell, I can get a dollar per unit sold on this one. But I don’t have any like. But we’re out of stock. Okay? So that that happens too.
104 00:13:25.750 ⇒ 00:13:33.109 Lexi Allen (she/her): So then sometimes they like, you know, mentally ignore some of them, you know, like, because of the notifications not actually useful for them.
105 00:13:33.580 ⇒ 00:13:37.149 Robert Tseng: Are you integrated to inventory management, or management, or anything like that, or.
106 00:13:37.150 ⇒ 00:13:40.309 Lexi Allen (she/her): We have our own in inventory. Let me show you that too.
107 00:13:40.310 ⇒ 00:13:40.929 Robert Tseng: Oh, okay.
108 00:13:40.930 ⇒ 00:13:46.589 Lexi Allen (she/her): We are able to see on like a newish feature. Oops.
109 00:13:47.380 ⇒ 00:13:53.789 Lexi Allen (she/her): It’s a newish feature, but not that new. It’s like in the last year or so.
110 00:13:54.500 ⇒ 00:14:04.110 Lexi Allen (she/her): where you’re able to see inventory on a brand side. But this is a paid feature. So this is like not all of them, not all
111 00:14:05.460 ⇒ 00:14:10.869 Lexi Allen (she/her): show us, but like we’re able to see inventory and the relative days on hand for
112 00:14:11.426 ⇒ 00:14:27.919 Lexi Allen (she/her): for each of them. However, not all of our customers use it, and, like our customers, are going and building a spark, of course, or an event on their own. So it’s like up to them to check the inventory before they send the spark. We don’t have many.
113 00:14:27.920 ⇒ 00:14:28.300 Robert Tseng: Yeah.
114 00:14:28.300 ⇒ 00:14:42.000 Lexi Allen (she/her): Currently to be like, Hey, just so, you know, like which we should like. Hey, you’re about to send a spark with like, but they don’t have anything in stock like heads up like that’s just like good product improvement that we’ve been talking about. But we don’t have that yet.
115 00:14:44.380 ⇒ 00:14:50.570 Lexi Allen (she/her): Okay, yeah. So they have inventory. Other things to note is that the?
116 00:14:51.140 ⇒ 00:14:54.530 Lexi Allen (she/her): Yes. So you’re talking about the middle of the funnel. So we have, like
117 00:14:55.590 ⇒ 00:15:07.280 Lexi Allen (she/her): the big. Okay, we have the big ones, multi-state operators. So think about the people that are sitting in like in corporate spaces. Then we have, like a high majority of our customers. Like, probably like.
118 00:15:07.690 ⇒ 00:15:08.530 Lexi Allen (she/her): like.
119 00:15:08.810 ⇒ 00:15:15.858 Lexi Allen (she/her): yeah, like, 75% of our customers are maybe like 60% of our customers are these like,
120 00:15:17.160 ⇒ 00:15:28.419 Lexi Allen (she/her): like, maybe they have one or 2 brands based on it. They’re single state operators, like a lot of them, are single state and they like have maybe like
121 00:15:28.500 ⇒ 00:15:51.409 Lexi Allen (she/her): 10 to 15 people that are working with them like it’s not like a big companies. So they love sparkplug because they can’t be everywhere at the same time, and like they don’t have enough capacity to like. Go to every store and see what’s going on. So it’d be interesting to like add in slash. They also need to be competitive, because there’s like a million of them. And
122 00:15:51.410 ⇒ 00:16:04.790 Lexi Allen (she/her): they’re not like camino, or they’re not like the big names that everyone knows in terms of. Like the Stizzy’s. The wannas, like those are big names that get the brand recognition. So they need to do sales incentives in order to get
123 00:16:05.050 ⇒ 00:16:06.480 Lexi Allen (she/her): recognized?
124 00:16:07.417 ⇒ 00:16:13.690 Lexi Allen (she/her): So they do different things. Have you? Do, you know, like the snaps, aspect, and everything like that?
125 00:16:14.340 ⇒ 00:16:15.030 Lexi Allen (she/her): Do you feel like.
126 00:16:15.030 ⇒ 00:16:17.090 Robert Tseng: I feel like too clear on the snaps. Yeah.
127 00:16:17.090 ⇒ 00:16:17.670 Lexi Allen (she/her): Okay?
128 00:16:18.550 ⇒ 00:16:20.220 Lexi Allen (she/her): So they’re like,
129 00:16:23.170 ⇒ 00:16:40.089 Lexi Allen (she/her): the different products we have for the employee side snaps, courses, events and sparks. Okay? So on the employee side like they get text. They’re gonna start getting notifications as well. They’re able to see these like snaps here. These are like.
130 00:16:40.880 ⇒ 00:16:41.670 Robert Tseng: Okay.
131 00:16:42.183 ⇒ 00:16:52.010 Lexi Allen (she/her): Sparks, and then in the earn tab we have courses, and then in the events that we have events, so they also can engage with like.
132 00:16:53.480 ⇒ 00:17:01.260 Lexi Allen (she/her): let me just see like a snap one where they’re able to like. See these little Mini Instagram stories of like
133 00:17:02.490 ⇒ 00:17:07.570 Lexi Allen (she/her): how this works, or like different headlines of like what? How to sell it, etc.
134 00:17:07.880 ⇒ 00:17:08.250 Robert Tseng: Yeah.
135 00:17:08.649 ⇒ 00:17:18.239 Lexi Allen (she/her): And these would go market wide, too. So that’s like one way, like, you know, these these features snapped here. And then events.
136 00:17:19.430 ⇒ 00:17:25.631 Lexi Allen (she/her): events, is just like a pretty basic calendar like nothing crazy. It’s just like a lot of these.
137 00:17:27.240 ⇒ 00:17:35.429 Lexi Allen (she/her): just like, do not discount how unorganized all these people are, you know, like we end up with like
138 00:17:35.890 ⇒ 00:17:41.009 Lexi Allen (she/her): Mega disorganization for the most part, and like
139 00:17:41.280 ⇒ 00:17:43.400 Lexi Allen (she/her): shooting at like people are like.
140 00:17:44.820 ⇒ 00:17:50.530 Lexi Allen (she/her): it’s just. It’s pretty interesting to see like that. This stuff like works and makes money because it’s like there’s not like.
141 00:17:50.730 ⇒ 00:18:03.989 Lexi Allen (she/her): There’s like a million parts of the business, and like no part is like super like organized, probably. Besides, like the licensing, and like the legal parts, and I have to be like extra like careful. But the rest is.
142 00:18:03.990 ⇒ 00:18:18.020 Robert Tseng: The inventory cycle count requirement in New York is crazy. My! My buddy runs combat down lower East Side, and like he, I mean just I just knowing they have to go and count their inventory so rigorously every day to stay compliant. I think that was like, that’s crazy. Yeah. So.
143 00:18:18.020 ⇒ 00:18:30.090 Lexi Allen (she/her): Exactly like. So the compliance of it all is like where people like put all their attention because they obviously don’t want to be illegal, but like otherwise, it’s like in terms of like the sales and stuff like there’s a lot of like.
144 00:18:30.440 ⇒ 00:18:30.760 Robert Tseng: Yeah.
145 00:18:30.760 ⇒ 00:18:33.780 Lexi Allen (she/her): Very startup, very scrappy like figuring it out.
146 00:18:36.190 ⇒ 00:18:39.229 Lexi Allen (she/her): I’m like trying to figure out what else I should tell you in terms of
147 00:18:40.770 ⇒ 00:18:41.590 Lexi Allen (she/her): I really think.
148 00:18:41.590 ⇒ 00:18:53.650 Robert Tseng: So those are the flows like on the employee side, and then the campaign workflow. You sold me how you could set it up at this point. There’s like this inventory module that’s like somewhat being used, but not really a core part of this product right now.
149 00:18:54.560 ⇒ 00:18:55.080 Robert Tseng: We.
150 00:18:55.810 ⇒ 00:19:01.690 Lexi Allen (she/her): Is another one that’s getting more and more play. This is quite. It’s like
151 00:19:02.520 ⇒ 00:19:12.294 Lexi Allen (she/her): pretty self explanatory on like they just like, take a course, and get 5 bucks or something like if they and it’s like a Google form. I said effectively, on the
152 00:19:13.740 ⇒ 00:19:20.490 Lexi Allen (she/her): like on this side, they just like go in and like, can make courses like, add videos and stuff.
153 00:19:20.840 ⇒ 00:19:21.520 Robert Tseng: Yeah.
154 00:19:21.880 ⇒ 00:19:36.809 Robert Tseng: so is the brand re is the brand incentive that they really see that, like their employees, have just like taken all these courses like, have all this engagement and that like translates to them being higher performers, or like, kind of what’s yeah, like, how do we like present that story, to the, to the brands.
155 00:19:36.910 ⇒ 00:19:42.399 Robert Tseng: or to the sorry, to the retailers, not the brands. The brands are the ones who are just like saying, Hey, sell my product? Yeah.
156 00:19:42.400 ⇒ 00:19:45.960 Lexi Allen (she/her): Yeah. Oh, to the retailers. Okay, so for the retailers,
157 00:19:47.660 ⇒ 00:19:53.040 Lexi Allen (she/her): for, like the Joe Schmo, retailer, that’s just like here to have a good time, like Mr. Nice, like.
158 00:19:53.736 ⇒ 00:20:02.300 Lexi Allen (she/her): So most of them are free. Okay? So it’s like, literally no skin off their back to join this because of the fact that.
159 00:20:02.680 ⇒ 00:20:03.510 Lexi Allen (she/her): like
160 00:20:04.360 ⇒ 00:20:18.349 Lexi Allen (she/her): it just makes their employees happy to be able to make money in different ways. So all they gotta do is accept sparks like they get notifications. Oh, someone’s gonna send it to you. You accept it. And then your employees
161 00:20:18.890 ⇒ 00:20:25.710 Lexi Allen (she/her): like this personally has 5 employees, but, like their employees, get paid out. And like, that’s basically like.
162 00:20:26.060 ⇒ 00:20:32.299 Lexi Allen (she/her): it’s like, there’s just no skip because it’s free. Now for the bigger retailers, like a Mr. Nice guy
163 00:20:32.930 ⇒ 00:20:59.049 Lexi Allen (she/her): that has like 88 employees. This is nice to be able to like sell the product that’s like about to like. So you’re saying the inventory and like self days and stuff like things are about to like expire. You can send a little incentive to be like, Hey, sell this product, or like just ways to like, incentivize your employees or soon we’ll have like ways to show. Like to educate your employees, too.
164 00:20:59.510 ⇒ 00:21:00.130 Robert Tseng: Yeah.
165 00:21:01.410 ⇒ 00:21:08.164 Lexi Allen (she/her): on this side. You’re also able to see, like top sellers and stuff this that we’re not giving
166 00:21:08.760 ⇒ 00:21:26.401 Lexi Allen (she/her): we’re basically not giving that retailers anything like revolutionary. Besides, the coordination with the brands like coordination brands is is the main thing that we’re getting. So it’s like, okay, you know, I can just like connect with a bunch of brands, and like they can connect with me. And then they can send me incentives. And it’s easy.
167 00:21:27.830 ⇒ 00:21:36.546 Lexi Allen (she/her): yeah. And then we’re they’re also, if they’re paid retailer, they can send sparks, or they can send snaps to their employees as well.
168 00:21:37.360 ⇒ 00:21:45.976 Lexi Allen (she/her): yeah. So on a brand side. You’re able to see these numbers, too, so you can see like who your top seller is, and like what they’re up to, what their total sales are.
169 00:21:47.340 ⇒ 00:21:52.413 Robert Tseng: But brands have to pay to be on, and that’s like they pay 500,000 a month
170 00:21:53.000 ⇒ 00:21:54.680 Robert Tseng: and you’re saying that
171 00:21:54.900 ⇒ 00:22:00.720 Robert Tseng: even if they don’t have a incentive, they just see the data. But, like, what? What data are they seeing if they don’t have any incentives loaded up.
172 00:22:00.720 ⇒ 00:22:06.560 Lexi Allen (she/her): Okay? So, brand, yeah, totally. This is like the. This is probably in terms of
173 00:22:06.770 ⇒ 00:22:13.279 Lexi Allen (she/her): main value, adds, it’s like Bud, tender engagement. So you can like connect to the bud tenders. But think about
174 00:22:13.650 ⇒ 00:22:15.170 Lexi Allen (she/her): so. I’m a brand
175 00:22:15.300 ⇒ 00:22:22.609 Lexi Allen (she/her): like I feel like it took me a second to like get to this point, but it’s like I’m a brand I sell myself
176 00:22:22.720 ⇒ 00:22:44.010 Lexi Allen (she/her): in, like all stores. Say, I sell in 15 stores, current or 35 stores, or like these people like tons of stores. Okay, yeah, I can’t keep track of that. Like, I know, I’m sending out product. And I know they’re selling it. And I know I’m making some money. But like, it’s really hard for me to actually quantify that without
177 00:22:44.400 ⇒ 00:22:50.219 Lexi Allen (she/her): genuinely in. Besides us, for the most part, people are like emailing brand.
178 00:22:50.630 ⇒ 00:23:00.790 Lexi Allen (she/her): Yeah, emailing the retailer. And we’re like, Hey, can you send me? June’s like the 1st week, 1st 2 weeks of June sales reports
179 00:23:01.060 ⇒ 00:23:11.290 Lexi Allen (she/her): or like, can you send me quarter one of Lexi’s brand because they don’t want to like? Ask every week, or they ask once a week if you can send me this. So it’s like super super manual.
180 00:23:11.780 ⇒ 00:23:12.330 Robert Tseng: Yeah.
181 00:23:12.330 ⇒ 00:23:18.400 Lexi Allen (she/her): We’re we’re integrated directly with their point of sale system. So.
182 00:23:18.690 ⇒ 00:23:19.429 Robert Tseng: Oh, okay.
183 00:23:19.430 ⇒ 00:23:26.930 Lexi Allen (she/her): This data. So it’s like, instead of having to like, send that on the retail side. Send that once a week, getting bogged down by all that.
184 00:23:27.060 ⇒ 00:23:30.100 Lexi Allen (she/her): or instead of on the brand side, having to like.
185 00:23:30.420 ⇒ 00:23:36.309 Lexi Allen (she/her): ask request that every time so like needing to request info. It’s just here.
186 00:23:36.410 ⇒ 00:23:43.529 Robert Tseng: So like, that’s a pretty big value. Add, you can roll it up for all of California, or you can go in and see like what.
187 00:23:43.890 ⇒ 00:24:00.299 Lexi Allen (she/her): This place is doing over the last like, these are their sales. Yeah, a little bit of a flat line. You’re like, okay, like, am I out of stock like, let me go check my inventory on this product. I can break it down by product. I can see like.
188 00:24:01.250 ⇒ 00:24:13.700 Lexi Allen (she/her): And I can see like, okay, how is Blueberry Kush doing these days? Like there’s a couple flat lines here that’s giving out of stock, you know. Like, if it was selling like that. But then it’s like flat, like, maybe I need to restock on that one.
189 00:24:13.970 ⇒ 00:24:17.510 Lexi Allen (she/her): Yeah, I mean, like, that’s just a huge value. Add to be able to see
190 00:24:17.650 ⇒ 00:24:22.340 Lexi Allen (she/her): all of these across without having to go to the store for having to like.
191 00:24:23.070 ⇒ 00:24:25.970 Robert Tseng: And all your paid retailers share point of sale data with you.
192 00:24:26.450 ⇒ 00:24:30.219 Lexi Allen (she/her): All of our all of our data, all of our retailers share.
193 00:24:30.220 ⇒ 00:24:32.829 Robert Tseng: See, even a retailer doesn’t pay anything. They come on.
194 00:24:33.120 ⇒ 00:24:39.320 Robert Tseng: they just, and they they get set up by hooking up to their point of sale data to to spark, plug.
195 00:24:40.360 ⇒ 00:24:42.540 Robert Tseng: Okay, so that’s part of like their onboarding. I see.
196 00:24:42.810 ⇒ 00:24:44.600 Lexi Allen (she/her): Exactly. So.
197 00:24:45.270 ⇒ 00:24:51.800 Lexi Allen (she/her): We have just a wealth of data that people are like dying to engage with
198 00:24:52.427 ⇒ 00:25:02.590 Lexi Allen (she/her): and they want to export it. They want to like have us to have Apis to like, spin it up other ways, like we have data that, like effectively, no one else has.
199 00:25:02.780 ⇒ 00:25:16.219 Lexi Allen (she/her): Other companies have, like menu scraping where they like, will like, try to things in carts and see when it goes out of stock and like. Then they derive the number from that, you know, like they’re just directly with the point of sale.
200 00:25:17.620 ⇒ 00:25:18.660 Robert Tseng: Oh, I see.
201 00:25:19.840 ⇒ 00:25:24.400 Robert Tseng: Okay, so that makes sense. Why, brands are, yeah, I mean, they’re basically just coming to you for, like,
202 00:25:25.090 ⇒ 00:25:32.360 Robert Tseng: yeah, for for re, for retailer data. Pretty much. Yeah, that’s interesting.
203 00:25:33.820 ⇒ 00:25:35.500 Lexi Allen (she/her): Yeah, okay.
204 00:25:36.190 ⇒ 00:25:56.260 Lexi Allen (she/her): yeah. So that’s like main value. And we also automatically, partner. So it’s like, if based on their brand name. So it’s like their brands. Names are sluggers D and Iced. We’ll scan all of the retailers in California, and then automatically connect them with all the retailers that have their product in in store.
205 00:25:56.810 ⇒ 00:25:57.370 Robert Tseng: Yeah.
206 00:25:57.540 ⇒ 00:26:06.650 Lexi Allen (she/her): And if they’ve sold in the last 60 days they are considered active, and if they’re not, then we can like inactive, as like sold in the last
207 00:26:06.930 ⇒ 00:26:10.640 Lexi Allen (she/her): like, not not sold in the last 60 days. So it’s like, Okay, yeah.
208 00:26:11.070 ⇒ 00:26:14.999 Lexi Allen (she/her): And then they can disable links if they want. But we automatically link them up.
209 00:26:16.260 ⇒ 00:26:26.250 Robert Tseng: Yeah. So this is a good proxy for stock outs. And then well, brands kind of have to go and figure out like where where they need to restock. Do you do any like surfacing of stuff to brands and be like, hey?
210 00:26:26.833 ⇒ 00:26:38.989 Robert Tseng: You know you’re this is this is the retailer that you have the highest like sales velocity in, and you’re stocked out like you should definitely go restock with Swan. Do we do any sort of recommendations like that.
211 00:26:39.260 ⇒ 00:26:45.479 Lexi Allen (she/her): So not yet. Inventory is still like relatively new, but also
212 00:26:45.710 ⇒ 00:27:04.120 Lexi Allen (she/her): it’s a paid add on. So if you add, on gets it. This is like the most where it’s like, okay, there are 31 out of stocks in this one. So if you want to go check specifically, but we don’t have roundups yet. So we would love to do roundups in the near future of being like, Hey.
213 00:27:04.120 ⇒ 00:27:04.670 Robert Tseng: Yeah.
214 00:27:04.670 ⇒ 00:27:07.350 Lexi Allen (she/her): All these out of stock. We’re still trying to like get
215 00:27:07.770 ⇒ 00:27:16.419 Lexi Allen (she/her): good on the data here, because some of the data is not always like perfect like clear like. Make that better before we like.
216 00:27:17.040 ⇒ 00:27:17.600 Robert Tseng: And this is.
217 00:27:17.600 ⇒ 00:27:23.479 Robert Tseng: it’s just a matter of like, I mean, I guess this is to me this is like client facing analytics like, how? How? Where is this data coming from.
218 00:27:24.760 ⇒ 00:27:26.939 Lexi Allen (she/her): Where is this data coming from the point sale.
219 00:27:27.520 ⇒ 00:27:34.909 Robert Tseng: Okay point of sale. You? I mean, you kind of do some, I mean, do you have? Do you store it? Obviously, when you store this data?
220 00:27:35.656 ⇒ 00:27:38.090 Robert Tseng: And then you kind of.
221 00:27:38.700 ⇒ 00:27:49.659 Robert Tseng: yeah, I guess you guys have a data warehouse. And then you you kind of do the transformations. And then you kind of update this on an hourly basis or kind of how does that? How does that? How does it go from point of sale to here?
222 00:27:49.660 ⇒ 00:28:14.720 Lexi Allen (she/her): Yeah. So it’s a little janky. We’re working on our data warehousing right now, like, this is the biggest one of our bigger projects on the platform side. We currently store in like a combination between mongoed postgres right now. And we have, like one big transaction object that we’re pulling. Basically, whatever the point of sale gives us, like we’ve taken, you know, like we just take it all.
223 00:28:14.840 ⇒ 00:28:38.860 Lexi Allen (she/her): And then the like one field is inventory. So we’ll like use that in this one lot, like we usually we just take like units sold like, or like the unit sold inventory like when it was sold, and then product, name category brand. Are the main ones that we’re working with. So yeah, so no like.
224 00:28:39.950 ⇒ 00:28:47.529 Lexi Allen (she/her): no like deep, deep transformation. And the thing is, there’s 30 different point of sale systems that we’re working with.
225 00:28:47.710 ⇒ 00:29:04.809 Lexi Allen (she/her): So we also, everyone’s like a little bit different, like, it’s not like everyone treats this exactly the same. So we’re trying to basically like streamline, all of the point of sale data and then like, make it like, just like make it the same across point of sales. So.
226 00:29:06.090 ⇒ 00:29:07.639 Robert Tseng: Got it. Yeah.
227 00:29:08.750 ⇒ 00:29:15.259 Robert Tseng: And this is, I guess this is also built by what Ryan and er what was the other guy’s date?
228 00:29:15.570 ⇒ 00:29:16.500 Lexi Allen (she/her): Worry, maybe.
229 00:29:16.500 ⇒ 00:29:20.049 Robert Tseng: Brandon present find your branded that that wrote that too.
230 00:29:20.901 ⇒ 00:29:26.518 Lexi Allen (she/her): So Brandon is their product designer. So he’s more of like the Ui guy.
231 00:29:26.920 ⇒ 00:29:27.610 Robert Tseng: Okay.
232 00:29:27.610 ⇒ 00:29:31.144 Lexi Allen (she/her): And then I think maybe Ryan and Corey was what we were talking about. But.
233 00:29:31.380 ⇒ 00:29:32.330 Robert Tseng: Okay. Okay.
234 00:29:32.330 ⇒ 00:29:34.829 Lexi Allen (she/her): Yeah, so
235 00:29:35.680 ⇒ 00:29:45.259 Lexi Allen (she/her): they are more front. We have like a whole platform team, too. So like most of the point of sales stuff is working with the platform team who you haven’t met yet.
236 00:29:45.700 ⇒ 00:29:54.070 Lexi Allen (she/her): And the front end is like, or like the full stack, like other feature work, is Ryan Corey.
237 00:29:55.100 ⇒ 00:30:06.090 Robert Tseng: I’m only asking because I mean, I, my background data engineering. So I mean, this is like a fun project that I would be interested if you don’t know, anyway. So I’m just asking.
238 00:30:06.090 ⇒ 00:30:13.339 Lexi Allen (she/her): Is like the one that would is doing all the data warehousing stuff. So yeah, okay, yeah.
239 00:30:13.810 ⇒ 00:30:14.540 Robert Tseng: Alright!
240 00:30:15.070 ⇒ 00:30:20.679 Lexi Allen (she/her): Yeah. Okay, what else can I tell you? Yeah, I think.
241 00:30:21.930 ⇒ 00:30:24.689 Lexi Allen (she/her): yeah, I’m trying to think of. Like, most notably,
242 00:30:27.850 ⇒ 00:30:31.009 Lexi Allen (she/her): it’s like a whole ecosystem. So like
243 00:30:31.360 ⇒ 00:30:37.959 Lexi Allen (she/her): we can’t just look at employees in in isolation. I think that’s like most important, and like the amount of
244 00:30:38.360 ⇒ 00:30:56.999 Lexi Allen (she/her): like the funnel of getting them campaigns, like actively and consistently, is just as important as like their daily use, or like, I would say, weekly use. Like me. Personally, I think weekly use is the better metric than daily also, events like events, are probably
245 00:30:58.010 ⇒ 00:30:58.700 Lexi Allen (she/her): like.
246 00:30:59.450 ⇒ 00:31:06.699 Lexi Allen (she/her): We don’t need a ton of events to con like to say that it was a good use of a session.
247 00:31:07.000 ⇒ 00:31:15.230 Lexi Allen (she/her): Yeah, like, all I really need to do on this is like log in, like, genuinely like I can.
248 00:31:17.020 ⇒ 00:31:18.139 Lexi Allen (she/her): It’s just not working.
249 00:31:20.388 ⇒ 00:31:23.140 Lexi Allen (she/her): Okay, I can like log in.
250 00:31:24.010 ⇒ 00:31:46.199 Lexi Allen (she/her): It’s like so many different ones. Log in check. This sparks like scroll down real quick check, earn. If there’s 1 thing to do like, answer the questions and then have one event and like doesn’t have to be like that. Many clicks for me to like have had a good experience here. But at the end of the month you probably are gonna realistically want to cash out, in which case like those events. Get a bit higher.
251 00:31:48.967 ⇒ 00:31:54.849 Robert Tseng: So people usually cash out like once a month or like not. It’s not like, yeah, not daily, or whatever. So.
252 00:31:54.850 ⇒ 00:32:06.380 Lexi Allen (she/her): It really depends on like the user. Often cash most a lot of sparks end at the end of the month. Therefore, like people like, Okay, you have a claim. You can claim it. And then, like.
253 00:32:06.380 ⇒ 00:32:06.830 Robert Tseng: Got it.
254 00:32:07.788 ⇒ 00:32:10.359 Lexi Allen (she/her): Some bud tenders like to like
255 00:32:10.460 ⇒ 00:32:30.790 Lexi Allen (she/her): pull it like, you know, they’re like, Okay, I’m gonna cash out like once a year so they can like get a vacation like that is definitely something we’ve seen or like. I can like, buy that. One thing I’ve been thinking about, and it’s like, not my bank account. So yeah, it does. It kind of depends. But people normally claim their rewards.
256 00:32:31.230 ⇒ 00:32:31.910 Lexi Allen (she/her): even if they don’t.
257 00:32:31.910 ⇒ 00:32:32.600 Robert Tseng: Oh, okay.
258 00:32:33.100 ⇒ 00:32:37.040 Lexi Allen (she/her): Cause. There’s like a claim step. So it’s like you have to claim them, and then you cash out.
259 00:32:37.870 ⇒ 00:32:38.410 Robert Tseng: Yeah.
260 00:32:42.130 ⇒ 00:32:49.560 Lexi Allen (she/her): Okay, I’m like trying to think of what else I can tell you in terms of info.
261 00:32:50.600 ⇒ 00:33:02.234 Lexi Allen (she/her): There, feedback employee feedback is also something that people like that the brands like love. So they’re doing a lot through courses right now.
262 00:33:04.900 ⇒ 00:33:06.980 Lexi Allen (she/her): for example, like.
263 00:33:08.010 ⇒ 00:33:14.259 Lexi Allen (she/her): how would you sell the slugger like how would you sell this product was was, what a thing and like. Let me just show you this.
264 00:33:15.050 ⇒ 00:33:15.480 Robert Tseng: Yeah.
265 00:33:15.480 ⇒ 00:33:27.989 Lexi Allen (she/her): So they can click in during courses. They watch this video. And they say, How would you sell it? So it’s like they watch a 6 min video. And then they ask how you sell it. And then they like, see? Okay.
266 00:33:30.000 ⇒ 00:33:41.599 Lexi Allen (she/her): like, which one is it like? Is it single source? Or like all the above or like this, is the right answer so incomplete, and you can hit it out of the park. So that’s like a sample quiz
267 00:33:41.790 ⇒ 00:33:52.120 Lexi Allen (she/her): with that one they have. How you sell then you can view all of the answers.
268 00:33:52.340 ⇒ 00:33:54.579 Lexi Allen (she/her): and people like can really go into
269 00:33:55.660 ⇒ 00:33:59.299 Lexi Allen (she/her): like detail here, which is, it’s kind of interesting to see, like all
270 00:33:59.350 ⇒ 00:34:11.240 Lexi Allen (she/her): some people like say, hack responses. So it’s like a kind of like in between. But people love this like raw feedback from the bud tender, so that they know exactly like what people are saying about their product.
271 00:34:11.280 ⇒ 00:34:31.201 Lexi Allen (she/her): Then next time they go in store, because they really are in person. They can go see Noah, and then give them like an ounce, because, like they did a good job, which is like something that happens, then they can also, like summarize this at the top, and then they usually take those like insights. This is like a 1,500 word, 1,500 response one, for example,
272 00:34:32.150 ⇒ 00:34:38.880 Lexi Allen (she/her): and then they’re also able to see, like the percent of their market that was completed. The trainings. So it’s like, hey? They really want to get to
273 00:34:39.000 ⇒ 00:34:42.280 Lexi Allen (she/her): like full market coverage of like having.
274 00:34:42.500 ⇒ 00:34:51.090 Lexi Allen (she/her): like understood their product, know what it is, etc. So 1,500 responses is like quite high for the California market. So far.
275 00:34:51.670 ⇒ 00:34:52.270 Robert Tseng: Got it.
276 00:34:54.339 ⇒ 00:34:59.499 Lexi Allen (she/her): Other ones that you might be interested in is the retool. So
277 00:34:59.939 ⇒ 00:35:07.259 Lexi Allen (she/her): terms of other data that we have. We have, like a little bit of like, just different dashboards. For, like
278 00:35:07.833 ⇒ 00:35:11.649 Lexi Allen (she/her): different data that we’re interested in. So like courses.
279 00:35:11.650 ⇒ 00:35:15.559 Robert Tseng: This is all your main bi tool. You guys don’t really use like a tableau or look or anything.
280 00:35:15.560 ⇒ 00:35:20.320 Lexi Allen (she/her): Yeah, exactly. So, courses like, see how much money we’ve
281 00:35:20.430 ⇒ 00:35:27.096 Lexi Allen (she/her): collect, how many fees collected, how many like $45,000. We just started this one in like January,
282 00:35:27.430 ⇒ 00:35:28.070 Robert Tseng: Okay.
283 00:35:28.320 ⇒ 00:35:43.189 Lexi Allen (she/her): To see like how much money has gone through the app on this one in the growth month over month. How many events have been through. So this is just like a little bit more data that we have in different broken down pieces, you know, like
284 00:35:43.450 ⇒ 00:35:48.000 Lexi Allen (she/her): full rhyme or reason per, but just more like mini dashboards per
285 00:35:48.920 ⇒ 00:35:51.660 Lexi Allen (she/her): or like product that we’re looking at.
286 00:35:52.060 ⇒ 00:35:52.620 Robert Tseng: Yeah.
287 00:35:56.090 ⇒ 00:36:02.120 Lexi Allen (she/her): Yep. And then we also have cash outs like our wallet report, too. So we’re able to see like
288 00:36:02.650 ⇒ 00:36:06.520 Lexi Allen (she/her): you know, how much since January. Like.
289 00:36:06.650 ⇒ 00:36:09.969 Lexi Allen (she/her): think it’s been like 6 million bucks of cash
290 00:36:10.780 ⇒ 00:36:13.059 Lexi Allen (she/her): blown through the app. So it’s like.
291 00:36:14.160 ⇒ 00:36:15.119 Robert Tseng: And year to date.
292 00:36:16.462 ⇒ 00:36:20.887 Lexi Allen (she/her): Yeah, from beginning of the year. Yeah, about 6 million
293 00:36:22.340 ⇒ 00:36:30.679 Lexi Allen (she/her): of. And then, like 400,000 unclaimed. So it’s like, there’s pretty a lot of money that we’re like funneling through the app. So.
294 00:36:30.680 ⇒ 00:36:31.320 Robert Tseng: Yeah.
295 00:36:32.190 ⇒ 00:36:39.919 Lexi Allen (she/her): Yeah, uploads of like profile pictures trying to get that a little bit more in there as well.
296 00:36:40.686 ⇒ 00:36:44.149 Lexi Allen (she/her): This is so slow today, it’s usually not this slow
297 00:36:45.228 ⇒ 00:36:47.861 Lexi Allen (she/her): but yeah, you get the idea.
298 00:36:48.300 ⇒ 00:36:57.500 Robert Tseng: This is like the main thing that Jake looks at when he’s thinking like, kind of or I guess yeah, executive level reporting as well like people. Just stop.
299 00:36:58.330 ⇒ 00:37:00.030 Robert Tseng: Yeah. 2 way checks on the bill.
300 00:37:00.030 ⇒ 00:37:02.519 Lexi Allen (she/her): I think that their reporting is not like.
301 00:37:03.240 ⇒ 00:37:09.860 Lexi Allen (she/her): I know that I report out on these things like every 2 weeks. And then.
302 00:37:11.370 ⇒ 00:37:19.362 Lexi Allen (she/her): like. I know that sometimes they take what I have reported out, and sometimes they don’t like. I don’t think it’s like so
303 00:37:20.230 ⇒ 00:37:28.140 Lexi Allen (she/her): hard fast is what I’d say, so yeah, feel like, that’s
304 00:37:28.570 ⇒ 00:37:32.940 Lexi Allen (she/her): like, what else can I tell you? Are there any questions that you have so far based on like
305 00:37:33.660 ⇒ 00:37:34.900 Lexi Allen (she/her): for this dump.
306 00:37:35.490 ⇒ 00:37:45.450 Robert Tseng: Oh, yeah, no, this is great. I mean, it’s kind of I had an outline in terms of areas I wanted to cover kind of covered most of it. Yes, kind of filling in the blanks outside of mixed panel, like everything else that’s going on.
307 00:37:45.450 ⇒ 00:37:45.830 Lexi Allen (she/her): Yeah.
308 00:37:47.390 ⇒ 00:37:49.469 Robert Tseng: Yeah. I mean, obviously, I go ahead.
309 00:37:49.940 ⇒ 00:37:53.649 Lexi Allen (she/her): I was just thinking in terms of outside mix panel, like other things that
310 00:37:53.790 ⇒ 00:38:08.479 Lexi Allen (she/her): we refer to is like our control center. So it’s like again, not anything like amazing to look at or to engage with. But we do have like on the accounts you can see, like
311 00:38:09.290 ⇒ 00:38:13.020 Lexi Allen (she/her): our recent sparks, we’re able to see like what sparks are going through the app
312 00:38:13.880 ⇒ 00:38:17.910 Lexi Allen (she/her): here. How many sparks per month, whatever you can like filter here.
313 00:38:18.460 ⇒ 00:38:25.579 Lexi Allen (she/her): or like fulfilled ones versus unfulfilled and we also have a by account. We can see, like pending users.
314 00:38:26.080 ⇒ 00:38:31.780 Lexi Allen (she/her): the amount of active sparks. And then Hubspot is also another big tool that people are using.
315 00:38:31.780 ⇒ 00:38:35.970 Robert Tseng: Oh, right? Yeah, you mentioned, we’re gonna show a hubspot usage of how people use that.
316 00:38:36.500 ⇒ 00:38:44.000 Lexi Allen (she/her): Yeah. So Hubspot is really more of a Cs tool than my tool to be honest. But
317 00:38:44.400 ⇒ 00:38:48.979 Lexi Allen (she/her): they let’s see, they have like different companies like.
318 00:38:49.340 ⇒ 00:39:12.399 Lexi Allen (she/her): obviously they’re in charge of certain accounts. And this is like more for the like sales to Cs flow. So it’s like from onboarding of new customers. We’re like, like sourcing customers to onboarding them. Then you have a good amount of data assigned to each like company trying to think of like
319 00:39:12.930 ⇒ 00:39:15.060 Lexi Allen (she/her): it’s like, Look up, natura, for example.
320 00:39:16.110 ⇒ 00:39:19.319 Lexi Allen (she/her): I don’t know which one is gonna be the perfect
321 00:39:20.048 ⇒ 00:39:28.689 Lexi Allen (she/her): but per, I know that they use this like a lot. But I again, I really am not using this so much. I don’t even know if that’s the right one.
322 00:39:29.470 ⇒ 00:39:36.889 Lexi Allen (she/her): etc. So they’ll like, it’s this one, yeah, private. So yeah.
323 00:39:36.890 ⇒ 00:40:01.020 Lexi Allen (she/her): that’s looking more legit. So they’ll they’ll do all their notes, calls everything, all their tasks associated with this. And we can just see a little bit more about their account here. And then people will be taking like different, like reports. I know that they do a lot of like Hubspot reports link to like retailers with. We want retailers to have like really high onboarding rates for their employees, like up.
324 00:40:01.020 ⇒ 00:40:01.360 Robert Tseng: Yep.
325 00:40:01.360 ⇒ 00:40:11.239 Lexi Allen (she/her): And it’s under 80%. They get flags, things like that. But this is a big tool that they use, and they always are asking us to funnel more and more and more information here.
326 00:40:12.490 ⇒ 00:40:12.930 Robert Tseng: Yeah.
327 00:40:12.930 ⇒ 00:40:13.470 Lexi Allen (she/her): You know.
328 00:40:14.720 ⇒ 00:40:25.050 Robert Tseng: So what data do you have you pushed into Hubspot? Out of the product? Or I guess, a a employee onboarding rate that you mentioned. So you somehow have
329 00:40:25.720 ⇒ 00:40:29.970 Robert Tseng: with their report a number of employees versus how many users you actually have signed up?
330 00:40:32.210 ⇒ 00:40:41.019 Robert Tseng: yeah, obviously, you can push data like, you know, number of number of courses like any sort of like activity based metrics. You could push with Hubspot. Yeah.
331 00:40:41.460 ⇒ 00:41:01.448 Lexi Allen (she/her): We push like, yeah, number per product. We have like a like a list of them. So it’s like courses active like courses published, you know, course? We also have entitlement data so like anything that like link to their add ons that we push in there as well.
332 00:41:01.990 ⇒ 00:41:05.070 Lexi Allen (she/her): what else do we push into Hubspot?
333 00:41:06.491 ⇒ 00:41:19.978 Lexi Allen (she/her): Honestly, there’s a lot of like one off requests that Cs will ask. So then we’ll pull it in, depending on like their needs. It’s not like for retailers on the
334 00:41:21.590 ⇒ 00:41:49.860 Lexi Allen (she/her): like Mr. Nice guy like for their enrollment. You’re able to see that in App. So you don’t really have to go to Hubspot. But a lot of the stuff that they ask for you can see in App, but they need like a a view that they can see across all of their accounts. So this has like 97% enrollment, which is great. It’s like this is a great enrollment number. But they’ll try to find, like the numbers of not enrolled like, how many percent of not are not enrolled here.
335 00:41:50.500 ⇒ 00:41:51.140 Robert Tseng: Yeah.
336 00:41:51.592 ⇒ 00:41:55.209 Lexi Allen (she/her): What else do they ask for in there?
337 00:41:55.886 ⇒ 00:42:05.650 Lexi Allen (she/her): Honestly, yeah, they like are constantly asking for, like a new thing in there. Like to be honest. So yeah, not like a perfect.
338 00:42:05.850 ⇒ 00:42:11.222 Lexi Allen (she/her): Okay. Everything like there’s no like clear, clear way of seeing it.
339 00:42:12.220 ⇒ 00:42:15.710 Lexi Allen (she/her): trying to think. Yeah, I don’t have like a perfect answer for you on that one, but they do have.
340 00:42:15.710 ⇒ 00:42:16.260 Robert Tseng: Of course. Yeah.
341 00:42:16.260 ⇒ 00:42:22.634 Lexi Allen (she/her): It’s a ton of different info, and we’re pretty like responsive and intercom is another one that we use
342 00:42:23.640 ⇒ 00:42:35.700 Lexi Allen (she/her): and that’s on the support side. So for intercom, we have whatever we push to Hubspot, we often push to intercom, too, so that so that support can do their job a little bit better.
343 00:42:36.620 ⇒ 00:42:37.220 Robert Tseng: Okay.
344 00:42:37.420 ⇒ 00:42:38.000 Lexi Allen (she/her): Yeah.
345 00:42:39.330 ⇒ 00:42:45.920 Robert Tseng: Got it. Yeah, that’s a great overview. I think. Definitely, a lot of, I’ve got a better understanding what data is kind of flowing where?
346 00:42:46.411 ⇒ 00:43:09.920 Robert Tseng: Yeah, I know the data that you use to surface in your app. Now, what data you push into. I mean, you don’t really have like a engagement platform. Everything seems to be like account based engagement. So it’s all intercom. And hubspot so I’m assuming you have like a Cs kind of team that just goes and kind of continues the relationship, or just does account management with your with mostly brands and retailers.
347 00:43:10.160 ⇒ 00:43:11.240 Lexi Allen (she/her): Yes, France.
348 00:43:11.380 ⇒ 00:43:12.859 Robert Tseng: Enemies? Is it similar.
349 00:43:12.860 ⇒ 00:43:16.069 Lexi Allen (she/her): Brands. Some paid retailers, if they’re like.
350 00:43:16.070 ⇒ 00:43:16.849 Robert Tseng: Updated till I’m.
351 00:43:16.850 ⇒ 00:43:21.619 Lexi Allen (she/her): You’re paid retailer. Then there’ll be an account. But they’ll mostly do like
352 00:43:21.760 ⇒ 00:43:27.770 Lexi Allen (she/her): that. We have a retail Csm. Cohort, and we have a vendors or a brand. Csm.
353 00:43:28.970 ⇒ 00:43:34.946 Robert Tseng: Yeah. So local revenue comes from brands. And then you facilitate all this. These like
354 00:43:36.390 ⇒ 00:43:41.750 Robert Tseng: payouts on your app. It’s kind of cool. I didn’t realize it’s like a venmo for these people.
355 00:43:41.750 ⇒ 00:43:43.343 Lexi Allen (she/her): Yeah. Venmo
356 00:43:44.740 ⇒ 00:43:45.250 Lexi Allen (she/her): They may.
357 00:43:45.250 ⇒ 00:43:50.670 Robert Tseng: And you don’t have to be accredited as a bank or anything. It’s just you’re facilitating 1 million dollars going through the app.
358 00:43:50.670 ⇒ 00:43:57.824 Lexi Allen (she/her): Yeah, exactly. That’s why I showed like 6 million like a million a month is like a non trivial amount of money.
359 00:43:58.150 ⇒ 00:43:58.860 Robert Tseng: Yeah, yeah.
360 00:43:59.510 ⇒ 00:44:16.849 Lexi Allen (she/her): Series a, I mean, like, very like very scrappy startup. And then it’s like people are changing their it’s like from going for 15 bucks an hour to like getting 200 bucks like every week based on these things like, it’s like a pretty meaningful change.
361 00:44:17.850 ⇒ 00:44:19.450 Lexi Allen (she/her): Their income. So.
362 00:44:19.880 ⇒ 00:44:45.620 Robert Tseng: Yeah. So the growth strategy is really just to bring on more brands. And then, as you have more brands and more retailers want to come on because most retailers it’s free for them. So there’s some awareness campaigns going to like get more retailers on boarded as well. But I’m assuming, since you’re not getting paid by them. That’s like probably a kind of a cost center for you in terms of how you onboard retailer, and you wanting to make that more frictionless for them. Yeah.
363 00:44:46.060 ⇒ 00:44:53.282 Robert Tseng: But then you also need them. Yeah, you need them to bring their employees on, because they’re the ones that are ultimately transacting with the brands.
364 00:44:53.810 ⇒ 00:44:54.930 Lexi Allen (she/her): Exactly. Yeah.
365 00:44:55.150 ⇒ 00:44:56.070 Robert Tseng: Decision.
366 00:44:56.677 ⇒ 00:45:04.619 Lexi Allen (she/her): And then there’s also definitely like a ton of opportunity to monetize this mass retail group that we have like.
367 00:45:04.620 ⇒ 00:45:05.609 Robert Tseng: Totally. Yeah.
368 00:45:05.610 ⇒ 00:45:12.569 Lexi Allen (she/her): Like thousands of retailers. So it’s like, definitely something that we’ve been thinking about in terms of how do we monetize them? So.
369 00:45:12.900 ⇒ 00:45:14.710 Robert Tseng: Yeah, okay.
370 00:45:15.240 ⇒ 00:45:26.909 Robert Tseng: super cool. I mean, I know that you’ve got blocked out 45 min. I mean, I can go a little longer. But yeah, overall. Thank you for the walkthrough. Yeah. I think I got a bunch of observations and things
371 00:45:27.299 ⇒ 00:45:49.100 Robert Tseng: next steps for me, like I’d love to just consolidate kind of like my notes, thoughts on kind of what I think you and yeah, I mean, I kind of want to just put a roadmap in front of like you, Jake. See if there’s opportunity for us to go after. Like other data projects. Obviously, on the data engineering side. I’d love to kind of talk to Sweeney and kind of hear what he’s doing on that side.
372 00:45:49.474 ⇒ 00:46:11.135 Robert Tseng: Just cause, like, you know. Obviously, at at this stage. It’s typically like the product engineer who spends like half their time doing like data stuff that’s not really platform building. So yeah, if I can. If me and my team could take some of that off your hands like I think that’s that’s what we love to do. So yeah, I don’t know, but overall like wow, like very cool. Thank you for the walkthrough, and
373 00:46:11.410 ⇒ 00:46:27.019 Lexi Allen (she/her): Yeah, let me know how I can help. Yeah, the data stuff. Totally. Freeni, I can always, like, you know, connect you guys with whatever I’m happy to look over whatever you have after. So yeah, just just hit me up. We can always schedule another call, too, if if you have questions good.
374 00:46:27.350 ⇒ 00:46:28.350 Robert Tseng: Okay, cool.
375 00:46:28.490 ⇒ 00:46:32.350 Robert Tseng: Well, thanks for thanks for the time, Lexi, and enjoy your time back home. Yeah.
376 00:46:32.350 ⇒ 00:46:34.589 Lexi Allen (she/her): Thank you so much. Have a good day. I’ll talk to you later.