Meeting Title: Marketing plan for Pros Date: 2024-08-06 Meeting participants: Kim Todaro, Jakob Kagel, Nicolas Sucari
WEBVTT
1 00:00:26.200 ⇒ 00:00:27.419 Jakob Kagel: Hi! How’s it going.
2 00:00:29.870 ⇒ 00:00:30.900 Nicolas Sucari: Thank you. Gum
3 00:00:31.270 ⇒ 00:00:33.340 Nicolas Sucari: all good. How about you?
4 00:00:35.150 ⇒ 00:00:36.849 Jakob Kagel: Doing well doing well.
5 00:00:39.060 ⇒ 00:00:40.409 Jakob Kagel: Hey, Kim, how are you.
6 00:00:41.100 ⇒ 00:00:42.479 kim todaro: Good. How are you guys.
7 00:00:42.650 ⇒ 00:00:44.749 Jakob Kagel: Doing well, doing well. Hope you’re having.
8 00:00:44.750 ⇒ 00:00:46.220 Nicolas Sucari: Good Hi! Kim.
9 00:00:46.690 ⇒ 00:00:47.570 kim todaro: Hi.
10 00:00:50.460 ⇒ 00:01:02.289 Nicolas Sucari: Okay, great. So the idea today is to try work together on creating like that marketing plan, we need to target the existing pros
11 00:01:02.290 ⇒ 00:01:24.440 Nicolas Sucari: and try to understand what we can do. As what we can do different so that we can reactivate them so we can. I don’t know. Think of some ideas that we can place into a plan, and then propose that to them that for existing pros, and then for new customers. I think the idea was using outscraper so that we can get some
12 00:01:24.570 ⇒ 00:01:30.395 Nicolas Sucari: information of some clients that we can go on target by direct email campaigns. Right?
13 00:01:31.460 ⇒ 00:01:37.494 kim todaro: I think. The scraper, too. We were gonna try to do some direct mail campaigns for them.
14 00:01:38.130 ⇒ 00:01:39.620 kim todaro: as well as email.
15 00:01:41.220 ⇒ 00:01:54.010 Nicolas Sucari: Okay, perfect. Yeah. I I wrote some ideas on an ocean page. If you want, I can show it. And we can. Yeah, discuss on what we can do. But if we can 1st focus on existing pros.
16 00:01:54.140 ⇒ 00:01:55.929 Nicolas Sucari: we can start
17 00:01:56.100 ⇒ 00:01:57.900 Nicolas Sucari: discussing here.
18 00:01:58.600 ⇒ 00:01:59.470 Jakob Kagel: Sounds good.
19 00:01:59.470 ⇒ 00:02:10.330 Nicolas Sucari: Are. Yeah, these are some ideas on what we can do for the existing pros. I mean, I wrote personalized support, exclusive discounts and feedback loop.
20 00:02:10.679 ⇒ 00:02:21.210 Nicolas Sucari: These are kind of 3 different actions that we can do, so that we can enable, like the conversation again with these kind of customers and see what we can offer to them.
21 00:02:21.970 ⇒ 00:02:29.849 Nicolas Sucari: and so that they can start buying again right? Because if they are pros, probably they are buying someone else if they are not buying us right?
22 00:02:31.860 ⇒ 00:02:40.959 kim todaro: Yes, and do you guys have the list? Or if you could just show me where the report is in real, so I can upload it to Klavio to see how many are like.
23 00:02:42.990 ⇒ 00:02:44.600 kim todaro: you know, subscribers.
24 00:02:46.420 ⇒ 00:02:48.130 Nicolas Sucari: Subscribe as as pros.
25 00:02:48.280 ⇒ 00:02:48.960 Nicolas Sucari: I mean.
26 00:02:49.465 ⇒ 00:02:51.484 kim todaro: Yeah. The pros segment.
27 00:02:52.260 ⇒ 00:02:56.240 kim todaro: is there a way I can get like a Csv, so I can upload it to Klavio.
28 00:02:57.050 ⇒ 00:02:57.400 Jakob Kagel: So like.
29 00:02:57.400 ⇒ 00:02:57.980 Nicolas Sucari: Yeah.
30 00:02:57.980 ⇒ 00:02:58.750 Jakob Kagel: It’s
31 00:03:01.920 ⇒ 00:03:03.660 Jakob Kagel: or emails. Yeah.
32 00:03:03.660 ⇒ 00:03:06.416 kim todaro: Yeah, yeah, exactly. I know. I know.
33 00:03:06.900 ⇒ 00:03:08.570 kim todaro: When Tom showed it to me.
34 00:03:09.250 ⇒ 00:03:25.080 Nicolas Sucari: Yeah. So if we go to this this report, it’s shopify customers we can find here. The dimension of is full pro derived. This is the one that I think it contains all of the different rules that we were setting
35 00:03:25.340 ⇒ 00:03:33.559 Nicolas Sucari: if they were flagged as a pull pro. So if we. Yeah, I don’t know what we are. Okay, that’s 3 months. Now let’s go all time.
36 00:03:34.130 ⇒ 00:03:36.950 Nicolas Sucari: So here we have, like the 1.8.
37 00:03:38.240 ⇒ 00:03:38.850 kim todaro: Nice.
38 00:03:38.850 ⇒ 00:03:49.490 Nicolas Sucari: Customers that we were that we were talking about. If we flag this as true, we can see, like all the information for these ones. And if you want to, if you want to.
39 00:03:49.600 ⇒ 00:03:54.269 Nicolas Sucari: I think, export some list of emails, we can go to the pivot table
40 00:03:55.990 ⇒ 00:03:57.550 Nicolas Sucari: and add
41 00:03:57.940 ⇒ 00:04:02.730 Nicolas Sucari: probably totally existing customers as a mess as a measure here.
42 00:04:02.730 ⇒ 00:04:03.110 Jakob Kagel: I can.
43 00:04:03.110 ⇒ 00:04:04.410 Nicolas Sucari: I can’t explored.
44 00:04:04.410 ⇒ 00:04:07.140 Jakob Kagel: For you, too, if you want, and just send it over.
45 00:04:07.140 ⇒ 00:04:09.709 Nicolas Sucari: Yeah, that will be easier, I think. Yes.
46 00:04:10.030 ⇒ 00:04:11.009 kim todaro: That’s perfect. Yeah.
47 00:04:11.010 ⇒ 00:04:15.840 Jakob Kagel: If you, if you only need exactly, if you only need the list of emails that are pool pro
48 00:04:17.560 ⇒ 00:04:20.279 Jakob Kagel: then yeah, that’s we can do that for sure.
49 00:04:22.550 ⇒ 00:04:42.999 Jakob Kagel: I guess. Like the part that I want to talk about to like just a little bit. Is sort of I know, Nico mentioned like sort of like, some specific actions and stuff that we can take. I just want to make sure that like before we do any of these actions that we sort of just have a plan in place for how we’re going to like track these like from the data perspective. So
50 00:04:43.400 ⇒ 00:05:01.120 Jakob Kagel: I mean, I think these are all you know. Good ideas for sure. I just want to make sure. You know that kind of we we because we don’t have like a snapshot table per se, like on pool pro yet that if we are going to go ahead with the action that we just say, you know, I can snapshot the table
51 00:05:01.350 ⇒ 00:05:11.069 Jakob Kagel: before we start, and then we can compare that, you know, to our most up to date table sort of at the end of the action, or whenever we’re trying to quantify sort of the impact.
52 00:05:11.990 ⇒ 00:05:21.689 kim todaro: Yeah, so I’m just looking at all. I all these ideas, and I agree with all of them. I have a call tomorrow morning with Dan and Ben.
53 00:05:23.453 ⇒ 00:05:24.240 kim todaro: So
54 00:05:25.210 ⇒ 00:05:29.039 kim todaro: they kind of like go back and forth with things. But now that we have this
55 00:05:29.090 ⇒ 00:05:34.400 kim todaro: list that’s approved right. Ben approved this list. Of 1,800 people. Oh, he didn’t.
56 00:05:34.730 ⇒ 00:05:35.060 Nicolas Sucari: Okay.
57 00:05:35.750 ⇒ 00:05:39.300 kim todaro: No, I mean I mean, I mean the segment. Did Ben approve the segment? Yet.
58 00:05:39.300 ⇒ 00:05:40.510 Jakob Kagel: Yeah, yeah.
59 00:05:40.510 ⇒ 00:05:42.461 kim todaro: Yeah, that’s so. That’s what I mean.
60 00:05:42.840 ⇒ 00:05:45.510 kim todaro: So I’ll I’ll talk to them tomorrow and
61 00:05:45.780 ⇒ 00:05:50.149 kim todaro: kind of see what they want me to do directionally, like as like an action item. Because
62 00:05:51.880 ⇒ 00:05:54.960 kim todaro: I feel like I haven’t really talked to him about it in a while.
63 00:05:55.000 ⇒ 00:05:58.190 kim todaro: Except for those 1st few phone calls we did like 2 months ago.
64 00:05:58.200 ⇒ 00:05:59.230 kim todaro: Sure
65 00:05:59.570 ⇒ 00:06:03.450 kim todaro: so. But I I think an email would probably be like
66 00:06:03.520 ⇒ 00:06:05.486 kim todaro: the best way to start
67 00:06:06.290 ⇒ 00:06:10.620 kim todaro: So let me think about what? What? That that should include. But
68 00:06:10.840 ⇒ 00:06:12.940 kim todaro: I you know, I agree we should measure like
69 00:06:13.200 ⇒ 00:06:16.199 kim todaro: success and everything. I just know they were like.
70 00:06:16.450 ⇒ 00:06:18.639 kim todaro: They change their minds a lot, and.
71 00:06:19.120 ⇒ 00:06:19.719 Jakob Kagel: I don’t know.
72 00:06:19.720 ⇒ 00:06:25.070 kim todaro: I don’t know exactly what they have in mind. And so I just wanna like kind of review that with them tomorrow.
73 00:06:25.530 ⇒ 00:06:26.690 Nicolas Sucari: That’s fine. I mean.
74 00:06:26.690 ⇒ 00:06:28.989 Jakob Kagel: Okay, I think, sorry. Go ahead.
75 00:06:29.570 ⇒ 00:06:44.630 Nicolas Sucari: Yeah, that we we can. We can send you this so that you can have this like action items. Obviously, we can. We can make it something different. If you want, we can add things or be more specific on some stuff. For example, the feedback loop. Probably. Now it’s
76 00:06:44.630 ⇒ 00:07:01.789 Nicolas Sucari: we. We don’t have like any feedback like right now to go and establish that communication with the pros. But we can like set up a survey or something so that we can start that communication going. But what Jacob was mentioning is having that snapshot of the table of, or the existing segment will let us know then.
77 00:07:02.106 ⇒ 00:07:29.950 Nicolas Sucari: If we do any any specific yeah action, we, we can measure how that segment will start to grow, or what are the changes that we will suffer? What, what, when, when we talk about the snapshot is kind of like establishing an A, a date on when that flag was activated or not for each of the customers, so that we can track when a customer became a pro or not, or or when? Yeah, exactly that. When a customer is becoming a pro.
78 00:07:29.950 ⇒ 00:07:34.060 Jakob Kagel: During a certain time period, like from the snapshot period, to like our most.
79 00:07:34.060 ⇒ 00:07:34.860 Nicolas Sucari: Yeah.
80 00:07:34.860 ⇒ 00:07:35.710 Jakob Kagel: Because.
81 00:07:35.820 ⇒ 00:07:41.416 Jakob Kagel: obviously, like our table like shopify customers, table is going to continue to refresh. And
82 00:07:41.840 ⇒ 00:08:04.090 Jakob Kagel: yeah. So it’s just good for us to have. I mean, the only thing I’m just trying to avoid and just saying all this is like that we go ahead with like one of these ideas. And then, like, we haven’t tracked, you know, for like a week or something. And then we’re missing, like, you know, we just didn’t capture that week of data that you know would be good like for us to quantify. And that’s just sort of like what my role is here. Yeah.
83 00:08:04.570 ⇒ 00:08:08.899 kim todaro: Yeah, I was. Gonna say, that’s probably something that you would keep track of right.
84 00:08:09.420 ⇒ 00:08:33.050 Jakob Kagel: Yeah, for sure. I’m just saying like, if we do decide to head with anything like, as far as like, you know, whatever any of these action items, or something like, let’s just have like a good line of communication. And that way it really won’t take me, you know, more than like a couple of minutes like to snapshot table. I just don’t want to like, you know. Just sort of be like randomly taking snapshots. It’s just like that way. We’ll just have the plan in place, and we can track it.
85 00:08:33.929 ⇒ 00:08:34.600 Jakob Kagel: Yeah.
86 00:08:34.830 ⇒ 00:08:35.169 Nicolas Sucari: Yeah.
87 00:08:35.179 ⇒ 00:08:35.889 kim todaro: We?
88 00:08:36.269 ⇒ 00:08:36.899 kim todaro: Oh, go ahead!
89 00:08:36.900 ⇒ 00:08:50.969 Nicolas Sucari: Yeah, sorry, Jacob. I think that independently, if we do some action or not, we need to add like that column or that field so that we can know when a customer is becoming a pro or not. Right, so probably we can.
90 00:08:50.970 ⇒ 00:08:59.169 Jakob Kagel: I definitely think it’s a good idea for us to put a ticket in for that. And yeah, like to have like a timestamp table for.
91 00:08:59.170 ⇒ 00:08:59.710 Nicolas Sucari: Yeah.
92 00:08:59.710 ⇒ 00:09:12.349 Jakob Kagel: Cool pro. But I think also like having just a snapshot table for the purposes of what we’re trying to do here should be perfectly fine. But I do think, yeah, that is definitely a good idea. If we do that as well.
93 00:09:13.140 ⇒ 00:09:14.210 Nicolas Sucari: Perfect. Yeah.
94 00:09:15.760 ⇒ 00:09:24.250 Nicolas Sucari: okay, yeah. More specifically, about these kind of ideas that we yeah, that I brought here. Like.
95 00:09:24.660 ⇒ 00:09:31.740 Nicolas Sucari: do do you know, Kim. If we were like trying to do something else with the existing pros, or you were thinking on
96 00:09:31.900 ⇒ 00:09:35.070 Nicolas Sucari: other action in order to reactivate them.
97 00:09:36.997 ⇒ 00:09:43.030 kim todaro: Last we talked it was, I think it was you, me utan and Cody, right?
98 00:09:43.480 ⇒ 00:09:46.970 kim todaro: Yeah, right? So I I thought
99 00:09:47.320 ⇒ 00:09:51.489 kim todaro: Tom was gonna go talk to Ben, and I haven’t heard anything since that.
100 00:09:52.659 ⇒ 00:10:01.340 kim todaro: So so I I think tomorrow I’ll I’ll just touch base with Ben during our monthly like team meeting, and Cody will be actually be on that call, too.
101 00:10:02.140 ⇒ 00:10:04.000 Nicolas Sucari: Okay, what? What? I
102 00:10:04.320 ⇒ 00:10:08.789 Nicolas Sucari: from yeah, from that meeting. I think that the meeting with Cody, what we
103 00:10:08.890 ⇒ 00:10:12.760 Nicolas Sucari: took from that meeting was like what we won’t be doing
104 00:10:12.780 ⇒ 00:10:28.379 Nicolas Sucari: like. We won’t be changing like, or we won’t be creating a different landing page, are we? And we won’t be like changing the buying experience for pro. So that that’s what we took. And I also added, here, yeah, probably it’s just for both pros, this one. So I can move everything up
105 00:10:28.550 ⇒ 00:10:29.740 Nicolas Sucari: here. Yeah.
106 00:10:29.740 ⇒ 00:10:30.750 kim todaro: That makes sense.
107 00:10:31.510 ⇒ 00:10:33.159 kim todaro: But yeah, I agree with you. I mean.
108 00:10:33.470 ⇒ 00:10:52.970 Nicolas Sucari: Th. This is also important because we’re not saying that we’re gonna create a different landing page, the workflow process or the yeah, the buyer experience for them is gonna be the same, and it’s gonna remain the same. We are just trying to contact them and try to see like by survey or by a discount or trying to reactivate them.
109 00:10:53.563 ⇒ 00:11:01.539 Nicolas Sucari: Yeah, we don’t need like any development extra development on a website or another process to reactivate them.
110 00:11:02.920 ⇒ 00:11:06.815 kim todaro: Right? Maybe if you guys are able to get the
111 00:11:07.540 ⇒ 00:11:20.379 kim todaro: when you get that report of the emails, if there’s another column that just shows how many times they purchased and what their total purchase value is. I don’t know if that can be done. But yeah, that would. That would be helpful.
112 00:11:20.380 ⇒ 00:11:27.449 Jakob Kagel: Sure. I mean, we can add a column. I can add a column in that for orders. And yeah, like total purchase value. Sure.
113 00:11:28.210 ⇒ 00:11:37.399 kim todaro: Yeah, that would be helpful, too. And then that way, I could show them tomorrow during the call. And just think of like some high value, low effort ways to start this.
114 00:11:38.210 ⇒ 00:11:51.786 Jakob Kagel: Yeah, for sure. I mean, I definitely think, like, yeah, email campaign of some sort makes the most sense. And it’s also kind of like the most easy for us to quantify, because we can just map everything back to email,
115 00:11:52.110 ⇒ 00:11:52.870 kim todaro: Yeah.
116 00:11:52.870 ⇒ 00:11:54.190 Jakob Kagel: So yeah.
117 00:11:54.650 ⇒ 00:11:56.200 Jakob Kagel: I’m in favor of that.
118 00:11:56.540 ⇒ 00:11:57.130 kim todaro: Yeah.
119 00:11:58.600 ⇒ 00:12:12.760 Nicolas Sucari: Okay, okay, great. So for for existing pros, we can create that. Or we can export that report from real Jacob, I think, any any other question that you need in order to export that any other information that would be valuable to have on that report.
120 00:12:13.000 ⇒ 00:12:14.159 Nicolas Sucari: What do you think, Kim?
121 00:12:17.890 ⇒ 00:12:22.919 kim todaro: maybe another another column for State location.
122 00:12:23.230 ⇒ 00:12:23.880 Jakob Kagel: Sure.
123 00:12:23.880 ⇒ 00:12:28.709 kim todaro: So so, state location, total orders, total total order value.
124 00:12:28.910 ⇒ 00:12:29.405 kim todaro: Yeah.
125 00:12:30.170 ⇒ 00:12:32.430 kim todaro: I think that would be like super helpful.
126 00:12:33.080 ⇒ 00:12:35.360 Jakob Kagel: We can do that. That shouldn’t be a problem.
127 00:12:35.360 ⇒ 00:12:41.199 kim todaro: And then Dan could be like. I think once Dan sees that he’s gonna be like be blown away. But we’ll see.
128 00:12:42.710 ⇒ 00:12:43.260 kim todaro: Yep.
129 00:12:43.260 ⇒ 00:12:52.739 Nicolas Sucari: Perfect. Okay, great. So that’s for existing pros. We can gather that report. Send it to you, and then you can go show that to Ben. And let’s see, then, what
130 00:12:52.860 ⇒ 00:13:12.260 Nicolas Sucari: of these ideas, or what our actions come out from that meeting? And then, regarding new customers, I don’t think we have so much. I think the only thing that we discussed and was what we were trying to do was to get the direct mail campaign targeting strategy. Gather some zip codes from
131 00:13:12.767 ⇒ 00:13:18.019 Nicolas Sucari: yeah, around North Florida. I think it was. And around Cape Coral.
132 00:13:18.100 ⇒ 00:13:41.741 Nicolas Sucari: trying to check if that zip codes that were the highest the best selling cities and trying to check, if we can have, like, more information on the demographics of that zip codes, and compared to other zones. I don’t know if we can actually do that. I don’t know, Jacob. Probably you, you know a little bit better, but we can get some information on those zip codes and try to see if we can get a list of
133 00:13:42.230 ⇒ 00:13:45.050 Nicolas Sucari: some zip codes that we would like to target right.
134 00:13:45.050 ⇒ 00:13:52.190 Jakob Kagel: What’s the what’s exactly the question that we’re trying to answer? I mean, you said, look for similarities between successful zip codes.
135 00:13:52.510 ⇒ 00:13:53.010 Jakob Kagel: And but.
136 00:13:53.010 ⇒ 00:13:53.819 Nicolas Sucari: So was it? Yeah.
137 00:13:53.820 ⇒ 00:14:08.162 Jakob Kagel: I mean, yeah, anything we can calculate like at the customer level, we can calculate at the Zip code level. So I mean, we can calculate total spend for a Zip code. Total orders, average order value.
138 00:14:08.970 ⇒ 00:14:13.660 Jakob Kagel: you know all of those things. But I don’t think that, like
139 00:14:14.090 ⇒ 00:14:19.950 Jakob Kagel: as far as like, how are we gonna identify new target areas is kind of like.
140 00:14:20.450 ⇒ 00:14:27.679 Jakob Kagel: it would have to be sort of agnostic of like our existing spend data, I mean, I think
141 00:14:27.830 ⇒ 00:14:31.490 Jakob Kagel: if we can get if we scrape, if we use this like scraping
142 00:14:32.053 ⇒ 00:14:42.689 Jakob Kagel: and and scrape all the pool listings, I think we can look at like, yeah, we could look at listings by zip code, like the count, or whatever like pools by zip code. And then
143 00:14:42.700 ⇒ 00:14:48.390 Jakob Kagel: the tricky part is like trying to match. I think, like who our existing customers are, because
144 00:14:48.750 ⇒ 00:15:01.969 Jakob Kagel: what we’ll have, basically when we scrape the data is probably just like a list of just everybody you know. And then we have to kind of figure out how to map like who is existing. And then who can like be captured?
145 00:15:02.310 ⇒ 00:15:04.230 Jakob Kagel: cause? Yeah, I don’t know.
146 00:15:06.040 ⇒ 00:15:08.060 kim todaro: Yeah, I think the last time
147 00:15:08.682 ⇒ 00:15:11.757 kim todaro: we met I was just telling
148 00:15:12.280 ⇒ 00:15:14.460 kim todaro: Tom and Nick like we.
149 00:15:15.330 ⇒ 00:15:18.500 kim todaro: I think Cape Coral is like our best selling area
150 00:15:18.750 ⇒ 00:15:22.679 kim todaro: year after year. It’s like the best selling city
151 00:15:22.963 ⇒ 00:15:32.179 kim todaro: overall in the United States. So I think that’s why we picked why, we picked that area. But then I think we were like, oh, are they? Are we like overly saturated in that area?
152 00:15:32.543 ⇒ 00:15:37.189 kim todaro: That was a question we were talking about but I could essentially like, if you guys
153 00:15:38.240 ⇒ 00:15:43.499 kim todaro: do have these addresses, what I could do is put them into Klavio along
154 00:15:43.820 ⇒ 00:15:45.099 kim todaro: with their email.
155 00:15:45.823 ⇒ 00:15:51.899 kim todaro: I could put them into Klavio. And I could see, like how many are existing and how many are not.
156 00:15:53.080 ⇒ 00:15:56.080 Jakob Kagel: Okay. I mean, that’s definitely a good way of to do the math.
157 00:15:56.080 ⇒ 00:15:56.599 kim todaro: I don’t know.
158 00:15:56.600 ⇒ 00:16:01.600 Jakob Kagel: Yeah, I mean, we probably can do that, too. We have, if we have the Clavio data in the table, and it has address.
159 00:16:01.600 ⇒ 00:16:02.200 kim todaro: Yeah.
160 00:16:02.200 ⇒ 00:16:07.679 Jakob Kagel: I just don’t know is everybody. Does everybody have to enter address, or is it like a voluntary field
161 00:16:08.500 ⇒ 00:16:09.030 Jakob Kagel: cause? It’s.
162 00:16:09.030 ⇒ 00:16:10.120 kim todaro: I only
163 00:16:10.410 ⇒ 00:16:11.920 kim todaro: only if they purchased.
164 00:16:12.230 ⇒ 00:16:14.200 Jakob Kagel: Okay, if they purchase. Okay, but that’s good.
165 00:16:14.200 ⇒ 00:16:14.880 Nicolas Sucari: And about it.
166 00:16:14.880 ⇒ 00:16:18.340 Jakob Kagel: I mean, that’s that’s that’s actually that’s actually pretty solid.
167 00:16:20.150 ⇒ 00:16:20.780 Jakob Kagel: I mean.
168 00:16:20.780 ⇒ 00:16:22.180 kim todaro: I think I can do that. Yeah.
169 00:16:22.180 ⇒ 00:16:41.280 Jakob Kagel: Could. Probably. Yeah, we could probably do that even just like with our shipping table. And just look at the shipping addresses and see if that, like the coverage to it, that might be even better. It’s just assuming, I mean, obviously, the assumption there is like that the parts get like shipped to the pool, which is not always kind of the case.
170 00:16:41.730 ⇒ 00:16:42.170 kim todaro: Okay.
171 00:16:42.170 ⇒ 00:16:42.870 Jakob Kagel: Right.
172 00:16:43.370 ⇒ 00:16:49.629 Jakob Kagel: you know, it’s worth a shot, or like at least worth like sort of understanding what the match rate is there? Yeah.
173 00:16:50.130 ⇒ 00:16:51.450 kim todaro: Yeah, it’s true.
174 00:16:53.160 ⇒ 00:16:56.512 kim todaro: yeah, I I know we’ve been talking about this for a while. But
175 00:16:57.030 ⇒ 00:17:00.460 kim todaro: yeah, I think it cost me like 50 cents per piece of mail
176 00:17:00.880 ⇒ 00:17:02.514 kim todaro: to send out
177 00:17:04.250 ⇒ 00:17:10.729 kim todaro: to send out a direct mail piece. So we could definitely try that once we have like a list that we feel comfortable with.
178 00:17:11.140 ⇒ 00:17:13.480 kim todaro: I kind of forget what we talked about. If
179 00:17:13.550 ⇒ 00:17:16.699 kim todaro: you’re able to scrape email to or just addresses.
180 00:17:17.069 ⇒ 00:17:18.560 kim todaro: don’t think.
181 00:17:18.569 ⇒ 00:17:22.409 Jakob Kagel: Brave email. But I’m not sure. Nico, maybe speak to them more.
182 00:17:22.410 ⇒ 00:17:23.150 kim todaro: Okay.
183 00:17:23.150 ⇒ 00:17:31.469 Nicolas Sucari: I’m not sure. Yeah, I’m gonna try to talk with them and see what the 3rd scraper tool was getting. But I think
184 00:17:32.140 ⇒ 00:17:37.859 Nicolas Sucari: he showed us some example of that. Okay, I’m gonna look at that and try to see. Okay.
185 00:17:38.310 ⇒ 00:17:41.690 kim todaro: Yeah, I kind of forget we’ve been talking about it for a while on and off. So.
186 00:17:41.690 ⇒ 00:17:42.050 Nicolas Sucari: Yeah.
187 00:17:42.050 ⇒ 00:17:43.849 kim todaro: Forget what we, what we talked about.
188 00:17:45.170 ⇒ 00:17:45.970 Jakob Kagel: Yeah. No worries.
189 00:17:45.970 ⇒ 00:17:46.550 Nicolas Sucari: Yeah.
190 00:17:47.790 ⇒ 00:18:03.459 Nicolas Sucari: okay. But the idea is a is that one. So we’re gonna go try to use that that tool, scrape some data and try to compare the information that we have with our shipping table to compare addresses for the ones that we already
191 00:18:03.932 ⇒ 00:18:19.570 Nicolas Sucari: for the customers that we already bought. They already buy with us and try to take them out from that list and get the list using the zip codes around Cape Coral, and probably Florida, some other city. That’s okay.
192 00:18:20.730 ⇒ 00:18:21.320 kim todaro: Yeah,
193 00:18:23.110 ⇒ 00:18:23.720 Nicolas Sucari: Okay.
194 00:18:24.640 ⇒ 00:18:33.755 Nicolas Sucari: okay, perfect. I think those are like the 2 things we need to work on. Now, we can send you that information team. And then we can continue talking.
195 00:18:34.620 ⇒ 00:18:35.000 kim todaro: Okay.
196 00:18:35.000 ⇒ 00:18:38.309 Nicolas Sucari: Jacob, if we can get that report today. So that Kim.
197 00:18:38.310 ⇒ 00:18:38.960 Jakob Kagel: Yeah, that’s.
198 00:18:38.960 ⇒ 00:18:48.340 Nicolas Sucari: Show the pros information to Ben tomorrow. That will be fine. And then, Kim, if you have any update on what you talk to, Ben, let us know when we can continue working on that. This. Okay.
199 00:18:48.340 ⇒ 00:18:50.160 kim todaro: Okay, yeah, that sounds good.
200 00:18:50.660 ⇒ 00:18:51.270 kim todaro: Don’t.
201 00:18:51.270 ⇒ 00:18:57.060 Nicolas Sucari: I’m gonna I’m gonna keep working on this so that we can yeah, have like this page with the
202 00:18:57.429 ⇒ 00:19:21.100 Nicolas Sucari: plan and ideas that we are working on so that we can have something more kind of yeah, I don’t know pretty in terms of what are we trying to do? Which is with each of the segments. And yeah, so that we can have like a finished document here. But that’s okay. That’s our that are our 2 action items for today. I think that pros report and then work with outscraper to get that list and
203 00:19:21.130 ⇒ 00:19:25.439 Nicolas Sucari: match it to the addresses, that of the clients that we already have. Okay.
204 00:19:26.900 ⇒ 00:19:27.690 kim todaro: Sounds good.
205 00:19:28.680 ⇒ 00:19:32.220 Nicolas Sucari: Perfect. Thank you very much, Kim, for your time.
206 00:19:32.860 ⇒ 00:19:34.390 Nicolas Sucari: Let’s talk tomorrow. Okay.
207 00:19:34.750 ⇒ 00:19:35.759 kim todaro: Thank you. Both.
208 00:19:36.200 ⇒ 00:19:39.949 Jakob Kagel: Sounds great sounds great. Have a great rest of your week. We’ll talk soon.
209 00:19:40.420 ⇒ 00:19:41.140 kim todaro: Bye.