Meeting Title: Weekly Project Check Date: 2025-03-07 Meeting participants: Uttam Kumaran, Amber Lin, Janiecegarcia, Yvetteruiz, Scott_Harmon
WEBVTT
1 00:00:08.550 ⇒ 00:00:10.080 Uttam Kumaran: Hey! Scott! Good morning!
2 00:00:11.150 ⇒ 00:00:12.220 Scott_Harmon: You, Tom, how you doing.
3 00:00:12.220 ⇒ 00:00:12.930 Uttam Kumaran: Good.
4 00:00:13.600 ⇒ 00:00:16.070 Scott_Harmon: Great Hi! Amber.
5 00:00:16.810 ⇒ 00:00:19.500 Amber Lin: Hi! There! Nice to meet you.
6 00:00:19.500 ⇒ 00:00:22.139 Scott_Harmon: Nice to meet you, too. I was just reading your Cv.
7 00:00:22.410 ⇒ 00:00:23.930 Amber Lin: Oh, wow!
8 00:00:24.110 ⇒ 00:00:25.389 Scott_Harmon: Oh, impressive! Wow!
9 00:00:25.390 ⇒ 00:00:27.389 Amber Lin: I hope I impressed you.
10 00:00:27.590 ⇒ 00:00:30.710 Scott_Harmon: Totally. I was just like blown away. That’s so interesting.
11 00:00:31.690 ⇒ 00:00:34.920 Scott_Harmon: We’re glad to have you on on board our little team.
12 00:00:35.210 ⇒ 00:00:36.700 Amber Lin: I appreciate that.
13 00:00:39.520 ⇒ 00:00:40.580 Scott_Harmon: Hi, Janice!
14 00:00:41.800 ⇒ 00:00:44.100 Scott_Harmon: Oh, I like your sweater. That’s cool.
15 00:00:44.350 ⇒ 00:00:46.289 JanieceGarcia: Thank you. Thank you. Thank you.
16 00:00:46.900 ⇒ 00:00:48.140 JanieceGarcia: I love the hat.
17 00:00:48.870 ⇒ 00:00:49.949 YvetteRuiz: Thank you.
18 00:00:50.860 ⇒ 00:00:53.440 Scott_Harmon: Event. I probably like your sweater, too. I just can’t see it.
19 00:00:54.310 ⇒ 00:01:01.510 YvetteRuiz: No worries. Steven will not be joining us today. He is still in another meeting today.
20 00:01:01.830 ⇒ 00:01:02.410 Scott_Harmon: Great
21 00:01:04.614 ⇒ 00:01:10.699 Scott_Harmon: hey? Just one thing while we’re getting organized, Tom. I could be the only one but the email you sent out for the
22 00:01:11.069 ⇒ 00:01:18.749 Scott_Harmon: meeting. The link for the slides didn’t go to the slides. It went to it, went to Amber’s.
23 00:01:18.899 ⇒ 00:01:26.620 Scott_Harmon: Cv, so can you drop the slide link into the the chat here.
24 00:01:26.620 ⇒ 00:01:31.449 Uttam Kumaran: Yeah, Amber, do you wanna go ahead and send that? And we can. Probably we can just get started.
25 00:01:31.450 ⇒ 00:01:35.238 Amber Lin: Yeah, totally. Let me share this link.
26 00:01:36.060 ⇒ 00:01:39.010 Amber Lin: actually let me download this as a Pdf.
27 00:01:39.130 ⇒ 00:01:41.919 Amber Lin: and so, and then I will share it.
28 00:01:42.160 ⇒ 00:01:44.240 Amber Lin: and I’ll start to share my screen
29 00:01:46.230 ⇒ 00:01:48.690 Amber Lin: here. I will put that in the chat
30 00:02:03.020 ⇒ 00:02:04.020 Amber Lin: one second.
31 00:02:26.230 ⇒ 00:02:32.049 Amber Lin: I have sent it in the chat. Let me know if you guys had it, and I will share my screen.
32 00:02:32.050 ⇒ 00:02:35.080 Scott_Harmon: Yeah, I just got it. I’m just downloading it. Yep, I got it.
33 00:02:36.770 ⇒ 00:02:38.840 Scott_Harmon: Do you get an event, Denise?
34 00:02:38.840 ⇒ 00:02:39.410 JanieceGarcia: Yes.
35 00:02:39.920 ⇒ 00:02:40.480 Scott_Harmon: Okay.
36 00:02:45.840 ⇒ 00:02:47.490 Amber Lin: Can everyone see my screen.
37 00:02:49.360 ⇒ 00:02:49.810 Scott_Harmon: He’d.
38 00:02:49.810 ⇒ 00:02:50.320 YvetteRuiz: Yes.
39 00:02:51.760 ⇒ 00:02:52.720 Amber Lin: So
40 00:02:53.290 ⇒ 00:03:08.070 Amber Lin: today we have a new member, which is me. I’m really happy to meet you guys and to join our fantastic team of engineers and I’ll be presenting today. But all the team efforts and all the wins goes to our fantastic team members.
41 00:03:08.260 ⇒ 00:03:09.050 Scott_Harmon: Great.
42 00:03:09.050 ⇒ 00:03:18.589 Amber Lin: And so today we’ll go through the progress. Last week, we’ll go through action items that we need to do to move things forward and what we plan for the next steps.
43 00:03:18.940 ⇒ 00:03:33.609 Amber Lin: So 1st of all, we are right now at the end of the phase one, and we’re just wrapping up the 1st month that we work together and moving forward. We’re looking at the second proposal for Phase 2.
44 00:03:33.910 ⇒ 00:03:35.660 Amber Lin: And so this week
45 00:03:36.210 ⇒ 00:03:58.979 Amber Lin: we had a very big achievement as we tease in the email, we read, we made the customer service rep, bought a lot faster. So last week we it was around 30 seconds or so we’re just not really usable for the Csrs. And right now we have it under 10 seconds. So averaging around 9 without affecting the accuracy. So that’s a really good thing.
46 00:03:59.630 ⇒ 00:04:05.119 Amber Lin: And so this you can see here before it was 30 seconds. And right now it’s a lot lot faster.
47 00:04:06.090 ⇒ 00:04:20.520 Amber Lin: We also created the evaluation data set, which is the golden data set of the correct answers. And we are measuring the accuracy. So this is a fancy measure of accuracy across different metrics.
48 00:04:20.790 ⇒ 00:04:39.870 Amber Lin: And we also, we’re in contact with Shannon and Grace, and we’ll be ready to onboard them once we have the updated documents, because we want to make sure that when they’re using the bot they can give the customers the right answer. So we’re just. I’ll be in touch with that. We’ll make sure that happens.
49 00:04:39.870 ⇒ 00:05:05.370 Uttam Kumaran: Amber. Can we go back one step just to the Eval data to the picture? Yeah. So just to say a couple of words about this. So this is really, it’s just looks really like technical. But really, this is how we are starting to run experiments on every change we make? How does it impact our accuracy and our speed? So we want to know that as we are improving the process, we’re not.
50 00:05:05.490 ⇒ 00:05:27.239 Uttam Kumaran: you know, making the agent dumber. It’s not getting slower. It’s actually all their metrics are going up. And so we’re starting to run experiments. The columns, you’ll see, are, there are several different ways to measure accuracy. I’m happy to go into more detail if anyone wants to. But just know that. That’s how we’re we’re starting to to improve the system here.
51 00:05:29.570 ⇒ 00:05:36.390 YvetteRuiz: Okay, I’m sorry I was trying to pull it up on my screen, because it’s too small for me right here. But yeah, thank you.
52 00:05:37.800 ⇒ 00:05:40.800 Amber Lin: Of course. I’ll move forward with this.
53 00:05:43.810 ⇒ 00:06:03.029 Amber Lin: and we also have a dashboard to measure all the all the requests that the bot will have, so that we can have a visual overview of everything happening within the bot. So this is definitely still under development. But right now we already have
54 00:06:03.030 ⇒ 00:06:16.429 Amber Lin: to see how many conversations there has been, and how what’s the average time, and how many total records has been passed. So this will really be helpful for you and for us to see overall how this is performing.
55 00:06:16.660 ⇒ 00:06:19.909 Scott_Harmon: One question about this dashboard.
56 00:06:20.897 ⇒ 00:06:29.010 Scott_Harmon: Utah. And I know we’re going to talk, maybe later about the metrics that we’re focused on.
57 00:06:31.460 ⇒ 00:06:33.809 Scott_Harmon: Does this track the
58 00:06:34.310 ⇒ 00:06:41.050 Scott_Harmon: the type of call, in other words. And specifically, I guess I’m sort of thinking about 1st call. Resolution is a really big
59 00:06:41.750 ⇒ 00:06:45.070 Scott_Harmon: big metric, I mean, I’m sure all these metrics are good.
60 00:06:47.180 ⇒ 00:06:51.869 Scott_Harmon: Does it track the metrics that we’ve discussed with Yvet and the team.
61 00:06:53.130 ⇒ 00:07:07.413 Uttam Kumaran: Yeah. So at the moment, we don’t have the data from the actual phone system. That’s something that, as we agree on the next steps will. In order to measure sort of the success we’ll need to know.
62 00:07:08.280 ⇒ 00:07:12.920 Uttam Kumaran: we’ll need to do. We’ll need to basically be able to join our data, of which
63 00:07:13.424 ⇒ 00:07:23.140 Uttam Kumaran: Csr is messaging the bot to what phone call they’re on. In order to do that. We haven’t done that yet. So everything here is just data we’re we’re getting from the
64 00:07:23.830 ⇒ 00:07:26.159 Uttam Kumaran: the the AI bot right now.
65 00:07:26.160 ⇒ 00:07:31.989 Scott_Harmon: So do we have okay? Thanks. That’s that’s helpful, I understand. Do we do? We have a way to track
66 00:07:32.760 ⇒ 00:07:38.429 Scott_Harmon: a successful answer versus a non-successful answer where the Csr would go.
67 00:07:38.820 ⇒ 00:07:41.140 Scott_Harmon: you know you answered my question, or you didn’t.
68 00:07:42.160 ⇒ 00:07:49.930 YvetteRuiz: So would you guys have to get into our 8 by 8 system to gather that data? How would I mean.
69 00:07:50.930 ⇒ 00:07:54.490 YvetteRuiz: or is it us that’s gonna be pulling it on our end.
70 00:07:54.960 ⇒ 00:08:04.019 YvetteRuiz: Yeah, this is something that we’ll have to work. I with team on I’m not sure about the mechanism. But one way or another. Yes.
71 00:08:04.433 ⇒ 00:08:09.719 Uttam Kumaran: In order to be able to match up the conversation with the active phone call. The second thing
72 00:08:10.310 ⇒ 00:08:32.919 Uttam Kumaran: got in terms of quality. Yeah, so we have, we have quality scores that we measure based on our evaluation data set. However, I think, amber. It’s a good point that potentially we can add a feedback flow for each conversation, so that the Csrs. Of course, after they finish their conversation, can provide some qualitative feedback
73 00:08:33.220 ⇒ 00:08:40.730 Uttam Kumaran: that way, we have that in association with what we understand about the conversation as well. I think that’s a
74 00:08:40.900 ⇒ 00:08:42.059 Uttam Kumaran: that’s a good point.
75 00:08:42.620 ⇒ 00:08:48.890 Scott_Harmon: Yeah, I think I think you need some kind of a closeout. Either. Was this helpful thumbs up, thumbs down, or.
76 00:08:49.400 ⇒ 00:08:56.649 Scott_Harmon: you know, just some direct feedback from the Csr. Because, again, I just don’t want to be in a position where
77 00:08:56.850 ⇒ 00:09:00.160 Scott_Harmon: our data says one thing, but event thinks something else.
78 00:09:02.290 ⇒ 00:09:19.969 Scott_Harmon: you, you know. So I’m just trying to get that we can both agree on, and cause I’ve been in something where I’ve got a dashboard that says, Oh, look how good we are! And then the users are like, oh, this thing is crap! You’re at a kind of a spot. So so I just try to get make sure we don’t metric ourselves into.
79 00:09:20.390 ⇒ 00:09:21.779 Scott_Harmon: you know, dead ends.
80 00:09:21.780 ⇒ 00:09:22.880 Amber Lin: Holy. I think that’s a.
81 00:09:22.880 ⇒ 00:09:38.767 YvetteRuiz: Your idea on the thumbs up. I think that’s there. There’s a lot of that. You know what I mean when you go in there, and you search a knowledge base. Was this helpful, or was it not? And it has the thumbs up and thumbs down? I mean, that would be really really cool to have on there. That’s good point, Scott.
82 00:09:39.880 ⇒ 00:09:44.570 Amber Lin: I’ve wrote that down, and we’ll talk with the team about that later.
83 00:09:47.140 ⇒ 00:10:04.849 Amber Lin: And we also, I know this is a really important part of upselling of the oh, by the way, system, and we’re already training that. So here’s a little response. And you can see, when we asked them question, they were able to say, Oh, by the way, since you’re interested in this, we can also offer
84 00:10:04.850 ⇒ 00:10:18.810 Amber Lin: something else. So we already got the documentation from you, and this is already in training. So hopefully, we’ll improve that even more, and we’ll I just wanted to hear any thoughts about this where where you want it to go.
85 00:10:20.930 ⇒ 00:10:26.760 Scott_Harmon: So, yeah, this is just a topic, Janice. I think you sent those over. Thank you for doing that.
86 00:10:26.760 ⇒ 00:10:27.310 JanieceGarcia: Who’s.
87 00:10:28.600 ⇒ 00:10:30.780 Scott_Harmon: What do you all think of this? Does this.
88 00:10:31.500 ⇒ 00:10:35.269 JanieceGarcia: And thank you for answering my questions in the email. Those were helpful.
89 00:10:35.850 ⇒ 00:10:54.190 JanieceGarcia: I do definitely like it. And I think you know something beating off of what Yvette said before when it comes to our oh, by the way, is the sheet that I sent you? That’s definitely our power offers. So those are the promotions that are gonna be focal points for within that month or the 2 months.
90 00:10:54.250 ⇒ 00:11:16.739 JanieceGarcia: however, all of our services are going to be. Oh, by the way, so like, if rodent is not a power offer or if trees not a power offer this time, but a customer is calling in because they have rodent activity. Then a good oh, by the way, for that would be tree services, you know. Well, ABC does offer some tree trimming. So
91 00:11:16.890 ⇒ 00:11:34.200 JanieceGarcia: I’m kind of thinking through on like seeing your questions. And I had answered them this morning, Scott, but thinking through on how I can get you something to where maybe that can help the bots of the customer. Or once you guys are able to start listening to the calls, then the bot can actually go in there and give ideas.
92 00:11:34.200 ⇒ 00:11:38.650 Scott_Harmon: I think. And and again, who, Tom, you know, or amber correct me if I’m wrong.
93 00:11:40.280 ⇒ 00:11:44.530 Scott_Harmon: it needs the bot needs a hint.
94 00:11:44.910 ⇒ 00:11:47.350 JanieceGarcia: I think on to when.
95 00:11:48.170 ⇒ 00:11:52.180 Scott_Harmon: You know? What about the client or this call.
96 00:11:52.710 ⇒ 00:11:53.070 Uttam Kumaran: It’s just.
97 00:11:53.240 ⇒ 00:11:54.979 Scott_Harmon: Wanted to to push.
98 00:11:55.120 ⇒ 00:11:59.140 Scott_Harmon: and you actually just mentioned it when you’re a little, when you were just chatting. I think
99 00:11:59.410 ⇒ 00:12:04.320 Scott_Harmon: you know, if they have a rodent problem, you know, like there’s some. If state, I guess that
100 00:12:04.450 ⇒ 00:12:08.610 Scott_Harmon: that if we could just give a little more color on the
101 00:12:09.020 ⇒ 00:12:13.910 Scott_Harmon: offers, then I think the AI can. Now it knows when to push them.
102 00:12:16.440 ⇒ 00:12:19.730 Scott_Harmon: Just any guide. I think we’re gonna need a little more guidelines. I guess.
103 00:12:19.730 ⇒ 00:12:26.110 Uttam Kumaran: Yeah, almost exactly how you would train your your agents, I mean, and on our side, if I, if I think about it, even
104 00:12:26.200 ⇒ 00:12:28.480 Uttam Kumaran: myself or our sales team.
105 00:12:28.550 ⇒ 00:12:46.559 Uttam Kumaran: You sort of have to have the feeling right. But for for this, you know, of course, our bot at the moment doesn’t have context in the full conversation. However, if we can think of some guidelines like, if a conversation starts, and maybe there’s no follow up questions or some amount of time
106 00:12:46.610 ⇒ 00:13:01.259 Uttam Kumaran: the bot can say, hey! Just as a reminder while you’re on the call, you you the the you. The person asked about this maybe suggest this and that can get sent after 30 seconds of no reply. 1 min, right? Or you know.
107 00:13:01.260 ⇒ 00:13:01.800 Scott_Harmon: So.
108 00:13:01.990 ⇒ 00:13:02.330 YvetteRuiz: Yeah.
109 00:13:02.330 ⇒ 00:13:10.060 Scott_Harmon: So just a slightly different direction, you know. Not not that it’s better or worse. But, Janice, I think if you would just add.
110 00:13:10.240 ⇒ 00:13:16.539 Scott_Harmon: because it sounds like, you know, the most about these, maybe even a sentence. I’m I’m just going to call it hints.
111 00:13:17.640 ⇒ 00:13:22.669 Scott_Harmon: you know, to a Csr like, here’s a really good time to to
112 00:13:23.100 ⇒ 00:13:29.969 Scott_Harmon: to push this offer and just just write down whatever you think right like you. You know the business really. Well.
113 00:13:30.460 ⇒ 00:13:34.680 Scott_Harmon: you know, just the 3 or 4 things that would be a clue
114 00:13:35.210 ⇒ 00:13:39.950 Scott_Harmon: to say, oh, by the way, and that’s really all the AI will need like
115 00:13:41.990 ⇒ 00:13:56.790 Scott_Harmon: And and I like your stuff, too, Tom, about just dead spaces and calls. But even simpler than that, if there’s just like real simple rules like boy, this would really work good. If the client has this or that, then I think the AI will just, it’ll love that.
116 00:13:57.090 ⇒ 00:13:57.620 Scott_Harmon: and.
117 00:13:57.620 ⇒ 00:13:58.320 YvetteRuiz: Yeah, really.
118 00:13:58.320 ⇒ 00:14:18.679 YvetteRuiz: I’ll kind of jump in on there, too. Because this is the part that we’ve not been very successful at is because we when we train, we tell them about the oh, by the ways, but that’s what our agents truly do struggle with is, when do I offer it, or what’s a good time. So these things are going to. So when we when I, when I originally was looking at the way we have these.
119 00:14:18.880 ⇒ 00:14:27.030 YvetteRuiz: I’m like, Okay, we’re going to have to do exactly what you guys are saying. And that’s what I was talking to. Janice is like, we’re going to have to find a way to go in there and give them trigger.
120 00:14:27.230 ⇒ 00:14:54.979 YvetteRuiz: You know we’re something that helps them. You know what I mean, whether it be like this at the rodent piece of it, or whether it be gutter cleaning or power washing, or Christmas lights. All those things we’re gonna have to know where to go in there and kind of pair them up, because there are things that go really really well with what what the callers originally calling for, and what pairs up with, you know that would be a good thing to bring up, or or if there’s nothing really tied to that just kind of in general. Hey? Just mention it. Don’t forget to mention it like you, said.
121 00:14:55.120 ⇒ 00:14:59.770 Scott_Harmon: It sounds like, we’re basically in violent agreement. Here, are you? Okay?
122 00:15:00.200 ⇒ 00:15:03.610 Scott_Harmon: Taking the action item, amber. If we want to give
123 00:15:03.850 ⇒ 00:15:08.530 Scott_Harmon: a veteran action item for the next week to just write down some of those hints.
124 00:15:08.950 ⇒ 00:15:09.270 Amber Lin: Total.
125 00:15:09.270 ⇒ 00:15:11.650 Scott_Harmon: Because, like I said, I think technically
126 00:15:11.980 ⇒ 00:15:17.670 Scott_Harmon: correct me. If I’m wrong, I think I think we just drop them right in. I think I think as soon as you give them to us
127 00:15:17.880 ⇒ 00:15:19.360 Scott_Harmon: we’ll be all over it.
128 00:15:19.630 ⇒ 00:15:28.450 Uttam Kumaran: And the and the lovely thing is like, we will start to be able to measure the amount of times that one our bot suggests. And then, ideally.
129 00:15:28.650 ⇒ 00:15:35.639 Uttam Kumaran: if we get the data from 8 by 8, how we’re how that was. Actually, if if that was actually taking action on right. So.
130 00:15:36.400 ⇒ 00:15:37.160 Scott_Harmon: Right.
131 00:15:37.320 ⇒ 00:15:42.029 Uttam Kumaran: Full cycle feedback loop. That amber would be great for us to find out how we can enable.
132 00:15:42.030 ⇒ 00:15:47.180 Scott_Harmon: Yeah, and yeah, I, we just really wanna focus on those things that move the
133 00:15:47.320 ⇒ 00:15:54.819 Scott_Harmon: financial needle for you of that. And I would imagine if you see an uptake in these offers
134 00:15:55.110 ⇒ 00:15:57.400 Scott_Harmon: from a financial perspective.
135 00:15:58.440 ⇒ 00:16:02.820 Scott_Harmon: You’re probably a hero, and we want to make you guys heroes here. So.
136 00:16:03.150 ⇒ 00:16:19.549 YvetteRuiz: This will be a big win. I could tell you that. I mean, this comes from Bobby Jenkins. Bobby talks about this all the time, and it truly is a success, because we’ve been in business, you know, I mean, for all many years, right? But there’s still people that don’t know that we do all these other lines of services.
137 00:16:19.550 ⇒ 00:16:24.379 Uttam Kumaran: I didn’t. I didn’t know. I, as Scott told me, I was like, Wow, you know.
138 00:16:24.380 ⇒ 00:16:24.990 YvetteRuiz: Yeah.
139 00:16:24.990 ⇒ 00:16:25.730 Uttam Kumaran: Yeah.
140 00:16:26.180 ⇒ 00:16:34.449 YvetteRuiz: So it the more that we can figure this out and kind of get it, you know. Fine tuned to where it makes it that easy for the agent to go in there and do it.
141 00:16:35.000 ⇒ 00:16:37.649 YvetteRuiz: Yeah, it’ll be a big win spot in.
142 00:16:37.650 ⇒ 00:16:41.219 Scott_Harmon: And amber. We could talk more about this offline. But just just to.
143 00:16:41.340 ⇒ 00:16:44.020 Scott_Harmon: you know, make sure that we internalize this the right way.
144 00:16:44.120 ⇒ 00:16:55.710 Scott_Harmon: ABC’s competitive advantages that they have a broad portfolio of services in the industry. They they have a really wide set of services they can sell to a homeowner. And
145 00:16:56.180 ⇒ 00:17:07.220 Scott_Harmon: and so what they want is uptake of multiple service lines. And so what the ideal is, instead of just one service, they buy 2, 3, or 4 services, and
146 00:17:07.680 ⇒ 00:17:21.619 Scott_Harmon: they’ve paid for the customer acquisition once. And now the monetization of each customer is just going up. It’s doubling every time you upsell. And so there’s just a huge amount of financial leverage for the business in this particular metric. So.
147 00:17:23.010 ⇒ 00:17:29.480 Amber Lin: So real quickly. Oh, by the way, is a very central system to ABC.
148 00:17:31.120 ⇒ 00:17:35.579 Scott_Harmon: Direct money. It drops right to the bottom line. I don’t, you know. It’s just like
149 00:17:35.950 ⇒ 00:17:40.290 Scott_Harmon: like, because you’ve got you’ve got an existing client. I’m an ABC. Customer.
150 00:17:40.710 ⇒ 00:17:42.810 Scott_Harmon: We buy 2 services.
151 00:17:43.400 ⇒ 00:17:51.899 Scott_Harmon: but some of these other services you mentioned I had no idea. As a matter of fact, I just got my ass up on the ladder 2 weeks ago, and clean those damn gutters, and that
152 00:17:52.350 ⇒ 00:17:54.053 Scott_Harmon: I almost killed myself.
153 00:17:54.480 ⇒ 00:17:56.490 Uttam Kumaran: I did. I did the same thing. Yeah.
154 00:17:58.230 ⇒ 00:17:58.770 YvetteRuiz: My!
155 00:17:58.770 ⇒ 00:18:17.999 YvetteRuiz: Well, we were just in a meeting. We were just in a meeting yesterday with Bobby and Matt, and we’re talking about our trash bin service, because that’s the newest service. Right now. We haven’t started rolling out. And oh, by the way, but we’re just doing trash bin services in San Antonio. They want to expand it to Austin. We’re talking through that process. But I mean what perfect.
156 00:18:18.660 ⇒ 00:18:23.270 Scott_Harmon: On the leap thing just to just to exemplify. There’s 2 times a year
157 00:18:23.560 ⇒ 00:18:29.540 Scott_Harmon: when I got to get up there and clean the leaves out, and one of them was last month, and you knew that right. And so
158 00:18:29.670 ⇒ 00:18:38.960 Scott_Harmon: if you’re talking to somebody in January or February, it’s a really good time to say, you know, do you want our leave service? So anyway, I think I think we all
159 00:18:39.610 ⇒ 00:18:44.300 Scott_Harmon: we’ve we’re in alignment here, and so we’ve got you down for an action item to send us
160 00:18:44.560 ⇒ 00:18:49.650 Scott_Harmon: some more guidance on pitching those. And I think it’s a great thing to focus on
161 00:18:51.050 ⇒ 00:18:53.740 Scott_Harmon: for measuring the bot’s performance.
162 00:18:54.060 ⇒ 00:19:15.239 Amber Lin: Yeah. And, Janice, I’ll be in contact with you, and we’ll work together to write that down, and so that I think we can have a bounce, the ideas back and forth. So I know you, you guys have so much knowledge inside you. But sometimes, if if you’re talking to someone it will come out very naturally, it’ll be less effort, so I’ll be. I’ll be in touch with that. So don’t worry.
163 00:19:15.440 ⇒ 00:19:16.800 JanieceGarcia: Awesome. Thank you.
164 00:19:16.800 ⇒ 00:19:17.195 Amber Lin: Hmm.
165 00:19:17.870 ⇒ 00:19:25.769 Amber Lin: and we’ll move on to the next part. We also implement. Let the bot know about the ABC core values.
166 00:19:25.880 ⇒ 00:19:47.169 Amber Lin: So this is a example of when we asked them, Hey, what’s the core values of ABC? And then they were able to answer all these values that you guys provided with us. And right now I so I think in the future this could influence how Dcsrs communicate. I do see a lot of potential in this feature.
167 00:19:48.220 ⇒ 00:20:04.370 Amber Lin: but that’s a big one for now and next, this is also something that’s very important. This is one of the 3 main pillars of our work together, which is improving the structure of our documents. And so what we did this week is that we
168 00:20:04.690 ⇒ 00:20:32.979 Amber Lin: made the print change the presentation into structured documents. So it’s a lot easier to look at, and it’s more standardized. We also put all the information into one single organized file, so it will be a lot easier to search or have the bot look at it. And lastly, we standardized the format and the tone across all of these documents so that it’s a lot. It’s a lot easier for the bot to give
169 00:20:33.050 ⇒ 00:20:35.329 Amber Lin: good and consistent answers.
170 00:20:36.740 ⇒ 00:20:54.010 Amber Lin: And so the next part, essentially the 3rd pillar of our work together is a trainer, assistant Bot. And this week we really improved the back end of all these documents which is related to how we organize the Google Drive, and this will allow for easier updates.
171 00:20:54.400 ⇒ 00:21:13.571 Amber Lin: And so once we do that, once we have done that, the next steps, we believe, is to we have to transform the existing data, and we’re gonna store it in an intermediary database, and we’ll enable the agent to update that. And this will allow us to write back into the Google, drive.
172 00:21:13.920 ⇒ 00:21:18.549 Scott_Harmon: Can I? Can we? Can we just pause on this? I so
173 00:21:18.890 ⇒ 00:21:21.630 Scott_Harmon: so just to, just to, you know.
174 00:21:21.970 ⇒ 00:21:29.289 Scott_Harmon: emphasize here, make sure we’re syncing up. And this is specifically Janice. I’m kind of thinking of you. So this is the second second agent.
175 00:21:30.060 ⇒ 00:21:33.270 Scott_Harmon: and this is primarily for you, too.
176 00:21:34.070 ⇒ 00:21:42.709 Scott_Harmon: where you’ll be able to add new knowledge to the system via a bot, and our goal is, you won’t have to directly write into files anymore.
177 00:21:44.230 ⇒ 00:21:44.880 JanieceGarcia: Okay.
178 00:21:44.880 ⇒ 00:21:49.079 Scott_Harmon: And so this second bot will be for the experts
179 00:21:49.520 ⇒ 00:21:52.800 Scott_Harmon: to use to to keep information current.
180 00:21:53.415 ⇒ 00:21:58.729 Scott_Harmon: It will get written through to the files, so you’ll be able to read the, you know. Make sure, hey?
181 00:21:58.940 ⇒ 00:22:05.210 Scott_Harmon: You know I can still read it. Those files aren’t going anywhere. Instead of having to open and edit, and.
182 00:22:05.660 ⇒ 00:22:07.920 Scott_Harmon: you know, do a bunch of documenting
183 00:22:08.070 ⇒ 00:22:19.489 Scott_Harmon: and and utam. I don’t know if you figured this out yet. I don’t. It’s gonna be a little bit, and maybe we have to test this. Is it going to be a bit of an interview flow for them? If I want to create a new bit of knowledge
184 00:22:19.930 ⇒ 00:22:28.099 Scott_Harmon: quite often. The way it’ll work is a bottle. Say, oh, what kind of knowledge is it? Oh, it’s a it’s an Oh, by the way, oh, okay. And it starts.
185 00:22:28.750 ⇒ 00:22:35.739 Scott_Harmon: you know, almost like interviewing you. And you answer questions. It asks you all the questions it needs, and then it goes and writes
186 00:22:35.740 ⇒ 00:22:37.269 Scott_Harmon: definitely, is that kind?
187 00:22:37.270 ⇒ 00:22:39.040 Scott_Harmon: What what you have in mind there, Utam.
188 00:22:39.040 ⇒ 00:23:00.230 Uttam Kumaran: Exactly in the past. When we’ve done one of the key things here is we want one of the, you know, the problems we’re trying to solve is making sure that the right information gets to the right place. So we’ll start with the 1st piece. The right information. You may have an idea like, let’s take the oh, by the way, we have a new service for trash cans that we want our Csrs to start marketing.
189 00:23:00.740 ⇒ 00:23:22.329 Uttam Kumaran: If you just start with that, of course, the success matters about all the information that you need so similar, what Amber Job Amber’s job would be to say, Okay, where is that offered? Okay, what are the details of the offer? Who can we offer to? What is the price? Those are all things that if if you were staring at a blank page, maybe you get 50% of it while it’s on your mind. But
190 00:23:22.370 ⇒ 00:23:47.999 Uttam Kumaran: you may also quickly realize I don’t have that. So that’s what we want. The trainer to assist is making sure that all data that gets in is a hundred percent quality from the start, so it will. The best flow that we’ve seen is for you to say, I want to do X, and then it will dynamically say great in order to do XI need y information, Z. Price, and once it’s once it has what it will determine as
191 00:23:48.120 ⇒ 00:24:11.500 Uttam Kumaran: cohesive information, not only about what, but then, where to put it, it will say, great! It’ll go. Do that. Then any information going into the knowledge base is full, right? So we’ve done 2 pieces we’ve went through and sort of cleaned up existing. But we want to make sure anything new that comes in stays clean. And so, having this process on the front end will help. With that. We’ve seen the interview process
192 00:24:11.860 ⇒ 00:24:19.030 Uttam Kumaran: a as like that interview sort of conversation style as as the best way to do it. And so that’s what we’ll probably deploy.
193 00:24:19.290 ⇒ 00:24:19.880 Scott_Harmon: Great.
194 00:24:20.460 ⇒ 00:24:21.120 JanieceGarcia: Awesome.
195 00:24:23.210 ⇒ 00:24:28.409 Scott_Harmon: And when do you expect in the schedule Amber to see the 1st version of that bot that
196 00:24:28.860 ⇒ 00:24:31.709 Scott_Harmon: Janice and Yvette can start playing with.
197 00:24:33.903 ⇒ 00:24:38.640 Amber Lin: Sorry, Utam and, Miguel, I’ll I’ll give that to you.
198 00:24:38.970 ⇒ 00:24:41.633 Uttam Kumaran: Do you want to go to the to the
199 00:24:42.660 ⇒ 00:24:47.408 Uttam Kumaran: Then the schedule slide. We can just talk, talk through that.
200 00:24:48.100 ⇒ 00:25:00.700 Uttam Kumaran: yes. So we’re basically started working on that this week, and probably about 2 weeks to get it done. It’s probably next week you’ll see a version of this that updates the knowledge that we can begin to test.
201 00:25:01.486 ⇒ 00:25:23.039 Uttam Kumaran: We’ve, I think, Scott, for context, we’ve done. We’ve made some improvements on how we’re storing the information technically, in order to enable this and then, of course, the Comp. The I would say, the the reason we need 2 weeks is the complication of making sure it ends up back into the right Google, Doc, or or document but this is really like our
202 00:25:23.330 ⇒ 00:25:29.400 Uttam Kumaran: our time, and maybe amber. I can let you walk through this or I. I sorry we skip some slides, so if there’s anything else we
203 00:25:29.570 ⇒ 00:25:30.510 Uttam Kumaran: we wanted to go.
204 00:25:30.510 ⇒ 00:25:57.600 Amber Lin: Just a little bit of what happens next is that I will be in touch to get all the accurate answers for the golden data sheet so that we can have we can improve the bot and deploy it for our for Shannon and Grace. And lastly, essentially updating files to Google drive. So I will be in contact with about these 2 things and about the oh, by the way, so I will remind you guys, don’t worry. You don’t have to write it down, I’ll be in touch.
205 00:25:59.050 ⇒ 00:26:05.709 Scott_Harmon: And sorry. This is a thinking back over. We’ve been working last couple of weeks.
206 00:26:06.110 ⇒ 00:26:09.409 Scott_Harmon: and I’ll confess I haven’t been testing the bot or
207 00:26:09.730 ⇒ 00:26:15.619 Scott_Harmon: or looking at the exact test scenarios. Who, Tom? I think the bots already working for the
208 00:26:16.260 ⇒ 00:26:20.439 Scott_Harmon: the questions that go to this to the spreadsheet. Is that correct? So there’s this.
209 00:26:20.440 ⇒ 00:26:21.710 Uttam Kumaran: That is correct.
210 00:26:21.710 ⇒ 00:26:26.230 Scott_Harmon: So we’ve already kind of now got the bot answering the questions that
211 00:26:26.470 ⇒ 00:26:28.940 Scott_Harmon: you used to have to go look up in the spreadsheet
212 00:26:30.420 ⇒ 00:26:33.979 Scott_Harmon: And and so those are some of our test scenarios. Is that correct?
213 00:26:33.980 ⇒ 00:26:38.115 Uttam Kumaran: That is correct. Yes, and maybe it would be helpful to
214 00:26:39.090 ⇒ 00:26:51.929 Uttam Kumaran: after next week. I think, Amber, once you have that spreadsheet cleaned up. Maybe it’s helpful to do one slide about like, what are we? How does what is our test criteria, and what types of tests are there, because
215 00:26:52.050 ⇒ 00:27:09.609 Uttam Kumaran: I think for me personally, what I want to see is that we are answering the easiest questions, the hardest questions and the types of questions. Is this something that we would previously have needed to go to a spreadsheet for? Is this a multi document question? What about for things that it doesn’t have right? So I would love to know.
216 00:27:10.187 ⇒ 00:27:19.400 Uttam Kumaran: Just like a 1 simple screen about here are we have 10 tests here, 10 tests here, 10 tests here. But yes, Scott, so we we have those right now.
217 00:27:19.400 ⇒ 00:27:24.549 Scott_Harmon: So service availability is kind of the 1st one. So if a Csr could just type in.
218 00:27:24.720 ⇒ 00:27:31.160 Scott_Harmon: do we offer? You know, this service in this Zip code in San Antonio. It it answers accurately.
219 00:27:35.980 ⇒ 00:27:49.229 YvetteRuiz: Once we upload that information, because I don’t. I don’t think what we have right now is just who who the scheduling side of it, but I don’t think we have the that information just yet with the type of services.
220 00:27:49.440 ⇒ 00:27:51.350 YvetteRuiz: if I’m not mistaken. But.
221 00:27:51.350 ⇒ 00:27:51.790 Scott_Harmon: Well, I thought.
222 00:27:51.790 ⇒ 00:27:52.350 YvetteRuiz: That’s what.
223 00:27:52.350 ⇒ 00:27:54.810 Scott_Harmon: I thought there were 2 spreadsheets.
224 00:27:55.570 ⇒ 00:27:58.820 Scott_Harmon: And I think we’ve imported them both. So I think we’re now able.
225 00:27:58.820 ⇒ 00:27:59.560 YvetteRuiz: Okay.
226 00:28:00.190 ⇒ 00:28:01.440 Scott_Harmon: Is that correct? You, Tom?
227 00:28:01.780 ⇒ 00:28:09.700 Uttam Kumaran: There is. There are several spreadsheets right now that we we have. I think Scott, to your point is, I think, maybe a
228 00:28:10.060 ⇒ 00:28:23.990 Uttam Kumaran: priority. Once we have, like what all those tests are categorized which are the most important tests to the team to get right? Cause we have. We have a couple of those we have the sophistication of the question. We have the type which is like, is it spreadsheet?
229 00:28:24.140 ⇒ 00:28:29.619 Uttam Kumaran: And then we, of course, have like it’s paramount that we get these right. Those all 3 may not.
230 00:28:29.690 ⇒ 00:28:57.469 Uttam Kumaran: may not be. They’re all kind of interrelated, but we may want to get the easy questions right and a particularly hard one. And what we want to make sure on the engineering side is every change we want to make sure that those continue to be answered. And that’s what helps us when we make changes to verify that we’re not affecting those. But also we want to make sure that those questions. If they’re the also the most frequently asked, then they get answered the fastest right? So
231 00:28:57.570 ⇒ 00:29:08.210 Uttam Kumaran: everything, even on our OP. As we’re starting to optimize to move this from 30 to 10, from 10 to a few. I want to direct the team towards going after the the most important piece.
232 00:29:08.210 ⇒ 00:29:22.039 Scott_Harmon: So can we? Can we just spend another 2 min on this topic? I if we’ve got time in the schedule and we do we only get? Can we look at the would you mind, Amber, if it’s possible, bringing up that spreadsheet of questions?
233 00:29:22.960 ⇒ 00:29:23.580 Scott_Harmon: But.
234 00:29:23.580 ⇒ 00:29:25.300 Amber Lin: In the Golden data sheet.
235 00:29:25.517 ⇒ 00:29:29.220 Scott_Harmon: I think that’s what I mean, the the spreadsheet of questions that we’re testing or we want.
236 00:29:29.220 ⇒ 00:29:30.050 Amber Lin: Definitely.
237 00:29:30.300 ⇒ 00:29:32.689 Scott_Harmon: Yeah, the yeah. The golden age. Okay, so.
238 00:29:32.690 ⇒ 00:29:45.379 Amber Lin: This is a data sheet of here. We have the questions of how how the question is gonna start. And in this column, E is where we’re going to fill in the correct answer. And so we’re going to compare these 2.
239 00:29:45.550 ⇒ 00:29:48.919 Amber Lin: And right now we’re trying to fill that in
240 00:29:49.130 ⇒ 00:29:54.640 Amber Lin: and trying to figure out what’s the discrepancy between these 2.
241 00:29:55.140 ⇒ 00:29:59.960 Scott_Harmon: So. So, okay, thank you. That’s that’s helpful. And the
242 00:30:00.550 ⇒ 00:30:08.909 Scott_Harmon: the the column. BI think I remember this from last week. Utam, I think is sort of interesting
243 00:30:09.040 ⇒ 00:30:13.840 Scott_Harmon: because it breaks down the different types of questions the Csrs sort of ask.
244 00:30:14.270 ⇒ 00:30:15.020 Scott_Harmon: I
245 00:30:16.030 ⇒ 00:30:21.669 Scott_Harmon: I guess I guess the point I want to make about this, in addition to getting it’s all filled out, which is super great.
246 00:30:22.660 ⇒ 00:30:26.539 Scott_Harmon: One of the things that I always guides me is the 80 20 rule
247 00:30:26.680 ⇒ 00:30:35.360 Scott_Harmon: that that there’s 20% of the types of questions that are going to have 80% of the value, and that we should really be focusing extra on early.
248 00:30:35.930 ⇒ 00:30:42.540 Scott_Harmon: And so I want to know from from a vet and Janice, okay, this. These are great questions we love to sheet.
249 00:30:42.720 ⇒ 00:30:45.169 Scott_Harmon: But, boy, these 5 or 7,
250 00:30:46.090 ⇒ 00:30:50.940 Scott_Harmon: we got to nail those and nail them early and nail them
251 00:30:51.340 ⇒ 00:30:57.800 Scott_Harmon: because they they’re the the most common or the heart, whatever it is that makes them like all these questions aren’t of equal value.
252 00:30:58.010 ⇒ 00:30:59.290 Scott_Harmon: And so
253 00:31:00.702 ⇒ 00:31:06.469 Scott_Harmon: I think it might help if we just knew if you could just go through and circle those or put them in.
254 00:31:06.640 ⇒ 00:31:08.960 Scott_Harmon: put them in a different color.
255 00:31:09.360 ⇒ 00:31:15.859 Scott_Harmon: Yvette and Amber, and just know, okay, these are great. These are the right questions. But, boy, these are the ones I would really
256 00:31:17.650 ⇒ 00:31:25.900 Scott_Harmon: do cartwheels over, and that allows us just to know where to focus because sometimes.
257 00:31:26.490 ⇒ 00:31:32.039 Scott_Harmon: you know, you just want to know. We’re going to get an A on all of it. Who, Tom, I’m sure. But you want to get A’s early on the.
258 00:31:32.040 ⇒ 00:31:36.580 Uttam Kumaran: No, no, I am. I’m totally with you. In fact, I don’t want us to spend our time on the
259 00:31:36.700 ⇒ 00:31:53.300 Uttam Kumaran: like. I I would rather spend the time while we have every day matters. And so we can really go after the core things. So I think, Amber, when you meet with the team just to have a column here that shows the level of importance that could literally be a checkbox.
260 00:31:53.300 ⇒ 00:31:54.230 Scott_Harmon: That’s a great idea.
261 00:31:54.230 ⇒ 00:31:57.169 Uttam Kumaran: Ideally. Of course not. Everything is the most important.
262 00:31:57.170 ⇒ 00:32:04.790 Scott_Harmon: That’s great. Maybe 1, 2, 3, and I would just suggest one means, hey? High priority for phase one.
263 00:32:05.250 ⇒ 00:32:10.259 Scott_Harmon: 2, you know, medium priority phase 2, and then maybe 3 is like, okay. Could wait.
264 00:32:10.260 ⇒ 00:32:10.990 Amber Lin: Hmm.
265 00:32:10.990 ⇒ 00:32:15.560 Scott_Harmon: Maybe we do it next month, or whatever scheme you like. Amber, but that would, I think, really help
266 00:32:16.020 ⇒ 00:32:22.459 Scott_Harmon: focus us on the right stuff utam, and make sure that there’s no expectation mismatch here.
267 00:32:24.160 ⇒ 00:32:49.079 Amber Lin: Yeah. And Scott, you mentioned the phase of the question. I also think that’s a very interesting point, because event engineers, for these questions, they are, for some of them won’t come up until the last parts right? Or do they come up equally often in different phases of the call, and that the agent does. Does some of them come earlier, or does some of them come later? Do we know anything about that?
268 00:32:49.790 ⇒ 00:32:51.740 JanieceGarcia: I mean, I guess it would, and I’m
269 00:32:51.820 ⇒ 00:33:03.759 JanieceGarcia: I want to see if I’m following correctly. But I know for us the very an important one would be knowing, okay, what services we do, in what area? And who can do those services?
270 00:33:04.177 ⇒ 00:33:29.210 JanieceGarcia: And then from there, I mean, we can have all kinds of questions come through depending on the customer. I mean, there’s even we even let our agents know we’re not able to give every single type of scenario for a customer calling in because there’s gonna be some random things. But we know what comes up more often, and it really does depend in regards to seasons as well.
271 00:33:29.210 ⇒ 00:33:42.739 Scott_Harmon: So I just to be that guy service availability is what we’ve called that. So questions related to service availability things consistently that Janice and Yvette have identified as priority one.
272 00:33:43.250 ⇒ 00:33:45.949 Scott_Harmon: Yeah, that that one isn’t.
273 00:33:46.400 ⇒ 00:34:05.920 YvetteRuiz: Yeah, that one is the beginning. And and I, that’s what I was kind of questioning, because I know some of the the sheets that we have. That’s why I was kind of questioning what we had right now, what was already up, because I know when when I was testing it, it didn’t have some of those. You know what I mean. I think Miguel had told me it was. He had only put in X. We’ve kind of we? We might have added more on there.
274 00:34:06.300 ⇒ 00:34:20.510 YvetteRuiz: But the definitely the serve, the type of services that we do, because that’s like a big thing. Again, going back to my meeting yesterday? This is it the question I was asking Matt and Bobby and all the DM. Saying, Okay.
275 00:34:20.580 ⇒ 00:34:46.600 YvetteRuiz: is, where could I go and extract all our service line, all our services, because I know what trades we do right lawn pest mechanical. But I want every service line in those trades that we do, because that’s the questions that we get asked. Do you do gutter cleaning, you know. Do you do trash bin services, do? And so our website has those. So I was going to say, if I can, if I can get all that and share that with.
276 00:34:47.139 ⇒ 00:34:49.169 YvetteRuiz: you know, with with you. We don’t.
277 00:34:49.340 ⇒ 00:34:57.690 YvetteRuiz: That’s gonna be like a big thing, because those are like Janice said the questions that do come in a lot from the customers asking that.
278 00:34:59.050 ⇒ 00:35:02.309 Scott_Harmon: And that’s why those I thought there were 2 spreadsheets right that.
279 00:35:03.120 ⇒ 00:35:22.529 Scott_Harmon: That are manually created, and lovingly I tend to pick on them because I like to pick on Janice, but because they’re they’re crazy. I call them the spreadsheets from hell there. But what what that is? Amber, just to kind of fill you in is Janice runs around. The organization might not be just her, but some others.
280 00:35:22.870 ⇒ 00:35:28.800 Scott_Harmon: and has to fill in all the detail about which services are offered, where
281 00:35:28.910 ⇒ 00:35:34.259 Scott_Harmon: by which technician on which day it’s it’s there’s quite a bit of detail about
282 00:35:34.700 ⇒ 00:35:42.960 Scott_Harmon: the services and which ones are available to whom? Under what circumstances, that data does not exist anywhere in the organization.
283 00:35:43.520 ⇒ 00:35:51.059 Scott_Harmon: It has to get scraped together manually by Janice. And and she’s put it in these 2 spreadsheets. Well, we’ve
284 00:35:52.280 ⇒ 00:36:04.669 Scott_Harmon: and so that that is kind of like a golden ticket. If we could import that, I thought we’d, you know, get them both imported. Now, people don’t need to read the spreadsheet anymore. They just asked the bot, because the spreadsheet can be kind of hard to read.
285 00:36:05.210 ⇒ 00:36:11.000 Scott_Harmon: Then the second phase is, Janice doesn’t have to maintain that spreadsheet anymore.
286 00:36:11.570 ⇒ 00:36:18.980 Scott_Harmon: She just, I think I think, probably the fullest of time. We want the bot to go automatically, update that information somehow.
287 00:36:19.640 ⇒ 00:36:27.169 Scott_Harmon: But at least we can sort of have Janice have it work with Janice to update it. So you don’t have to maintain the spreadsheet.
288 00:36:27.440 ⇒ 00:36:29.920 Scott_Harmon: Did I describe that right?
289 00:36:32.490 ⇒ 00:36:33.520 Amber Lin: Yeah, yeah.
290 00:36:33.520 ⇒ 00:36:34.120 YvetteRuiz: Yes, Scott.
291 00:36:34.120 ⇒ 00:36:59.650 Amber Lin: We do have the spreadsheet to the, to the to a lot of different services. Ashley Miguel showed me that yesterday. So we do have that. And yes, it is a lot of information. So we’re trying to keep that up to date. Have that integrated. And I do believe we do have some progress on that but I’ll work with you guys to make sure this is the most up to date, and so that we can get the best answers to our.
292 00:36:59.650 ⇒ 00:37:17.360 YvetteRuiz: Okay per perfect, because I know, even look, even with our spreadsheet, that the the big spreadsheet does not have the details that I need in there, and this is what I was alluding to early on. And Scott, that I was telling you is like we have a good spreadsheet that goes in there and says, lawn past.
293 00:37:17.580 ⇒ 00:37:22.209 YvetteRuiz: and we have the zip codes and all that, but it still doesn’t get granular enough.
294 00:37:22.598 ⇒ 00:37:26.890 YvetteRuiz: Have you all seen our website. I mean, I’m sure you guys have been on our ABC website.
295 00:37:26.890 ⇒ 00:37:27.680 Scott_Harmon: Yeah.
296 00:37:28.320 ⇒ 00:37:36.419 YvetteRuiz: Okay. So in there. If if I were to go in there and it says, appliance repair right? Or or you could pull pull it up right there.
297 00:37:38.095 ⇒ 00:37:48.444 YvetteRuiz: It’s gonna go in there and it’s gonna go even granular. You can go to Austin because Austin has all the services, not all our branches do all our services. Which is another reason why this is so important.
298 00:37:50.240 ⇒ 00:37:50.660 Scott_Harmon: Go.
299 00:37:50.660 ⇒ 00:38:10.249 YvetteRuiz: So go into the home services and go to A/C and heating. So if I go to A/C and heating screen and scroll down, it’s gonna so here’s here’s where it gets so granular. We do air quality, we do A/C heating. We do A/C maintenance tune ups. We do. So that’s those are the questions that get asked to us that we don’t.
300 00:38:10.560 ⇒ 00:38:13.760 YvetteRuiz: All our spreadsheet says is that we do.
301 00:38:14.120 ⇒ 00:38:14.840 JanieceGarcia: Hvac.
302 00:38:15.140 ⇒ 00:38:24.689 YvetteRuiz: Hvac services. Okay? Well, what in Hvac service? What? Because we get asked those questions specifically, or even an appliance repair. Do you install a ceiling fan.
303 00:38:25.200 ⇒ 00:38:38.719 YvetteRuiz: What on our spreadsheet? It just says appliance. Right? I gotta get that granular so that because those are the questions that the Csr’s go in there asking like, Do we do it? And do we do it in San Antonio? Do we do it in corpus? Do we do it in this zip code.
304 00:38:38.720 ⇒ 00:38:40.269 YvetteRuiz: So so this is.
305 00:38:40.510 ⇒ 00:38:48.730 Scott_Harmon: This is new to me only because I probably wasn’t paying attention. I thought you had figured out a way to get all this into your spreadsheet, and you’re telling me no.
306 00:38:48.980 ⇒ 00:38:53.069 Scott_Harmon: So a. Ca. Csr would then just be trained. Go to the website and look.
307 00:38:54.360 ⇒ 00:38:55.480 YvetteRuiz: No. Yeah.
308 00:38:56.040 ⇒ 00:38:56.570 JanieceGarcia: Then.
309 00:38:56.570 ⇒ 00:39:06.269 YvetteRuiz: That’s the question. They don’t go to the website. They just go in there and they start asking. I was, I’ve been trying to. And I know, Steven. I know we talked about this because even Steven went in there.
310 00:39:06.770 ⇒ 00:39:34.320 YvetteRuiz: I have to physically go in there and drag this information from our Dms to give us this information. So I finally said, because I’ve been wanting to give you this since we started talking about this. So yesterday I had a firm conversation with Matt Bobby, and said, How can I please get all the service lines that we do? So? I could share that with brain. You know, Brainforge, to easily pull up these questions? Because and of course they’re they lit up to saying that makes sense. So.
311 00:39:34.320 ⇒ 00:39:34.900 Scott_Harmon: Again. It’s.
312 00:39:34.900 ⇒ 00:39:36.891 YvetteRuiz: There’s just so many pieces.
313 00:39:37.290 ⇒ 00:39:39.049 Scott_Harmon: I’m sorry I’m just confused
314 00:39:39.810 ⇒ 00:39:46.769 Scott_Harmon: is the stuff you just showed us on the website, accurate or not. And if it’s accurate, why do you have trouble getting it. You just said it’s on the website.
315 00:39:47.620 ⇒ 00:39:56.600 YvetteRuiz: Right. That’s that’s what I’m asking. That’s what I’m asking. My, that’s what I’m asking. Matt and Bobby. Is it a accurate information
316 00:39:57.200 ⇒ 00:40:00.550 YvetteRuiz: accurate? Great. I can go in there and say, Hey.
317 00:40:00.550 ⇒ 00:40:00.980 Scott_Harmon: God.
318 00:40:00.980 ⇒ 00:40:04.250 YvetteRuiz: How do? How do I get all this in into our, into our.
319 00:40:04.250 ⇒ 00:40:06.119 Scott_Harmon: I got it. Okay, yeah, you don’t.
320 00:40:06.120 ⇒ 00:40:22.679 Scott_Harmon: you know. So somewhere, some magic person somewhere within the business updates that website every so often. And you want to know if the website is updated reliably in a trustable way. You don’t know that there’s some person called a DM. Or somebody in the operation side.
321 00:40:24.000 ⇒ 00:40:29.159 Scott_Harmon: But yeah, I’m guessing that website probably isn’t updated accurately all the time.
322 00:40:29.470 ⇒ 00:40:54.180 YvetteRuiz: They seem to think that it is. But we’re having a big conversation on Tuesday, because our marketing managers in charge of our website he has. He’s in the same situation as I am making sure that our division managers give us that information to make sure this is as accurate as possible. So that is everything. That’s the final piece that I’m getting to. You guys, we have a lot of information. We just don’t have that granular.
323 00:40:54.490 ⇒ 00:40:54.990 Scott_Harmon: So.
324 00:40:54.990 ⇒ 00:40:56.871 YvetteRuiz: Information. That is what we deal with.
325 00:40:57.140 ⇒ 00:41:05.719 Scott_Harmon: So, okay, thank you. That’s helpful information. I don’t think we planned on doing it. So I don’t want to add things to the schedule.
326 00:41:05.720 ⇒ 00:41:08.550 Uttam Kumaran: We just we did. We did it. Yeah.
327 00:41:08.790 ⇒ 00:41:09.620 Scott_Harmon: You did it.
328 00:41:09.620 ⇒ 00:41:11.979 Uttam Kumaran: Yeah, we we already have the website.
329 00:41:12.200 ⇒ 00:41:14.619 Scott_Harmon: Oh, you scrape the service definitions from the website.
330 00:41:14.620 ⇒ 00:41:21.479 Uttam Kumaran: I think we scraped the whole thing. Yeah, but I don’t. I don’t think I’m not sure if it’s getting used. We have it, though.
331 00:41:21.750 ⇒ 00:41:26.060 Scott_Harmon: But is so. Do you stick it in a document? You must stick it in a document. Everything you scrape you.
332 00:41:26.060 ⇒ 00:41:44.269 Uttam Kumaran: Yeah, it’s there. It’s there. I will have to. I’ll have to confirm early on the project when we were testing, and we didn’t have information. We we went and looked. We scraped the entire pest website and the primary home website. If that ends up being the source of truth, then we, that’s we can just leverage that.
333 00:41:44.510 ⇒ 00:41:54.340 Scott_Harmon: So so we could. Let’s go back and check. Did we? Did we really scrape it? And is it, you know? Did we stick it into a file, so the agent can read it, and then, coming back to this sheet
334 00:41:54.700 ⇒ 00:42:05.599 Scott_Harmon: amber, we should be able to identify the questions that are associated with service availability, and next week
335 00:42:06.070 ⇒ 00:42:10.430 Scott_Harmon: the agent should be able to answer those questions accurately. As a matter of fact.
336 00:42:10.790 ⇒ 00:42:13.509 Scott_Harmon: Janice and Yvette shouldn’t be able to break it
337 00:42:14.470 ⇒ 00:42:20.840 Scott_Harmon: like like, like, you shouldn’t be able to ask it a question. It can’t answer about service availability.
338 00:42:23.700 ⇒ 00:42:24.519 Uttam Kumaran: I agree.
339 00:42:24.520 ⇒ 00:42:33.249 Scott_Harmon: Like, absolutely like you’re like, Oh, my God, I can’t stump it like, Okay, that’s our goal, all right.
340 00:42:36.260 ⇒ 00:42:38.320 Uttam Kumaran: That’s my goal. Yeah, I don’t like
341 00:42:38.880 ⇒ 00:42:42.740 Uttam Kumaran: my expectations could not be higher. So bye.
342 00:42:42.820 ⇒ 00:42:48.938 Uttam Kumaran: if there’s even more pressure, it’s great, because I want this to work 100% of the time.
343 00:42:49.260 ⇒ 00:43:10.704 YvetteRuiz: Me too. This is again, I have my Csr so pumped up because this this is so, this means so much to us, because this is this is everything. We’re on the phone. And we do again a lot of lines of businesses. So I’m just trying to make sure that I’m relaying the information correctly, so as best that I can.
344 00:43:11.040 ⇒ 00:43:19.090 Scott_Harmon: Now, later on in the future, we could probably help you with that getting those service line data reliably updated.
345 00:43:19.310 ⇒ 00:43:25.580 Scott_Harmon: There’s some future version of the of the training bot where somebody can. Just.
346 00:43:25.710 ⇒ 00:43:37.959 Scott_Harmon: you know, again, I don’t want to take us off topic, but that’s an easy problem to solve down the line that the Aih can help. You make sure that the service definitions are getting written to the reps website accurately. And you know.
347 00:43:38.640 ⇒ 00:43:44.570 Scott_Harmon: reviewed and approved, and all that stuff which they probably aren’t. There’s probably not a good
348 00:43:45.090 ⇒ 00:43:50.130 Scott_Harmon: approval workflow for those service definitions. And that’s that’s an easy problem to solve down the line.
349 00:43:51.050 ⇒ 00:44:02.079 YvetteRuiz: Utah last question. I’m sorry not. I’m I don’t mean to scroll either. But when you said you scrubbed our website, you went to our ABC website, our Kim free website and our Turing Mesh website.
350 00:44:02.280 ⇒ 00:44:06.599 Uttam Kumaran: We just went to the one where it had just the pest related Pdfs.
351 00:44:07.040 ⇒ 00:44:10.089 YvetteRuiz: Oh, you went to our Nps site.
352 00:44:10.090 ⇒ 00:44:10.729 JanieceGarcia: Yeah, bye.
353 00:44:10.730 ⇒ 00:44:15.660 Uttam Kumaran: That, and we went to the main ABC homecomercial.com, although if there’s more.
354 00:44:15.940 ⇒ 00:44:17.929 Uttam Kumaran: we’ll take all we’ll take. We’ll take all.
355 00:44:18.341 ⇒ 00:44:20.400 YvetteRuiz: Got it? Got it? Okay.
356 00:44:20.400 ⇒ 00:44:30.020 Uttam Kumaran: So you can take a note to get any of their any of their customer facing websites. I think the other piece we’ll need to know is what is what is accurate, of course, and like what.
357 00:44:30.290 ⇒ 00:44:37.409 Scott_Harmon: Were. Those were those service definitions we just looked at are those htmls? I didn’t. We didn’t click on one. I assume they’re htmls. We can.
358 00:44:37.860 ⇒ 00:44:41.029 Uttam Kumaran: Yeah, I think we can. I think they’re all just plain tax. We can grab those.
359 00:44:41.030 ⇒ 00:44:46.170 Scott_Harmon: Yeah, I just wanna make sure we get, though I’m I know I’m being a dog with a bone here. But I just wanna make sure we get those
360 00:44:46.510 ⇒ 00:44:49.929 Scott_Harmon: in addition to everything else. But but that stuff needs to be
361 00:44:51.190 ⇒ 00:44:54.619 Scott_Harmon: captured for us to answer that set of questions accurately.
362 00:44:54.960 ⇒ 00:44:56.280 Amber Lin: Oh, yeah, maybe.
363 00:44:56.280 ⇒ 00:45:04.259 YvetteRuiz: We didn’t go. We didn’t scroll far enough down, but if you scroll even more down, it’s gonna really break it down even more with those services.
364 00:45:04.260 ⇒ 00:45:05.420 Scott_Harmon: Look real quick.
365 00:45:05.580 ⇒ 00:45:06.340 Scott_Harmon: So those are.
366 00:45:06.340 ⇒ 00:45:07.149 YvetteRuiz: Yeah. Go.
367 00:45:07.150 ⇒ 00:45:09.190 Scott_Harmon: Or HD. HTML pages.
368 00:45:10.510 ⇒ 00:45:12.490 YvetteRuiz: Okay, so go.
369 00:45:13.160 ⇒ 00:45:15.299 YvetteRuiz: I’m trying to see where. Okay, right here.
370 00:45:15.860 ⇒ 00:45:17.450 Scott_Harmon: Click on appliance, repair.
371 00:45:18.125 ⇒ 00:45:18.320 YvetteRuiz: Oh!
372 00:45:18.320 ⇒ 00:45:19.900 Scott_Harmon: Holy crap!
373 00:45:21.470 ⇒ 00:45:22.070 Scott_Harmon: Keep going.
374 00:45:22.070 ⇒ 00:45:25.710 YvetteRuiz: Remember, this is broken down by Brand, so not every city.
375 00:45:25.710 ⇒ 00:45:29.999 Scott_Harmon: Would you click on one of those? What’s I just want to figure out what’s at the bottom of the link.
376 00:45:31.850 ⇒ 00:45:34.358 YvetteRuiz: It just frequently asked questions.
377 00:45:37.090 ⇒ 00:45:42.470 Scott_Harmon: So at the bottom there’s there’s HTML text Utam, that that defines the service.
378 00:45:42.480 ⇒ 00:45:42.970 Uttam Kumaran: Okay.
379 00:45:43.790 ⇒ 00:45:50.109 Scott_Harmon: There, is it? Yeah. Okay, holy cow, I get it now.
380 00:45:53.370 ⇒ 00:45:55.170 Scott_Harmon: Oi perfect.
381 00:45:56.640 ⇒ 00:46:04.310 Scott_Harmon: So we should be able to crawl all of this if we’re not already and dump it into a file. The trick’s going to be. You gotta dump it into a file that the agent can read.
382 00:46:06.380 ⇒ 00:46:08.160 Uttam Kumaran: No trick. We got it.
383 00:46:08.560 ⇒ 00:46:10.999 Scott_Harmon: All right. I love it, I love it.
384 00:46:11.000 ⇒ 00:46:22.253 YvetteRuiz: Awesome, awesome. And this is where we can start connecting. We can start connecting dots, because with this, this is where, oh, by the way goes in there. Well, if he calls in for a dishwasher repair here.
385 00:46:22.550 ⇒ 00:46:24.250 YvetteRuiz: No, and it’s actually very helpful.
386 00:46:24.750 ⇒ 00:46:32.949 Uttam Kumaran: If you guys know that this is going to be the most up to date instead of taking it moving it somewhere else, we will just keep trying to like. Get it
387 00:46:33.350 ⇒ 00:46:36.958 Uttam Kumaran: from here on some cadence, you know. And
388 00:46:37.520 ⇒ 00:46:44.010 Uttam Kumaran: That solves another sort of rock. But again, I think good, really good. I’m glad we got to this today to hear that.
389 00:46:46.020 ⇒ 00:46:51.759 YvetteRuiz: Yeah, absolutely. I. I will keep on working with our division managers and everyone.
390 00:46:52.270 ⇒ 00:46:54.624 YvetteRuiz: That is where a lot of
391 00:46:55.680 ⇒ 00:46:56.900 Scott_Harmon: So our goal for.
392 00:46:56.900 ⇒ 00:46:58.185 YvetteRuiz: There’s that work to do. There.
393 00:46:58.400 ⇒ 00:47:05.070 Scott_Harmon: Goal for next week is to have a contest to see on the Service availability questions. If Janice can break it.
394 00:47:05.360 ⇒ 00:47:06.060 Uttam Kumaran: Yes.
395 00:47:06.510 ⇒ 00:47:07.460 YvetteRuiz: There you go!
396 00:47:07.700 ⇒ 00:47:09.710 Scott_Harmon: So next Friday.
397 00:47:09.710 ⇒ 00:47:11.396 YvetteRuiz: Do it.
398 00:47:12.240 ⇒ 00:47:14.760 Uttam Kumaran: If you can stop it, we’re gonna send you
399 00:47:14.760 ⇒ 00:47:16.930 Uttam Kumaran: yeah. So I gotta think of something.
400 00:47:16.930 ⇒ 00:47:20.139 Scott_Harmon: A free prize right, and our armadillo.
401 00:47:20.140 ⇒ 00:47:22.557 Uttam Kumaran: You get your own. AI bot.
402 00:47:22.960 ⇒ 00:47:27.360 YvetteRuiz: Who’s on? Who’s who? Who’s sharing our website right now? Is it you, Scott? Or.
403 00:47:27.360 ⇒ 00:47:28.360 Scott_Harmon: No, it’s number.
404 00:47:29.000 ⇒ 00:47:29.680 Amber Lin: Oh, it’s.
405 00:47:29.680 ⇒ 00:47:34.759 YvetteRuiz: Amber. Okay, I was just gonna ask you go. Can you just go quickly to the Kim free?
406 00:47:35.690 ⇒ 00:47:37.060 YvetteRuiz: Yes, website.
407 00:47:41.100 ⇒ 00:47:42.760 Amber Lin: As well.
408 00:47:42.760 ⇒ 00:47:44.380 JanieceGarcia: The one tier.
409 00:47:46.270 ⇒ 00:47:47.649 YvetteRuiz: Is it that? No, that’s not that.
410 00:47:47.650 ⇒ 00:47:48.500 JanieceGarcia: No, that’s not bad.
411 00:47:48.500 ⇒ 00:47:51.850 YvetteRuiz: It’s supposed to be right.
412 00:47:53.570 ⇒ 00:47:54.310 JanieceGarcia: That one.
413 00:47:54.310 ⇒ 00:47:57.840 YvetteRuiz: So here’s our our Kim free services.
414 00:47:58.760 ⇒ 00:48:01.530 Amber Lin: Let’s see if I click on 1st one.
415 00:48:02.260 ⇒ 00:48:04.340 Amber Lin: It will bring us to.
416 00:48:05.200 ⇒ 00:48:07.869 YvetteRuiz: And it should kind of have the similarities.
417 00:48:08.200 ⇒ 00:48:19.817 YvetteRuiz: But these are all like questions that you know can be asked. You know, why, what’s the difference with Kim free, or what you know. What? How do you treat mosquitoes organically?
418 00:48:20.170 ⇒ 00:48:23.080 Scott_Harmon: Chem free is the is the organic
419 00:48:23.630 ⇒ 00:48:25.880 Scott_Harmon: version of the pest stuff. If I’m a
420 00:48:26.170 ⇒ 00:48:32.859 Scott_Harmon: granola type, I and I want all the the non chem, you know the I don’t want to grow 3 arms. This is the one I get.
421 00:48:37.350 ⇒ 00:48:38.460 Amber Lin: So you would you have.
422 00:48:38.460 ⇒ 00:48:39.130 YvetteRuiz: Once more!
423 00:48:39.130 ⇒ 00:48:44.610 Amber Lin: To scrape the ABC scrape the ken free. And I know there’s another website. What is that one called.
424 00:48:44.610 ⇒ 00:48:45.510 JanieceGarcia: Termy mesh.
425 00:48:46.020 ⇒ 00:48:46.530 YvetteRuiz: Mesh.
426 00:48:47.490 ⇒ 00:48:48.820 Amber Lin: 30.
427 00:48:49.470 ⇒ 00:48:50.540 Scott_Harmon: Perma mesh.
428 00:48:51.260 ⇒ 00:48:53.190 YvetteRuiz: Is the top one.
429 00:48:53.190 ⇒ 00:48:53.830 Amber Lin: Oh!
430 00:48:54.170 ⇒ 00:48:54.880 Scott_Harmon: And.
431 00:48:56.470 ⇒ 00:48:56.920 YvetteRuiz: We.
432 00:48:56.920 ⇒ 00:48:57.590 JanieceGarcia: No.
433 00:48:57.590 ⇒ 00:48:58.630 YvetteRuiz: That one hit Janice.
434 00:48:58.630 ⇒ 00:49:01.529 YvetteRuiz: Not it. No, no, okay, sorry. No, it is.
435 00:49:01.530 ⇒ 00:49:05.799 JanieceGarcia: Wait, hold on it was term me, stop. Yes, it is. Turn me, stop.
436 00:49:06.050 ⇒ 00:49:08.660 JanieceGarcia: U.S.A, dot com, yeah, that’s it
437 00:49:09.240 ⇒ 00:49:10.429 Scott_Harmon: What’s this for.
438 00:49:11.300 ⇒ 00:49:15.069 JanieceGarcia: Specifically for our termy mesh services.
439 00:49:15.070 ⇒ 00:49:16.299 Scott_Harmon: Oh, so this termite.
440 00:49:16.300 ⇒ 00:49:26.685 YvetteRuiz: Termite. Yes, so these this is for more the houses before they’re built. This is a wiring mesh system that we do for termite treatments.
441 00:49:27.070 ⇒ 00:49:32.440 Scott_Harmon: Why is this on another website? Is this like a from a company that does this for you?
442 00:49:33.350 ⇒ 00:49:34.020 YvetteRuiz: It’s it’s our.
443 00:49:34.020 ⇒ 00:49:37.660 YvetteRuiz: No, it’s our go ahead, Janice.
444 00:49:38.060 ⇒ 00:49:58.489 JanieceGarcia: No, I was just gonna say it is definitely ours. But we have customers that, or builders that are able to actually purchase directly through that as well, and then we have to go in our system and create accounts for them under termie mesh, and then send it out. And so it is separate from.
445 00:49:58.490 ⇒ 00:50:00.930 Scott_Harmon: Well, it sounds like it’s almost a different line of business with an agent.
446 00:50:00.930 ⇒ 00:50:02.280 JanieceGarcia: It is, it is.
447 00:50:02.280 ⇒ 00:50:05.050 YvetteRuiz: It is a different kind of business, but it’s owned by ABC.
448 00:50:05.050 ⇒ 00:50:05.439 JanieceGarcia: A, b.
449 00:50:05.440 ⇒ 00:50:11.560 YvetteRuiz: It’s just the the way the treatment is done again. It’s more for new home builders
450 00:50:12.620 ⇒ 00:50:17.510 YvetteRuiz: that are building their home. And it’s a different way of treating termites.
451 00:50:17.510 ⇒ 00:50:23.140 Scott_Harmon: 3 websites to make sure we’re scraping properly, utam, which you think’s a slam dunk.
452 00:50:23.630 ⇒ 00:50:27.610 Scott_Harmon: and next week the agent will be able to
453 00:50:27.830 ⇒ 00:50:33.819 Scott_Harmon: answer questions about service availability for all of it. Do you offer terminesh
454 00:50:33.990 ⇒ 00:50:38.079 Scott_Harmon: on Thursdays in San Antonio? If I have an apartment? But, like
455 00:50:38.390 ⇒ 00:50:40.929 Scott_Harmon: whatever the stop questions are okay.
456 00:50:40.930 ⇒ 00:50:46.235 YvetteRuiz: Yeah, we’re gonna have fun with this, I can tell you. We scrape all that. There’s gonna be a lot of questions to ask in here.
457 00:50:46.630 ⇒ 00:50:47.710 JanieceGarcia: There is.
458 00:50:47.980 ⇒ 00:50:48.670 Amber Lin: Great.
459 00:50:49.200 ⇒ 00:50:52.584 JanieceGarcia: I would be surprised if I stumped it too.
460 00:50:53.625 ⇒ 00:50:54.290 Scott_Harmon: Excellent.
461 00:50:54.290 ⇒ 00:50:56.209 Scott_Harmon: Good. Conversation. Okay.
462 00:50:56.510 ⇒ 00:51:12.589 Amber Lin: Yeah. So right now, we’re at our 2 last pages. We’re just gonna talk a little bit about the next steps. And we are currently developing a proposal. I don’t know if I sent out already, but we’ll be in talks about that, and how to move forward together.
463 00:51:12.760 ⇒ 00:51:16.959 Amber Lin: We’ll be improving the oh, by the way, integration as we talked about
464 00:51:17.090 ⇒ 00:51:31.879 Amber Lin: and we’ll improve, we’ll work. We’re working on improving. The accuracy of the Csr bot. It’s this last week was very much focused on getting that to a workable speed. And so this next week we’re going to make it faster and make it more accurate.
465 00:51:32.190 ⇒ 00:51:35.440 JanieceGarcia: So, Trina Bot, we just talked about that.
466 00:51:35.590 ⇒ 00:51:46.130 Amber Lin: And getting, enabling that to be enabling knowledge to be updated a lot easier. And then last one, we’re going to test that. So
467 00:51:46.669 ⇒ 00:51:59.189 Amber Lin: I just wanna hear a little bit more about that from Utam of. I think we’re going to test it after we get the updated knowledge right? Or what’s the progress on that.
468 00:52:01.760 ⇒ 00:52:04.520 Uttam Kumaran: Terms of the last piece, just the testing or the trainer. Bob.
469 00:52:05.547 ⇒ 00:52:06.920 Amber Lin: The Csr bot.
470 00:52:07.320 ⇒ 00:52:12.719 Uttam Kumaran: Oh, yeah. So I mean what I I think this is basically around amber, you spending time with.
471 00:52:13.090 ⇒ 00:52:13.460 Amber Lin: No.
472 00:52:13.460 ⇒ 00:52:16.210 Uttam Kumaran: Shannon and Grace right.
473 00:52:16.210 ⇒ 00:52:16.630 Amber Lin: Okay.
474 00:52:18.750 ⇒ 00:52:19.550 Uttam Kumaran: Yeah.
475 00:52:19.550 ⇒ 00:52:20.770 Amber Lin: Oh, boy, okay.
476 00:52:20.770 ⇒ 00:52:22.629 Uttam Kumaran: Janice, is grace related to you.
477 00:52:23.040 ⇒ 00:52:23.700 JanieceGarcia: No.
478 00:52:24.030 ⇒ 00:52:29.003 Uttam Kumaran: Okay, I was gonna ask. I had to add. I saw the last. I said, Oh, maybe they’re maybe they’re related.
479 00:52:29.640 ⇒ 00:52:30.410 JanieceGarcia: Okay.
480 00:52:31.063 ⇒ 00:52:45.159 Uttam Kumaran: Great. So yeah. And really, we have ongoing improvements. And one thing that we’ll talk about for the next phase is, there’s we’re gonna we’ll do our best to isolate like we’re making pushes on things. But as we find cheaper, faster, easier way to do things.
481 00:52:45.260 ⇒ 00:52:47.780 Uttam Kumaran: we’re gonna make that available. So
482 00:52:48.191 ⇒ 00:53:16.270 Uttam Kumaran: that’s something ongoing, I think probably will, for anything ongoing. I don’t like to say every anything’s ongoing. We’ll probably it’ll probably drop from the side next week, but I think it’s helpful to know that we do have a process of continuous, you know, improvement. But the 4 items on top are really are are our next steps, and I think Amber, and particularly really getting with Shannon and Grace as soon as possible and and getting them, you know, to really pressure test. And
483 00:53:16.570 ⇒ 00:53:33.690 Uttam Kumaran: I think the other item that we learned today is the website items as well as we need to start a discussion around 8 by 8 in parallel with the conversations about the next proposal. So all those items, I think, would be would be really awesome to make progress on next week.
484 00:53:34.650 ⇒ 00:53:35.120 YvetteRuiz: Yeah.
485 00:53:35.557 ⇒ 00:53:42.760 YvetteRuiz: Uda, maybe on that. If that if we’re gonna be talking about start talking about 8 by 8, obviously, I would like to have our data
486 00:53:43.533 ⇒ 00:53:51.376 YvetteRuiz: my workforce manager, who is working works with 8 by 8, who does all our metrics and all that? Maybe be part of this.
487 00:53:53.810 ⇒ 00:53:54.450 Uttam Kumaran: Okay?
488 00:53:55.340 ⇒ 00:53:57.079 Uttam Kumaran: Oh, and we have one more slide. Right?
489 00:53:57.080 ⇒ 00:53:58.169 Amber Lin: Yeah, it’s full.
490 00:53:58.170 ⇒ 00:53:59.899 YvetteRuiz: Yeah, I was like I was waiting for that one to come.
491 00:53:59.900 ⇒ 00:54:01.679 JanieceGarcia: I wanna see all
492 00:54:05.000 ⇒ 00:54:06.240 JanieceGarcia: I like one colorful one.
493 00:54:06.750 ⇒ 00:54:12.780 Amber Lin: Oh, yeah, what is our votes on? So we want to make sure it has a name, and we it has a face.
494 00:54:15.020 ⇒ 00:54:18.110 Uttam Kumaran: I know we talked about doing this as a competition, too, but we just want.
495 00:54:18.110 ⇒ 00:54:18.940 YvetteRuiz: Yes, I like.
496 00:54:19.450 ⇒ 00:54:21.575 Uttam Kumaran: It has a profile photo.
497 00:54:22.000 ⇒ 00:54:25.410 Scott_Harmon: I love the Andy that it’s got the A and the I in it. I think that’s.
498 00:54:25.410 ⇒ 00:54:28.370 Uttam Kumaran: I do. I do really like that. I think that’s like.
499 00:54:29.370 ⇒ 00:54:32.269 Uttam Kumaran: no, we’re like a I guess we’re a great marketing team here because.
500 00:54:35.610 ⇒ 00:54:36.139 Scott_Harmon: So how do you.
501 00:54:36.140 ⇒ 00:54:38.859 YvetteRuiz: Love to pass this to the, to our team.
502 00:54:38.860 ⇒ 00:54:39.270 Uttam Kumaran: Okay.
503 00:54:39.270 ⇒ 00:54:42.320 YvetteRuiz: To do a vote, and I could have it by next Friday. We’ll just do a quick.
504 00:54:42.320 ⇒ 00:54:43.329 Uttam Kumaran: Yeah, if you need like.
505 00:54:43.330 ⇒ 00:54:46.413 Uttam Kumaran: Oh, so if you need our help to facilitate that
506 00:54:46.710 ⇒ 00:54:47.330 YvetteRuiz: Okay.
507 00:54:47.330 ⇒ 00:55:04.319 Uttam Kumaran: Anything like I I’m we’re happy to just let me know or I mean, people can use AI and go generate their own. That could be fun, too. But I yeah, we I don’t know. I think, Amber. Maybe you can take that as a note and event. However, we can help facilitate that and get the results. We can create a Google.
508 00:55:04.320 ⇒ 00:55:04.850 YvetteRuiz: Okay.
509 00:55:04.850 ⇒ 00:55:05.750 Uttam Kumaran: Something.
510 00:55:06.410 ⇒ 00:55:11.539 Scott_Harmon: And then, if you’re gonna do that, do the contest, let us know which one you like, and then
511 00:55:11.810 ⇒ 00:55:17.889 Scott_Harmon: usually, if there’s a marketing person somewhere. They’ll have a color palette of
512 00:55:18.080 ⇒ 00:55:20.779 Scott_Harmon: approved ABC colors that you can.
513 00:55:20.780 ⇒ 00:55:21.380 YvetteRuiz: Yeah.
514 00:55:21.820 ⇒ 00:55:25.670 Scott_Harmon: So it’s using the right, you know, it doesn’t clash with a you know other ABC stuff.
515 00:55:25.670 ⇒ 00:55:26.650 Scott_Harmon: Okay, very good.
516 00:55:26.650 ⇒ 00:55:29.640 Scott_Harmon: Just get the color palette, and we’ll generate it for you.
517 00:55:30.630 ⇒ 00:55:50.060 YvetteRuiz: What I’ll do is after this. I’ll email our marketing person less. And then just let them know what we’re we’re working on. Then we can get that. And then, yeah, if you guys can help me put the I mean, we’ve done it before with the whole contest stuff so we can either do it. But if I mean I if you guys do, it’d be really cool, too, because
518 00:55:50.060 ⇒ 00:56:01.302 YvetteRuiz: our company meetings next Thursday. So if we can, you know, kind of make that announcement. Look, here’s our new picture or future picture of our AI Bot.
519 00:56:02.480 ⇒ 00:56:05.100 Scott_Harmon: Okay, send it color palette, and then tell us.
520 00:56:05.210 ⇒ 00:56:10.110 Scott_Harmon: give us a thumbs up, and then we’ll make sure. We company meeting on Thursday.
521 00:56:13.200 ⇒ 00:56:14.570 Amber Lin: I’m noting that tab.
522 00:56:19.460 ⇒ 00:56:20.190 Amber Lin: Yeah.
523 00:56:20.470 ⇒ 00:56:22.410 Scott_Harmon: Well, great great progress.
524 00:56:22.410 ⇒ 00:56:27.120 Amber Lin: Down our contact information, I think. Oh, what is this?
525 00:56:27.330 ⇒ 00:56:43.620 Amber Lin: I think you guys would have this in your Pdf, as well. So if you guys want to email any of us or get in touch, I’ll be the main point of contact from now on, because I’m taking that over from, and we’ll be in touch soon.
526 00:56:43.900 ⇒ 00:56:46.079 Amber Lin: Welcome aboard, Amber.
527 00:56:46.080 ⇒ 00:56:47.280 JanieceGarcia: Welcome!
528 00:56:47.280 ⇒ 00:56:48.009 Amber Lin: It seems like a.
529 00:56:48.490 ⇒ 00:56:49.450 YvetteRuiz: You amber.
530 00:56:50.310 ⇒ 00:56:51.230 Amber Lin: Okay.
531 00:56:51.590 ⇒ 00:56:51.930 JanieceGarcia: Love it.
532 00:56:51.930 ⇒ 00:56:54.525 YvetteRuiz: Forward to to working with you, Miss Amber.
533 00:56:55.280 ⇒ 00:56:57.961 Amber Lin: I look forward to work with you both too.
534 00:56:58.626 ⇒ 00:57:03.389 Scott_Harmon: Can I get you to stay on just for a second, just for.
535 00:57:03.390 ⇒ 00:57:05.760 Uttam Kumaran: I have to. We have a company. I have to jump.
536 00:57:05.760 ⇒ 00:57:08.499 Scott_Harmon: Oh, it’s top of the hour. Okay, I’ll catch up with you later.
537 00:57:08.500 ⇒ 00:57:09.950 Uttam Kumaran: Okay. Okay. Thank you.
538 00:57:10.180 ⇒ 00:57:10.610 Scott_Harmon: Okay.
539 00:57:10.980 ⇒ 00:57:12.619 YvetteRuiz: Bye, guys, happy. Friday.
540 00:57:13.100 ⇒ 00:57:13.850 Amber Lin: Bye, guys.
541 00:57:13.850 ⇒ 00:57:14.890 Uttam Kumaran: Bye.