Meeting Title: Brainforge x ABC Home and Commercial_ Weekly Project Check Date: 2025-03-28 Meeting participants: Uttam Kumaran, Amber Lin, Steven, Janiecegarcia, Yvetteruiz
WEBVTT
1 00:01:12.590 ⇒ 00:01:14.458 YvetteRuiz: Hi, amber! How are you doing
2 00:01:14.770 ⇒ 00:01:15.940 JanieceGarcia: Good morning!
3 00:01:16.450 ⇒ 00:01:16.920 Amber Lin: Morning.
4 00:01:16.920 ⇒ 00:01:18.240 YvetteRuiz: Happy. Friday.
5 00:01:18.540 ⇒ 00:01:20.173 Amber Lin: Happy Friday to you, too.
6 00:01:22.030 ⇒ 00:01:25.390 YvetteRuiz: Yes, let’s see my volume up.
7 00:01:28.290 ⇒ 00:01:28.820 Amber Lin: Oh, you fit
8 00:01:28.820 ⇒ 00:01:29.780 YvetteRuiz: My crowd.
9 00:01:29.780 ⇒ 00:01:35.709 Amber Lin: To invite Brian to this meeting as well, so he can get caught up on our processes
10 00:01:36.773 ⇒ 00:01:50.169 YvetteRuiz: Well, that’s I was. I haven’t had a chance to respond. I’m gonna respond to you because I spoke. What I want to do is I? Wanna make sure that I got the right players in here. So Brian’s a key player. But David is is over, Brian. So
11 00:01:50.730 ⇒ 00:01:56.800 YvetteRuiz: I wanna make sure cause right. I just met with. So I’ll circle back with you and kind of give you all the kind of the idea of what I’m thinking
12 00:01:56.800 ⇒ 00:02:08.949 Uttam Kumaran: I agree. And I think we’re probably gonna need this Friday for like Demos. But I think probably something else like I think we have. We have the day to day stuff. I think we’re gonna start to have something around just data. And then probably this meeting
13 00:02:09.410 ⇒ 00:02:13.139 Uttam Kumaran: that’s probably better. Otherwise. Yeah, this meeting. I know we’re gonna just run out of time pretty fast.
14 00:02:13.140 ⇒ 00:02:26.760 YvetteRuiz: Yeah, and that was my goal. My hope you, Tim, is like, Okay, can. And and again, it’s all great to bring all the heads together, but just trying to keep that. So I felt like, maybe it would be better for us to have a meeting with the data team together.
15 00:02:26.760 ⇒ 00:02:27.980 YvetteRuiz: Yes, yeah.
16 00:02:27.980 ⇒ 00:02:30.330 Amber Lin: That’s good. We can
17 00:02:30.330 ⇒ 00:02:36.409 YvetteRuiz: Yeah, they oh, and Steven said, he’s running late. So we just got out of a meeting. So is Scott gonna join
18 00:02:36.660 ⇒ 00:02:41.470 Uttam Kumaran: I think Scott is, he said. He’s in Dallas for the weekend. He may be out
19 00:02:44.340 ⇒ 00:02:45.509 Uttam Kumaran: so maybe not.
20 00:02:47.750 ⇒ 00:02:51.272 YvetteRuiz: So then this is it. No.
21 00:02:52.580 ⇒ 00:02:57.059 Uttam Kumaran: We can get started. I don’t mind, and Steven can kind of join. Let’s just let’s go for it.
22 00:02:57.060 ⇒ 00:03:00.839 Amber Lin: Yeah. And I mean, we have recordings that people can watch too.
23 00:03:01.130 ⇒ 00:03:02.000 YvetteRuiz: Awesome.
24 00:03:02.960 ⇒ 00:03:05.609 Amber Lin: Let’s go to the presentation here.
25 00:03:12.420 ⇒ 00:03:14.970 Amber Lin: Everyone can see my screen. Right? Yeah.
26 00:03:15.130 ⇒ 00:03:15.990 YvetteRuiz: Okay.
27 00:03:17.330 ⇒ 00:03:24.030 Amber Lin: So we’re going to go over mainly 3 things today. So the dashboard.
28 00:03:24.370 ⇒ 00:03:27.879 Amber Lin: the error reporting and then the rollout action plan.
29 00:03:29.260 ⇒ 00:03:31.450 Amber Lin: 1st of all it’s looked. We have
30 00:03:31.630 ⇒ 00:03:43.679 Amber Lin: improved the dashboard significantly. So the visual layout is much better. It’s much more intuitive for the execs to understand what’s most important to them.
31 00:03:45.390 ⇒ 00:04:00.879 Amber Lin: so right here we have the quality score. We have the error rate, the average execution time and the total exchanges, and these allow you to track. How how well the bot responses are.
32 00:04:01.130 ⇒ 00:04:05.000 Amber Lin: and how long it would take, and also
33 00:04:05.360 ⇒ 00:04:08.560 Amber Lin: usage of how much it’s being used.
34 00:04:08.930 ⇒ 00:04:12.429 Amber Lin: And so when we go to the dashboard here?
35 00:04:16.550 ⇒ 00:04:25.280 Amber Lin: Yeah. So if we go to the dashboard here, we’ll be able to see all these different scores.
36 00:04:25.460 ⇒ 00:04:32.150 Amber Lin: and you can go and select each of them to have a further breakdown.
37 00:04:32.360 ⇒ 00:04:38.579 Amber Lin: So I’ll let you guys explore this in more detail. Everything is linked, and
38 00:04:38.760 ⇒ 00:05:00.209 Amber Lin: I will also send you guys the link to this dashboard, it should be the same link as before. But if you guys need, I can send that again, so we can explore that in more detail. And so the next step for us is to fine tune it and make it even even better and more accurate. So we can know. We can extract more information from that
39 00:05:00.840 ⇒ 00:05:15.149 YvetteRuiz: Okay, yeah, I did going ahead. And I save it as I saved it as my favorites. Now, because it’s I’m gonna make it a routine to make sure that I’m in there poking around. So then that way, I get really familiar with it. As long as it’s the same link.
40 00:05:15.530 ⇒ 00:05:18.990 YvetteRuiz: I’m good. I don’t know if you have yours saved, or
41 00:05:18.990 ⇒ 00:05:19.930 Amber Lin: Totally.
42 00:05:19.930 ⇒ 00:05:20.355 YvetteRuiz: Okay.
43 00:05:20.780 ⇒ 00:05:43.270 Amber Lin: And honestly, we’ll start all our weekly meetings from that dashboard, so we’ll able to see how we’re performing this week. How did it compare to last week. And what can we improve on? So actually, here’s an example of what we’re gonna do? Specifically, maybe not in this meeting, but in a lot of our review meetings
44 00:05:43.270 ⇒ 00:05:47.880 Uttam Kumaran: I love. I love this slide. Yeah, I was just looking at it. This is great. Yeah. Sorry. Go ahead.
45 00:05:48.420 ⇒ 00:05:49.210 Amber Lin: So
46 00:05:49.600 ⇒ 00:06:15.529 Amber Lin: we have a pretty good error rate. Right here we have a 16.6 7, especially because we’re testing a lot of the harder questions. Because we know the bots gonna get the basic questions correct. So we’re it’s 16, because there’s a lot of hard questions. But you can see, there’s a trend going up. And we want to know why is it going up? Because that’s really important to us. We want to know if it’s gonna work right? So I went in. And we.
47 00:06:15.530 ⇒ 00:06:27.750 Amber Lin: I saw the different questions they asked and the answers they gave. So 100% or anything more than 0 means that there’s an error. And 0% means that it’s good.
48 00:06:28.450 ⇒ 00:06:29.080 YvetteRuiz: Okay.
49 00:06:29.760 ⇒ 00:06:36.649 Amber Lin: And so when we look at these, we find 2 things. One. Some of these questions answers are correct.
50 00:06:36.770 ⇒ 00:06:47.879 Amber Lin: So it’s on us to make our error measurement more flexible, because sometimes, if it’s just wording issues, we still marked it as an error. But for us to
51 00:06:48.590 ⇒ 00:07:02.219 Amber Lin: be more flexible, understand what’s actually wrong, we’ll have to improve our error measurement. That’s number one. And so number 2 is that some of them are errors because we don’t have the answers
52 00:07:02.750 ⇒ 00:07:17.590 Amber Lin: in our database. So the bot hallucinated. And so that will just identify gaps that we can go in as a team and fix them. So all of these are just pointers for our improvement, and I’ll pause here for
53 00:07:17.690 ⇒ 00:07:19.370 Amber Lin: any questions or input
54 00:07:20.280 ⇒ 00:07:28.500 YvetteRuiz: Okay, yeah, no. Like Udem, said I. I really like this piece right here. So, Janice, have you? Ex, have you? Checked on some of these
55 00:07:28.990 ⇒ 00:07:31.359 JanieceGarcia: These are actually questions that I’ve asked
56 00:07:31.360 ⇒ 00:07:33.549 YvetteRuiz: You were okay. You were the one asking him, okay.
57 00:07:34.251 ⇒ 00:07:52.640 JanieceGarcia: Because I know that for the most part some of these questions were right, but they’re like Amber was saying, it’s wording or the biggest thing for me, too, and I know Eva with us, having rodent season has not ended. I don’t think it’s
58 00:07:52.640 ⇒ 00:07:53.409 JanieceGarcia: thank you.
59 00:07:53.410 ⇒ 00:08:16.009 JanieceGarcia: Yeah, it’s not ever going to but a big thing for me is making sure that we can get the durations in there, and I know that they have information on the durations. But how can we make the bot understand what the durations are for? A specific service doesn’t matter if it’s rodent or termite, you know, those are the ones that are going to be defined, based off of the
60 00:08:16.110 ⇒ 00:08:34.800 JanieceGarcia: amount, the cost right? The actual production cost. So these are things that actually Amber and Miguel and I have a meeting on Monday to talk about the answers, and to really figure all of that out so. And that’s why I was looking forward to our meeting, too, Yvette, because I have. I have notes
61 00:08:35.289 ⇒ 00:08:36.859 YvetteRuiz: Okay, so.
62 00:08:36.860 ⇒ 00:08:37.580 JanieceGarcia: I’m ready
63 00:08:37.740 ⇒ 00:08:53.759 YvetteRuiz: Awesome. Well, thank you for letting me know that. So question Amber once we so like, let’s say, we start testing start asking more new questions and stuff. Are we going to be able to see that week to week? So like we’ll, we’ll have the new questions that we’re finding new errors. We’re not
64 00:08:53.760 ⇒ 00:08:54.080 Amber Lin: To see.
65 00:08:54.080 ⇒ 00:08:56.560 YvetteRuiz: The same thing. What does that look like? Does that get archived
66 00:08:56.560 ⇒ 00:09:00.030 Amber Lin: Oh, so let me go to the next slide
67 00:09:00.030 ⇒ 00:09:01.500 YvetteRuiz: Oh, okay, so.
68 00:09:01.500 ⇒ 00:09:04.890 Amber Lin: On the I mean, we’re on. We’re thinking about the same thing.
69 00:09:05.590 ⇒ 00:09:33.209 Amber Lin: These were aligned. So this is what how we’re gonna re report and review the error. So on the left side is is in slack. So that’s real time. That’s immediate. We’ll get to see what went wrong and why we think that was wrong, and then we can improve that. So we’ll get instant slack alerts in the channel. We can add you guys to the channel. If you guys want but it will be quite a few notifications, as the Csrs ask these questions.
70 00:09:33.210 ⇒ 00:09:53.299 Amber Lin: and on the right side is all of these errors that’s flagged is in a Google sheet. So we’ll be able to go into that sheet and filter. For what type of questions did we get wrong? And so that we can improve or have a session to go over them.
71 00:09:53.660 ⇒ 00:09:56.439 YvetteRuiz: So these are the 2 things that we have.
72 00:09:56.900 ⇒ 00:10:02.060 YvetteRuiz: Gotcha. Hmm, okay. Alright. Well, that makes sense perfect sense. There
73 00:10:02.620 ⇒ 00:10:16.589 Amber Lin: So next, I think I want to put some time on the next important part of rolling out, because ultimately our goal is for the Csr. To use them, and for it to be beneficial
74 00:10:16.590 ⇒ 00:10:27.049 Uttam Kumaran: Amber. I just had one question on the previous slide. So, for this, like, how? Yeah. So the weekly review is that, are you guys just doing that in stand ups right now.
75 00:10:27.550 ⇒ 00:10:28.630 Uttam Kumaran: yeah, is that
76 00:10:28.760 ⇒ 00:10:53.219 Uttam Kumaran: cause I cause what I guess my one of my things. The overarching is one. Our volume is gonna start to go up. And so, of course, like we expect our error like our goal for error rate is no errors. But there will, there will constantly be some, especially as we start to get the volume up. And so one of the things I just want to know is like, Okay, yeah, I guess this is probably my next question is like, when we’re gonna do the the error reconciliation
77 00:10:53.740 ⇒ 00:10:59.095 Uttam Kumaran: Process each each week, and then ideally over time. Maybe it’s it’s on a it’s on a
78 00:10:59.940 ⇒ 00:11:01.329 Uttam Kumaran: longer cadence.
79 00:11:02.060 ⇒ 00:11:14.869 Amber Lin: Yeah, totally. I’ll go. I think that’s a big part of our rollout plan is to have that feedback loop, especially so I’ll just. I’ll just dive in here. So
80 00:11:15.650 ⇒ 00:11:44.710 Amber Lin: what we want for a rollout as we talked about last week is, we want to have a small scale rollout, and then we want to roll it out to everybody, and the importance or the goal for this smaller scale rollout for just 5 Csrs is that we want to validate the core functionalities, make sure things are working and make sure we’re ready to skill. So that means we need to check in on a lot of the gaps. We need to identify them so we can fill them.
81 00:11:44.760 ⇒ 00:11:47.050 Amber Lin: We need to
82 00:11:47.550 ⇒ 00:12:04.260 Amber Lin: make sure that it’s working that the Csr is finding them helpful. And also another important part is about the evaluations and measurements. That’s where Brian will come in and data team will come in. So we’ll know
83 00:12:04.610 ⇒ 00:12:08.310 Amber Lin: what we’re doing is actually helpful for the business.
84 00:12:09.520 ⇒ 00:12:17.240 Amber Lin: And so here’s a actually let me go to this slide first.st
85 00:12:17.850 ⇒ 00:12:43.650 Amber Lin: So what we’re gonna do for meetings as as I see it, and I wanted to bring it up in this meeting, so we can talk over. It is meeting cadences and structures of feedback loop structures. So for the daily part and ongoing part of, we saw the slack alerts of error messages right? So that’s just ongoing. That’s where all you automated that so that will just continue coming.
86 00:12:43.760 ⇒ 00:13:04.120 Amber Lin: Our team has daily stand ups, and Janice is joining us, is already have joined us, for the daily stand ups, and for those we’ll just look at the different usages. Look at the different errors, look at what we can improve on, and you guys will also get a update on that, since Denise is already in our stand ups.
87 00:13:04.424 ⇒ 00:13:20.579 Amber Lin: We also hope that the managers will be able to check in with the Csrs daily to see if they’re using it. What kind of questions comes up? So maybe that will be more mid level managers, such as Janet and grace, but probably Denise will relay that message to us as well
88 00:13:20.940 ⇒ 00:13:21.510 YvetteRuiz: Yeah.
89 00:13:21.510 ⇒ 00:13:28.990 Amber Lin: So that’s for the Daily Part weekly part, we have this meeting, which, moving forward, I want to start on
90 00:13:29.160 ⇒ 00:13:51.199 Amber Lin: looking at the Kpis and the usages. Everything is connected to the business outcomes. So we want to see is this functionality, this spot helping the business, and that will give Steven and Matt, or and all the effects a view of how this is performing. For the other parts, more technical parts.
91 00:13:51.790 ⇒ 00:14:16.449 Amber Lin: So that will be the data team, and maybe some of you, if you want, you can join, we’ll be talking about errors. We’re talking. We’ll talk about contact gaps, what we need to improve and check in on improvements that have been made. So we have 2 separate meetings. What? That was my intention, and lastly, monthly, or say
92 00:14:16.780 ⇒ 00:14:31.830 Amber Lin: bi-weekly, it just okay, overall. How are we? How are we doing what we want for the next steps? Are we? Do we feel aligned? So that’s what I envision for our daily, weekly, and monthly cadences. I’ll pause here
93 00:14:33.690 ⇒ 00:14:34.320 YvetteRuiz: Okay.
94 00:14:35.217 ⇒ 00:14:56.830 YvetteRuiz: really, quick question. So on the. So we already have picked out, and I may be jumping out. So we already picked up the 5 people, Janice, that we Janice and I met yesterday just to confirm who they were. So once they start testing it. Obviously all this is gonna start coming. You know, more stuff is gonna be coming up. So what we’re saying is
95 00:14:56.980 ⇒ 00:15:15.399 YvetteRuiz: when those, whatever they find, whether it’s an error, it’s going to alert us right away, or your team right away. Is that is that what I’m hearing? I’m sorry. And then what are we going to make sure, how are we going to make sure that that gets updated? Obviously, it’s going to get logged as the error. But how do we make sure that we’re gonna be updating that
96 00:15:16.390 ⇒ 00:15:18.060 Amber Lin: Information
97 00:15:18.440 ⇒ 00:15:48.290 Amber Lin: totally. So if it’s small adjustments that we can make quickly, that’s what the stand up so for. So we’ll see that, and we’ll make sure that every day something’s being improved. And for bigger chunks of updates, maybe a new document, maybe a whole change of structure. That’s where the weekly feedback is for cause. Maybe we’ll have Shannon and Grace join, and they can know. Okay, these are all the things that we needed to make with the central dog, or whatever. And
98 00:15:48.290 ⇒ 00:15:53.309 Amber Lin: you can also approve those bigger changes in the central dock. So we’ll have
99 00:15:54.840 ⇒ 00:16:00.889 Amber Lin: like one that’s quick, quick, and small, and the other one is bigger and
100 00:16:00.890 ⇒ 00:16:12.390 YvetteRuiz: Okay, alright. So so you answer my question. So they are going to be on the stand ups. Y’all’s daily stand up. That’s when you all will do the quick and and what you just said right there and then. Of course, anything that needs to be updated or uploaded. Those may be
101 00:16:12.770 ⇒ 00:16:28.409 YvetteRuiz: more of a weekly. I just wanna make sure that that checks and balances. Because before we just go in there and update those things that cause that that big piece, especially if we’re adding, or there’s a big chunk, let’s say, like the save tactics. I did share those with Janice. So she was asking, so that
102 00:16:28.610 ⇒ 00:16:40.239 YvetteRuiz: making sure that we get those in, and that we get those approved with, whether it be the branch managers or the Dms. Making sure everyone got their sign off before it gets in there. I just wanna make sure that I understand that step
103 00:16:40.650 ⇒ 00:16:54.560 Amber Lin: Totally. Yeah, that’s a key part of the document update process. And that’s why we want Shannon and Grace there, so they can suggest the edits, and if we have that meeting we have a set time where you know when to go in to approve them.
104 00:16:54.560 ⇒ 00:16:55.030 YvetteRuiz: Okay.
105 00:16:55.030 ⇒ 00:16:56.910 Uttam Kumaran: Yeah, I think one thing Amber here is
106 00:16:56.910 ⇒ 00:16:57.430 Amber Lin: Hmm.
107 00:16:57.430 ⇒ 00:17:17.349 Uttam Kumaran: Both a mix of the spreadsheet. And in the document itself, you can just suggest changes in the Google Doc. So I think that’s probably the best way to say is to just go in there. You can click on. I want this to be a suggestion, and you can just make the change. It’ll come up as a suggestion. And yeah, you’ll have to review that and basically click, approve for it to apply
108 00:17:17.460 ⇒ 00:17:19.270 Uttam Kumaran: that. That seems pretty straightforward
109 00:17:19.270 ⇒ 00:17:20.139 YvetteRuiz: Great. Okay.
110 00:17:20.140 ⇒ 00:17:39.349 Uttam Kumaran: I think at this point we’re we’re, of course, doing things every day, but we want to move towards like again, not having to have everybody. Here’s time every single day to just patching it once a week, and then maybe once every 2 weeks, and sort of again, nailing this process so ideally as we go to more departments, we sort of have, like the who what, when you know
111 00:17:39.640 ⇒ 00:18:01.750 YvetteRuiz: Yes, yes, understanding. And that’s what I want to make sure that I’m doing my part. Because that I have already been the suggestions and everything that Grace and them have been. I’ve gone and I’ve updated and I’ve cleared some of those I was just making sure. Is there something going to be. Is that going to change? But obviously, maybe not. I’ll just continue doing what I’m doing. Once they put those suggestions out there
112 00:18:03.170 ⇒ 00:18:03.750 Amber Lin: Hmm!
113 00:18:04.600 ⇒ 00:18:05.830 Amber Lin: Sounds great.
114 00:18:06.020 ⇒ 00:18:28.769 Amber Lin: So let me go back to the previous slide. So I made a action plan for how we’re gonna roll out, because there’s little things that we also need to do to get people on boarded. So we’ve already finalized the Css. Csr group. As you mentioned, that is great. So the next part is, we want to make sure we have a
115 00:18:28.990 ⇒ 00:18:54.649 Amber Lin: so Csrs know what how to use it or how to get it, how to get started with it and how they’re going to use it in their daily flows. So we already have a loom video that you guys use to get on the bot. But we also want to create working with Janice, of looking at how the Csr is going to use it in their daily flows. So we want to instruct them. So we get as much data as possible.
116 00:18:54.760 ⇒ 00:19:01.490 Amber Lin: So that’s something that we also want to do. And we’ll touch on that on our Monday meeting. So that’s already scheduled.
117 00:19:02.162 ⇒ 00:19:16.310 Amber Lin: Other parts is well, enabling access for them, of course, and daily check-ins. Maybe maybe not, Janice, but maybe Shannon and Grace can go check in with them. Are you guys using this? Is it going? Well?
118 00:19:16.760 ⇒ 00:19:22.039 Amber Lin: Why are you not using it? Or what did you find helpful like questions like that to
119 00:19:22.180 ⇒ 00:19:29.750 Amber Lin: keep us updated on the process. And maybe I can also get in touch with the Csrs and talk to them
120 00:19:30.430 ⇒ 00:19:48.469 Amber Lin: and more on the data side is establishing that baseline. So that’s where Brian will be super super helpful. And we’ll get that data. So eventually we’ll be able to measure the business impacts of not just the and not just that the bot is working, but that it’s actually helping the businesses.
121 00:19:49.410 ⇒ 00:20:06.890 Amber Lin: and eventually, towards the end or in the middle. And towards the end we do want to conduct maybe a feedback survey with the Csrs just to get an idea of. Okay, how do you feel with this item? And has it improved her daily processes?
122 00:20:07.384 ⇒ 00:20:15.530 Amber Lin: That will be a supplement for the data that we’ll get. So it’s qualitative and quantitative, both of them at the same time.
123 00:20:15.950 ⇒ 00:20:25.479 Amber Lin: So that’s my view of the action. Our view of the action plan how this is going to move forward. I just want to pause here for
124 00:20:26.653 ⇒ 00:20:27.759 Amber Lin: any questions
125 00:20:27.760 ⇒ 00:20:28.130 YvetteRuiz: Perfect.
126 00:20:28.130 ⇒ 00:20:29.050 Amber Lin: You guys have
127 00:20:29.590 ⇒ 00:20:54.539 YvetteRuiz: I I did have a question. So as we’re doing the rollout I finally got our our marketing manager to to give me the colors for the contest for Andy. So I’ll I was gonna work with you guys to see if you guys can help me just put that together. So in that way we can do that contest piece. But then I also had a conversation with Steven, because it we we had wanted to officially announce what we were
128 00:20:54.540 ⇒ 00:21:02.459 YvetteRuiz: working on, or give our agents some some kind of an update on what what’s coming. We didn’t get to cover it on that meeting. So
129 00:21:03.060 ⇒ 00:21:07.340 YvetteRuiz: do you think we could work together? Maybe put a presentation or something of 100%
130 00:21:08.030 ⇒ 00:21:11.549 Uttam Kumaran: Yeah, I think there’s kind of a couple aspects here. I think one.
131 00:21:11.590 ⇒ 00:21:30.010 Uttam Kumaran: Some people learn via presentation. Some people they may not be around. I think we should do a couple of things. One we should certainly do like a, we use loom, which is basically like a video walkthrough so amber, we can probably. And this will help us. And anyone new is basically record our own set of training documents, which is just like
132 00:21:30.030 ⇒ 00:21:51.990 Uttam Kumaran: an overview. How to ask this type of question, how to provide feedback. We just have those videos. I think that would be perfect to roll out. I think the second piece is certainly we can put together a slide deck that anyone can utilize. You know we’ll we’ll theme it for for all ABC. Or if you guys have a classic slide template that you use, we can use that and just basically have
133 00:21:51.990 ⇒ 00:22:13.990 Uttam Kumaran: an overview how to use it. And like what what the goals are of the project. That way. It’s a nice overview of of sort of like what we came into, what the goal is, and sort of what the solution is. I also wanna think about a way for us to collect feedback from from anyone in the company who, even if they’re not a direct user. If they just think about something to sort of get it to this group.
134 00:22:14.040 ⇒ 00:22:43.649 Uttam Kumaran: whether whether that’s making our email available or giving you all a form or something like that. I’m sure a lot of people will start to flood with questions. Some of those will just be excitement, but some of those, if they’re if they are real suggestions, we can just triage them somehow. I would. I would throw up Amber’s email there. But she’s gonna get a lot of emails. So maybe if we could think of a Google form or or something we can use that I think that that way. I’m sure a lot of people will have questions. You can say just if you have a question submitted on the form.
135 00:22:43.700 ⇒ 00:22:46.919 Uttam Kumaran: and then we can start to, you know, build those relationships
136 00:22:47.590 ⇒ 00:22:59.819 YvetteRuiz: Yeah, for sure. No, I think we can. You know, even if it funnels up to the data team to send it to you guys, because we have something like our compliment, email that they get, we can do something similar for this
137 00:22:59.820 ⇒ 00:23:00.460 Uttam Kumaran: Great
138 00:23:00.760 ⇒ 00:23:04.289 YvetteRuiz: Stephen, did you want to add anything? On the whole introduction piece
139 00:23:04.820 ⇒ 00:23:08.088 Steven: No, yeah, I think that’s great. That’s kind of what we had talked about. We talked about presenting it
140 00:23:08.480 ⇒ 00:23:15.710 Steven: at a meeting, and then, when that didn’t work. Maybe that we’re like his team could create a way better presentation. We could have anyways. So
141 00:23:16.270 ⇒ 00:23:33.549 Steven: we and we we kind of like the idea of having this a little bit separate, because if we do it at the meeting, it needs to be really quick. And I think some kind of video with the loom, and showing how it can be utilized. And a few examples would be awesome that we can just kind of send out to everyone, and then I agree, we’ll need some way to have some feedback, because people
142 00:23:33.680 ⇒ 00:23:43.610 Steven: ask questions and then also a slide deck that we can show up at, you know. Either event, either Bobby could do it, or you could do it at the next meeting. Just a real quick. 3, 4, 5 min
143 00:23:44.083 ⇒ 00:23:55.410 Steven: overview, and I think would send the video out 1st and then kind of recap on the on the slide deck at the meeting. So yeah, no, I think y’all could do a much better job than what we could put together, so
144 00:23:55.410 ⇒ 00:24:01.729 Uttam Kumaran: Perfect. And I I actually think, probably, like Janice, you or you, that should do the recording. We can give you the
145 00:24:01.990 ⇒ 00:24:14.450 Uttam Kumaran: the script, or like sort of how to click through it. But I think it would mean a lot to come from y’all. And then, yeah, anything we can do to help put the deck together, and set it up so you guys can talk to it more than happy.
146 00:24:14.843 ⇒ 00:24:40.379 Uttam Kumaran: So I think we’ll add that as an action item, amber. And we can basically record, we can just go through a quick like, what do we want to cover in the video? And again it’ll just be quick like, click this thing. Open this thing. How to give feedback. What questions can you ask? Right? So that we’ll try to hit the most common videos again, a lot of people. You could write that in text. But it’s something that you’re gonna want them to see or refer back to. So then we can send out those loom videos and people have them.
147 00:24:40.694 ⇒ 00:24:46.730 Uttam Kumaran: So they can refer back about how to get feedback. Even things like where to go find it. In my Google Workspace.
148 00:24:47.175 ⇒ 00:24:51.419 Uttam Kumaran: You know, issues like that. We we just start to create a repository of these videos.
149 00:24:51.950 ⇒ 00:24:58.719 Steven: Yeah. And I, I love the I love the idea of even. I talked about that, too, about showing the yeah where we started, what our goals were.
150 00:24:58.720 ⇒ 00:24:59.260 Steven: Totally.
151 00:24:59.260 ⇒ 00:25:06.779 Steven: we’re really showing the the goals. And this because you know, the fear right now is, oh, man, is this, gonna take our job. But no, that here’s what we’re trying to accomplish. We’re trying to
152 00:25:06.780 ⇒ 00:25:07.340 Uttam Kumaran: Yeah.
153 00:25:07.340 ⇒ 00:25:12.970 Steven: Trying to increase 1st call resolution. This is how it’s helpful. This is how it helps customer, how it helps you, how it helps companies
154 00:25:12.970 ⇒ 00:25:31.890 Uttam Kumaran: Totally, and I think my my conversation with the event and Brian actually shine a lot of light on like, even for the Csr. Like, what is the daily struggle here which is having to get up and find the answer to the question having to probably deal with unhappy customers on the call. It is also a lot of like.
155 00:25:31.930 ⇒ 00:25:56.309 Uttam Kumaran: Hey, currently, you know, we have goals of people trying to take on more calls and solve more problems. But right now we’re going to overflow. And of course, people are probably stressed out. They’re not hitting their numbers. Things like that is the are the things that we’re gonna solve. I think one thing that I tell even my team is that there’s like plenty of problems like no one’s going anywhere. It’s actually the fact that, like we don’t want to double, we, our only choice is to double the team
156 00:25:56.310 ⇒ 00:26:06.189 Uttam Kumaran: or like or what. And so this is really a solution to help everybody. You know, and so we’ll we’ll, I think, Amber 1. 1 of our slides really upfront should be
157 00:26:06.320 ⇒ 00:26:09.449 Uttam Kumaran: something around like this is not eliminating your job.
158 00:26:09.450 ⇒ 00:26:09.820 Uttam Kumaran: Yeah.
159 00:26:09.820 ⇒ 00:26:20.329 Uttam Kumaran: I don’t know if we want to be that direct. But I I really tell that to our team, too, because I say, think about how much time you spend waiting for the information, trying to go find out who to ask.
160 00:26:20.330 ⇒ 00:26:43.679 Uttam Kumaran: These are not things any of us here want to do. You want to be spending more time with the customer, and more time leveling up and being able to do more work? Multi department like those are the positives, you know. We want to share with people not sit in like 6 month training like those are the things I think we’ll we’ll share with folks. The additional thing is for the veterans that you talked about is like allowing them to actually take their veteran knowledge and and provide it back
161 00:26:43.800 ⇒ 00:26:55.249 Uttam Kumaran: to the rest of the team right? And get people. And again you mentioned that you know a lot of people. They take a long time to train, and maybe they get unhappy and leave. That’s what we’re trying to mitigate. You know, more than anything
162 00:26:56.350 ⇒ 00:27:08.359 YvetteRuiz: You know, obviously all the positives for sure enhancing the enhancing. I was gonna say something on that. But I think, Janice, we we could do it kind of like the way we did the call source.
163 00:27:08.980 ⇒ 00:27:09.800 YvetteRuiz: I think. So.
164 00:27:09.800 ⇒ 00:27:16.290 YvetteRuiz: We went in there. We did a double part as far as the introduction and what the positives were, and how it all worked, and stuff like that. But
165 00:27:16.530 ⇒ 00:27:21.339 YvetteRuiz: I pre I would appreciate that that would be good. So then that way, we can get that going to the team
166 00:27:22.830 ⇒ 00:27:28.449 JanieceGarcia: And I wouldn’t mind doing the recording the voice over either. I’ve I do training videos. So
167 00:27:28.450 ⇒ 00:27:33.050 Uttam Kumaran: Oh, great. Okay, yeah. Then you’re the expert. I don’t. Even we don’t need to do anything. Yeah, that’s perfect.
168 00:27:36.810 ⇒ 00:27:38.130 YvetteRuiz: Okay, what’s
169 00:27:38.660 ⇒ 00:27:45.650 Uttam Kumaran: Yeah, I guess any other questions, Steven, from your side, or or yeah, for anyone really
170 00:27:46.330 ⇒ 00:27:51.879 Steven: No, I said, Yeah, if we could get that, do we think we could get that even? I’m trying to look at the calendar technically.
171 00:27:52.110 ⇒ 00:27:58.310 Steven: Tuesday is the first, st the second Tuesday is technically, where am I at?
172 00:27:58.540 ⇒ 00:28:02.530 Steven: Yes, technically it’d be the following week. But I doubt we’ll have a company meeting that week.
173 00:28:02.720 ⇒ 00:28:08.800 Steven: But I’m thinking, if do we think we could have, like the video done by the end of next week to shoot it out the following week.
174 00:28:08.950 ⇒ 00:28:12.000 Steven: and then we have the company meeting the following week, where we can do the slide deck
175 00:28:12.000 ⇒ 00:28:22.279 Uttam Kumaran: Yeah, I think that’s reasonable. I think if we if we say 2 weeks for the for the deck, and then I think the videos should take, you know, just a few minutes to to record and polish. And then that’s it.
176 00:28:22.880 ⇒ 00:28:23.489 YvetteRuiz: Okay. Yeah.
177 00:28:24.435 ⇒ 00:28:27.659 Steven: As far as yeah. I know y’all are working on getting the phase. 2 pricing
178 00:28:27.660 ⇒ 00:28:28.460 Uttam Kumaran: Yes.
179 00:28:28.460 ⇒ 00:28:44.649 Steven: I’m working on that. But otherwise no, I just like know if it’s spent in Janice. Spend a lot of time on this I like popping in, just, you know, be a fly on the wall and see the progress when you’re doing great. I think it’s everyone’s gonna enjoy it. I think, Matt.
180 00:28:45.000 ⇒ 00:29:03.400 Steven: you know, on the pricing side Matt sees there’s value in it just solely from a tool purpose just to have a tool for someone to use and ask questions. Obviously that value is this much, and the value to the company and saving money is even more. But I think people, once they can get their heads around this. There’s a lot of people that have still never even use chat, gpt here
181 00:29:03.400 ⇒ 00:29:06.599 Uttam Kumaran: Yeah, I was just talking to a friend yesterday about this.
182 00:29:07.260 ⇒ 00:29:07.710 Uttam Kumaran: Yeah.
183 00:29:07.770 ⇒ 00:29:30.699 Uttam Kumaran: So hopefully, this is their 1st interaction with the tool. And then, you know, it’s a good one, right? It’s a positive one, and they can think about other opportunities in their day to day where automation can be applied. I think another thing, if you have a moment, I think the dashboard is in a really really good. Is it in a good state? I think if you if you spend a moment and and go on there, I think what you’ll see. If I could just take a moment here.
184 00:29:30.945 ⇒ 00:29:50.370 Uttam Kumaran: One thing that we’ve done is we’ve made it easily filterable to a couple of pieces. One, we’re gonna filter out, test users, test users are like our our team. Basically as you could see, we, we’ve been asking a lot of the questions. So and a lot of the questions we’ve been really trying to stump. So we initially were like, Oh, a score so bad. And I was like, you probably need to filter out
185 00:29:50.500 ⇒ 00:30:10.929 Uttam Kumaran: the stuff where we’ve been testing and things like that. Additionally, we have a flag here that’s like, is, it doesn’t need escalation. So basically a lot of the ones you’ll need escalation, you can see are these like, I’m sorry. I don’t know things like that. So we will want to see like, one of the things we’ll show is basically the percent of and amber. We can add this, the percent of questions that need escalation.
186 00:30:11.880 ⇒ 00:30:30.789 Uttam Kumaran: the other thing is our error rate. And I think we? We. We talked a little bit about all the scores, but basically we want to give you is this an error or not? And then for the ones that are error. How bad are they? And again we will start to see their volumes go up. We will start to. Probably we want to see these go down as a percentage of total.
187 00:30:30.790 ⇒ 00:31:00.209 Uttam Kumaran: we may still see that there are errors, and of course, 10% of a bigger number is still a big number. But we want to see that go down. Additionally, we want to start seeing the execution time go down. We do have a path internally to get this to 3 seconds. Actually. I just told the team to focus on getting this right in the rollout to the next 5 right but we’ve done a bunch of research in the last 2 weeks when we sort of took on the optimization problem, and we have a pretty clear way to to continue to boil this down over time.
188 00:31:00.607 ⇒ 00:31:24.029 Uttam Kumaran: And then, of course, we’ll be encouraging people to give more feedback and thumbs up the last piece, I’ll say here is. And this is where I think in the next 2. In the next month we’ll see. A lot of progress is linking in the phone data. And so this is where Brian, comes in and the data team comes in. We’ll be bringing in just the raw 8 by 8 data and then ideally over time connecting to the Api and then starting to link the calls
189 00:31:24.190 ⇒ 00:31:28.309 Uttam Kumaran: based on the person and the time with with the chat
190 00:31:28.739 ⇒ 00:31:44.089 Uttam Kumaran: and being able to see, oh, this is this is the call that happened. It was with this person. This was the exchange between the Csr and the Bot. And then, ideally, this is the outcome. Right? Okay. The call got resolved, that person renewed, or that person got upsold. And so that is the real like
191 00:31:44.140 ⇒ 00:32:13.580 Uttam Kumaran: that. I pro probably will take us a month to sort of iron all that out which I’m really happy. Brian is excited to to sort of be in the fold. And I I want actually him to work within the system like I don’t want it to be like a handoff to us. He he’s totally qualified to to work on, you know, getting his own dashboard into here, and for all of that data. And you know I was speaking to him. One of the pieces and data is, it’s actually, you may think it’s 80% digging through and finding information. It’s actually like 80% cleaning up
192 00:32:13.640 ⇒ 00:32:31.940 Uttam Kumaran: right? So getting data from whatever system being like, this column is messed up or 8 by 8 doesn’t give us this. And then 20% of time you’re spending sort of thinking about how this is important. We want to flip that we want. He has so much knowledge. It was really clear about the business and about how to run an effective operation. And I want him to spend as much time
193 00:32:31.940 ⇒ 00:32:47.020 Uttam Kumaran: analyzing the data and finding the nuggets, and, you know, coming to the executive team with with what the decisions should be made, are so hopefully, I think this will get him out of spreadsheet world a little bit and and more onto that, so super excited to have him sort of join, stand ups and things
194 00:32:48.670 ⇒ 00:32:54.459 YvetteRuiz: Yeah, I know he’s super excited to Uda, yeah, he was like, yeah, some of the stuff
195 00:32:54.460 ⇒ 00:32:56.680 Uttam Kumaran: Tried to speak his language a little bit. Yeah.
196 00:32:56.935 ⇒ 00:33:17.339 YvetteRuiz: He really gets in there. I mean, he the way back home, you know he had. You know, we’re thinking we’re bouncing a lot of ideas off of each other regarding some of the reportings and things like that. But I’m I’m excited that they’re going to be joining the team. To be able to see those results. I think that’s gonna be awesome. I was sharing that with Steven this morning as well. So all good stuff
197 00:33:17.340 ⇒ 00:33:22.790 Uttam Kumaran: Okay, great, that’s all I had. Thanks, thanks, Amber, for for letting me taking a little time. Yeah.
198 00:33:23.860 ⇒ 00:33:27.810 JanieceGarcia: Do you, Amber want the 5 Csrs now
199 00:33:27.810 ⇒ 00:33:28.800 Amber Lin: Oh, do you want me to eat?
200 00:33:28.800 ⇒ 00:33:29.160 JanieceGarcia: Smell them.
201 00:33:29.160 ⇒ 00:33:36.609 Amber Lin: That’d be great. You can just text them in the chat or email them to me
202 00:33:37.000 ⇒ 00:33:39.280 Amber Lin: like I’ll just put them somewhere
203 00:33:39.810 ⇒ 00:33:41.000 JanieceGarcia: I’ll email them to you.
204 00:33:41.000 ⇒ 00:33:41.820 Amber Lin: Okay. Thank you.
205 00:33:41.820 ⇒ 00:33:45.560 JanieceGarcia: Go ahead and email that way. You can have their email address and everything
206 00:33:45.560 ⇒ 00:33:47.700 Amber Lin: Great. Yeah, that’s fantastic.
207 00:33:48.390 ⇒ 00:33:48.740 Uttam Kumaran: Okay.
208 00:33:48.960 ⇒ 00:33:51.110 Amber Lin: Yeah, it’s all about my 3.rd Yeah.
209 00:33:51.110 ⇒ 00:33:53.079 Uttam Kumaran: Thank you. Everyone have a really great weekend
210 00:33:53.080 ⇒ 00:33:53.999 Steven: Thank you. Have a good
211 00:33:54.410 ⇒ 00:33:55.479 Uttam Kumaran: Talk to you later
212 00:33:55.480 ⇒ 00:33:56.139 YvetteRuiz: Care. Bye-bye
213 00:33:56.140 ⇒ 00:33:56.530 JanieceGarcia: Bye.
214 00:33:56.530 ⇒ 00:33:57.050 Uttam Kumaran: Bye.