Meeting Title: Brainforge x ABC Home and Commercial: Weekly Project Check Date: 2025-08-28 Meeting participants: read.ai meeting notes, MattBurns, Amber Lin, Samuel Roberts, Uttam Kumaran, JanieceGarcia, Steven, YvetteRuiz
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1 00:01:30.960 ⇒ 00:01:34.450 Amber Lin: That doesn’t that… he counters me. He has ult. He kills me.
2 00:01:35.090 ⇒ 00:01:36.239 Amber Lin: Hi, Matt!
3 00:01:36.470 ⇒ 00:01:38.459 MattBurns: Hi, Amber, how are you today?
4 00:01:38.460 ⇒ 00:01:40.370 Amber Lin: I’m good, nice haircut!
5 00:01:42.020 ⇒ 00:01:45.390 MattBurns: It’s too hot to have long hair, right?
6 00:01:45.390 ⇒ 00:01:52.649 Amber Lin: No, I know too, I… last summer, I also buzzed my head, and now it has grown back, so I feel you.
7 00:01:53.550 ⇒ 00:01:57.880 MattBurns: Well, good. Utam, hello?
8 00:01:57.880 ⇒ 00:01:59.100 Uttam Kumaran: Hey, how are ya?
9 00:01:59.600 ⇒ 00:02:01.440 MattBurns: Doing good, doing good. How are you doing?
10 00:02:01.880 ⇒ 00:02:02.760 Uttam Kumaran: Good.
11 00:02:03.280 ⇒ 00:02:04.930 Uttam Kumaran: Doing well.
12 00:02:04.930 ⇒ 00:02:10.279 MattBurns: I know Yvette is in Austin today, so hopefully she will be with us shortly.
13 00:02:10.280 ⇒ 00:02:11.799 Uttam Kumaran: Oh, great, okay.
14 00:02:12.260 ⇒ 00:02:19.320 Uttam Kumaran: Yeah, I need to stop… I need to stop by, maybe I’m gonna… I was gonna ask her today if I could stop by next week sometime, or when she’s back in town.
15 00:02:21.330 ⇒ 00:02:23.680 MattBurns: Janiece, do you know, is Yvette gonna join us today?
16 00:02:23.680 ⇒ 00:02:28.509 JanieceGarcia: Yes, she is. Yes, sir. We, both just hopped out of another meeting, so she’s.
17 00:02:28.510 ⇒ 00:02:29.519 Amber Lin: I bet.
18 00:02:29.650 ⇒ 00:02:30.400 Amber Lin: She’s here.
19 00:02:30.610 ⇒ 00:02:31.519 JanieceGarcia: Oh, there she is.
20 00:02:32.010 ⇒ 00:02:33.580 YvetteRuiz: I am.
21 00:02:36.030 ⇒ 00:02:38.509 Amber Lin: Hi, have you guys met Sam before?
22 00:02:39.140 ⇒ 00:02:40.260 MattBurns: I haven’t.
23 00:02:40.350 ⇒ 00:02:42.250 JanieceGarcia: I thought he was in our last one.
24 00:02:42.250 ⇒ 00:02:46.019 Samuel Roberts: I was on the… yes, yes, I believe I was. I met a few of you, but….
25 00:02:46.020 ⇒ 00:02:47.000 YvetteRuiz: Did I meet you?
26 00:02:47.000 ⇒ 00:02:47.500 Samuel Roberts: through you?
27 00:02:47.500 ⇒ 00:02:49.230 YvetteRuiz: Was I in that meeting?
28 00:02:49.500 ⇒ 00:02:49.820 Samuel Roberts: I mean.
29 00:02:49.820 ⇒ 00:02:51.170 JanieceGarcia: We were on PPO, actually.
30 00:02:51.170 ⇒ 00:02:54.299 YvetteRuiz: Okay. I was like, I don’t remember, Sam, I’m sorry.
31 00:02:54.300 ⇒ 00:02:55.359 Samuel Roberts: That’s okay, that’s okay.
32 00:02:57.260 ⇒ 00:03:08.480 Amber Lin: Yeah, Sam’s leading our, AI and automations team, so he will be, providing high-level insight and supporting our efforts, so I want him here as well.
33 00:03:09.340 ⇒ 00:03:10.010 YvetteRuiz: That’s it.
34 00:03:10.010 ⇒ 00:03:11.060 MattBurns: Excellent.
35 00:03:11.060 ⇒ 00:03:21.240 Amber Lin: Yeah. I can start off with our presentation today. I know Utam wanted to talk about… oops, sorry.
36 00:03:21.440 ⇒ 00:03:25.399 Amber Lin: I know Ujam wanted to talk about the 8x8.
37 00:03:25.840 ⇒ 00:03:27.390 Amber Lin: Stuff first.
38 00:03:27.390 ⇒ 00:03:28.360 Uttam Kumaran: ES.
39 00:03:28.360 ⇒ 00:03:37.169 Amber Lin: pop in a bit, and then we can… and then I have a few things on my agenda I just want to show. Also, Sam will demo the, …
40 00:03:37.390 ⇒ 00:03:53.980 Amber Lin: one of the non-Google chat-based UIs, so that one will have more capabilities than currently what we have, so we want to show that to you guys. But let’s… I’ll let Utam need the first part on this discussion.
41 00:03:54.310 ⇒ 00:03:58.109 Uttam Kumaran: Yeah, I guess, I didn’t have a chance to chat with you last week, so I wanted.
42 00:03:58.110 ⇒ 00:03:58.480 YvetteRuiz: I know.
43 00:03:58.480 ⇒ 00:04:18.130 Uttam Kumaran: maybe… maybe even tomorrow, if you even have, like, 30 minutes, or sometime next week, I can grab time. One, yeah, just want to sort of walk through, sort of what, like, some of the AI features you’re seeing in 8x8 are, and then also maybe get, you know, a contact from their side, or whoever we’ve been working with. I can start to…
44 00:04:18.130 ⇒ 00:04:20.859 Uttam Kumaran: Explore, like, what options we have.
45 00:04:20.860 ⇒ 00:04:21.540 YvetteRuiz: Okay.
46 00:04:21.540 ⇒ 00:04:25.390 Uttam Kumaran: So yeah, that’s probably it. Just wanted to see if you have… if you have times to….
47 00:04:25.390 ⇒ 00:04:25.780 YvetteRuiz: I….
48 00:04:25.780 ⇒ 00:04:26.960 Uttam Kumaran: To chat through that.
49 00:04:27.180 ⇒ 00:04:35.239 YvetteRuiz: Yes, and I’m sorry, I have not been able to connect with you. So I’m off tomorrow, but if you’re available Tuesday, I could work it in on Tuesday, Udom.
50 00:04:35.410 ⇒ 00:04:36.610 Uttam Kumaran: Let’s do Tuesday, okay?
51 00:04:36.610 ⇒ 00:04:37.390 YvetteRuiz: Okay.
52 00:04:37.390 ⇒ 00:04:40.569 Uttam Kumaran: I just gotta look at my calendar, ….
53 00:04:40.570 ⇒ 00:04:41.690 YvetteRuiz: Very, like….
54 00:04:42.070 ⇒ 00:04:48.319 Uttam Kumaran: Please, yeah, you can send me… just send me any times that work with you, and then I can book that. Afternoon is… looks like it’s best for me.
55 00:04:49.220 ⇒ 00:04:54.850 YvetteRuiz: It’s probably open for me in the afternoon, too. Okay, I can do that. I’ll send you… Times.
56 00:04:55.920 ⇒ 00:04:57.110 YvetteRuiz: Thank you.
57 00:04:58.180 ⇒ 00:04:58.920 Uttam Kumaran: Perfect.
58 00:04:59.500 ⇒ 00:05:00.270 Amber Lin: Okay.
59 00:05:00.400 ⇒ 00:05:06.529 Amber Lin: That’s fast. I’m gonna… I thought there was gonna be a discussion here, so….
60 00:05:06.530 ⇒ 00:05:15.509 Uttam Kumaran: No, I don’t know, it’ll take up the whole call, so I just… I just want to make sure I can get time, and I have some questions, so we’ll report back to everybody.
61 00:05:15.510 ⇒ 00:05:17.219 Amber Lin: Okay, sounds good. Thank you.
62 00:05:17.220 ⇒ 00:05:17.660 YvetteRuiz: Thank you.
63 00:05:17.660 ⇒ 00:05:30.230 Amber Lin: This part, Sam is gonna lead, so, we talked about this, I think, a week or so ago, and we built something, that’s not in Google Chat that might have a bit more capabilities than
64 00:05:30.270 ⇒ 00:05:43.939 Amber Lin: what we have currently in Andy, especially now that we have, if we want to have real-time feedback, like, with the transcripts, this is something that we might have to switch to, so I’ll let Sam, demo this real quick. Sam, feel free to share screen.
65 00:05:55.960 ⇒ 00:05:57.369 YvetteRuiz: I think he might be mute it.
66 00:05:57.890 ⇒ 00:05:59.439 MattBurns: It’ll last 30 minutes.
67 00:05:59.440 ⇒ 00:06:01.360 Samuel Roberts: Sorry about that, yep, I’m talking to myself as I’m getting.
68 00:06:01.360 ⇒ 00:06:03.070 Uttam Kumaran: Oh, I forget.
69 00:06:03.070 ⇒ 00:06:04.729 Samuel Roberts: Let me get this over here so you aren’t missing.
70 00:06:06.150 ⇒ 00:06:13.270 Samuel Roberts: But basically, what I had, what I’ve done here is we’re looking at, this tool called CopilotKit. I believe some of you may have, got an update on this.
71 00:06:13.280 ⇒ 00:06:26.439 Samuel Roberts: Previously, but basically it’s its own, you know, chat UI here. And what I’ve done here is basically just, like, plugged it in to the N8N workflows, that we have. So, …
72 00:06:26.540 ⇒ 00:06:36.859 Samuel Roberts: it is a little more than Google Chat. We’re obviously doing our own chat when we can style it and do all kinds of things to… but what we can also do, I’m trying to think what a good…
73 00:06:36.920 ⇒ 00:06:47.950 Samuel Roberts: Question here is, what can we do? So this is, right now, basically the same thing. But what we can eventually do, and I should have got that page out, fortunately, but, …
74 00:06:48.150 ⇒ 00:06:49.830 Samuel Roberts: Is tie this into…
75 00:06:51.430 ⇒ 00:07:00.900 Samuel Roberts: Yeah, okay. That’s not helpful right now. I apologize. I didn’t have any, prepped, like, questions, because I’m not, used to testing this right now. But, …
76 00:07:01.050 ⇒ 00:07:08.619 Samuel Roberts: Yeah, this is… this is basically a little more… what’s the word I want to use here? Flexible, customizable, …
77 00:07:08.980 ⇒ 00:07:14.200 Samuel Roberts: it allows us to provide it with more feedback here, like, you can see, like, I can…
78 00:07:14.620 ⇒ 00:07:20.880 Samuel Roberts: respond to it, I can do a few more things. We have complete control over this… this UI as well. …
79 00:07:21.220 ⇒ 00:07:29.889 Samuel Roberts: And so, I’m trying to see if I have anything from the history here that I can run real quick. Does anybody know what a good question is here?
80 00:07:29.890 ⇒ 00:07:31.680 Uttam Kumaran: I could just ask about, like.
81 00:07:31.810 ⇒ 00:07:35.859 Uttam Kumaran: Tell me about, like, recent policies, or tell me about any policy.
82 00:07:39.710 ⇒ 00:07:45.370 Samuel Roberts: Let’s see what it does. So, … Yeah.
83 00:07:45.970 ⇒ 00:07:49.659 Samuel Roberts: It’s a little slow, because of the way I have it set up currently, but …
84 00:07:50.330 ⇒ 00:07:54.470 Samuel Roberts: I didn’t feed it that. Okay, let me jump around. I apologize.
85 00:07:55.580 ⇒ 00:07:56.700 Samuel Roberts: One second.
86 00:07:56.700 ⇒ 00:08:11.379 Uttam Kumaran: Yeah, so maybe, Sam, while you pull up a couple examples, the, sort of the… what we were pitching last time is, like, okay, there’s probably some improvements to having something, that is standalone, right? Like, the Google Chat worked, and I think it gave us this fast-paced
87 00:08:11.410 ⇒ 00:08:27.929 Uttam Kumaran: way to get adoption. But we can’t do helpful things like, share exactly where in the central doc, information is. For example, like, having very clear references. I think, Sam, even there’s… we have a contextual demo.
88 00:08:27.930 ⇒ 00:08:30.339 Samuel Roberts: That’s the one I’m pulling up right now that I, … Cool.
89 00:08:30.510 ⇒ 00:08:32.460 Samuel Roberts: So there’s an ability to, like….
90 00:08:32.460 ⇒ 00:08:50.159 Uttam Kumaran: Yeah, to just look at… look at the exact reference of where it is in a document. Second, helpful features like speech-to-text, or having always-listening features. For example, while a CSR is talking to somebody, the AI could potentially listen in on the call and
91 00:08:50.160 ⇒ 00:09:03.989 Uttam Kumaran: dynamically pop things up to share with them. You know, so it’s a little bit of a broader… we have just a broader set of UI features that we can do. So yeah, this, like, just click on any of these, and additionally, like, even some of these features, like.
92 00:09:04.020 ⇒ 00:09:08.190 Uttam Kumaran: These suggested messages that pop up at the bottom.
93 00:09:08.500 ⇒ 00:09:13.970 Uttam Kumaran: These are all opportunities for us to continue to add and just make the whole tool easy.
94 00:09:14.080 ⇒ 00:09:24.840 Uttam Kumaran: This is a demo that we share with some folks, and basically what you can do is, what you’re seeing is the AI actually links to the exact part of the document where.
95 00:09:24.840 ⇒ 00:09:25.290 YvetteRuiz: Oh, God.
96 00:09:25.290 ⇒ 00:09:26.929 Uttam Kumaran: From, and highlights it.
97 00:09:27.150 ⇒ 00:09:39.369 Uttam Kumaran: So you can see it’s summarized, right? So this is a… this is an example of, like, a lot of our… we just put in a bunch of fake contracts, but you could tell that the AI not only responds, but actually has a reference.
98 00:09:39.370 ⇒ 00:09:54.199 Uttam Kumaran: right back to where the document is, and it highlights. So that’s really, really powerful, because, you know, sometimes you ask a question, you get an answer, but you want to see the surrounding information, or see the source of truth. This is a great way. But of course, doing this in Google Chat is.
99 00:09:54.200 ⇒ 00:09:54.710 YvetteRuiz: Yep.
100 00:09:54.710 ⇒ 00:09:56.460 Uttam Kumaran: Really, really difficult, you know?
101 00:09:57.350 ⇒ 00:10:11.659 YvetteRuiz: Gotcha. Ucham, so… okay, so that’s… I just wanted clarity on this. So, you’re just talking about, instead of going through the Google Chat the way we have it set up currently, this would be the tool that we could ultimately use to get… gather more information.
102 00:10:12.050 ⇒ 00:10:31.460 Uttam Kumaran: Yeah, this is more about, like, when a CSR asks a question, how can we give them all of the information that they may need? Whether it is the AI answering, or it is a link to the doc, you know, and so doing that in a more broader environment. The Google Chat works, but also there’s also helpful features like
103 00:10:31.460 ⇒ 00:10:47.480 Uttam Kumaran: We can suggest follow-up questions to answer, and again, things like if we want to listen into the text, if we want to pull in 8x8 data directly into this page, those are all things that we can’t accomplish via just the Google Chat window right now.
104 00:10:48.250 ⇒ 00:10:52.030 Steven: So where does this live? It’s just a web page?
105 00:10:52.330 ⇒ 00:11:05.519 Uttam Kumaran: Yeah, so, again, this is just… we’re sort of all brainstorming. I think, what I kind of told the team is, like, look, I think we’re… we’re at kind of the peak of what we can do with Google Chat. If we want to start to level up and… and…
106 00:11:05.520 ⇒ 00:11:18.029 Uttam Kumaran: you know, Yvette talked a little bit about, can we integrate some data from 8x8, can we do some of the AI voice stuff? This would live in its own website, so we’d probably work with Tim and see if we could host this on the ABC’s domain.
107 00:11:18.030 ⇒ 00:11:28.779 Uttam Kumaran: But yes, it would be something that you could log in and access, but it would be a standalone website. So the friction here is, because it’s a standalone website, it would be another thing to do.
108 00:11:28.890 ⇒ 00:11:34.120 Uttam Kumaran: But, you know, ideally, if we do kind of go down this path, there would be such a
109 00:11:34.300 ⇒ 00:11:41.459 Uttam Kumaran: a level of… there’d be some more rich features here that you could still access it in Google Chat, or you could access it here.
110 00:11:43.600 ⇒ 00:11:48.310 JanieceGarcia: I do have an idea, because if we went this way, Yvette.
111 00:11:48.520 ⇒ 00:11:51.490 JanieceGarcia: Then they wouldn’t be pulling up the central dock, right?
112 00:11:52.280 ⇒ 00:11:54.229 JanieceGarcia: They wouldn’t have to chat
113 00:11:54.760 ⇒ 00:12:02.010 JanieceGarcia: As much, so they’re just leaving their email up in regards to their emails that come through that, you know, we all send.
114 00:12:02.450 ⇒ 00:12:08.139 JanieceGarcia: And this could… could this go to the ABC Pest NPS website?
115 00:12:08.870 ⇒ 00:12:16.800 JanieceGarcia: or the ABCMPS website, to where now there’s not only the pest protocols and all of that, but now you have this.
116 00:12:17.180 ⇒ 00:12:21.949 JanieceGarcia: that actually kind of integrates, so I’m… I… I like….
117 00:12:22.500 ⇒ 00:12:25.420 YvetteRuiz: what ties it all together, it’s kind of like… Exactly.
118 00:12:25.840 ⇒ 00:12:44.460 Steven: Yeah, and I like, you know, because I was just thinking about bringing this up, you know, further down the road, again, I know we’re doing mechanical and got a lot going on, I want to focus on that, but ultimately bringing in the technicians and or, you know, one of the easy ones was the HR handbook. Like, that would be a lot easier from here, and then also on technicians, you could put
119 00:12:44.480 ⇒ 00:12:58.799 Steven: you know, an app or a homepage on their phone, they click on, and they can ask it, you can even ask Andy, or whatever you want, that they can ask the HR questions, or their policy questions, SOP, and then they could bring it up for them, versus in chat.
120 00:12:58.800 ⇒ 00:13:05.600 Steven: you know, chat one, it doesn’t bring up a chat, it just… interface isn’t as good. Plus, yeah, there are so many different chats going on.
121 00:13:05.920 ⇒ 00:13:07.830 JanieceGarcia: I don’t know, I can get a little mud, so….
122 00:13:07.830 ⇒ 00:13:08.520 YvetteRuiz: Yep.
123 00:13:08.960 ⇒ 00:13:10.400 Uttam Kumaran: Yeah, the additional thing is history.
124 00:13:10.400 ⇒ 00:13:11.250 JanieceGarcia: issue.
125 00:13:11.280 ⇒ 00:13:11.750 Steven: Yeah.
126 00:13:11.750 ⇒ 00:13:18.930 Uttam Kumaran: Yeah, you’re totally right. That’s, you know, something that I think we should also list out, is you can start to see a history of other people’s chats.
127 00:13:18.990 ⇒ 00:13:35.049 Uttam Kumaran: So, whether we tag those, or you have… you know, there’s just… it’s just a little bit bigger of a sort of a shift. I don’t think we need to… this has to be, like, a replacement, necessarily, but I think as we start to evolve and want to add more features, we’re kind of hitting the limits of what we can do.
128 00:13:35.270 ⇒ 00:13:37.630 Uttam Kumaran: just within the Google Chat little window.
129 00:13:38.080 ⇒ 00:13:45.760 YvetteRuiz: Yeah, makes sense. And I’m sorry, Udom, he said it… this could also be the speech. Can you tell me… can you say that again? The voice….
130 00:13:45.760 ⇒ 00:13:50.680 Uttam Kumaran: Yeah, so… so one thing that we’re thinking about, is…
131 00:13:50.920 ⇒ 00:14:00.559 Uttam Kumaran: and this is where, like, I just need to call the people at 8x8 and see what’s possible. I didn’t see it directly in the API, but there’s sort of, like, one version which is, hey, while, while,
132 00:14:00.680 ⇒ 00:14:13.809 Uttam Kumaran: CSR is on a call, this application could just listen to their side of the call and suggest helpful things, right? So if they’re, like, saying, oh, it seems like your problem is this, the AI would listen.
133 00:14:13.870 ⇒ 00:14:23.800 Uttam Kumaran: maybe suggest dynamically questions to answer, right? As we’ve talked about time and time again, the limiting factor is actually asking Andy the right question.
134 00:14:23.800 ⇒ 00:14:37.990 Uttam Kumaran: And so, those are the things that we want to try to get better on. In an ideal world, you know, I could either… hopefully, you know, we’ll see is maybe I can get the live audio feed from 8x8 directly, and then you have kind of both sides of the conversation.
135 00:14:37.990 ⇒ 00:14:46.430 Uttam Kumaran: what we want the AI to do is, while the CSR’s on the call, start to pop up with, like, hey, maybe this is actually more important to reference.
136 00:14:46.430 ⇒ 00:14:56.250 Uttam Kumaran: You know, there’s also other things, you know, you could use… we could start to do, which is providing the CSR with information about their past calls, you know.
137 00:14:56.410 ⇒ 00:15:04.939 Uttam Kumaran: there’s just a host we can… of course, if we go this route, we’ll also probably put the dashboard within this, too. So, there’s just some benefits there, as well.
138 00:15:05.380 ⇒ 00:15:22.349 YvetteRuiz: Okay, yeah, I really like that. I mean, we were talking earlier, I was talking to Matt, and then we were talking about more of, again, the cancellation piece of it, you know, something that can really, you know, get those key phrases, you know, if they’re moving, okay, what are the suggestions? That stuff automatically pops up for them here, and kind of guiding them through that conversation.
139 00:15:24.970 ⇒ 00:15:26.579 YvetteRuiz: I was looking…
140 00:15:30.110 ⇒ 00:15:37.060 YvetteRuiz: Sorry, Udom, I was trying to see… I had a meeting next week with 8x8, and I was going to say maybe you can also join in on that meeting.
141 00:15:37.320 ⇒ 00:15:39.900 Uttam Kumaran: Oh yeah, you can feel free to toss me in there.
142 00:15:40.330 ⇒ 00:15:45.370 YvetteRuiz: Yeah, I’m sorry, I was looking at my schedule to kind of see what day it was, but I’m not finding it.
143 00:15:46.500 ⇒ 00:15:49.550 YvetteRuiz: Okay. So, no, I really like this.
144 00:15:50.830 ⇒ 00:15:57.189 Uttam Kumaran: Yeah, so it’s something I think if you guys think it’s, like, a good direction, I think one thing I’m gonna work with Sam on is….
145 00:15:57.680 ⇒ 00:16:02.299 Uttam Kumaran: Thinking through, like, what the level of effort is here.
146 00:16:02.620 ⇒ 00:16:18.669 Uttam Kumaran: you know, for us, I think, you know, and this is something probably, Matt, we can talk about whether this falls in scope with what we, you know, are currently working on. I think Amber will sort of chat today, and I think, Steven, you’ll be interested in seeing some of the growth that we’ve had overall in the usage.
147 00:16:18.670 ⇒ 00:16:33.450 Uttam Kumaran: And so for us, you know, on our side, it’s like, I’m happy to continue investing as long as we’re… we’re seeing that growth, and we can start to hit some of the higher tiers, but that’s something maybe once I get an estimate, if it’s gonna take quite a bit longer to develop, maybe, Matt, we can chat and see
148 00:16:33.500 ⇒ 00:16:45.710 Uttam Kumaran: what we can piece off, but yeah, that’s… that’s probably it for today, I think. If there’s any questions, you know, I think probably for next week we can come with a little bit of a plan on, like, what we could do here.
149 00:16:45.820 ⇒ 00:16:47.589 Uttam Kumaran: If we’re all comfortable with that.
150 00:16:49.430 ⇒ 00:16:51.009 MattBurns: network, so it’ll IQ.
151 00:16:51.420 ⇒ 00:16:52.470 Uttam Kumaran: Okay, thank you.
152 00:16:57.050 ⇒ 00:16:59.279 Uttam Kumaran: Cool, Amber, you can take it back over, yeah.
153 00:16:59.280 ⇒ 00:17:00.110 YvetteRuiz: Sorry.
154 00:17:00.480 ⇒ 00:17:05.589 Amber Lin: Awesome. Let me share screen right here.
155 00:17:08.970 ⇒ 00:17:12.959 Amber Lin: So, as usual, starting with the usage.
156 00:17:13.230 ⇒ 00:17:31.780 Amber Lin: Last week we saw… so last week we saw the highest user ever, so we saw 700 sessions in total, which is about, 77% of our goal. This week in particular, because we… it’s only been a week since the last session.
157 00:17:31.780 ⇒ 00:17:38.139 Amber Lin: This week in particular, we’re seeing a little bit of a dip in usage. We’re seeing about 230.
158 00:17:38.140 ⇒ 00:17:44.980 MattBurns: And I was trying to see what the reason was for this dip in usage. I was looking at each person, and if.
159 00:17:44.980 ⇒ 00:17:47.860 Amber Lin: usage has declined, and I think…
160 00:17:48.550 ⇒ 00:17:52.930 Amber Lin: It’s because we’re seeing a few declines from the main
161 00:17:53.200 ⇒ 00:18:02.559 Amber Lin: From those who was leading usage forward, so we’re seeing a little bit of decline from Brian, some… some decline from the past users.
162 00:18:02.800 ⇒ 00:18:12.159 Amber Lin: And I’m probably a little bit from lead line, because I’m looking here, and it seems like, maybe Natalie, very Deanna, and then…
163 00:18:12.510 ⇒ 00:18:24.270 Amber Lin: So they’re from… maybe Lewis, they’re probably from the Leadline team, and then we have a few declines on the S team? I was wanting to ask about this, because I know this week…
164 00:18:24.410 ⇒ 00:18:38.739 Amber Lin: I asked Denise on Wednesday on a working session. I don’t think we had a CSR working session, and I just want to see what you guys think is the decline usage, because we did have a lot,
165 00:18:39.190 ⇒ 00:18:40.610 Amber Lin: In the previous week.
166 00:18:40.610 ⇒ 00:18:41.160 MattBurns: And we’re.
167 00:18:41.160 ⇒ 00:18:52.099 Amber Lin: almost at a target, and then this week we were not as close, so I was wondering what the reason might be, because it seems that we’re able to do it, but we didn’t… we didn’t hit the target this week.
168 00:18:53.380 ⇒ 00:18:59.590 YvetteRuiz: So, working sessions this week, our teams are doing trainings right now, so we’re gearing up for,
169 00:18:59.630 ⇒ 00:19:10.240 YvetteRuiz: there’s a lot of different trainings going on. One’s our overflow training, but… and they’re doing live monitoring calls right now. And we have porch pumpkins that we’re getting rolled out, so that’s…
170 00:19:10.240 ⇒ 00:19:25.950 YvetteRuiz: We’re meeting with a lot of agents regarding that, so we had a lot of different meetings that we’ve been having with our agents, this past week. And we killed… Makes sense. We did not have those sessions because we needed to, coordinate all that.
171 00:19:26.830 ⇒ 00:19:31.900 Amber Lin: I see, that makes sense. So maybe the decline, is from…
172 00:19:32.680 ⇒ 00:19:41.429 Amber Lin: Because I… most of it is from with more experienced people, from the PEST team. Maybe they were part of the training of.
173 00:19:41.430 ⇒ 00:19:43.329 YvetteRuiz: They were all part of that training, yeah.
174 00:19:43.330 ⇒ 00:19:43.949 Amber Lin: Makes sense.
175 00:19:44.310 ⇒ 00:19:58.669 Amber Lin: Okay, that’s good to know. So we’ll… we know that overall, people are more inclined to use it, it’s just the, the top users are those more… somehow are those more experienced users. I think they do see the benefit.
176 00:19:58.670 ⇒ 00:20:01.409 YvetteRuiz: Of Andy, which I’m happy to see.
177 00:20:01.410 ⇒ 00:20:02.490 Amber Lin: ….
178 00:20:04.690 ⇒ 00:20:22.179 YvetteRuiz: And Janice, I’m sorry, what… we agreed that once we get the working sessions, we were going to start working with the, like, mechanical, home improvement, and lawn, right? Because I feel like we’ve already gone down the line with most pest agents. Correct. Now we’re going to start working with the other divisions.
179 00:20:22.180 ⇒ 00:20:33.629 Amber Lin: I wanted to ask that, too, if next week, I wanted to schedule a call with Mechanical to see if they… they think it’s ready to roll out, because we’ve been in…
180 00:20:33.630 ⇒ 00:20:45.100 Amber Lin: testing and improvements the whole last week and a little bit of the week before. Tara’s using the ticketing system, so every feedback that comes in, she’s able to see that and be able to make the updates.
181 00:20:45.100 ⇒ 00:20:52.070 Amber Lin: I’ve asked our team to improve how Andy responds to those based on those feedback, but I do think
182 00:20:52.070 ⇒ 00:21:10.690 Amber Lin: The central dog might still miss a few things. I really wanted to check with them if they feel confident to roll it out, because we’ve already added all the documents that exist, but maybe sometimes questions come up and they haven’t, seen that before. So maybe next week we can do a working session with the…
183 00:21:10.750 ⇒ 00:21:14.760 Amber Lin: maybe the most experienced mechanical CSRs, and they can gauge?
184 00:21:14.760 ⇒ 00:21:16.570 JanieceGarcia: Okay. On if Andy is ready.
185 00:21:17.460 ⇒ 00:21:18.900 YvetteRuiz: Yeah, we can do that.
186 00:21:19.100 ⇒ 00:21:20.110 Amber Lin: Yeah, awesome.
187 00:21:20.720 ⇒ 00:21:21.450 Amber Lin: Okay.
188 00:21:23.120 ⇒ 00:21:27.769 Amber Lin: So, we’re at the end of August. I think…
189 00:21:28.030 ⇒ 00:21:38.659 Amber Lin: Apart from the training, I want to see next week, maybe if training is not as busy, if usage improves, but I do think we’re quite close to hitting our initial goal of…
190 00:21:38.980 ⇒ 00:21:42.139 Amber Lin: 200… 2,000 sessions per month.
191 00:21:43.060 ⇒ 00:21:48.290 Amber Lin: And so, this week, I wanted to touch upon our main…
192 00:21:48.490 ⇒ 00:21:58.550 Amber Lin: focus this week, so we were working on the zip code database, and we’ll show you how we plan to do that, and what that can enable in a moment.
193 00:21:58.610 ⇒ 00:22:12.070 Amber Lin: Also created the Home Improvement Central doc, so I think of one or two of them I still don’t have access on either account, so I’m just asking Brenda for that. And there’s a, our team is working on incorporating
194 00:22:12.150 ⇒ 00:22:22.309 Amber Lin: Adding a few spreadsheets, so that should be added into ANDI by end of this week, so next week, Home Improvement can start testing and then find out what gaps exist in their documentation.
195 00:22:22.620 ⇒ 00:22:28.150 Amber Lin: This week I also worked with Denise on the feedback, so all the tickets…
196 00:22:28.260 ⇒ 00:22:31.479 Amber Lin: has been assigned an owner, I think…
197 00:22:31.680 ⇒ 00:22:47.209 Amber Lin: already half of them has been completed, and then the rest, I believe, are on track for one week resolution time, because I checked with our… my team today, and then, I make sure that each of them know what they’re taking on, what needs to be edited.
198 00:22:48.070 ⇒ 00:22:49.020 Amber Lin: ….
199 00:22:49.020 ⇒ 00:22:56.080 YvetteRuiz: I’m sorry, Amber, you said that you were missing a couple of documents that weren’t accessible from the home improvement. Is that what I understood?
200 00:22:56.080 ⇒ 00:22:57.629 Amber Lin: Yeah, I already messaged Brenda.
201 00:22:57.630 ⇒ 00:22:58.739 YvetteRuiz: He did, okay.
202 00:22:58.740 ⇒ 00:22:59.250 Amber Lin: Yeah.
203 00:22:59.950 ⇒ 00:23:06.200 Amber Lin: So, Amy, what we aim for for next week is we want to…
204 00:23:06.650 ⇒ 00:23:11.350 Amber Lin: So here is how we want to do the database. So…
205 00:23:11.390 ⇒ 00:23:30.810 Amber Lin: This will… this… the base of this is the zip codes, right? So all of this should be based on the zip codes, and each zip code will… will tell us, okay, is this zip code serviced at all for this service? Who is the technician for that, and who is the inspector, for that zip code?
206 00:23:31.350 ⇒ 00:23:46.779 Amber Lin: So, we’re pulling data, we’re building this based on all the spreadsheets that exist, you know, the service area spreadsheet, the pest directory, the inspector sheets, skills and zips, and ultimately want to connect it together so that
207 00:23:46.780 ⇒ 00:24:00.199 Amber Lin: it’s connected to the Google Form. So, in the Google Form, usually people fill in the name of the inspector, and the area, and the services. So, when we receive that, we want to take that information and
208 00:24:00.200 ⇒ 00:24:09.639 Amber Lin: update the respective fields in the database, and… and when we return the answer with Andy, it’s gonna pull from…
209 00:24:09.720 ⇒ 00:24:21.770 Amber Lin: This database, so it’s easier to maintain and less prone to error than the current spreadsheet, because there’s just so many different tabs to keep track of.
210 00:24:22.960 ⇒ 00:24:30.910 YvetteRuiz: This is very cool, Steven. So what… just kind of a background on the sales piece of it, that’s the form that…
211 00:24:31.420 ⇒ 00:24:43.779 YvetteRuiz: like, Bo and MJ, I don’t know if you filled this one out before, but that’s the Google form that is filled out by you guys, assigning, you know, quadrants, areas, is that correct, Amber? Is that what you’re.
212 00:24:43.780 ⇒ 00:24:44.330 Amber Lin: Nope.
213 00:24:44.330 ⇒ 00:24:48.859 Steven: Yeah. I haven’t used it, but I’ve seen it, I’ve… yeah, I’ve looked at it, so….
214 00:24:48.860 ⇒ 00:24:57.439 YvetteRuiz: Yeah, but that’s gonna be very cool to be able to get that form, and then it autofill these sheets automatically, and that feeds into Andy.
215 00:24:57.610 ⇒ 00:24:58.710 Amber Lin: Yeah, and the best.
216 00:24:58.710 ⇒ 00:24:59.170 YvetteRuiz: Very cute.
217 00:24:59.170 ⇒ 00:25:18.520 Amber Lin: Having it in a database is that we can say for a certain quadrant, say Austin North, we can assign all these zip codes to Austin North, so that right now, CSRs can only look at the image of the zip codes to say, oh, this zip code is next to this one, but in the future, I think we can say,
218 00:25:18.520 ⇒ 00:25:27.339 Amber Lin: this zip code. Okay, this person’s not available. Oh, this code… this one belongs to Austin North, so let’s pull up all the other inspectors
219 00:25:27.340 ⇒ 00:25:34.370 Amber Lin: in Austin North, so that we can have backup. So that’s something that I discussed with Janiece earlier this week as well.
220 00:25:34.720 ⇒ 00:25:38.109 YvetteRuiz: Yeah, yeah, and that’s, again, those meetings that we’ve talked about
221 00:25:38.120 ⇒ 00:25:59.510 YvetteRuiz: Because a lot of the times, what would end up happening is they would see, okay, Steven’s this zip code right here, and they would say he’s booked out for the entire week, and they would book into next week, versus here, they’ll know, like, okay, yes, Steven does cover this area, but then I have these other people that can also cover, so that’s going to stop a lot of stuff for our CSRs.
222 00:25:59.510 ⇒ 00:26:00.210 Amber Lin: Mmm.
223 00:26:02.420 ⇒ 00:26:03.510 YvetteRuiz: ….
224 00:26:03.510 ⇒ 00:26:19.220 Amber Lin: Going back here… so next week, my plan is to check in with Mechanical. We’ll have that working session on Wednesday to see if it’s rollout ready. I’m gonna create the central dock for lawn and add it to Andy, and similarly for home improvement.
225 00:26:19.220 ⇒ 00:26:23.949 Amber Lin: I’ll… I think they will be able to start testing it next week.
226 00:26:24.060 ⇒ 00:26:30.400 Amber Lin: And, … And I think… Yvette, you asked me about transcripts.
227 00:26:30.510 ⇒ 00:26:34.029 Amber Lin: on Monday when we met, and right now, we’re…
228 00:26:34.280 ⇒ 00:26:50.079 Amber Lin: were… I think Utam’s working on the pipeline just to fix some minor issues, and I did a quick sample with, 3 transcripts that I got, so just to see, okay, what are some capabilities we can find with the transcript data.
229 00:26:50.330 ⇒ 00:27:06.539 Amber Lin: And very first is something that we already have using the 8x8 data, so that’s called duration and efficiency. But I think with transcripts, we can relate that number with what are the CSRs spending time talking about.
230 00:27:06.570 ⇒ 00:27:16.570 Amber Lin: So, we can actually benchmark it, make a fair judgment to say that, oh, this is too long, because sometimes they might actually be dealing with a problem.
231 00:27:16.840 ⇒ 00:27:27.299 Amber Lin: And with transcripts, we’ll be able to determine, okay, is this resolved? Usually, if it’s not resolved, there will be a hint in the words that say, oh.
232 00:27:27.650 ⇒ 00:27:30.199 Amber Lin: This issue was still present.
233 00:27:30.310 ⇒ 00:27:37.239 Amber Lin: And, with transcripts, as Sputo mentioned earlier, we can find out more opportunities to
234 00:27:37.460 ⇒ 00:27:43.920 Amber Lin: assist the CSRs and offer them perhaps in real time, or at least after the fact.
235 00:27:45.090 ⇒ 00:27:55.990 Amber Lin: And another thing that I’m not sure if the ABA system does already right now is to classify the different issues. So…
236 00:27:56.400 ⇒ 00:27:58.889 Amber Lin: Right here on the top, …
237 00:27:59.050 ⇒ 00:28:13.389 Amber Lin: When I got the transcript, it already had the titles for Hold It for initial production, but I think with the transcripts, we can classify it even more specifically of what type of service it might be, and also maybe on the urgency of.
238 00:28:13.950 ⇒ 00:28:15.759 Steven: of these issues.
239 00:28:17.830 ⇒ 00:28:27.380 Amber Lin: And I think the third part is pretty, pretty important, especially for revenue, is, okay, is there an upsell opportunity that was missed?
240 00:28:27.520 ⇒ 00:28:40.299 Amber Lin: When we just ask CSRs, sometimes they don’t even know, or sometimes they gloss over it, but with transcripts, we have, a written down evidence of, okay, this was an opportunity.
241 00:28:40.300 ⇒ 00:28:54.280 Amber Lin: This was missed, and then perhaps we can look at it by person or by period. How many was… of all the upsell opportunities that came up, how many people did do it, and how many people succeeded?
242 00:28:54.340 ⇒ 00:29:01.490 Amber Lin: And I think that’s a good metric to hold people accountable, and then that will impact the bottom line.
243 00:29:02.740 ⇒ 00:29:09.870 MattBurns: Yeah, Amber, this is, … As you were talking through some of this, what I’m…
244 00:29:10.770 ⇒ 00:29:15.499 MattBurns: what I’d love to get to, and I know it’s probably early, and maybe we could even do it with
245 00:29:16.100 ⇒ 00:29:18.089 MattBurns: Just the pest team.
246 00:29:19.270 ⇒ 00:29:21.789 MattBurns: But you’d really like to be able to say.
247 00:29:23.440 ⇒ 00:29:26.209 MattBurns: for those that are using ANDI,
248 00:29:28.690 ⇒ 00:29:39.260 MattBurns: We offered more, oh, by the ways. We… saved more… cancellation opportunities. We… …
249 00:29:39.780 ⇒ 00:29:44.760 MattBurns: the efficiency of the call was better, the accuracy of the call was better. You know, some of those are…
250 00:29:45.290 ⇒ 00:29:52.640 MattBurns: somewhat tangible, some of them are a little bit more looking at the transcript, or reading the call, or whatever, but you…
251 00:29:52.990 ⇒ 00:30:01.989 MattBurns: If you, if you can really demonstrate by whatever… Metrics are the most… measurable, or…
252 00:30:02.140 ⇒ 00:30:10.130 MattBurns: Or however we define it, but you’d love to be able to say, here’s my… …
253 00:30:10.580 ⇒ 00:30:14.750 MattBurns: almost my KPI score, for those who use ANDI.
254 00:30:15.280 ⇒ 00:30:17.770 MattBurns: This is the KPI score.
255 00:30:18.020 ⇒ 00:30:21.519 MattBurns: for those who don’t, and actually be able to say.
256 00:30:23.120 ⇒ 00:30:28.399 MattBurns: how much better the call is if they utilize ANDI, for whatever metric we want to…
257 00:30:28.520 ⇒ 00:30:31.579 MattBurns: And we’ve identified some of the more important ones.
258 00:30:32.080 ⇒ 00:30:34.980 MattBurns: But yeah, I feel like you’re…
259 00:30:35.980 ⇒ 00:30:38.360 MattBurns: What you mentioned over the last few minutes is…
260 00:30:38.460 ⇒ 00:30:49.200 MattBurns: It’s going in that direction, which is good, because The more we can demonstrate the helpfulness, the accuracy…
261 00:30:49.370 ⇒ 00:30:52.870 MattBurns: the opportunities, sales opportunities, whatever, the better. So that’s….
262 00:30:52.870 ⇒ 00:30:53.470 YvetteRuiz: Yeah.
263 00:30:53.470 ⇒ 00:30:58.270 MattBurns: I know that’s the goal we all want, because then we can really coach…
264 00:30:58.870 ⇒ 00:31:01.040 MattBurns: Those that are not using it.
265 00:31:01.250 ⇒ 00:31:05.339 MattBurns: To say, well, here’s the results of the people that are using it.
266 00:31:05.710 ⇒ 00:31:08.370 MattBurns: And… Kind of stress the….
267 00:31:08.550 ⇒ 00:31:11.500 YvetteRuiz: The improvements, or the differences, or whatever we want to….
268 00:31:11.500 ⇒ 00:31:13.870 MattBurns: Want to call it, so… Yeah.
269 00:31:13.870 ⇒ 00:31:14.670 Amber Lin: Totally.
270 00:31:14.670 ⇒ 00:31:16.889 MattBurns: Yeah, this is the right direction here, no.
271 00:31:16.890 ⇒ 00:31:20.129 YvetteRuiz: Yeah, absolutely, and she’s pulling, like, all right there, Matt. I mean, the
272 00:31:20.570 ⇒ 00:31:36.249 YvetteRuiz: AHT time, the call resolution. I mean, first… I mean, that’s huge. Someone called in, did we resolve that issue, or was it just left pending out there? And then that cross-selling, so yeah, you’re absolutely right. Those transcripts are going to help a lot to be able to identify.
273 00:31:37.100 ⇒ 00:31:43.560 MattBurns: Yeah, cause you would… again, some of it’s experience, I know some of it’s… …
274 00:31:43.820 ⇒ 00:31:50.009 MattBurns: there’s other factors, but still, you’d love to be able to say the group that’s using Andy is here.
275 00:31:50.390 ⇒ 00:31:54.449 MattBurns: The group that’s not is… is down here. Yeah. Whatever.
276 00:31:55.020 ⇒ 00:31:55.880 Amber Lin: Totally.
277 00:31:55.880 ⇒ 00:31:56.780 MattBurns: And I think….
278 00:31:57.020 ⇒ 00:32:16.700 Amber Lin: what transcripts can help with training is that we can take good calls, especially from more experienced people, and summarize the scripts that they use. I think this will make writing scripts a lot easier, and so here we can check if… so… because AI has all
279 00:32:16.700 ⇒ 00:32:20.689 Amber Lin: the words that one person says, it can check, okay,
280 00:32:20.690 ⇒ 00:32:35.810 Amber Lin: this person confirmed the address, confirmed the phone number, confirmed the time window, and it asked clarifying questions. So I think those are things we can check for if we have an existing framework, which we do, and I think it goes both ways of helping enforce
281 00:32:35.810 ⇒ 00:32:46.729 Amber Lin: our existing training processes, and helps go back to the CSR to say, okay, this is what your successful peers have been doing.
282 00:32:48.530 ⇒ 00:32:49.710 YvetteRuiz: Absolutely.
283 00:32:50.130 ⇒ 00:32:58.330 Amber Lin: And lastly, it just… this is more, I would say it’s more subjective, it’s more sentiment, analysis of… okay.
284 00:32:58.330 ⇒ 00:33:18.099 Amber Lin: Especially for stressed calls, did it get resolved? How was our service? Is our people warm and inviting? Do people enjoy doing business with ABC, or are they calling in frustrated and leaving frustrated? So I think that’s something we can also try to assess. Though AI is going to be limited, because it can’t…
285 00:33:18.350 ⇒ 00:33:24.699 Amber Lin: Monitor the tone yet, because we’re only looking at the transcript, so is that something that we can do as well?
286 00:33:25.540 ⇒ 00:33:26.080 MattBurns: Yup.
287 00:33:26.690 ⇒ 00:33:32.030 Amber Lin: Yeah. … I think that’s all, and…
288 00:33:32.030 ⇒ 00:33:51.219 Amber Lin: eventually, after we get all these insights, we would be able to create a dashboard that has a summarized view of all of this. I think once Utam talks with you about the 8x8 capabilities, we can see what’s already existing, and what we need to build, because there’s no point in investing double effort.
289 00:33:51.220 ⇒ 00:33:57.029 Amber Lin: into that, so, … I’ll see… we’ll see what happens next week after their discussion.
290 00:33:59.010 ⇒ 00:34:00.070 YvetteRuiz: Sounds good!
291 00:34:00.070 ⇒ 00:34:00.400 Amber Lin: Yep.
292 00:34:00.400 ⇒ 00:34:17.979 YvetteRuiz: Well, this is all great stuff. Thank you, Sam, for taking the time to share that with us, and Amber, thank you for getting the… that was a big win on the inspector stuff. I mean, that’s gonna be so much better. That’s… that whole flow. And then the transcript thing, that’s going to be another game changer for us, for sure.
293 00:34:17.989 ⇒ 00:34:26.339 Amber Lin: Yeah, I’ll keep you guys posted. We’re meeting next Monday, I’m meeting Janice next Wednesday, so we’re frequently in touch, so you’ll get all the updates.
294 00:34:27.429 ⇒ 00:34:27.879 YvetteRuiz: Sounds good.
295 00:34:27.880 ⇒ 00:34:28.620 Steven: Yo.
296 00:34:28.620 ⇒ 00:34:29.260 MattBurns: Thank you, guys.
297 00:34:29.880 ⇒ 00:34:31.069 Samuel Roberts: Alright, bye guys!
298 00:34:31.389 ⇒ 00:34:32.449 MattBurns: Bye-bye.